3-1528 July 1986 Aiiififiév t- ‘ption 0f FLIPSIM V: lefi‘ a General Firm Level Policy Simulation Model é E. ggii-n P THE TEXAS AGRICULTURAL EXPERIMENT STATION AGRICULTURAL a FOOD POLICY camera Neville P. Clarke, Director/The Texas A&M University System/College Station, Texas [Blank Page in Original Bulletin] DESCRIPTION OF F LIPSIM V: A GENERAL FIRM LEVEL POLICY SIMULATION MODEL James W. Richardson Associate Professor and Clair J. Nixon Associate Professor Agricultural and Food Policy Center Department of Agricultural Economics Texas Agricultural Experiment Station Texas A&M University [Blank Page in Original Bulletin] Table of Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Overview of the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Capabilities and Uses of the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Model Validation and Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1O Description of the Computer Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Subroutines DATA1-DATA7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Subroutines CROPMX and PIVOT1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Subroutine STOCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Subroutine DAIRY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Subroutine LVSTK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Subroutine VCOSTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Subroutine FCOSTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Subroutine FINAN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Subroutine LANDVL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Subroutine DEPREC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Subroutine LEASE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Subroutine MKTG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Subroutine RECPTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Subroutine POLICY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Subroutine INVEN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Subroutine CASHIN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Subroutine CONSF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Subroutine CASHFL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Subroutine UPDATE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Subroutines TAXES and TAXTAB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Subroutines REFIN and SOLVNT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Subroutine GROW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Subroutine IROR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Subroutines PRINTI, PRINTZ. PRINT3, and PRINT4 . . . . . . . . . . . . . . . . . . . . . . . 43 Subroutine ITSUMM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Subroutine STAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Appendix A: Coding Instructions for all Input Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Appendix B: Sample Set of Input Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Appendix C: Sample Output from the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Appendix D: Files and Variable Names in the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 *The authors are grateful-to Vicki McClain for typing this manuscript and to Edward Rister. Tom Knight. David Leathatn. and Ardan Pope for their helpful review comments. [Blank Page in Original Bulletin] Description of FLIPSIM V: A General Firm Level Policy Simulation Model Introduction FLIPSIM V is the current version of a Fortran computer simulation model developed by Richardson and Nixon in 1981. The original F LIPSIM model was developed under a cooperative agreement between the Texas Agricultural Experiment Station and the Farm Sector Economics Branch of NED, ESS, USDA. Since completion of the cooperative agreement in 1981, the model has undergone major modification. The computer program has been lengthened from 5,000 statements to over 10,000 statements. The major improvements in the model include changes for the 1981 farm program (acreage limitations) and inclusion of the 1981, the 1982, the 1984, and the proposed 1985 income tax acts. In addition, the capabilities of the model have been enhanced by: (a) adding a dairy sector, (b) expanding the beef cattle sector, (c) adding a crop marketing decision sector, (d) increasing the number of agricultural policies that can be simulated, (e) adding the capability to draw random values from empirical probability distributions, (f) including the flexibility to lease farm machinery, and (g) adding a quadratic programming algorithm to determine crop mix. The model was developed to allow analysis of the probable consequences of alternative farm policies and income tax developments on typical or representative farms} To do this, the model had to be capable of simulating a wide variety of farms in all regions of the country. lt has been used at Texas A&M University for analyzing alternative agricultural policies, alternative income tax developments, farm structure, marketing strategies, machinery leasing, farm management strategies, financial bailout strategies, and debt servicing capacity of crop producers, dairy farms, and cow/calf operators. Numerous policy analyses have been made by analysts in USDA using modifications of the original version of the model. The purpose of this report is to describe the Fortran computer program which constitutes the FLIPSIM V model. The first section provides an overview of the model. The second section describes the types of analyses the model has been used for, followed by a section on validation. The final section describes the individual subroutines in the model. A technical description of the equations in the model is available in Richardson and Nixon (1985). 1A typical farm is one which represents the typical farming operation in a particular region for a given size category. The data are generated based on primary data and may represent averages of the number of machines, the number of acres devoted to each crop. the costs of production, the firm’s initial financial situation, etc. The analyst should be able to find numerous farms in the region which are examples of the completed data set. On the other hand, representative farms describe the general characteristics of some farms, or at least one farm, in a region. Representative farms do not necessarily have the average initial financial position of farms in the region. the typical machinery complement. the typical crop mix. or costs of production. Despite these shortcomings. representative farms can be used to evaluate the impacts of alternative policies or management strategies for farms organized a particular way. having a particular crop mix or initial financial position. Overview of the Model FLIPSIM V is a firm level, recursive, simulation model which simulates the annual production, farm policy, marketing, financial management, growth, and income tax aspects of a farm over a multiple-year planning horizon. The computer program is capable of simulating a case farm situation for 1 to 10 years. The model recursively simulates a typical farm by using the ending financial position for year 1 as the beginning position for the second year, and so on. An option to use a programming algorithm (LP or OP) to select the optimal (profit or utility maximizing) crop mix for years 2 through 10 is included in the model. The model, however, is a simulation model as opposed to a programming model. This is because FLIPSIM V does not include an overall objective function to be optimized but rather analyzes the outcome of a given set of input data and assumptions for a typical farm. Accounting equations and identities constitute almost all of the computational components of the model. Virtually no econometric relationships with fixed parameters are included. The model (Fig. 1) simulates a given farm situation for 1 to 10 years (inner loop YEARS), and repeats this multiple-year planning horizon for 5O iterations (middle loop ITER) during a stochastic analysis. At the end of each iteration, the model records the results for future analysis. Prior to simulating iterations 2 through 50, the model reinitializes the farm to the beginning situation used for the first iteration. The model is capable of simulating up to 300 iterations. Upon completion of the last iteration, the model performs a statistical analysis of 39 to 489 output variables, develops cumulative probability distributions (cdf) for these output variables, and estimates the probability of the farm operator remaining solvent for the duration of the planning horizon. An outer loop (NOFARM) allows the model to analyze additional farm situations as provided. At the beginning of each year in the planning horizon, the model determines the crop mix (Fig. 1). For year 1, the crop mix is fixed by the user. In years 2 through l0 the crop mix can be: (a) constant, (b) determined by an LP which maximizes expected net returns over variable production costs. or (c) determined by a QP which maximizes expected utility, Expected net returns are calculated using a weighted average of past yields and prices, modified for relevant loan rates, target prices, expected disaster or crop insurance payments, and acreage set aside restrictions. An LP or QP algorithm is solved for the optimal crop mix using the expected net returns, monthly labor requirements, covariance matrix (if applicable), and crop mix constraints imposed by the analyst. A distinction is made between irrigated cropland and non-irrigated cropland in the LP or QP tableau, and double cropping is taken into consideration in calculating expected net returns per acre. If the analyst prefers to predetermine the crop mix outside the model. the programming portion of the model is ignored. Annual prices and yields for up to 10 crops are determined by the analyst in the deterministic mode. When the model is run using stochastic prices and yields, annual crop prices and yields are drawn at random from probability distributions specified by the analyst. The analyst can select from independent or multivariate distributions for annual crop prices and yields, annual livestock prices (cows, heifers, steers. bulls, stockers, and feeders), annual dairy prices (milk. cull cows, replacement cows, and calves), and milk production per cow. Variable cost of production is calculated for each crop enterprise and then summed to obtain total input costs. Harvest costs are calculated by multiplying each crop’s production (harvested zicreage times yield) by its harvesting cost per yield unit. It is assumed the farm operator does not harvest a crop merely to maintain farm program yield so cropland is abandoned if the per acre cost of harvesting exceeds the expected revenue per acre. Variable production costs per head of livestock and dairy cows are multiplied by their respective herd size numbers to estimate livestock and dairy production costs. START l ————————————# NOFARM=NOFARM+l l INPUT l l————————+ ITER=ITER+l l *———* YEAR=YEAR+l l CROPMX STOCH+——-————————+GAUSE DAIRY LVSTK VCOSTS FCOSTS FINAN LANDVL DEPREC LEASE MKTG RECPTS POLICY INVEN CASHIN CONSF REF INSSQLVNT CASHFL TAXES+——————————+TAXTAB T +qRcw UPDATE+—————————+SOLVNT IROR no<-—-—~l YEARZlO PRINT l ITSUMM +——————+IROR l no<-—————— 11112350 l STAT l n<><—-——i~ NOFARMZM —-—> STOP re l. Schematic of the overall FLIPSIM V model. 3 Labor cost is the sum of updated, full-time employee salaries and benefits plus wages paid to part-time employees. The amount of part-time labor hired is the residual labor required each month after fully utilizing full-time employees and family labor for all crops, as well as the dairy andbeef cattle enterprises. Labor requirements for each crop are a function of the number of acres planted and the crop’s monthly labor requirements per acre. Monthly labor requirements for the dairy enterprise are calculated based on the number of cows milked monthly, as well as the number of heifer calves, replacement heifers, and dry cows to be cared for each month. Similarly, monthly labor requirements for the beef cattle enterprises are calculated based on number of cows, replacement heifers, bulls, stockers, and feeders and the monthly labor needs of each. Interest cost for operating capital is calculated based on the farm’s total variable costs of production for crops, cattle, and dairy; the annual interest rate for operating capital; and the fraction of the year an operating loan is used. Annual values for exogenous fixed costs are calculated by inflating their initial values by the appropriate annual percentage changes provided by the analyst. Property taxes are calculated as the product of the appropriate property tax rate and the market value of land owned in the previous year. Existing and new long- and intermediate-term loans are amortized based on their respective loan life, initial amount borrowed, and annual interest rate. These values are provided at the outset by the analyst. All loans are amortized using the remaining balance formula. Variable interest rate mortgages are assumed for new loans, and the annual interest rates for these loans are provided by the analyst. Variable interest rate mortgages are used for initial loans if the analyst provides different interest rates in each year of the planning horizon. The market value of land and farm machinery is updated annually. The market value for used equipment is adjusted using the percentage changes in used equipment prices supplied by the analyst. The market value of farmland can be either inflated in a similar fashion, say, a constant 3 percent per year, or it can be calculated using the estimated capital gains rate for cropland. The capital gains rate is calculated as a function of the weighted average rate of return to production assets. Next. assuming the farm operator is a cash-basis taxpayer for federal income purposes, depreciation is calculated for each item in the machinery complement, as well as purchased breeding stock, milk cows, and buildings. For depreciable items purchased before 1981, the model calculates depreciation using the analysts specified method. either the double declining balance or the straight line method. Depreciable items placed into service after 1980 and before 1986, are cost recovered using either an accelerated (double declining balance or accelerated cost recovery system [ACRS], respectively) or straight line method. Machinery placed into service after 1985 can either be Class II or Class III equipment. The recovery life for equipment and livestock can be set by the analyst at 3, 5, or 12 years. Farm equipment, breeding stock. and milk stock that has reached the end of its economic life is traded in or sold and a replacement purchased. The farm operator is permitted to replace an obsolete piece of equipment if sufficient cash is available (including the market value of the old piece of equipment) to meet, for example, a 30 percent down payment, and the additional debt does not cause the intermediate-term equity ratio to fall below the minimum? F irst-year expensing can be taken for all purchases of equipment, as well as investment tax credit. If equipment or cattle are sold rather than traded in, the capital gains 0r losses realized from the sale are calculated and used in computing personal income taxes. Depreciation recapture is calculated when applicable. An option in the model permits the farm operator to lease some or all of the farm equipment. Equipment is leased on a multi-year basis and can be re-leased or purchased at the end of the lease. When leased equipment is purchased, the model depreciates (cost recovers) the equipment based on options selected by the analyst. At this point in the simulated crop year, the operator has sufficient information to plan the marketing strategy for crops and thus reduce personal income taxes for the current year. By marketing a crop in the next tax year, a farm operator may reduce the accrued income tax burden in the current year. This is done in the model by calculating the operator’s expected income tax deductions and cash receipts from all sources to determine the proportion of all crops to market in the current year. A seasonal price index for each crop allows the operator to take advantage of seasonal price differentials available to producers who normally store their crops to take advantage of seasonal price differences. Annual cash receipts are calculated for the portion of the crop marketed in the current tax year plus the receipts for selling crops stored from the previous year. Crop cash receipts are adjusted to reflect the share paid to the landowner for share rented cropland. Cash receipts for the dairy enterprise are the sum of receipts from monthly milk sales; baby calves sold; old bulls sold; cull cows sold; and replacement heifers sold due to failure to breed, sickness, or the operator’s herd replacement strategy. Cash receipts for the beef cattle enterprises are the sum of receipts for selling cull cows; heifers; steers; old bulls; stockers; feeders; and replacement heifers sold clue to failure to breed. sickness, or the operator’s herd replacement strategy. When a dairy enterprise is to be simulated. the analyst must specify a herd replacement strategy for culling milk cows (fraction culled annually), heifer calves kept (fraction sold at birth). normal calving fraction, death loss of heifers over 1 year of age (fraction), and the fraction of replacement heifers sold after l year of age due to failure to breed or sickness. Given the initial herd size (milk cows and replacement heifers over l year). and the replacement strategy, the model buys and sells cows. heifers, and heifer calves to keep the milking herd at its desired level. If a beef enterprise is to be simulated, the cow herd is maintained at the analysts desired herd size (say. 50 or 60 cows) over the 10-year planning horizon by raising and/or buying replacements. When replacements are raised, the model keeps track of replacement heifers held over and bred each year and the number of heifers sold. or that die. before entering the herd. When replacements are purchased, the model buys the necessary replacements each year and depreciates purchased cows. Cows and bulls are culled based on their age and the average length of time these animals are kept in the herd. After updating the beef cattle and dairy herds at year end. the model determines the current market value of the livestock. The value of livestock is included in the market value balance sheet and is thus a component in determining the operator’s net worth. ZThe model does not keep track of the number of hours each machine is used. Nlachinery/ operating expenses and replacement are therefore not a function of actual hours used. As a result. annual machinery operating expenses do not increase if the farm operator is unable to replace a particular machine when it is scheduled for replacement. To minimize the adverse effects of this limitation. the operator may put off machinery replacement for a maximum of l year. Refinements in this section of the model are being planned. 5 The farm programs in the model are activated separately by options specified by the analyst. When the net loan rate (price support) for a crop is greater than its market price, the operator’s share of the crop is placed in the CCC loan or farmer-owned reserve (FOR), if available. Stocks are withdrawn from the loan the next year if their market price exceeds the loan rate plus interest costs. Stocks are withdrawn from the FOR if the market price exceeds the trigger price less storage costs during the 3 years after entry into the reserve. Storage payments by the government for stocks in the reserve are paid annually. If applicable, payments for diverted cropland are paid based on acreage diverted and the announced per acre payment rate. Deficiency payments are paid if a crop’s average market price in the first 5 months of the marketing year is less than its target price. The deficiency payment is the product of the crop’s payment rate (lesser of target minus average price or target minus loan), national allocation factor, farm program yield, and harvested acreage.3 Low yield disaster payments, or federal crop insurance indemnity payments, are made if a crop experiences a yield lower than its guaranteed yield. Premiums for federal crop insurance are calculated annually based on the acres of each crop insured and their respective per acre premium rates. As the loss ratio for federal crop insurance increases (or decreases) the per acre premium rate is increased (or decreased), based on schedules published by the Federal Crop Insurance Corporation (FCIC). Annual cash withdrawals from the operation for family living expenses can be calculated several ways. Specific consumption functions relating farm family consumption to family size, age of operator, after-tax disposable income, and the Consumer Price Index (CPI) are provided for 11 regions. The analyst can select one of these functions or specify a linear consumption function which relates withdrawals and farm income. An additional option is available which simply increases set value of family living expenses by the percentage change in the CPI. If the calculated value for family consumption is less (greater) than the minimum (maximum) consumption value specified by the analyst and updated for percentage changes in the CPI, the minimum (maximum) is used. Once family cash withdrawals are calculated for the year, the final cash flow position for the farming operation is determined. Cash flow deficits can be covered several ways, such as: (a) granting a loan secured by crops held for sale in the next tax year, (b) obtaining a mortgage on equity in farmland and/or intermediate-term assets, or (c) selling farmland. The operator may obtain a mortgage on a portion (one minus the minimum equity ratio) of the equity in farmland and/or intermediate-term assets. If forced to sell land, the operator sells the most recently purchased farmland first. Cropland sold to meet cashflow deficits is leased back in subsequent years to avoid having more machinery than is necessary to farm the remaining acreage. If an operator tries all of these options and still cannot remove the deficit, the farm is declared insolvent. When a cash flow surplus exists, the operator can either invest the surplus in a high yield financial instrument at prevailing interest rates or use the surplus to prepay principal payments on current debts. Personal income taxes and self-employment taxes are calculated annually for the farm operator-assuming the operator is married, filing a joint income tax return. and itemizing personal deductions. The regular income tax liability is computed using two methods: (a) income averaging (if qualified) and (b) standard tax tables. The model selects the tax strategy which results in the lower income tax liability. All investment tax credit allowances are deducted from the regular income tax liability with the result being compared to the income tax liability under the alternative 3T0 avoid overstating deficiency payments. the analyst must use a localized loan rate for each crop and localize the target price accordingly. An example would be to convert the national loan rate for cotton (55 cents/pound) to a Texas High Plains loan rate. one must subtract about 8 cents/pound. The cotton target price must be reduced by the same amount to avoid overstating the deficiency payment rate by about 8 cents/potmd. minimum tax. The operator pays the excess of the alternative minimum tax over the regular income tax liability. If a net operating loss is incurred it is carried to the next year. lf the operator purchases additional machinery in conjunction with growth, the income tax liability is recomputed based on the additional cost recovery allowances and investment tax credits. When additional machinery is purchased, it is assumed the property qualifies under ACRS. This allows the operator to utilize first-year expensing and investment tax credit for the purpose of reducing the current year’s income tax liability. Income tax rate schedules and provisions for the 1981, 1982, 1983, and 1984 income tax acts and President Reagan’s Treasury II tax proposal are included in the model, as well as an optional procedure to develop tax rate schedules for 1985-90 based on changes in the CPI. Growth in terms of purchasing or leasing additional cropland is considered at the end of the tax years if the analyst has selected this option. The availability of cropland for lease and/or purchase can be predetermined each year, or the availability can be random with the probability distributions for land availability provided by the analyst. The farm operator purchases the largest parcel he/she can afford while keeping the farm’s long-term equity ratio above its minimum acceptable level. The operator is allowed to borrow against existing equity in farmland to meet up to 5O percent of the land downpayment, but machinery downpayments must be paid in cash. The operator is permitted, by option, to purchase additional farm machinery once the operation grows to where the current machinery complement is insufficient to handle the total cropland in a timely manner. Decisions to lease additional cropland are made in a similar fashion. If machinery is purchased, accrued income taxes are recomputed as described earlier. After simulating the growth aspects of the farm, the model computes the farm's end of year balance sheet. The model then updates the farm size and prepares to simulate the next year of the planning horizon. The annual process is repeated until the entire planning horizon (the inner loop in Fig. l) has been simulated. For a deterministic analysis. the model prints various output tables at this point. Capabilities and Uses of the Model A large number of options are programmed into the computer program. For example. rather than designing both a farm growth version of FLIPSIM and a static farm size version. a farm growth option was incorporated into the basic computer program. By doing this, tremendous economies to size were obtained in the development of the model. Also. one model may now be maintained rather than maintaining many different versions of the same basic model. The major options available to the analyst are summarized in Table 1. Many of the options in the model are independent so the number of combinations and permutations is large. Several farm policy options are linked to avoid redundant combinations, e.g.. the analyst may not simulate a crop insurance program and a low yield disaster program at the same time. The same set of input data for a typical farm can be simulated using deterministic or stochastic values for prices and yields by changing one character on the Option Card (Input Card 2). Similarly. a typical farm can be simulated under two types of depreciation rules with a single change on the Option Card. This flexibility enhances the usefulness of the computer program which constitutes FLIPSIM V. Since completion of the first version of FLIPSIM in 1981. the model has been used extensively at Texas A&M University. The model has been used in two Ph.D. dissertations. Smith (1982) used the model to evaluate the impacts of alternative farm policies on different size cotton farms in the Texas Southern High Plains. His analyses estimated the structural bias inherent in 7 TABLE 1. SUMMARY OF THE OPTIONS IN THE FLlPSlM V COMPUTER PROGRAM Decision Variables Type of Analysis _ Number of ears simulated _ If the mode is run stochastic Type of Farm: Cro farm Bee cattle ranch Dairy Cropmix and Tenure: Cro mix Ful owner. tenant. or part owner Part owner Tenant operator Landlord Marketing Rental costs Farm Growth: Growth throu h land acquisition Means of crop and acquisition Cropland ayailability Lever eiiisting equity _ _ Capability to change costs. yields, prices, machinery as farm grows No. of larger size farms one can provide data for Machiner '. Buildings and Breeding Stock: Num er machines owne Number machines leased Means of disposal Depreciation Cost recovery _ First year 6_Xp€l'lSlI‘l%: Reduce basis for lT General: Use surplus cash to prepay principal Sell cro land to survive Family iving expenses Farmland market values Farm Policies: Price sup ort (recourse and/or nonrecourse) lndirect ‘OR usin" price sup ort for l year Direct. entr ' FOR bypassing tiie price support Release F0 stocks at release price or trigger price Direct entry F‘_()R price different from loan rate Target price (tixed or tied to loan) Low 'ield dissaster program FCl crop insurance Acreage diversion Acreage set-aside Marketing quota Acreage allotment Marketing certificate Marketing loan Number of years FOR interest is char ed on the loan Adjust FClLinsiirance premiums for oss records Payment limitation Scale program benefits by size (acres) Scale program benefits by size (cash receipts) Federal Income Tax Policies Maximum interest deductions Cash vs. accrual accounting Adust income tax rates for changes in CI’! after 1084 Reduce basis for_l"_l‘(“ Income tax provisions Stochastic Features: g Types of distributions Random values for cro _s Random values for bee cattle Random values for dairy Variance over time Number or Types of Options Available to Analyst --deterministic or stochastic --1 to 10 ears _ --2 to 3 iterations --b alternative distributions for selecting --4 alternative means for presenting the statistical analysis --4 alternative means for presenting cummulative distributions --1 to ll) crop enterprises --_O to 5 beef enterprises _ _ --includes or does not include a dairy enterprise --constant or_ variable (LP or QP) --any beginning e uity level --cropshare or cas lease --cropshare or cash lease --cro share or cash lease to the tenant --4 a ternatives for marketing crops --constant, increasing over time. or a function of land value --the farm ma or may not grow --purchase an /or lease_ _ _ -—.._options for land availabilit --either no leverage possible or lever up to 50% of downpayment --yes or no --0 t0 l() --1 to 0Q machines --1 to 5U machines --traded-in or cash sale "straight line or double declininiglbalance --straight line or accelerated (AC S) --yes or no --yes or no --yes or no --yes or no “can be calculated l4 different ways --either exogenous or endogenous --can be t.urned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year, for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --can be turned on or off each year. for each crop --() to 3 years --yes or no --_ves or no --yes or no --yes or no --yes or no --yes or no --yes or no --yes or no "1982, 1984.01’ 1985 --independent and multivariate normal --independent and multivariate empirical --independent and multivariate triangular --annual crop prices and crop yields --annual prices lor culled cows. heifers. steers. replacement heifers. culled herd bulls. stockers. and feeders. --annual rices for milk. culled cows. replacement cows. calves. airy feed. and annual milk production per cow --relative variance for empirical and triangular pdf's can be constant or altered over time. different farm programs. The model was used to evaluate the impacts of alternative farm programs. financial bailout programs, technology, and federal income tax provisions on different size crop farms in Texas, Mississippi, Illinois, Nebraska, and the Southern Great Plains, as well as for different size dairy farms in Minnesota, Florida, California, and Arizona (OTA 1985). Bailey (1983) used the model to evaluate technical marketing strategies for cotton producers on the Texas High Plains. Daily futures and cash cotton prices were simulated in the model and technical marketing strategies (moving averages and channels) were evaluated as to their contribution to the survival and growth of a whole farm (Bailey, Brorsen, and Richardson 1984). Lippke is extending this work to include options. Shirley (1981) used the model to determine the impacts of a limited number of farm policies on the survival of the typical size Texas High Plains cotton farm. In addition, the model has been used to evaluate the impacts of various farm programs on typical producers in selected regions of Texas. Richardson and Nixon ( 1982a) used the model to evaluate probable producer preferences for various farm policies including a cotton farmer owned reserve. In this analysis, alternative farm policies were simulated stochastically for 5O iterations. The estimated probability distributions for after-tax net present value were compared using stochastic dominance with respect to a function for risk adverse, risk loving, and risk neutral producers. Lemieux, Richardson, and Nixon (1982) used the model to compare various levels of the FCIC all-risk crop insurance to the low yield disaster program for cotton producers on the Texas High Plains. Producer preference for the insurance options was determined using stochastic dominance with respect to a function on the simulated probability distributions for after-tax net present value. Duffy, Richardson, and Smith (1984) used the model to evaluate the impacts of alternative farm policies and alternative levels of price variability on the survival and growth of different size Texas cotton farms. Five levels of price variability (normal. two levels greater than normal, and two levels less than normal) were simulated for a 511 acre farm and a 1.088 acre farm under selected provisions of the 1981 farm bill. Richardson, Nixon. and Smith (1982) used the model to compare the contributions of the 1981 Tax Act to those of the 1981 Farm Bill for a typical High Plains cotton producer. Ray, Richardson, and Li (1982) reported an inter-regional comparison of the effects of the 1981 Farm Bill on feed grain producers in Texas and Illinois. Grant. Richardson, Brorsen, and Rister (1984) evaluated the effects on rice producers of changing the rice farm program and the general economy in the early 1970’s on Texas rice producers. A similar study was done by Brorsen, Richardson. Grant, and Schnake (1984) for changes in the wheat farm program. Baum. Richardson, and Schertz (1984) used an early version of the model to evaluate alternative inflation scenarios and farm policy outlooks on the survival of cotton~sorghum producers in Texas. Several applications of the model have been made in the area of income tax policy (Richardson and Nixon 1982b; and Nixon and Richardson 1982). The model has been used to compare changes in income tax regulations from 1980 to 1981. both deterministically and stochastically. A more recent analysis compares the effects of the 1981 and 1982 income tax changes to the income tax provisions for 1980 (Richardson and Nixon 1984a). Richardson and Nixon (1984b) evaluated 16 alternative depreciation (cost recovery)/expensing/investment tax credit/disposition strategies for a typical farm to determine which strategy was preferred based on expected utility. The results indicated that if risk was present, a risk averse operator would prefer a straight line cost recovery system. and if no risk w'as present. the operator would prefer accelerated cost recovery. A number of applications of the model in the area of farm management have been made thus far. Richardson, Lemieux, and Nixon ( 1983) used the model to evaluate the probable benefits to new entrants from machinery leasing, land leasing, and/or land purchase. Their findings indicated that owning land and renting machinery increases the probability of survival for a new entrant relative to the traditional approach for entering farming, namely renting land and owning machinery. Richardson and Bailey (1983) used the model to deterministically analyze the debt servicing capacity of typical crop and livestock producers in 13 regions of Texas. The model was also used to evaluate the economic impacts of the 1982 disaster (hail storm) on typical cotton producers in the Texas High Plains. Further extensions in the area of farm management are underway at Texas A&M University by Rister, by Ellis, and by VanTassel. Perry, et al. (1985) used the model to evaluate alternative cropping patterns and crop share arrangements for Texas rice farmers. The model was run using stochastic prices and yields to generate probability distributions of after-tax net present value for a typical tenant rice producer under alternative share arrangements (and cropping patterns. The estimated probability distributions were compared using stochastic dominance to determine the utility maximizing crop mix/crop share arrangements for tenant rice farmers with alternative preferences for risk. Numerous sensitivity analyses were performed for the purpose of identifying the impact of key assumptions relating to stochastic yields and prices, government programs, and financial criteria, among others. The study by Perry, et al. ( 1985) has thus far been the most extensive application of FLIPSIM V and the most complete in its interpretation of results. Model Validation and Verification There are numerous views on validation of economic models. These views can be separated into three methodological positions--rationalism, empiricism. and positive economies (Naylor 1971). Rationalism holds that economic models are based on postulates that are of unquestionable truth so the problem of validation is merely a problem of identifying the underlying assumptions in the system to be modeled. Empiricism holds that observation of results is the only source and the ultimate judge of knowledge. Empiricism thus rejects those postulates and assumptions that can not be empirically verified. Positive economics holds that the validation of a model rests on the model‘s ability to predict the dependent variables and not on the validity of the basic assumptions in the model. A middle of the road approach to model validation which recognizes the benefits of predictability, empirical relationships, and assumptions is preferred by economists who have been faced with the validation problem (Ray and Richardson 1978). Naylors (1971) multistage validation is one such approach. The first stage is a formulation of the set of postulates describing the system. The second stage consists of a validation of the tentative hypotheses outlined as postulates in stage one. Stage three calls for testing the model’s ability to predict the behavior of the system. This multistage approach to model verification and validation was applied to FLIPSIM V. Stage One of Validation The process of identifying the underlying postulates for a firm level policy simulation model is more straightforward than, for example. a macro-agricultural, policy simulation model (Richardson and Condra 1981). The basic underlying functions of a farm simulation model include: crop and livestock production. cash receipts. variable and fixed costs. family living expenses, asset valuation. farm growth. machinery replacement. income taxes. loan acquisition and repayment. and farm programs. These basic functions. excluding farm policies. have been included in earlier firm IO i i 1 level simulation models (Hutton and Hinman 1971; Patrick and Eisgruber 1968; Hardin 1978; and Richardson and Condra 1981). An extensive review of these and other farm simulation models was conducted before developing FLIPSIM. The basic functions that must be performed annually by a farm manager were specified for the FLIPSIM V model to conform to accepted farm management, financial, and accounting principles. To insure the model included the necessary functions for a generalized farm simulation model, the equations necessary to estimate all of the variables in a detailed set of financial statements (income, cash flow, and balance sheet) were initially specified. Next the accounting functions and identities necessary to calculate depreciation, federal income taxes, and self-employment taxes were developed from the federal tax codes. The equations necessary to simulate the impacts of alternative farm policies on individual farmers’ production and cash receipts were developed from USDA publications (Johnson, et al. 1982; and Johnson and Ericksen 1977). Behavioral relationships in a farm simulation model, such as growth, decay, family living, machinery replacement, timing of cash sales, and farm program participation were identified and included in the model. For each of these behavioral relationships, two or more equations for simulating a farm operator’s response were programmed. The alternative formulations for these behavioral relationships were based on (a) options provided by law (e.g., alternative depreciation methods). (b) alternative specifications found in the literature (e.g., family consumption functions), and (c) the results of producer surveys conducted by researchers at Texas A&M (Smith 1982; Perry, et al. 1985) and other universities (e.g., Patrick and Eisgruber 1968; Hardin 1978). Stage Two of Validation Stage two involved empirically testing the basic postulates or relationships in the model. For an econometric model, stage two involves estimation and statistical testing of the parameters in the model. In the case of a firm level simulation model such as FLIPSIM V, there are virtually no parameters in the model to be estimated. Thus, stage two consisted of programming the basic functions and relationships into a working model and testing their numerical accuracy when used with other functions and the stochastic elements of the model. The stochastic components of the model were tested to insure that they produced random prices and production levels from their assigned distributions. Two separate tests have been conducted to determine how many iterations are necessary to obtain an acceptable estimate of the cumulative probability distribution for net present value. The model was simulated for 300. 250. 200. 100, 50, and 25 iterations. The results of these tests indicated that 50 iterations produced the same parameter values and shape for the net present value cumulative probability distribution as 300 iterations. Four seminars describing the basic relationships in the model were presented to agricultural economists at USDA and Texas A&M University during the formative stage of model development. These seminars provided a format for obtaining peer review of the basic postulates in the model. This stage of model validation is a continual process as the model is expanded to simulate different types of farming situations and policies (e.g., dairy farms, farrow-to-finish hog farms. alternative farm programs, new income tax provisions). Feedback from researchers at Texas A&M University and journal reviewers continues to provide peer review of the basic postulates in the model. ll Stage Three of Validation Stage three calls for testing the model’s ability to predict the behaviour of the system it represents. Various tests of a model’s predictive ability have been suggested (Van Horn 1971, Naylor 1971). Naylor (1971) argues that one cannot determine a model’s predictive value by observing its ability to reproduce history. Rather, one must compare the model’s predictions to (a) parallel predictions of other models, (b) theoretical predictions, or (c) actual outcomes for the system being modeled. Van Horn (1971) has proposed using a Turing Test for evaluating the theoretical soundness of predictions and agreement with parallel research. A series of Turing Tests to evaluate FLIPSIM’s predictive ability were conducted with agricultural economists at Texas A&M and USDA. Numerous predictions of the model have been reviewed by scientists specializing in farm policy, farm management, finance, and income taxes to test the theoretical soundness of the predictions and agreement with other research in these areas. Corrections to the model were made when errors in logic were discovered or improvements in specification were recommended. In addition, numerous anonymous reviewers for the American Journal of Agricultural Economics, the Western Journal of Agricultural Economics, the Southern Journal of Agricultural Economics, and the Agricultural Economics Research journal have reviewed predictions of the model for theoretical accuracy and consistency. Model predictions have also been reviewed by farm operators in several regions of Texas to provide feedback as to the model's ability to simulate different types of farms under a variety of conditions. Sufficient time has not elapsed to allow comparison of a complete 10-year FLIPSIM prediction to the outcome for particular farms. However, the results of FLIPSIM predictions reported by Richardson and Bailey (1983), Grant, et al. (1984), and Smith (1982), have been tentatively verified by empirical observation. In 1983, Richardson and Bailey predicted that typical highly leveraged tenant rice producers in the Upper Gulf Coast of Texas would be forced out of business within 10 years. A large number of tenant rice producers were forced out of business in this region between 1982 and 1983. Because of the magnitude of this adjustment problem, the Texas rice industry is the subject of considerable research by the Texas Agricultural Experiment Station. A more detailed study of rice producers in the Texas Gulf Coast by Grant. et al. (1984) confirmed the results of Richardson and Bailey (1981). The latter study simulated representative Texas rice farms under alternative farm policies. The results for the 1960s type of farm policy indicated typically leveraged tenant and part owner rice farms had a high probability of remaining solvent for 10 years and being an economic success. By contrast. these same farms had a significantly lower probability of being an economic success and a much lower probability of remaining solvent for 1O years under a post-1975 farm policy. The simulation results for the 1960’s type farm program for rice are consistent with the performance of the Texas rice industry during the 1960’s. Based on information provided by local financial institutions. the results for the post-1975 farm policy are also consistent with the performance of many Texas rice farms for 1976-84. Further analysis by Perry, et al. (1985) also indicates that there are significant differences in the probability of survival and average net present value among tenant, part-owner, and full-owner rice producers in Texas. Based on extensive simulation analyses of different size Texas Southern High Plains cotton farms, Smith (1982) predicted a shift toward fewer mid-size farms and more small and very large farms. This predicted change in farm structure for the study area has recently been reported in the Census of Agriculture (USDC 1984). These types of studies do not validate the ability of FLIPSIM V to predict the behavior of a particular farm operator. However. they verify the ability of the model to predict the economic well-being of farm operators in different regions which was the original purpose for developing FLIPSIM. 12 Model validation is a continual process. As the model is expanded and improved, the three stages of validation are repeated for the modification as well as for the model as a whole. Peer review has been, and will continue to be, an integral part of this validation process--both in terms of review of the basic postulates in the model and the predictions of the modelf‘ Description of the Computer Program FLIPSIM V is programmed in FORTRAN and consists of more than 9,400 source statements. The model requires over 500K of object code and 550K of array storage when compiled in FORTRAN H Extended on an Amdahl 470 mainframe computer. The full model can run on a 16/32 bit microcomputer equiped with 1024K, a Fortran 77 compiler, and a hard disk. The computer program for FLIPSIM V is made up of a series of subroutines that perform specialized operations. A schematic of the order in which these subroutines are called by the Main program and the design of the overall computer model is presented in Fig. 1. The model consists of three parts. The first part processes the analyst's data for the simulator (a detailed schematic of this section is provided in Fig. 2). The second part consists of numerous subroutines that perform the calculations and are called once each year of the planning horizon. The third part of the model analyzes the stochastic results and prints all output tables (see Fig. 3 for a detailed schematic of this section). It is the second part of the model which is of primary interest to analysts. since that is where the calculations are performed. This section describes the operations performed in each of the subroutines with the major emphasis on those subroutines in the second part of the computer program. Subroutines DATA1-DATA7 FLIPSIM V processes the information for one farm (data set) at a time. Since the analyst supplies all input data for each farm, the model can simulate multiple versions of the same farm. For example, a given farm can be simulated for several alternative loan rates or financial bailout policies. Alternatively, one can analyze farms for different regions in the same run. A complete description of the input for the model is provided in the last section of this report. Subroutines DA TAI and DA TAZ read all of the input data for the farm to be simulated (Fig. 2). After processing each input card image. a message to that effect is written to unit 10:“ Error messages due to cards being out of order are written to unit 6 prior to causing the program to stop. If an error is encountered in reading the input. the analyst can also consult the unit 10 output file to locate where the problem occurred. Only minor calculations, using the user’s input data. are made in DATA] and DATAZ. 4Future validation will benefit from agricultural economists at Utah State University. University of Arkansas. Oklahoma State University. Louisiana State University. Auburn. Clemson. Mississippi State University, University of Minnesota. University of Illinois. and USDA. 5Unit 10 is an output source identified in the job control language (JCL) for the model. Unit l0 should be attached to the line printer if the analyst wants a debug list of card images processed. lf such a list is not wanted. unit l0 can be attached to a dummy sysout unit. 13 UNIT5— read input data for WV one farm DATAl ¢ s. <-—-——- DATA2 = UNITl0— writes a ———+ record of cards processed DATA3 UNIT6— errors process = encountered on reading input data data are printed UNIT6—write a summary DATA4 +——-——» of all options to be used DATAS UNIT6—write tables of & +—-———+ all input data except DATA6 dairy information UNIT6—write tables of DATA7 +—————» input data for dairy enterprise Figure 2. Schematic of the functions performed in the input section of the model. 14 UNIT9—print all major PRINTl +—-———+ matrices in the program UNIT6-print income PRINT2 +—————+ statement, cashflow, & balance sheet, and PRINT3 production summary UNIT6-print output PRINT4 +—-———+ table for dairy enterprise ITSUM: for a stochastic analysis, pre- pare values for a statis- tical analysis UNIT6-print statistical STAT: summary for perform +———» key output statistical variables analysis for stochastic ¢ 7 simulation UNIT3—store summary statistics UNIT4—store the net pres- ent value cdf Figure 3. Schematic of the functions performed in the output section of the model. 15 Subroutine DA TA3 processes the input data to develop necessary values that are either not provided by the analyst or are provided in a different form than the model requires. If the farm being simulated includes a dairy, this subroutine determines the replacement calendar year for each bull, the total value of cows, heifers, and bulls, and the cost of bulls purchased. If the farm may grow by acquiring cropland and the analyst provided information for alternatively larger farms, the model uses these data to establish the mean crop prices and yields for the larger farms. Accumulated depreciation for each item of machinery and each head of purchased breeding stock is calculated in DATA3. Those items purchased prior to 1981 are depreciated using the analyst's choice of either the straight line or the double declining balance method. Additional first-year depreciation is used for all pre-1981 items if first-year expensing is elected by the analyst. For items placed into use after 1980 and before 1985, the model uses either the straight line method or the ACRS to calculate accumulated depreciation. In making these calculations, it is assumed the operator claimed first-year expensing on all items placed into use after 1980 if this option is elected for future years. Information to amortize existing long— and intermediate-term debts is processed next. Since the analyst can provide the debt-to-asset ratio and original loan amount information several ways, the model determines what form these values are in and processes them accordingly. If the original balance of the loan is not provided, the model approximates this value based on: length of the loan, interest rate, outstanding debt for the asset, capital gain rate for year t-l, current market value of the asset, and minimum downpayment. Beginning net worth for the farm is calculated on both a book value and a market value basis. Net worth takes into consideration all debts and assets, including cash on hand, off-farm investments, land, buildings, machinery, all beef cattle, and all dairy stock. Total debts include accrued income and self-employment taxes due in year 1 of the planning horizon. Information to simulate random values from the multivariate empirical distribution for prices and yields are processed next. The multivariate empirical distribution for the dairy and beef enterprises are also processed in this subroutine. Percent deviates about the mean, provided by the analyst, are sorted from low to high for use by a table lookup function in Subroutine STOCH. Subroutine DA TA4 prints the FLIPSIM V cover page and the page summarizing the options selected for the particular analysis. A sample of the option page and other output from the model is provided in Appendix C. Each of the options activated on Card 2 of the input data are checked in subroutine DATA4 and a message written, indicating the setting for each option. Subroutines DATA5 and DA 7146 print a summary of all input data except the dairy herd data (Fig. 2). Appendix C includes a sample of the input summary printed by DATA5 and DATA6. At the end of this subroutine, the compound inflation rates for calculating inflated production costs, land values. etc. are calculated using the annual inflation rates provided by the analyst. These calculations are made here to avoid repeating this same calculation in the simulation loop. Subroutine DA TA7 prints the summary tables for all input data pertaining to the dairy enterprise (Fig. 2). Appendix C includes a sample of the output from this subroutine. The last function of this subroutine is to store all information describing the initial economic environment for the farm in a series of backup arrays. These backup arrays are used to reinitialize all working files in the model at the outset of each iteration for a stochastic simulation. This insures that each iteration in a stochastic simulation uses the same set of beginning data, program options. inflation rates. interest rates. yields. costs. etc. 16 .4 m. Subroutines CROPMX and PIVOT1 Subroutine CROPMX is the second subroutine called each year of the planning horizon (Fig. 1). The purpose of CROPMX is to determine the farm’s crop mix each year of the planning horizon using one of three methods. First, the analyst can predetermine the crop mix each year of the planning horizon. Second, the crop mix can be developed from a profit maximization LP algorithm. Third, a QP algorithm which seeks to maximize expected utility can be used to determine the crop mix. Before determining the crop mix each year, this subroutine updates values for off-farm income, minimum cash reserve, and non-taxable income by inflating‘ their base values using the analyst’s annual percentage changes for these variables. CROPMX next determines which set of cost data to use for the farm if the analyst has specified that the farm may grow by purchasing and/or leasing cropland. Information for different size farms, beyond the initial farm size, are provided by the analyst. These data include cost of production for each crop; machinery requirements; crop prices, yields and labor requirements; and flexibility constraints on the crop mix. The model annually determines which set of farm size data to use based on total cropland acreage available for that year. This section is skipped if the analyst has specified on the Option Card that the farm may not grow. One of the farm policy options which can be used is an option to discontinue direct farm program benefits once a farm has grown beyond a designated size. The analyst may either prevent participation in all farm programs through this program option or prevent participation in all farm programs except the federal crop insurance program. If the farm reduces its size below the target level of acres or crop sales, it again becomes eligible for farm programs. Availability of farm programs is critical to the crop mix decision. The model determines whether the operator is eligible to participate in particular farm program provisions prior to determining the crop mix. if the crop mix is allowed to vary from year to year. The threshold farm size designated by the analyst for curtailing program benefits can be based on either total acreage or value of farm program crops, e.g., farms over 1,500 acres are not eligible for all programs, or farms that produce more than $100,000 in farm program crops are not eligible. The model prevents farm program participation by disabling the policy options once the farm grows beyond the analyst’s specified limit. The total value of farm program crops used for determining program eligibility is calculated by summing the product of each crop’s loan rate, mean yield, and normal planted acreage for the year being simulated. The resulting total receipts are reduced for the portion of each crop paid to the landowner on share rented land. In the case of a predetermined crop mix, the model uses the analyst’s predetermined planted acreages for year 1 in all years of the planning horizon. If the farm is permitted to grow and the crop mix is to be constant, the initial crop mix is maintained by using the initial ratio of planted acres for each crop and total cropland to determine the crop mix after the first year. Harvested acreage equals planted acreage times the fraction of planted acreage normally harvested for each crop, whether the crop mix is fixed or varies. The model provides an option to determine the crop mix after year 1 based on a profit or utility maximization algorithm (LP or OP). To use an LP or QP algorithm the model must calculate expected net returns per acre for each crop. Expected crop prices and yields are calculated using a 3-year weighted average of past values (the weights are 0.7. 0.2. and 0.1 for values 1-. 17 2-, and 3-years-old, respectively)!’ [For years 2 and 3 of the planning horizon, expected cash receipts are calculated using years 1 and 2, respectively, of prices and yields.] The product of expected prices and yields per acre provides expected total receipts per acre which is adjusted for the farm policies available to the operator before subtracting expected costs of production. Expected cash receipts are decreased by the net effect of acreage reduction programs (set aside, diversion, or acreage limitation) if the analyst has selected one of these programs. Expected cash receipts are increased if the crop’s expected price is less than the loan rate or the direct FOR entry price, given that the crop is eligible to participate in these programs. The expected deficiency payment per acre (program yield times payment rate) is added to each crop’s expected cash receipts if the expected price is less than the target price and the program is in effect for the particular crop. Expected payments for low yield disaster or federal crop insurance are added to each crop’s expected cash receipts when these programs are in effect and the expected yield is low enough to trigger a payment. Expected net returns per acre (Cfs for the LP and OP) are calculated by subtracting the expected non-labor, non-interest variable production cost per acre from expected cash receipts. Expected variable costs are the sum of per acre input costs inflated for annual increases in production costs. Subroutine PIVOT1 is called from CROPMX to solve for a profit maximizing crop mix at this point. Upon returning from PIVOTI, or after using the fixed crop mix provided by the analyst, subroutine CROPMX reduces the planted and harvested acreage if an acreage reduction program is in use. For an acreage set aside or diversion program, the model reduces planted acreage for each crop by the percentage reduction specified for that crop in that particular year. Harvested acreage equals planted acreage minus acreage set aside and/or diverted. Slippage from an acreage reduction program is accounted for by calculating the production that will actually be forthcoming on the fraction of the land set aside through more intensive use of inputs on land in production. The added production costs associated with this phenomenon are calculated in Subroutine VCOSTS. When an acreage limitation farm program is being simulated, the analyst should not use the LP or OP since a crop’s reduced acreage is a percent of its base acreage and the base is fixed by the analyst. Subroutine PI VOT1 sets up the LP/QP tableau for a QP solver (Subroutine CNTRL) written by Harpaz and Talpaz (1982). The same algorithm is used for the LP and OP options since a QP problem with a zero risk aversion coefficient produces the LP result. The first time the subroutine is called_, the Aifs, covariance matrix of net returns, and right-hand sides are set up and stored on unit 16.’ Each successive time the subroutine is called, unit 16 is read and necessary changes to the right-hand sides are made based on the farm’s current size. As farm size increases over time, changes are generally made in total acres. minimum and maximum acres for each crop, total irrigated acres, total hours of labor available from family members and full-time employees, as well as net returns per acre for each crop enterprise. The tableau has 12 monthly labor constraints for each crop enterprise and it permits the farm operator to buy part-time labor each month at the analyst’s specified hourly wage rate (Fig. 4). The right-hand sides for labor are the monthly totals of labor available from all full-time employees and (‘Weights for computing the 3-year moving average of prices and yields were set so the greatest weight was on the most recent year and the least weight was placed on year t—3. These weights can be changed by the analyst by simply modifing the appropriate lines in Subroutine CROPMX. ifUnit l6 is a sequential access data set attached to a temporary storage unit. such as a disk or a tape. If attached to a hard disk. the data set must have at least 18 tracks. 18 Activities -Purchase Labor By Month- -Crop Production- Constraints Jan Feb Mar Dec Crop 1 Crop 2 Crop n RHS Obj. function -m -m -m -m n n n --- Total Acreage l) l) 0 l) 1.0 l.l) l.l) =total acres Jan Labor -l.l) l) 0 0 L,, L,2 L,,, sJan hours Feb Labor 0 -l.l) 0 0 L2, L22 L2,, sFeb hours Mar Labor l) 0 -l.l) l) L3, L32 L3,, sMar hours April Labor 0 0 0 l) L4, L42 L4,, sApr hours May Labor l) 0 0 l) L5, L52 L5,, sMay hours June Labor 0 O l) l) L,,, L62 L,,,, sJune hours July Labor 0 l) l) 0 L7, L72 L7,, sJuly hours Aug Labor 0 l) l) l) L8, L82 L8,, sAug hours Sept Labor 0 0 0 l) L,,, L92 L.,,, sSept hours Oct Labor l) 0 0 l) L,,,, L,,,2 L,,,,, sOct hours Nov Labor l) l) l) O L,,, L,,2 L,,,, .<_Nov hours Dec Labor l) 0 l) -l.l) L,2, L,22 L,2,, sDec hours Irrigation 0 0 0 l) I, l2 l,, slrrigated acres Max Crop 1 l) l) l) l) 1.0 l) l) sCrop l Max acres Max Crop 2 0 l) l) l) l) l.l) l) sCrop 2 Max acres Max Crop n l) l) l) l) 0 l) l.l) sCrop n Max acres Min Crop l l) l) l) l) l.l) l) l) zCrop l. Min acres Min Crop 2 l) l) l) l) l) l.l) l) _>_Crop 2 Min acres Min Crop n l) l) l) l) l) l) l.l) zCrop n Min acres Figure 4. General description of the crop mix linear programming tableau in FLlPSlM V. 19 unpaid family labor. There is no constraint on the availability of part-time labor that can be hired each month. A constraint in the tableau requires the operator to use all cropland. This constraint can be modified if it creates an unrealistic situation for the farm modeled. Crops are differentiated as either irrigated 0r non-irrigated, and constraints in the tableau force the crop mix to adhere to the limits on the number of irrigated acres. Flexibilities (upper and lower bounds) on the acreage of each crop are provided by the analyst and are used for the final set of constraints in the tableau. The tableau is printed using unit 8 each year for a deterministic simulations The tableau is not printed for a stochastic analysis due to the large volume of output that would be generated. The covariance matrix of net returns per acre for all of the crop enterprises is provided by the analyst only when the QP is used to determine the crop mix.9 The risk aversion coefficient for the farm operator is also provided by the analyst. If the coefficient equals zero and the QP option is elected, the crop mix solution is the same as for the LP option. Subroutine STOCH Subroutine STOCH is the first subroutine called each year of the planning horizon (Fig. 1). Annual crop yields, crop prices, livestock prices, milk prices, and dairy production values are determined each year in this subroutine. When the model is run deterministically. the analyst’s values for each enterprise’s prices and yields are copied to their appropriate locations in the working files each year of the planning horizon. In the stochastic mode, the model generates random values for yields and prices each year from the independent or multivariate normal, triangular, or empirical probability distribution specified by the analyst. Technical information on generating random numbers in simulation models is provided in Law and Kelton (1982); King (1979); Naylor (1971); Clements, Mapp, and Eidman (1971); and Richardson and Condra (1978). To generate random numbers from the normal distribution, subroutine STOCH calls GAUSE to generate independent standard normal deviates each year. These deviates are multiplied by the factored covariance matrix for crop yields and prices and the product is added to the vector of mean yields and prices for the relevant year. Since the analyst provides mean prices and yields for each year of the planning horizon. there can be a trend or cycle in the distributions employed. Random values can be drawn from a multivariate or independent normal probability distribution for annual crop prices, crop yields, beef prices, dairy prices, and milk production per cow. Prices for the beef enterprises are correlated to themselves but are independent of the other random values in the model. A similar situation exists for random prices and production for the milk enterprise. Triangularly distributed random values for annual crop prices. crop yields, and beef cattle prices can be drawn from the analyst's distributions (minimum, mode, and maximum) for these variables. Subroutine GAUSE is called each year of the planning horizon to generate independent normal deviates. These deviates are multiplied by the factored correlation matrix for the random variables to be correlated, and the product is transformed to the unit scale (0 to 1.0) using the error “Unit 8 is an output source identified in the JCL for the model. Unit 8 should be attached to the line printer if the analyst wants a printout of the LP/QP tableau each year of the planning horizon. This output can be avoided by attaching unit 8 to a dummy sysout unit. qThe covariance of net returns can be calculated based on historical net returns for the crop enterprises to be simulated. Caution must be taken to define net returns for each crop as they are defined and calculated in the CROPMX subroutine. 2O function (ERFF).10 The transformed values are then used in the triangular distribution formula to scale the values for the analyst’s minimum, modes, and maximum values. The result is a set of appropriately correlated values for annual prices and yields that are distributed multivariate triangular. The general procedure for correlating non-normal distributions has been described by Richardson and Condra (1978) and by King (1979). Empirically distributed random numbers can be developed annually for crop prices, crop yields, beef cattle prices, dairy prices, and milk production per cow. Subroutine GAUSE is called each year to generate independent normal deviates. The deviates are multiplied by the factored correlation matrix for the variables to be correlated and the product is transformed to the unit scale (0.0 to 1.0) using the error function (ERFF). These transformed values are used in the inverse transformation formula to calculate random values from an empirical cumulative probability distribution. See Law and Kelton (1982) for a discussion of the procedure. An option is included in the model which allows the analyst to increase or decrease the relative variability of the empirical probability distributions for prices and yields. This option allows the variance about average prices to increase over time to coincide with the fact that more is known about price in year 1 of the planning horizon than year 10. The distributions are increased or decreased independently for each crop to allow for added flexibility. The last function performed by subroutine STOCH, each time it is called, is to check all random values to insure none are less than zero. If a value is less than zero, it is set equal to zero. Additionally, the subroutine checks each random value to insure that it is within the limits of its distribution if it is drawn from a finite (bounded) distribution. If rounding error causes a random value to be less than its minimum or greater than its maximum, the value is set equal to the appropriate limit. Subroutine DAIRY As the name implies, this subroutine simulates a dairy enterprise on the representative farm. When the farm being simulated has no dairy enterprise, this subroutine is skipped. A dairy enterprise in the model generally consists of a milking herd, replacement heifer calves under 12 months. replacement heifers over l2 months, and herd sires. However, a California type dairy consisting of only milk cows can also be simulated. The annual cash receipts for milk are the product of annual production per cow, number of cows milked. and the annual average price received for milk. These values are separated into a series of monthly calculations using seasonal indices for prices and production so the monthly cash flow for the dairy enterprise could be analyzed. Monthly labor requirements for the herd are calculated for cows milked, as well as dry cows and replacement heifers fed each month. These labor requirements are combined in Subroutine VCOSTS with labor requirements for the crops and beef cattle herd to determine the farm's monthly requirement for part-time labor and total labor costs. Interaction between the dairy herd and crop production is handled in this subroutine and the RECPTS subroutine. For each crop produced on the farm, the model calculates the total quantity fed to the dairy herd. Annual feed requirements per head for each crop (‘e.g.. bushels of corn/cow or tons of hay/heifer) are multiplied by the number of head in that category to calculate total feed WERFF is a fortran subroutine for integrating a standard normal distribution from minus infinity to x, where x is a deviate drawn at random from a normal distribution. 21 requirements of each crop. The total quantity of each crop fed to the dairy herd is calculated by summing feed requirements over the dairy herd categories. Surplus and/or deficit crop production is reconciled in subroutine RECPTS. Cash receipts from the sale of calves and replacement heifers are calculated based on the analyst’s replacement schedule, calving rates, and prices. Prices are either the annual average values provided by the analyst or random values drawn from specified distributions. The model sells a specified fraction (provided by the analyst) of all live calves at their annual per head price. One-half of the culled replacement heifers over 12 months of age are assumed to bring a price equal to 50 percent of the replacement cost for cows, while the other half sells for 4O percent of the replacement cost for cows. These fractions assume one-half of the heifers were culled due to sickness or failure to breed while the remainder would go into another milking herd. If the analyst prefers a different set of fractions for pricing culled replacement heifers, new fractions can be entered. The non-labor, non-interest costs for the dairy enterprise are calculated next. The analyst must provide initial annual per head non-labor, non-interest cash costs for milk cows, dry cows, heifers, calves, and bulls and the annual inflation rate for these costs over the planning horizon. These cash costs should not include the costs for repairs, taxes, or crops raised on the farm as they are accounted for elsewhere. Variable production costs are calculated as the sum of the products for these inflated costs and the number of head in each category. The total non-labor, non-interest variable production cost for the dairy is added to other variable costs in subroutine VCOSTS, prior to calculating interest costs on operating capital. Purchased livestock (bulls and dairy cows) are eligible for depreciation (cost recovery under the 1981 and 1982 federal income tax acts). Bulls and cows purchased before 1981 are depreciated using the analyst’s information for purchase price, economic life (depreciation life)“, salvage value, etc. Bulls and cows placed into service after 1980 are cost recovered using the analyst's data for purchase price, year purchased, number of years to be cost recovered, etc. A detailed description of the depreciation assumptions used in the model is provided in subroutine DEPREC. Since the depreciation statements for the dairy are the same as those in DEPREC, they are not presented here. Once dairy cows and bulls reach the end of their respective analyst specified economic lives, they are sold. Capital gains or losses on each animal are calculated and depreciation recapture, if applicable, is computed. Cost recovery schedules for bulls and cows purchased as replacements or for increasing herd size (growth) are established automatically. Based on analyst specified options, the model uses either a straight line or accelerated (ACRS) 3- or 5-year cost recovery system for purchased dairy animals. Investment tax credit and first-year expensing are calculated for both purchased bulls and cows if the analyst elects these options. The market value of all dairy animals on the farm at year end is estimated using the stochastic (or deterministic) livestock prices for the year and the number of head in each category. Cows over 2 years old are valued at the price of replacement cows. These market value figures are used to update the farm’s balance sheet at year end. “Throughout this documentation, economic life is referred to as the normal length of time a depreciable asset is used on the farm being analyzed. Although the economic life of a tractor may be 15 years it may only be used on a given farm for 5 years. The economic life of a particular asset thus depends on the farm operator’s normal machinery replacement strategy and not on an optimal replacement strategy. 22 ma...1....,.... .-. .15 “M... ..., The final function of the subroutine is to update the dairy herd for the following year. This involves solving several identities for the calf herd (birth, death, and sale) to determine the number of heifers entering the replacement herd; the replacement herd (death, sale, and breeding) to determine the number of replacements entering the milking herd; and the milk cow herd (culling and death) to determine the number of cows to sell or buy to achieve the analyst’s desired herd size for the next year. These values are calculated using the number of head in each category and the replacement strategy provided by the analyst. All cows and bulls purchased as replacement stock or for growth are financed as intermediate-term assets. The downpayment is calculated using the minimum downpayment fraction specified by the analyst and the total value of the purchase. All loans are amortized in subroutine FINAN. Subroutine LVSTK All calculations for a beef cattle enterprise are made in the LVSTK subroutine. This subroutine is skipped if the farm has no beef cattle. A beef enterprise can consist of a mother cow herd, replacement heifers, and herd bulls, as well as stockers and/or feeder cattle. As with dairy cattle and farm equipment, purchased breeding stock are depreciated using the straight line or declining balance method for pre-1981 assets. Post-1980 assets are cost recovered using a 3- or 5-year straight line or ACRS method and the cost recovery rules under the 1981, 1982, and 1984 federal income tax acts or the 1985 proposed tax bill. A detailed description of the depreciation calculations is provided in subroutine DEPREC. Once breeding stock has passed its analyst specified economic life, it is sold and replacements are purchased. Depreciation recapture is calculated, if applicable, as well as realized capital gains and losses on the sale. Investment tax credit and first-year expensing are taken for replacements if the analyst elects these options. The model calculates the number of calves born and sold each year using the cow herd size, calving fraction, and calf death loss fraction provided by the analyst.” It is assumed that one-half of the calves born each year are heifers. Young heifers can either be sold or retained for the replacement herd. The fraction of heifers sold is specified by the analyst. so the number retained is the difference between those born and those sold. Heifers in the replacement herd (12— to 24-months-old) are sold based on the analyst specified fraction of replacement heifers sold. The number of cows culled annually is determined by a fraction provided by the analyst and the size of the cow herd. The number of cows to be replaced each year is the greater of this value and the number to be culled because of age (determined in the depreciation calculations). Since the analyst must indicate the desired herd size each year of the planning horizon. the number of cows to buy (or sell) at year end is calculated based on: number of cows on the farm on December 31. number of replacement heifers to enter the cow herd in the next year. total number of cows to be culled. and desired herd size for the next year. The number of bulls in the herd each year is specified by the analyst: therefore. the number to buy or sell each year is calculated based on the number of bulls on the farm December 31. the l’) . . . . "Values for calving fraction and death loss are constant across years and do not vary depending on the age of the mother cows or cows. 23 number of bulls culled, and the desired number of bulls in the following year. The purchase of replacement bulls is financed based on minimum downpayments for intermediate-term assets. Annual cash costs (non-labor and non-interest variable costs) for each livestock category are provided by the analyst along with an annual inflation rate for updating these base costs over time. Total annual cash cost, by livestock category, is the product of the inflated variable cost and the number of head in the respective category. Monthly labor requirements for the beef herd equal the sum of labor requirements for each category (the product of the number of head and the hours required per month per head). If the farm has a stocker herd, the model calculates the cost of buying the stockers based on the price and sales weight specified by the analyst for weaned steer calves. Similarly, feeder cattle are purchased at the price and sale weight for stocker steers. Stockers and feeders are assumed to be bought, fed, and sold all in the same income tax year. Interaction between the beef herd and crop production is handled in this subroutine and the RECPTS subroutine. The model calculates the total quantity of each crop fed to the beef herd each year. Annual feed requirements per head for each crop (e.g., hundredweight of sorghum/cow or tons of hay/replacement heifer) are multiplied by the number of head in that category to calculate total feed requirements. The total quantity of each crop fed to the beef herd is calculated by summing the crop's total feed requirements over the beef categories. Surplus and/or deficit crop production is reconciled in subroutine RECPTS. Cash receipts for the individual beef categories are calculated using the number of animals sold, their average sale weights, and their stochastic or deterministic prices. Cash receipts for stockers and feeder cattle are reduced to reflect the average annual death loss fractions provided by the analyst. Value of heifers added to the herd is calculated based on the average value of yearling heifers. The market values for cows, replacement heifers. and herd bulls are calculated as the product of their respective number of head. average weight per head. and price. The market values of the beef herd are used to calculate the change in the value of livestock and the farm’s net worth. The LVSTK subroutine may be used to simulate a hog enterprise, a sheep enterprise, a goat enterprise, or a poultry enterprise.13 For example. the calving fraction can be specified to allow multiple births per sow, or nanny, instead of a normal beef cow calving fraction in the range of 0.80 to 0.95. Subroutine V COSTS Variable costs of production for all crop enterprises and total labor costs for the firm are calculated in this subroutine. The analyst must provide the initial per acre costs, by crop enterprise. for seed, fertilizer. fuel. chemicals, machinery repair, other production costs. and harvesting costs. BTo do this. the analyst must provide the input data for the sow herd in place of data for cows, the gilt replacement herd in place of data for replacement heiferes, etc. The model is designed to shorten the depreciation life for purchased breeding shock from 5 years to 3 years if the calving fraction exceeds l.0. When a hog enterprise is simulated. the appropriate value for the calving fraction is about 13.0. Printed output for the livestock enterprise is oriented to beef. even if the calving fraction exceeds l.0. 24 . .1..- _...a.s.....__... .._. ..M.__._a.4_4......-. ".._.. . _ . _ . _.__...__s ....__.._._.,m..__..t......,4i_..i_...aa.....-._. These initial costs are adjusted annually, using their respective annual percentage changes provided by the analyst, t0 reflect their nominal costs each year of the planning horizon. Variable production costs (non-labor and non-interest) are calculated by summing the products of each crop’s planted acreage and its inflated per acre production cost for seed, fuel, chemicals, etc. Harvesting costs are calculated for each crop as the sum of the products of harvested acres, yield per acre, and inflated harvesting cost per yield unit. Each component of variable costs for the crop enterprises can be shared differently with the landowner. The landowner’s share of variable costs are deducted prior to determining the operator’s total variable production cost for the year. Harvested acreage is reduced to zero and harvesting costs are set to zero if the marginal cost of harvesting the crop exceeds the marginal revenue to be received for the crop. This may occur when yields and/or prices are very low in a stochastic simulation. The occasional practice of harvesting an uneconomical crop yield to protect farm program yield is not accommodated by this assumption in the model. Monthly labor requirements for each crop are calculated as the product of planted acreage and the monthly labor requirements (hours per acre) for the respective crop. Probability distributions for crop yields incorporate the reduction in yields. Total monthly labor requirements for each crop are added to the monthly labor needs for the dairy herd and the beef herd. Total part-time labor which must be hired each month is the difference between total labor available and total labor required each month. Available labor each month is the sum of hours provided by unpaid family members and the product of hours worked each month per full-time employee and the number of full-time employees. Total labor cost for the farm is the sum of salaries for full-time employees and part-time labor costs. Annual salaries and hourly wage rates for part-time employees are adjusted annually using percentage change in price values provided by the analyst. If cropland and/or pastureland is rented on a cash basis, the model calculates the cash rent based on the adjusted per acre rental rate and the number of acres rented in each category. The cash rental rate for cropland can be adjusted independent of land value or the rental rate can be tied to the value of cropland, for example, 4 percent of land value in the previous year. When the latter option is used, the fraction must be provided by the analyst. Labor and crop lease costs are added to the variable production costs for all crops, the dairy herd, and the beef herd to get total cash operating expenses. The resulting total cash operating expense is multiplied by an annual interest rate and the fraction of the year an operating loan is outstanding to calculate the annual cost for operating capital. Subroutine FCOSTS Fixed costs for the farm are calculated in this subroutine. Property taxes are calculated as the product of the property tax rate and the updated value of owned real estate. The property tax rate is expressed as the dollars of property tax paid per dollar of real estate market value. Personal property taxes on machinery are not calculated directly by the model. Instead. the analyst specifies the initial personal property tax for the farm and the model updates this value over the planning horizon. Other costs considered to be fixed and calculated annually in this subroutine are accountant and legal fees, unallocated maintenance, insurance, and miscellaneous fixed costs. These costs are calculated by inflating their initial values using the appropriate annual percentage change rates specified by the analyst. 25 Subroutine FINAN All non-operating loans for the farm are amortized in this subroutine. Initially the farm may have one long-term debt and one intermediate-term debt. As dairy and beef cattle, machinery, and land are purchased, the firm generates additional loans to be amortized in this subroutine. Loans obtained to refinance cash flow deficits are also amortized in FINAN. Each loan is processed in the same manner. The annual payment for each loan is calculated using the remaining balance formula (Penson and Lins 1980). The annual interest payment is the product of the loan’s annual interest rate and the outstanding principal at the start of the year. The annual principal payment is the difference between the annual payment and the annual interest payment. The outstanding principal for the loan is reduced by the annual principal payment. If the resulting outstanding principal is less than zero, the principal payment is reduced to the amount necessary to fully repay the outstanding balance. Future applications of the model can expand this subroutine to include other methods of financing agricultural loans. Obvious expansions include balloon payment financing of real estate. Subroutine LAN DVL The market value of land is calculated in this subroutine using the method selected by the analyst. Additionally, the subroutine updates the market value of all farm machinery and off-farm investments. One option for updating the market value of cropland is to tie the annual capital gain rate for cropland to the percentage change in the CPI or some other index. This can be done readily in the model because the analyst may specify the annual change in land values for each year of the planning horizon. These capital gain rates could be zero in all years. A second option for updating land value is to tie the annual capital gain rate for land to the annual rate of return to production assets. This option is also available in the model. An ordinary least squares equation is included in the model to relate the rate of return to production assets (RRPA) to the capital gain rate (CGRL): CGRL, = -0.05s + 0.367 CGRLH + 2.490 RRPAM The equation was estimated using national average data for the capital gains rate for farm land (USDA 1970-84) and the national rate of returns to production assets (USDA 1982). The coefficients for this equation were all statistically significant at the 9O percent level. the F-ratio was 6.55 and the R-square was 68.6. Artificial bounds of i 10.9 percent were imposed on the equation based on the observed values used to estimate the equation. The lagged values for the rate of return to assets and capital gains to land in year 1 are provided by the analyst. For succeeding years, the annual rate of return to production assets for the firm are calculated in subroutine UPDATE. The annual percentage change in the market value of buildings is specified by the analyst and used to update building values over the planning horizon. The nominal market value of farm machinery is updated annually to reflect its value in the balance sheet and its value as a trade-in. Annual percentage changes in the market value of used 26 equipment are provided by the analyst. Changes in market value are treated as unrealized capital gains or loses. The market value of off-farm investments is updated in a manner similar to machinery. Subroutine DEPREC Depreciation (cost recovery) of all farm machinery and buildings (both regular and special purpose) is calculated in this subroutine. Replacement of farm machinery is also handled in the DEPREC subroutine. The subroutine incorporates the 1981, 1982, and‘ 1984 changes in the federal income tax law in the calculation of depreciation for each item of machinery, livestock, buildings, and other depreciable assets.14 The analyst may choose among several options, including first-year expensing on newly acquired qualifying property, straight line versus accelerated depreciation under the ACRS, whether to trade-in, sell, or keep machinery once it has reached the end of its economic life, and whether to claim the full investment tax credit with a corresponding reduction in the basis for depreciation or a reduced investment tax credit with no reduction in the asset’s basis for depreciation. The 1985 tax bill (TFSEGA) has also been programmed into the model to allow this depreciation schedule to be used after 1985. The analyst indicates whether the straight line or double declining balance method is to be used to depreciate assets acquired prior to 1981. Machinery purchased to replace worn-out machinery after 1980 is either depreciated using the straight line or accelerated method (The Economic Recovery Tax Act of 1981 [ERTA]) based on the method specified by the analyst. Only two class lives, 3 and 5 years, are applicable for farm machinery under the post-1980 Tax Acts. A 5-year class life is used for special purpose agricultural structures (dairy barns, etc.). For depreciable real estate purchases (buildings, etc.), the analyst may again choose between the straight line or accelerated methods. A class life of 15 years for existing regular purpose buildings is incorporated into the subroutine. The analyst specifies whether to sell, trade, or keep the machine, when replacing it at the end of the machine’s economic life. Economic life must be greater than or equal to the tax life. The method of disposing of the machine has important income tax implications. A sale of the old machine may trigger depreciation recapture which is added to the farm operator’s taxable income. If the machine is traded-in on a replacement, the basis for depreciation on the new machine is reduced, but no depreciation recapture is involved. The third option of keeping the machinery on the farm for parts. etc., has no income tax consequences as the asset has already been fully depreciated. The model also calculates capital gains or losses when machinery items are sold, based on the sale price of the old machine and its purchase price. Before a new machine can be purchased, the necessary downpayment must be secured. The program calculates the minimum downpayment based on the cost of the new machine and the minimum downpayment fraction specified by the analyst. If a machine is traded-in. then the value of the trade-in may serve as all or part of the downpayment. Otherwise, there must be sufficient cash reserves to meet the downpayment requirement. If the farm has insufficient cash reserves and/or borrowing capacity to replace the machine when it reaches the end of its economic life, the model allows the farm to defer replacement for only l year. “Additional information explaining the federal income tax code for depreciation. investment tax credit. etc. is available in Prentice Hall (1984). 27 The first-year expensing provision introduced in ERTA allows farm operators to directly expense an initial amount of the cost of newly acquired machinery and livestock in the year of acquisition. The maximum amount of expensing available to the firm increases over time, through 1986, and is incorporated into the program. When the 1984 Tax Act option is selected, the maximum expensing limits under this act are used. The model also distinguishes between special purpose agricultural structures and other farm buildings. The different depreciation schedules and the investment tax credit available on special purpose structures are provided as options in the model. Changes in the federal income tax law dealing with the investment tax credit (ITC) beginning January 1, 1983 requires that the farm operator select whether to claim the full ITC (10 percent on 5-year property and 6 percent on 3-year property) with one-half of the claimed ITC reducing the asset's basis for depreciation or to claim a reduced ITC (8 percent on 5-year property and 4 percent on 3-year property) with no reduction ‘in basis. The model can handle both options. The 1985 tax proposal eliminates ITC so the model bypasses the ITC calculations after 1986 when this option is specified. No ITC recapture is calculated since the farm operator is assumed to keep the asset for its full economic life, which exceeds the recapture period. The subroutine concludes by summing the depreciation for each machinery item, buildings and other depreciable real estate, special purpose agricultural structures, and purchased livestock. This value is treated as a farm expense and becomes part of the income statement to assess the profitability of the farm. In addition, the investment tax credit is used to directly reduce the farm operator’s federal income tax liability. Subroutine LEASE This subroutine permits the analyst to simulate a farm which leases up to 5O individual pieces of equipment as well as owns other equipment. The annual lease payment for each item leased is calculated based on its annual lease rate provided by the analyst. Annual lease costs are treated as a cash expense and are paid in advance, i.e., at the beginning of the tax year. Most machinery leases have a provision for the purchase of the machine at the end of the lease for a predetermined (analyst specified) recovery value. The subroutine permits the analyst to simulate this option as well as several other machinery disposal options at lease end. See input Card 55 for a list of the various disposal options that can be specified independently for each machine. When the machine is purchased at lease end, it is set-up on the same cost recovery system (straight line or accelerated) as other farm machinery purchased after 1980. The number of years to recover the purchase cost can be 3 or 5. First-year expensing and investment tax credit are calculated for each machine purchased if the analyst elected these options. The value of purchased machines is added to the value of other owned machinery, and an intermediate-term loan is obtained to finance the purchase. The minimum downpayment requirement (fraction) is the same as for other machinery purchases. When the leased machine is turned back at lease end, a new replacement can be leased. In this case, the model estimates the market value of the new machine by inflating the machine’s replacement cost in year l using the compounded annual inflation rate for new machinery. The annual lease rate (percent of market value new) for the new machine is assumed to be the same as its predecessor. The estimated recovery value at lease end is the same proportion of new market value as the original machinery. 28 Subroutine MKTG Income tax consequences frequently determine the proportion of crops sold during the tax year they are harvested. The analyst may specify either a cash accounting system or an accrual accounting system. When the accrual accounting system is in use, the MKTG subroutine sets the proportion of crops to sell in the following year equal to zero. If a cash accounting system is in use, the subroutine determines the proportion of crops to be sold in the current year which will achieve a designated, taxable income target specified by the analyst, for example, $7,500 when the cash accounting system is in use. The first step in calculating this fraction is to determine the operator’s expected income tax deductions. Estimated deductions include: fixed costs, interest payments, variable production and harvesting costs, labor costs, cash rent for land, depreciation, crop insurance premiums, and personal income tax deductions ($1,000 per dependent plus excess itemized deductions). Estimated cash receipts include: value of all crops if sold in the current tax year; value of crops held over from the previous year and sold in the current year; all off-farm income; other farm income; and when applicable, deficiency payments and cash receipts from the dairy and beef enterprises. Potential receipts from government programs and crop insurance are not included. If estimated cash receipts are less than estimated tax deductions plus the targeted taxable income. all crop production is sold in the current tax year. When this inequality does not hold, the proportion of crops sold in the next tax year is calculated assuming the only margin for adjustment is in the sale of the current year’s crop production. The proportion of crop production sold in the current tax year equals one minus total deductions plus targeted taxable income minus total estimated cash receipts all divided by estimated receipts for crops eligible for sale. The proportion is bounded by zero and one. A second option is available to the analyst for handling crop sales across income tax years. This option involves fixing the fraction of each crop normally marketed in the same tax year it is produced. When this option is selected. cash receipts are calculated based on the analyst's proportions specified for each crop and not on the values described above. Subroutine RECPTS Cash receipts for all crop enterprises are calculated in this subroutine, whether the operator's share of production is sold in the spot market or enrolled in the marketing loan or placed under a FOR or CCC loan. The first step in calculating cash receipts is to determine the total production of each crop which can be sold by the operator. This value equals harvested acreage times per acre yield less the landowner’s share on that portion of total cropland which is share rented. If an acreage reduction program is in effect, production is increased for the portion of set aside acreage which did not result in reduced production (slippage). When the farm includes a beef cow enterprise or a dairy enterprise, total crop production available for sale is reduced for the quantity of the crop fed to livestock on the farm. Total quantity of each crop fed to livestock is calculated in subroutines DAIRY and LVSTK. The quantity of each crop fed is subtracted from the crops total production (less the landowners share) to arrive at the net quantity available for sale. When this value is negative, the model calculates the cost to purchase additional feed required for the livestock herd. The cost of additional feed is the deficit quantity for each crop multiplied by ll0 percent of the crops respective price. When this adjustment is made. the additional feed costs are added to the total cost of production for the livestock and interest costs for operating capital are updated. 29 The subroutine has two sections for calculating crop cash receipts. The first section calculates cash receipts when the operator may not use the government loan program to "carry over" crops held for sale in the next tax year. The second section calculates cash receipts when the operator uses the government loan to "carry over" crops to the next tax year. The two sections are described here in the order they appear in the subroutine. In the first section, the operator uses the government loan (CCC or FOR) only if the full crop is placed under loan or sold through the marketing loan program. Since each crop can be sold in 2 marketing months, the subroutine calculates each crop’s average price in the 2 designated months. The monthly average prices are calculated using the stochastic (or deterministic) annual crop prices and a seasonal price index provided by the analyst. The price index is also used to compute the average price during the first 12 months of the marketing year, assuming the first marketing month for each crop is the first month of the marketing year. This 12-month average price is used to calculate deficiency payments. The quantity of each crop’s production to be sold in the current year is calculated as the product of total production and one minus the fraction of the crop to be held for sale in the next tax year. If a nonrecourse CCC loan (or FOR) is available for the crop, the model determines whether the total production should be placed under loan. Total production is put in the loan if the weighted average cash price between the 2 sales months is less than the net loan rate. The current price (say, December) for the crop is known so the expected price for the sale month in the following tax year (say, January) is the indexed value based on the current year’s price.15 The two monthly average spot prices are weighted by the fraction of the crop sold in each month. The net loan rate for the CCC loan equals the announced loan rate less 9 months’ storage cost. The net direct entry FOR loan rate is the direct entry loan rate minus the Secretary’s announced interest charge (1 year or none) and the difference between the announced government payment for storage and 1 year’s storage cost. When a crop’s total production is placed under a government loan. the face value of the loan is added to the farm’s cash receipts, and quantities of stocks to be sold in years t and t+ 1 are set to zero. If the loan is not available or is a less profitable alternative. the operator sells the crop on the spot market. Because of this flexibility, the model can simulate a crop farm which has one or more crops that are not eligible for the loan, in addition to having several crops that are eligible for the FOR and one or more that are eligible for only the CCC loan. A recourse CCC loan or a maximum on the nonrecourse CCC loan can be simulated for each crop enterprise on a representative farm. When a binding maximum on the nonrecourse CCC loan is encountered, the operator puts the maximum stocks under the loan if it is more profitable (as described above) than selling the crop. The remainder of the crop can be placed into a recourse CCC loan or sold immediately, depending on the option specified by the analyst. lf only a recourse CCC loan is available, the operator makes use of the loan if it is more profitable (as described above) The marketing loan program in the 1985 farm bill is incorporated in the model. lt is assumed eligible crops are sold at the prevailing cash price and the government makes a direct payment equal to the marketing loan rate minus the greater of the cash price or the repayment price. In the RECPTS subroutine. cash receipts for crops eligible for the marketing loan equal total production times the spot price. The spot price is not allowed to fall below the marketing loan repayment rate. The marketing loan direct payment is calculated in the POLICY subroutine. “The bias created by assuming the next year's price is a linear function of the current price is quite small if the 2 months are separated by only l month. for example. December to January. 3O Cash receipts are the sum of receipts for the portion of the current year’s crop sold and for the portion of the previous year’s crop sold in the current tax year. Interest and storage costs for the portion of the current tax year’s crop placed in storage are paid in advance. Interest costs are paid only for the months the crop will be stored and are computed using the annual interest rate for operating loans. Storage costs are paid for the same length of time and are calculated using the annual cost for storage provided by the analyst. The model is capable of simulating up to 10 crops and each crop may have a different marketing strategy, i.e., some crops may be sold during the year they are harvested while others may always be held for sale in the next year, and others may be split between income tax years due to normal harvesting and marketing patterns. In the second section of subroutine RECPTS, cash receipts are calculated, but in this case the operator uses the nonrecourse CCC loan to "carry" an inventory across income tax years. By obtaining a CCC loan on the inventory carried over, the operator generally gains because government loans have lower interest rates than the typical operating loan. A description of this option is provided below. Each crop is simulated separately in this section of the subroutine. The first step for each crop involves calculating the monthly average prices for the 2 months the crop is ‘normally marketed (the current price is known so the expected price for the sale month in the next year is the indexed value based on the current price). Next, the subroutine determines whether it is more profitable to put the whole crop under the CCC loan (or FOR) or to sell it in the cash market. These evaluations are the same as in the first section of the subroutine. Next, the model checks the feasibility of redeeming stocks placed under CCC loan in the previous year, as part of this marketing strategy. Stocks are redeemed if the cash price exceeds the respective loan rate plus the interest charges due for the loan. "Cash receipts for each crop are calculated in the same fashion as the first section of this subroutine. If stocks carried from the previous year in the CCC loan are not redeemed, they do not enter into the cash receipts calculation since they will be forfeited to the CCC. The portion of the current crop carried in the CCC loan until possibly sold in the next tax year is placed into the loan regardless of the net loan rate’s value relative to the cash price. Storage costs for these stocks are paid in advance and the face value of the loan is received by the operator. The final calculations in RECPTS are to sum cash receipts for all crop. beef cattle, and dairy enterprises. Subroutine POLICY The POLICY subroutine is capable of simulating a wide array of commodity programs for each crop enterprise on a typical farm. Each commodity program is activated on the option card. The commodity programs included in POLICY are described here in the order they appear. Descriptions of past farm program provisions are available in Knutson and Richardson (1984); Johnson and Ericksen (1977); Johnson. Rizzi, Short. and Fulton (1982); and USDA (1980). Flexible Loan Rates. The model calculates each crops loan rates for the following year using a moving average formula if the analyst selects this option. If this option is not selected. the model uses the annual loan rates provided for each year of the planning horizon. The loan rate for the following year equals a fraction (provided by the analyst, for example, 0.75) of the moving average of past and current prices (1. 2. 3. 4. or 5 years are analyst specified). For each crop. the maximum decrease in the loan rate each year and the minimum loan rate can be specified by the analyst. The moving average can exclude either (or both) the maximum or (and) minimum price over the period. Each crop can have a separate loan rate formula. but the formula must remain constant over all 31 years in the planning horizon. Both the nonrecourse CCC loan rates and the marketing loan rates are updated by these formulas. Target Prices Tied to Loan Rates. Target prices can be specified for each year of the planning horizon or they can be determined as a function of the loan rate. (See footnote 3.) When this latter option is elected, the model calculates the target price (for the following year) based on the loan rate (for the next year) and the analyst supplied fraction relating the target price and loan rate. The fraction between the loan rate and target price can change from year to year and from one crop to the next. This option is most useful when loan rates are calculated by a moving average formula. Base Acreage and Farm Growth. The base acreage or allotment for each crop is assumed to increase as the farm grows. Each crop’s base acreage increases in proportion to its relationship to the initial farm size as the farm grows. In other words, a 50 acre cotton base on a 100 acre farm is increased to a 250 acre base if the farm grows to 500 acres. This is important because the farm program (or base) acreage is used to calculate deficiency payments. These adjustments implicitly assume all land acquired in growth has an allotment proportional to the initial farm. Farm Program Yield. The model calculates farm program yield (or payment yield) internally. Farm program yield is used to calculate deficiency and disaster payments. Farm program yield is calculated for each crop using the following formula: average of actual yields for the last 5 years ignoring the highest and lowest values. The model prevents the calculated farm program yield from declining below its value in the previous year. This formula was used for the 1981 farm bill for cotton and rice. The history for the farm’s past five yield values is provided by the analyst so farm program yield can be calculated for all years. Deficiency Paynzenzs. For eligible crops, deficiency payments are calculated using the formula specified in the 1981 farm bill (Johnson, et al. 1982). Two deficiency payments are calculated in the model. The first is limited by the payment limitation and the second is unlimited (Findley payment). For the first deficiency payment, the model determines whether the crop has a nonzero target price and then whether the crop is eligible for a deficiency payment (target price greater than the average price in the first 12 months of the marketing year). If these conditions hold but the loan rate exceeds the target price, the crop is not eligiblefor a deficiency payment. The deficiency payment rate is the smaller of the target price minus the loan rate or the target price minus the 12-month average cash price. Deficiency payments for each crop equal the product of the crop’s deficiency payment rate, farm program yield, farm program acreage, and National Allocation Factor. The analyst provides annual values for target price, loan rate, National Allocation Factor, and program acreage for each crop on the Policy Data Cards described in Appendix A. The payment is reduced for the landowners share on share rented cropland. The second deficiency payment (Findley payment) is calculated as the difference between the formula loan rate and the market price or the formula loan rate and the CCC loan rate. This payment rate is multiplied by farm program yield, National Allocation Factor, and farm program acreage to calculate the total payment. The second deficiency payment is not subject to the payment limitation. The second deficiency payment is equal to zero if the average market price in the first 12 months of the marketing year is greater than the formula loan rate. It is possible to receive both deficiency payments. When the Findley payment is in use. the first (limited) deficiency payment is paid based on the difference between the target price and the formula loan rate entered on Policy Data Card P41 or the market price. Acreage Diversion. Diversion programs differ from set aside programs in that they provide a payment to producers for the acreage withdrawn from production. The distinction in the model is made by whether the analyst provides a nonzero, positive payment rate for idled land (Policy Data Card P9). The diversion payment for each crop is the product of the per acre payment rate and the number of diverted acres. The total diversion payment is reduced for the landowners share on 32 share rented cropland. Low Yield Disaster Payments. Grain and cotton producers were eligible for low yield disaster payments from 1973 through 1981. This type of program can be simulated for any and all crops produced on the typical farm. The planted acre yield for each crop is calculated by dividing total production by planted acreage. When planted acre yield is greater than a given fraction of the crop’s farm program yield, no disaster payment is paid. The analyst must provide the appropriate yield loss fraction, for example, 0.66 percent for grains and 0.75 percent for cotton. These were the fractions specified in the original farm program. The disaster payment is the product of the target price, the fraction of target price designated for low yield payments, the acres planted, and the lost yield per planted acre. Lost yield per acre for grains is the difference between planted acre yield and the product of the yield loss fraction (0.66 percent) times the farm program yield. Disaster payments are reduced for the landowner’s share on share rented cropland. A provision in the 1977 farm bill provided that deficiency payments must be reduced for disaster payments on the same acreage. This provision is included in the model so deficiency payments are reduced if the crop received both types of payments on the same acreage. The value of the deficiency payment on the production lost due to low yield is subtracted from the crop’s deficiency payment. Federal Crop Insurance. After 1981, federal crop insurance was made available for all crops. Federal crop insurance can be simulated for each crop enterprise in any or all years of the planning horizon. This part of the POLICY subroutine is designed to simulate the FCIC multi-peril crop insurance program. Since FCIC premiums can be increased (or decreased) for favorable (or unfavorable) coverage, the subroutine first updates the farm's insurance history for each crop. The loss ratio over the farm’s experience in the program (sum of indemnities divided by the sum of premiums) is estimated using the operator's history (analyst provided) prior to the planning horizon and simulated values for earlier years. The loss ratio and the number of years in the program are used in an FCIC schedule to determine the premium rate adjustment factor for the year simulated. Federal crop insurance premiums are calculated annually for each crop as the product of planted acreage, the per acre premium rate. and the rate adjustment factor calculated earlier. Premiums are reduced for the landowner’s share on share rented cropland. Indemnity payments for each crop are calculated based on the planted acre yield. The lost yield which receives an indemnity payment is the difference between guaranteed yield and planted acreage yield. Indemnity payments for each crop are the product of lost yield. the price election, and the planted acreage. Indemnity payments are reduced for the landowner’s share on share rented cropland. Redemption of CC C Stocks. Prior to maturity in the CCC loan. stocks can often be redeemed at a profit. When the price of the crop is less than the net loan rate, the operator places the total production for that crop in a l-year nonrecourse CCC loan (see the RECPTS subroutine). The possible redemption and sale of these stocks is determined the following year in this subroutine. When an indirect FOR is available for the crop, the operator may move nonrecourse CCC stocks into the reserve rather than releasing them. Nonrecourse CCC stocks are released if the current year’s spot price is greater than the loan rate plus the cost of 9 months‘ interest. The spot price is the seasonally adjusted stochastic (or deterministic) price for the first month the crop is sold in. as specified by the analyst. 1f stocks are redeemed. the net proceeds from selling the stocks and repaying the CCC loan are added to cash receipts. lnterest is generally not paid if the stocks are forfeited to pay the loan; however. an option 33 is included which can force payment of this interest. Recourse CCC loan stocks are redeemed after being in the loan for 1 year, regardless of the market price. When the recourse loan is redeemed, the model sells the stocks and repays the CCC loan. The difference between the market value of the stocks and value of the CCC loan is added to total cash receipts, whether this difference is positive or negative. Delayed Entry FOR. The FOR was initially established as a 3-year reserve for grains after they had been in the CCC loan for 1 year. The delayed entry reserve is simulated first followed by the direct entry FOR. The analyst must specify which type of reserve is to be used and must provide each crop’s entry price (direct reserve only), length of the reserve, and release (or trigger) price. By using zero and nonzero values for the length of the reserve, the analyst can simulate a reserve for one crop and only a CCC loan for the other crops. To simulate a delayed entry FOR, the model first determines the release price based on the option to release stocks at either the release or the trigger price. Next, the stocks in the FOR are increased by the amount of stocks that have matured in a CCC loan during the current year. The value of the CCC loan for these stocks is added to the loan values for all stocks presently in the reserve. On maturity (after 3 years), stocks in the FOR are assumed to be forfeited to the CCC and the loan on these stocks is forgiven. Based on this calculation, ending year stocks and loan values are adjusted for stocks that matured during the past year. Interest charges on the FOR loans are calculated one of four ways depending on the option selected by the analyst. FOR interest charges can be: (a) zero in all years, (b) paid in only the first year, (c) paid in only the first 2 years, or (d) paid in all years. FOR stocks are released if the estimated market value of stocks in the reserve exceeds the value of the FOR loan, and the market price exceeds the designated release (trigger or call) price. When stocks are released, the quantity of reserve stocks and the value of the FOR loan are set to zero and the net proceeds from the sale of FOR stocks and repayment of the loan is added to cash receipts. Also. when stocks are released, both the government payment for FOR storage and the off-farm storage costs are calculated for 6 months (if stocks are not released. the storage payment and storage costs are computed for a full year). Direct Entry FOR. Entry of stocks into the direct entry FOR is determined in the RECPTS subroutine. Value of the new FOR loan is calculated in subroutine POLICY based on the quantity of stocks added to the reserve and the direct entry loan rate. Annual updating of stocks in the reserve (addition of new stocks and purging of matured stocks) is handled the same as for the delayed entry FOR. Similarly, calculation of interest costs, government storage payments, and off-farm storage costs are the same as for the delayed entry FOR. Release from the reserve and loan repayment is also handled the same as for the delayed entry reserve. Marketing Loan. The 1985 farm bill established a marketing loan program for several crops. Producers receive a payment based on the difference between the marketing loan rate and the greater of the market price on the loan repayment rate. To simulate this farm program provision, it is assumed all eligible production is sold on the spot market (see RECPTS subroutine) and the government makes up the difference with a direct payment. The total payment equals the product of the operators share of the crop and the difference between the marketing loan and the greater of the market price and the loan repayment rate. CCC interest and commercial storage on the crop is charged for 6 months because producers will have to enter the conventional CCC loan and store their grain to enroll in the program. a Marketing Quota. The two-loan rate, marketing quota program that has been used for peanuts can be simulated for any and all crops produced on the farm. To simulate this policy. the analyst must provide both the quota and non-quota loan rates as well as the poundage quota for 34 each crop eligible for the program. The quota portion of the operator’s production is assumed to be eligible for the quota (higher) loan rate. Ten percent of any unused (extra) poundage quota, due to under marketings in a given year, can be carried over to the next crop year (the 10 percent value was used based on recent history with the peanut program). When prices are less than the net, non-quota loan rate (loan rate minus 9 months’ storage), it is assumed the operator uses the quota loan up to its maximum and then places all remaining production in the non-quota loan. Nine months’ storage cost is paid in advance for production placed in the loan. The total value of the loan equals the quota loan rate times the quantity placed under the quota loan (the quota on total production) and the non-quota loan times all remaining production for the crop. When prices are less than the net quota loan rate but greater than the net non-quota loan rate, the operator is assumed to place the maximum amount of the crop in the quota loan program. Nine months’ storage is paid in advance and the value of the total CCC loan is based on the quota loan rate and the quantity of stocks placed under this loan. Stocks are redeemed from the loan the following year if the market value of stocks in the CCC loan exceeds the value of the loan plus accrued interest. Nine months’ interest for the loan is paid if the stocks are redeemed. The net proceeds from selling the stocks and repaying the loan are added to cash receipts for the crop and to total cash receipts. Gramm-Rudntan. The Gramm-Rudman-Hollings Act requires that all government expenditures be reduced a certain fraction each year to achieve a balanced budget by 1991. The required annual reductions under this act must be provided by the analyst. If the Gramm-Rudman option is selected, the model reduces deficiency payments, Findley payments, marketing loan payments, and diversion payments the specified fraction. This reduction is calculated after enforcing the payment limitation. Payment Limitations on deficiency and diversion payments ($50,000 per farmer) and disaster payments ($100,000 per farmer) were a part of the 1981 farm bill. The model provides options to allow the analyst to make these limitations effective at any desired level or to turn them off completely. The last segment of the POLICY subroutine sums costs and receipts associated with the various farm programs by crop. If the sum of deficiency and diversion payments for all crops exceeds the analysts specified maximum payment and the limitation is in effect. total payments are reduced to the maximum. The same is true for maximum disaster payments. Subroutine INVEN The value of stocks held for sale and livestock are updated in this subroutine. Stocks held for sale, not under a government loan, are treated separately from stocks under a government loan. The value of breeding stock is updated using current market values estimated in subroutine LVSTK. The change in the value of livestock (beef and dairy) and crops from the previous year is calculated for use in the income statement. Subroutine CASHIN This subroutine totals cash receipts and cash expenses to arrive at net cash farm income 35 adjusted for off-farm income. Total cash farm income includes: total crop and livestock receipts, deficiency and diversion payments, disaster payments, other farm income (specified by the analyst annually), value of CCC and FOR loans, payments for FOR storage, marketing certificate payments, and indemnity payments for crop insurance. Total cash expenses include: operating, intermediate- and long-term interest payments; crop insurance premiums; total variable production and harvesting costs for crops, dairy, and beef cattle; hired labor costs; cash rental payments for cropland; value of livestock purchased for resale; property taxes paid; other fixed costs; interest and storage costs for CCC and FOR loans; and lease costs for machinery. Net cash income for the farm is the difference between total cash receipts and total cash expenses. Dividends from off-farm investments are calculated as the product of the annual return on these investments and their market value. Interest earned on current cash reserves is the product of the annual interest rate and the farm’s beginning cash reserve for the year. Total other cash income for the operator includes: off-farm income, non-taxable income, interest on cash reserves, dividends from off-farm investments, and exogenous cash investments in the farm from outside sources. Subroutine CONSF Annual cash withdrawals for family living expenses are computed in this subroutine. Annual withdrawals are computed using either a consumption function or by holding constant, in real dollars, the minimum family living expenses provided by the analyst. When the consumption function option is selected, the subroutine estimates annual cash withdrawals using the appropriate consumption function in Table 2 or the function specified by the analyst. After-tax income used in the function is the sum of net cash farm income and other cash income less income taxes and self-employment taxes paid in the current year (accrued in the previous year). Consumer unit size in the consumption function is the number of tax exemptions. Age of the household head and region of the country being simulated are provided by the analyst. The consumption functions in Table 2 were estimated using the SRS-USDA "Farm Operator Family Living Expenditures Survey for 1973." The CPI was included in the consumption functions after estimation to adjust the expenditure values for changes in the CPI since 1973. The inclusion of the CPI was done assuming that the functions are homogenous of degree one in prices and incomes, using the procedure suggested by Brake (1968). The analyst may specify a linear consumption function which relates family living expenses to income. This function specifies that cash expenses equal minimum family living expenses plus the marginal propensity to consume, for example, 0.20 times after-tax income minus minimum family living expense and a machinery replacement expense. The machinery replacement expense is the value of annual straight line depreciation for machinery and purchased livestock. The value of straight line depreciation is subtracted to avoid withdrawing all cash from the business and not having sufficient cash for growth and machinery replacements. The analyst must provide the minimum and maximum values for annual family living expenses. These values are adjusted annually for percentage changes in the CPI, so the purchasing power of the minimum and maximum withdrawals are maintained over time. If the annual family living expense estimated by the consumption function is less (greater) than the inflated minimum (maximum), the latter is used. A third option for determining the annual cash withdrawal value for family living expenses uses the inflated minimum consumption value each year rather than a value estimated by a consumption function. 36 . ~ H Q u M Na xfln » Q ..m.@ .w>MumUHHQHuHSE mum mcofiumsvm one .mucwHuHuumou m>Huuwmmmu ufiwcu 3OHwQ umucwmmum mum mm:Hm> uuucmnsum .cmwa wnu um Umumasuamu mesmcou op >u~m:wmoum Hmcwmuma ms“ wfi um: .AooHu>omH mmmmv mmuH>~mm new mmfiuwuoeaou ~Hm pow xwn:H muflum umssmcou wcu “H Hmu .mamu@ msowcmflamumwe new .oucmu:mc~ .muHmmmu _~msu .cuHmmc _HMUAUOE .coH»mu:Uw _co@umuuommcmuu .mu:uH:usu .mcHm:oz .mcwzuoHu .©oow now musufiucmmxm Hm~o» mfi coaumasmcou mfiflemm Amo.>Hv A¢w.¢|v A>¢.@v .@m.o~v wHm.o H-.o m¢.m>H oH@.Q o@~.o ¢-.o| H¢~.o @m<.m~ .m = A>m.~v A>o.mv A>@.@v Hm~.o H¢H.o o@.m mH>.o mw~.o @@m.Q -m.¢H wwumpw uflwflumm A~o.mv Amm.mv .~¢.¢v ~wm.o ~mm.o @w.~m ~>m.o w~@.o >>~.Q ~m~.m mcflmfim =~@=~=om A>w.Hv A¢o.~av .o~.~v A~¢.@v wmH.o Nmo.o w@.m mow.o HmH.o omm.o| >¢~.o m~@.QQ~ mcwmfim cumnuuoz A>@.~v .>o.~v m>H.o m>o.o ~H.> ¢m>.o w@~.o oQo.m~ wwumum =H@»¢=oz A~w.¢V Am@.~-v A>¢.@v ¢o¢.o m-.o mm.>~ w¢m.o ~m¢.o m~¢.Q| mo¢.m¢ mw~m~w mufiwn AmH.@v Aw¢.~-v ~o~.mv @m¢.o ~>~.Q o>.m~ ~@¢.o Qmm.o mH¢.Q- ¢>m.m~ ~mm@=~=om A@m.>v A~o.~-v Aom.mv A~¢.mv mm ¢mm.o w~m.o mm.mm >»¢.Q mHm.o m-.o‘ ~@~.o m-.¢H mflzumam ¢ A~@.>v Am~.~v A@¢.¢v -H.~Hv @¢~.Q ~Q~.o Hm.H¢ ~>w.o @~m.o >mH.ol wm~.Q wmQ.>~ Qflwm =~ou Amm.~v Am¢.mv Ao~.~Hv Hm.>H mwumum wxmq Aw~.mv Am>.~. m~mm.mv wHv.O ¢w~.o mm.m~ mmm.o >w¢.o @¢~.o ¢w>.@ vummmnuu0z mum: ~m oHmmw|m ~Hmu weoucw wmwm uaommmsom wnflm uacb uawuumucH cofiumm xmalumuum no 004 HQEDM COU 37 Subroutine CASHFL The ending year cash flow for the firm as well as the firm’s balance sheet information is determined in this subroutine. Total unrealized capital gains (or losses) from machinery, land, and off-farm investments are calculated first. The model then determines the total debt for the firm. Total debt is the sum of outstanding principal for all intermediate- and long-term debts. lt is assumed the operating loan is self-liquidating so it is not added to the firm’s total debt at year end. Net farm income is calculated as the sum of net cash farm income and total non-cash adjustments to income. Depreciation and changes in the value of livestock and stored crops are the components of non-cash adjustments to income. Other adjustments to net farm income (depreciation recapture and realized capital gains) are summed for later use. An example of the income statement generated by the model is provided in Appendix C. Subroutine TAXES is called at this point. Accrued income taxes and self-employment taxes are calculated in TAXES for the year simulated. These accrued income taxes will be paid the following year. After calculating accrued income taxes, investable funds generated in the current year (cash reserves) are calculated as net cash income plus other income, off-farm income, receipts from the sale of old equipment and livestock, and other adjustments to net farm income minus all cash expenses. Cash expenses include cash downpayments for machinery and livestock, principal payments on loans, and total operator cash withdrawals (family living expenses and personal taxes). Ending year cash reserve for the firm is the sum of beginning cash reserve and total investable funds at year end (for an example of the cashflow statement refer to Appendix C). If the firm’s ending cash reserve is negative, the model calls subroutine REFIN to resolve the cash flow deficit. Family living expenses are set to the minimum level if the farm experiences a cash flow deficit. The model next checks the possibility of the firm growing through cropland lease or purchase by calling subroutine GROW. Subroutine GROW is skipped if the analyst has specified that the farm cannot grow. If the farm acquires cropland at year end, subroutine CASHFL updates the firm’s total depreciation files, total net farm income, cash reserves, land and machinery values, and total debts. If the analyst elected to use surplus cash for early repayment of debts, the model executes a set of statements to determine which debts can be repaid. Cash available for early debt repayment is equal to total year end cash minus the minimum cash reserve. The most recent intermediate-term debts are repaid first until all intermediate-term debts are repaid. After repaying these debts, the most recent long-term debts are repaid first until all but the original long-term debt is repaid. After prepayments are made, total debts and ending cash reserves are updated. An example of the balance sheet generated by the model is provided in Appendix C. Contingent capital gains tax and depreciation recapture tax are calculated assuming the operator has a constant marginal income tax rate of 30 percent. The actual payment of these taxes. should disinvestment occur, are based on the current year’s taxable income (tax bracket). The subroutine next calculates net worth two ways, a market value net worth and a net worth that does not include capital gains (i.e.. based on historical book value). For the net worth calculation. all crops under CCC and FOR loans are valued at the loan rate so their asset values just offset their debts. a 38 Subroutine UPDATE All financial ratios are calculated in this subroutine. In addition, the subroutine computes the annual rate of return to production assets, the breakeven costs for each crop enterprise and the dairy, and updates the acreage files for the next year in the planning horizon. UPDATE is the last subroutine called from the MAIN program for the annual simulation loop (Fig. 1). Annual return to production assets is calculated for use in the LANDVL subroutine when estimating the annual capital gain rate for land. The annual rate of return to all production assets is estimated using the Hottel-Evans (1979) formula. The current market value of all livestock, farm machinery, and land is used to estimate the value of assets at year end. Based on work by Hottel and Evans (1979), returns to the operator’s labor and management are assumed to be 5 percent of gross income over all acres farmed plus the wages unpaid family members would have received if paid the same hourly wage rate as part-time employees. Total returns to all production assets include not only the returns produced on owned cropland but also the cash value of the cropshare lease paid for rented land. The ratio of total returns and market value of total production assets (including rented land) reflects the annual rate of return from farming. Therefore, as this value rises (decreases), land values should increase (decrease) in a region if the farm simulated is typical of most farms in the region. Financial ratios calculated annually in this subroutine include total debt to total assets, total equity to total assets, leverage (total debt to total equity),m equity to asset ratio_s for both long- and intermediate-term assets, percentage change in net worth, debt coverage ratio,“ earned equity growth trend,“ and collateral ratio“). If the leverage ratio exceeds its maximum, implicit in the minimum long-term equity ratio. the farm is forced into bankruptcy and subroutine SOLVNT is called. The farm may have a positive net worth when insolvency occurs but it does not have sufficient equity to meet the minimum standards for local banking institutions after meeting current cash flow deficits. For example, if the minimum equity ratio is 30 percent, a farm operator would be declared insolvent if equity to assets falls to 25 percent even though the operator has a positive net worth. After simulating the last year in the planning horizon, this subroutine calculates the firms after-tax internal rate of return and after-tax net present value over the planning horizon. The internal rate of return is calculated in subroutine IROR using the annual cash returns to the operator (family withdrawals less off-farm income and outside investments in the farm) and the mDebt-equity ratio is the ratio of total debt for the farm divided by total net worth, all in the current year. 17Debt coverage ratio is calculated over the current year and the 2 previous years. The numerator for the ratio is the 3-year total of net cash farm income, off-farm income, and interest payments (operating, intermediate, and long-term) minus the 3-year total of family cash withdrawals (living expenses. income taxes, and self-employment taxes). The denominator for the ratio is the 3—year total of interest payments and principal payments for long- and intermediate-term debts. “The earned equity growth trend coefficient is calculated based on the average change in earned equity over the most recent 3 years. lqThe collateral ratio is the ratio of current and intermediate term debts to current and intermediate term assets after disposal. Machinery and livestock market values are reduced l0 percent in the calculation to account for the cost of liquidating these assets. 39 change in net worth over the entire planning horizon. After-tax net present value for the firm is calculated by discounting the same income series using the discount rate provided by the analyst. Breakeven costs of production for each crop enterprise grown and for the dairy enterprise are calculated next. Labor costs for each crop are calculated assuming unpaid family labor received the same hourly wage as part-time laborers. The opportunity cost for capital invested in farm machinery is computed using the annual interest rate for new intermediate-term loans. Machinery costs, cropshare (or cash) rents, and other fixed costs are allocated to individual crops based on each crop’s planted acres as a fraction of total cropland acres. Breakeven costs are calculated by dividing each crop’s total costs by total production (including the landowner’s share). The breakeven cost for producing milk is computed similarly. However, the model assumes the majority of crop production on the dairy farm is fed to the dairy herd in calculating breakeven costs. The final function of UPDATE is to update the acreage files for the following year. Total cropland in the next year equals owned and leased cropland in the current year plus additional acres purchased or leased at year end. If the firm was declared insolvent, the year counter (i) is set equal to the number of years to be simulated, thus forcing the model to stop simulating the present planning horizon. Subroutines TAXES and TAXTAB Subrourine TAXES includes changes in the federal income tax law through the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA), the Social Security Amendments Act of 1983, the 1984 Tax Act (TRA), and the 1985 Treasury II proposal (TFSEGA). To calculate the sale proprietor’s accrued income tax liability, net farm income is required. If the analyst elects to limit maximum annual interest deductions to, for example, $25,000, the firm’s net farm income is recalculated when total non-CCC interest costs exceed the maximum. Other factors affecting taxable income include depreciation recapture, capital gains and losses. off-farm income, and personal exemptions and itemized deductions. The value for itemized deductions is a fraction (specified by the analyst) of family living expenses, e.g., 20 percent. If there is a net operating loss from prior years, taxable income in the current year is reduced. If there is a net operating loss in the current year, it is automatically carried forward. Calculation of the state income tax (where applicable) is a fraction of the federal taxable income. The model calculates the operators federal income tax liability using both the regular income tax schedules and income averaging. The 3-year base period for income averaging is updated annually. The lesser of the two tax computations is further reduced by tax credits and compared to the alternative minimum tax calculation. Any unused investment tax credit from previous years is used in the current year. if possible. Changes to the alternative minimum tax under TEFRA and TRA are incorporated in the program. The income tax liability is the greater of the alternative minimum tax or the regular tax liability (regular tax computation or income averaging). The self-employment tax is added to the income tax liability to determine total accrued taxes. In addition to these more current income tax provisions. the model is capable of simulating all income tax provisions over the 1971-81 period. The provisions for these years are incorporated in the model in subroutine DEPREC, TAXES. and TAXTAB. The analyst may only use these pre-1982 tax provisions when analyzing crop farms that are not permitted to grow. The depreciation sections of subroutines DAIRY. LVSK. and GROW sections have not been expanded to include the 1971-81 depreciation and investment tax credit provisions. TAXTAB Submarine is called from TAXES to calculate the income tax liability using the federal income tax schedules. Under the Economic Recovery Tax Act of 1981 (ERTA) there are 40 separate tax rate schedules for 1981-84. For tax years after 1984, the exemptions, zero bracket amounts, and tax rate schedules are indexed. Percentage changes in the CPI are used in the model for indexing these values for tax years 1985 and beyond when the 1982 and 1984 Tax Acts are selected. The proposed tax schedule of 15, 25, and 35 percent for TF SEGA is used for years 1986 and beyond when the 1985 tax proposal is selected by the analyst. Subroutines REFIN and SOLVNT Subroutine REFIN is called by CASHF L if the firm has a cash flow deficit at year end. Deficits are initially reduced by granting a lien on crops held for sale in the next tax year. The remaining deficit is handled in one of four ways: (a) obtain a mortgage on long-term equity, (b) obtain a mortgage on intermediate-term equity, (c) obtain a mortgage on both long- and intermediate-term equity, or (d) sell cropland. This subroutine considers each alternative method in the order listed here. The model first tries to refinance the deficit using equity in long-term assets. The deficit plus minimum cash balance can be financed with long-term equity if the additional debt does not decrease the long-term equity ratio below its minimum. When the deficit can be fully refinanced with long-term debt, a new loan is acquired and total long-term debt is increased to reflect the value of the deficit plus the appropriate refinance charge specified by the analyst. If insufficient long-term equity is available, the model finances a portion of the deficit with long-term equity and the remainder with intermediate-term equity. In this case, two new loans are created and the value of debt against both types of assets is increased. In the case of tenant farmers, there is no long-term equity so the model tries to meet the deficit by obtaining a loan against intermediate assets. If there is insufficient equity (long- and intermediate-term) to finance the deficit, the model tries to se_ll cropland. If the operator owns no cropland or the analyst has elected to not allow the sale of cropland, the farm is declared insolvent. When the farm has to sell cropland to meet cash flow deficits. the model sells the most recently purchased parcel(s) first. The model assumes the operator pays off all outstanding debt on cropland when it is sold; thus, more land must be sold to meet a given deficit than the total deficit divided by the per acre market value of cropland. If the operator owns sufficient land to cover the deficit, land is sold, long-term liabilities and assets are reduced. and the operator pays a realized capital gains tax and the deficit. The cropland which has been sold is assumed to be leased back to avoid a situation where the farm has an over-investment in machinery relative to cropland. When the operator can not reduce the deficit to zero after selling all cropland, the firm is declared insolvent. Subroutine SOL VNT is called by subroutines REFIN and UPDATE when a firm is declared insolvent. The purpose of this subroutine is to develop summary information indicating the farm’s financial condition when the firm was declared insolvent. Suhroutine GROW Farm growth through purchase or lease of cropland is determined in GROW if the analyst has specified this option?“ This subroutine is called by CASI-IFL each year of the planning horizon. The farm operators maximum bid price for cropland is calculated using an after-tax net present value formula described by Lins. Harl. and Frey (1982). After determining the maximum bid price. the model returns to CASHFL if the farm may not grow (analysts option). if the farm had to sell 41 cropland to remain solvent that year, if the farm operator’s leverage ratio exceeds 1.10, or if the farm has insufficient cash (cash reserves less than minimum cash balance)?! The model first tries to purchase additional cropland. If none is available, or if the maximum bid price is less than the market price, the operator tries to lease additional cropland. The analyst must supply information as to the availability of cropland. Cropland availability can either be a predetermined number of acres each year or a random event. In the latter case, the analyst specifies the probabilities of four different size parcels becoming available each year, and the model determines at random which parcels are available. The operator is not allowed to buy cropland if the maximum bid price is less than the average per acre market value of cropland. The operator purchases the largest parcel he can pay the downpayment for when given a choice among parcels. The immediate cost of the expansion is the minimum downpayment for the land plus the minimum downpayment for additional equipment necessary to farm the proposed ‘ larger size farm. Downpayments for machinery must be paid from cash reserves, while up to 50 j percent of the downpayment for cropland can be paid using equity in (or increasing total debt on) a existing land. Prior to finalizing the purchase, the model checks the equity ratios that would exist after the purchase. The proposed sale is canceled if the purchase would overextend the debt bearing i capacity of the operation. Qnce the purchase is made, the firm’s financial variables (total debts and i assets) are updated to reflect the purchase. If land can not be purchased, the operator tries to lease cropland. Cropland available for lease can either be predetermined or treated as a stochastic variable. The operator leases the largest parcel available each year if he can pay the downpayment for the additional machinery out of cash reserves. Prior to leasing land, the model checks the pertinent equity ratios to insure the proposed machinery purchase will not force the farm to declare bankruptcy. Machinery requirements for larger farm sizes are provided by the analyst. By forcing the operator to add full complements of farm machinery as the firm grows, the model incorporates both the nonlinearities inherent in agriculture and the lumpiness of machinery purchases. Machinery and land purchases are financed based on the market value of the assets purchased, the assets’ minimum downpayment. and the number of years and interest rates for the types of loans involved. All machinery purchases for firm growth are assumed to occur at the end of the year. Machinery purchased in GROW is depreciated, for tax purposes, like other new farm machinery items purchased by the operator in subroutine DEPREC. Investment tax credits are calculated, as well as first-year expensing for all new purchases, if the analyst requested these options. All equipment purchased for growth is cost recovered assuming a 5-year recovery period. Subroutine TAXES is called when machinery is purchased in GROW and the operator’s accrued income taxes are recalculated. incorporating the deductions resulting from the machinery purchase. wSensitivity analyses to determine the effects of farm growth on the results are recommended to insure that growth does not cause distortion of the farm survival results. 31A maximum zillowable leverage ratio for growth of 1.1 is based on an assumption that the financial community currently is discouraging operators from leveraging their present equity to purchase additional cropland. A leverage ratio of 1.1 implies a debt to asset ratio of 0.47 for the farm operator. 42 Subroutine IROR This subroutine uses a Newton iterative procedure for calculating the internal rate of return of earnings. The earnings stream used to compute internal rate of return is the annual income withdrawn in the form of family living expenses plus the annual value of home consumption minus annual outside capital invested in the farm minus annual off-farm income plus ending net worth minus initial net worth. This series of earnings accounts for all income generated by the farming operation over the planning horizon, whether the income is removed from the operation or retained. A description of the procedure is available in Stark (1970). The subroutine is called by UPDATE and ITSUMM. Subroutines PRINT1, PRINTZ, PRINT3, and PRINT4 At the end of a deterministic simulation, the model prints the output for the analysis as well “as all intermediate answers generated by the model (Fig. 1). Four subroutines perform these printing functions. Subroutine PRINTI prints (dumps) all intermediate and final solutions for the model and can only be accessed during deterministic runs. FLIPSIM V makes use of matrix notation (row and column) to keep track of variables, years, etc. By doing this, all variables in the model are assigned column numbers in one of seven matrices rather than assigning six letter names to over 800 variables in the model. A complete list of variables in the model (i.e., column numbers for the matrices), is provided in Appendix D. Since the intermediate and final values for all variables in the model are in a limited number of matrices, these values can be printed for hand verification. The output from PRINT1 is written to unit 922 so it does not interfere with the final output tables written to unit 6.23 This subroutine also prints three matrices whose values are fixed in the model through a BLOCK DATA statement. These matrices hold data for the 1981, 1982, 1983, and 1984 income tax rate schedules, cost recovery fractions under TEFRA, and the schedule for adjusting FCIC premiums for changes in the loss ratio. Subroutines PRINTZ and PRINT3 write the final output tables for the model. The tables written are income statement. income tax calculations summary, breakeven costs summary, cashflow statement, balance sheet. and farm growth/crop mix/farm policy summary. A sample output is included in Appendix C. This subroutine writes to unit 6 and is not used when a stochastic simulation has more than 5 iterations to avoid excessive output for a stochastic analysis. Subroutine PRINT4 writes the output table for the dairy enterprise. This subroutine is not used when a stochastic simulation has more than five iterations. The dairy enterprise output table is written to unit 6. 22Unit 9 is an output source identified in the JCL for the model. Unit 9 should be attached to the line printer if the analyst wants a printout of the values used for all intermediate calculations. This output consists of all tows and columns of the primary arrays and matrices in the model. The output to unit 9 can be avoided by attaching unit 9 to a dummy sysout unit. 33Unit 6 is the standard output unit number in the JCL for the model. Unit 6 must be attached to the line printer to obtain any printed output from the model. 43 Subroutine ITSUMM At the end of each iteration in a stochastic simulation (Fig. 1), the model summarizes the results and stores part of the results in matrices PV and S. The present value of the farm’s income stream (after-tax net present value) is calculated in ITSUMM, as well as the present value of ending net worth and the internal rate of return for the iteration (subroutine IROR). After-tax net present value is the present value of the following income and wealth flow over "n" years--annual cash withdrawals for family living plus value of home consumption minus outside capital invested in the farm minus all off-farm income. The present value of the farm’s net worth for the last solvent year is added to this flow and the firm’s initial net worth is subtracted to incorporate the present value of returns from capital gains and retained earnings. Other key output variables related to ending farm size and debt are stored in matrix PV. Several hundred variables are stored in matrix S, such as, annual crop prices, acreages, and yields; annual family consumption; annual accrued income taxes; annual government payments; and annual ending year cash reserves. For iterations in which the farm was declared insolvent, a brief summary table of key output variables is written to unit 6 from this subroutine. This summary table provides information for annual prices and yields, cropland owned and leased, net income, cash reserves, assets, liabilities, and net worth. The subroutine concludes by reinitializing the farm to its beginning economic situation by setting the work arrays to the analyst’s original input data for the firm. Subroutine STAT Statistical analysis of the output variables in the PV and S matrices are performed in this subroutine. Cumulative distributions are calculated for each of the output variables by sorting each variable’s simulated values over the 50 or so iterations (dimensions for the PV, S, and A arrays can be increased from 50 to 300, if 300 iterations are desired). The probability of the farm having a positive net present value, i.e., of being an economic success, is determined using the cumulative distribution for net present value. A table summarizing the probability of the firm remaining solvent each year of the planning horizon is printed as the last function of the subroutine. A sample of the output from this subroutine is in Appendix C. All output from this subroutine is written to unit 6. The cumulative probability distribution for net present value is stored on unit 4 for future analysis.” Because the model can analyze multiple scenarios in a single run, the net present value cdf for each scenario is stored in a separate record on unit 4. The analyst should specify the record (file) number for storing the scenarios on unit 4 (Core Data Card 3). Each scenario must have a unique number between l and 99 to avoid overwriting the results with future runs of the model. “Unit 4 is a direct access file on a hard disk for storing the net present value cumulative probability distributions. This workspace can be addressed if a stochastic dominance analysis is to be performed on the scenarios analyzed. Each of the 99 records for this data set contains 400 words consisting of the scenarios name and the net present value for each iteration. 44 &.u".ul.lnflubdz. z .i .. Jana-manila. a. i§L>v>‘vwv‘.t.i_ The statistics (mean, standard deviation, coefficient of variation, minimum, and maximum) for the first 23 output variables analyzed in subroutine STAT, as well as the probabilities of survival and success are stored on unit 3.25 A report writer can be developed to prepare tables of these output variables for multiple scenarios. The analyst should specify the record (file) number for storing each scenario on unit 3 to avoid overwriting the results with successive runs of the model. The record number specified for the net present value cdf on unit 4 is also used for the statistics stored on unit 3. Concluding Remarks This manuscript is a complete description of FLIPSIM V at the present time. The model will continue to be updated and expanded to analyze complex problems facing farmers. The present documentation provides a starting point for analysts who want to modify FLIPSIM V for the particular problem or problems to be addressed. Areas of potential expansion and modification of the model are: O Multidirectional linkage between FLIPSIM and a macroeconomic policy simulation model to provide annual average values for interest rates, percentage change in input costs, and crop prices. O Integration of the model into an expert system for analyzing problems faced by farmers in a whole-farm, systems approach. 0 Expansion of the livestock section to simulate a ranch which is subject to stochastic weather and thus random pasture conditions. 0 Respecification of the farm machinery sector to determine machinery operating costs and replacement based on hours of use. 0 Expansion and improvement of the crop marketing sector for the evaluation of alternative marketing strategies. 0 Modification of the random number generating process to include intertemporal, multivariate probability distributions for crop prices and yields. 0 Respecification of the model to make interest and inflation rates random based on a multivariate probability distribution. Each of these changes would involve at least l additional year of research and testing, so they are left to other researchers. Anticipated and current uses of the model by researchers in the Texas Agricultural Experiment Station include: O Informal linkage of the COMGEM model developed by Penson, Hughes. and Romain with FLIPSIM V to allow indepth analyses of macroeconomic/agricultural policies on representative farms in Texas. 0 Inclusion of FLIPSIM V into the Farm Level Expert System (FLEX), an expert system which uses artificial intelligence technology for analyzing problems facing cotton and rice producers. 35Unit 3 is a direct access file on a hard disk for storing the summary statistics for up to 99 stochastic scenarios. The file can be accessed with a report writer to retrieve the results in any order the analyst prefers. Data in each record of unit 3 are stored as follows: the first 100 words contain the title of the simulation. the next five words contain the statistics for net present value. the next five words contain the statistics for present value of ending net worth. etc. The last two words of each record contain the probabilities of survival and success. 45 O Development of a detailed ranch simulation sub-model for evaluation of alternative grazing systems in West Texas. O Expansion of the marketing sector of the model to evaluate the use of options as a marketing tool for cotton producers. O Use of the model to evaluate alternative crop mix strategies for farmers in the Coastal Bend and the Blacklands of Texas. O Incorporation of the model to evaluate the impacts of alternative macroeconomic/agricultural policies on the survival of rural communities. O Inclusion of a stochastic world cotton simulation (POLICOT) into FLIPSIM V to facilitate analysis of alternative farm policies and international trade policies on Texas cotton farmers. Numerous cautions should be extended to future users of the model. It goes without saying that the reliability of the results depends on the quality of the input data. Instructions for entering data in the model are very extensive and are included in Appendix A. The robustness of the results should always be checked using extensive sensitivity analyses. Model results for a given farm size are sensitive to macroeconomic and agricultural policies, crop price and yield distributions, off-farm income, family living expenses, tenure arrangement, and initialdebt to asset ratio. In addition, if the farm scenario being reported allows for farm growth, the model should also be run not allowing the farm to grow. A final caution would be to analyze each scenario deterministically before the stochastic analysis. This added expense points out omissions and errors in the input data before the more expensive stochastic analysis. 46 References Bailey, D. V. "Economic Analysis of Selected Marketing Strategies for Cotton in the Texas Southern High Plains: A Whole-Farm Simulation Approach." Department of Agricultural Economics, Texas A&M University, Ph.D. Dissertation, 1983. Bailey, D. V., B. W. Brorsen, and J. W. Richardson. "Dynamic Stochastic Simulation of Daily Cash and Futures Cotton Prices." Southern Journal of Agricultural Economics, 16(1984): 109-116. Baum, K., J. W. Richardson, and L. Schertz. "A Stochastic Recursive Interactive Programming Model for Farm Policy Analysis." Computers and Operations Research, 10(1984): 199-222. Brake, J. R. "Firm Growth Models Often Neglect Important Cash Withdrawals." American Journal of Agricultural Economics, 50(1968): 769-72. Brorsen, B. W., J. W. Richardson, W. R. Grant, and L. D. Schnake. "Impacts of Price Variability on Marketing Margins and Producer Viability in the Texas Wheat Industry." Western Journal of Agricultural Economics, 9(1984): 342-352. Clements, A. M., Jr., H. P. Mapp, Jr., and V. R. Eidman. "A Procedure for Correlating Events in Farm Firm Simulation Models." Technical Bulletin T-131, Oklahoma Agricultural Experiment Station, 1971. Duffy, P. A., J. W. Richardson, and E. G. Smith. "The Effects of Alternative Farm Programs and Levels of Price Variability on Different Size Farms." Paper presented at the American Agricultural Economics Meeting, Ithaca, New York, 1984. Grant, W. R., J . W. Richardson, B. W. Brorsen, and M. E. Rister. "Economic Impacts of Increased Price Variability: A Case Study With Rice." Agricultural Economics Research, 36(1984): 17-27. Hardin. M. H. "A Simulation Model for Analyzing Farm Capital Investment Alternatives." Ph.D. Dissertation, Oklahoma State University, 1978. Harpaz. A. and H. Talpaz. "SOP User's Guide." Texas Agricultural Experiment Station, Department of Agricultural Economics, Texas A&M University and The Volcani Center, Department of Statistics, ARO. Bet-Dagon, Israel, (mimeo). 1982. Hottel. J. B. and C. D. Evans. "Returns to Equity Capital in the U.S. Farm Production Sector." Balance Sheet of the Farming Sector, I979: Supplement. USDA. ESCS. Agr. Info. Bul. No. 430, 1980. Hutton, R. F. and H. R. Hinnman. "Mechanics of Operating the General Agricultural Firm Simulator." pp. 21-64 in Agricultural Production Systems Sintulation. (ed. V. R. Eidman) Stillwater: Oklahoma Agricultural Experiment Station, 1971. Johnson, J . and M. H. Ericksen. Commodity Program Provisions Under the Food and Agriculture Act of I977. USDA, ERS. CED, Agri. Econ. Rep. No. 389. 1977. Johnson, J., R. W. Rizzi. S. D. Short, and R. T. Fulton. "Provisions of the Agriculture and Food Act of 1981." USDA. ERS, NED. Staff Rep. No. AGES81l228, 1982. King, R. P. "Operational Techniques for Applied Decision Analysis Under Uncertainty." Ph.D. Dissertation, Michigan State University, 1979. Knutson, R. and J. W. Richardson. "Alternative Policy Tools for U.S. Agriculture." Texas Agricultural Experiment Station. Bulletin. B-1471, 1984. 47 Law, A. M. and W. D. Kelton. Simulation Modeling and Analysis. New York: McGraw-Hill Book Company, 1982. Lemieux, C. M., J . W. Richardson, and C. J. Nixon. "Federal Crop Insurance vs. ASCS Disaster Assistance for Texas High Plains Cotton Producers: An Application of Whole-Farm Simulation." Western Journal of Agricultural Economics, 7(1982): 142-53. Lins, D., N. Harl, and T. Frey. Farmland. Skokie: Century Communications, 1982. Naylor, T. H. Computer Simulation Experiments with Models of Economic Systems. New York: John Wiley and Sons, Inc., 1971. Nixon, C. J. and J. W. Richardson. "The Economic Recovery Tax Act of 1981: Consequences for Farm Operators." Agricultural Finance Review, 42(1982): 1-10. Office of Technology Assessment. Technology. Public Policy, and the Changing Structure of American Agriculture: A Special Report for the I 985 Farm Bill. Washington, D.C.: U.S. Congress. OTA-F-272, 1985. Patrick, G. F. and L. M. Eisgruber. "The Impacts of Managerial Ability and Capital Structure on Growth of the Farm Firm." American Journal of Agricultural Economics, 50(I968).' 491-506. Penson. J. B., Jr., and D. Lins. Agricultural Finance: An Introduction to Micro and Macro Concepts. Englewood Cliffs: Prentice-Hall, 1980: 178-179. Perry, G. M., M. E. Rister, J. W. Richardson. J. Sij, and W. Grant. "The Impact of Tenure Arrangements and Crop Rotations on Upper Gulf Coast Rice Farms: A Survival Approach." Texas Agricultural Experiment Station. Department of Agricultural Economics, (mimeo), 1985. Prentice-Hall, Inc. 1984 Federal Tax Handbook. Englewood Cliffs: Prentice-Hall, 1984. Ray, D. E. and J. W. Richardson. "Detailed Description of POLYSIM." Oklahoma Agricultural Experiment Station. Technical Bulletin, T-15l', 1978, p. 46. Ray, D. E., J. W. Richardson, and E. Li. "The 1981 Agriculture and Food Act: Implications for Farm Prices, Incomes and Government Outlays to Farmers." American Journal of Agricultural Economics, 64(l982):957-64. Richardson, J. W. and D. V. Bailey. "Debt Servicing Capacity of Producers in the Northern High Plains." Report to the Farm Credit Banks of Texas, Department of Agricultural Economics, Texas A&M University, 1983. (Thirteen reports with a similar title for different regions in Texas were completed.) Richardson, J. W. and G. D. Condra. "Farm Size Evaluation in the El Paso Valley: A Survival/Success Approach." American Journal of Agricultural Economics, 63(l98l):430-37. Richardson. J. W. and G. D. Condra. "A General Procedure for Correlating Events in Simulation Models." Texas Agricultural Experiment Station. Department of Agricultural Economics. (mimeo), 1978. Richardson. J. W.. C. M. Lemieux. and C. J. Nixon. "Entry into Farming: The Effects of Leasing and Leverage and Firm Survival." Southern Journal of Agricultural Economics, l5(l983): 139-45. Richardson. J. W. and C. J. Nixon. "The Farm Level Income and Policy Simulation Model: FLIPSIlVl." Texas Agricultural Experiment Station. Department of Agricultural Economics, Departmental Technical Report No. 81-2. i981. 48 . . ..»._...._||.;..L ._i.t..i¢.4. d“; iA.-.-4k‘m."fldlhm. vnajqhflqlilp-lqlrln...‘.ijmt_la\-fllflxfl4i~._).>4Qn41~d.4r._m.nn4l.nn~a i Richardson, J. W. and C. J. Nixon. "Producer’s Preference for a Cotton Farmer Owned Reserve: An Application of Simulation and Stochastic Dominance." Western Journal of Agricultural Economics, 7(1982a): 123-32. Richardson, J. W. and C. J. Nixon. "The Economic Recovery Act of 1981: Impacts on Farmer’s Liquidity, Equity, and Growth." Journal of Farm Managers and Rural Appraisers, 46(1982b): 10-15. Richardson, J. W. and C. J. Nixon. "Effects of the 1980, 1981 and 1982 Tax Laws on Texas Rice Farmers." Southern Journal of Agricultural Economics, 16(1984a): 137-44. Richardson, J. W. and C. J. Nixon. "Selecting Among Alternative Depreciation Methods: A Stochastic Dominance Approach." Paper presented at the American Agricultural Economics Association Meeting, Ithaca, New York, 1984b. Richardson, J. W. and C. J. Nixon. "Technical Description of the Firm Level Income Tax and Farm Policy Simulation Model (FLIPSIM V)." Texas Agricultural Experiment Station, Department of Agricultural Economics, (mimeo). 1985. Richardson, J. W., C. J. Nixon, and E. G. Smith. "Economic Impacts of the 1981 Agricultural Act and the 1981 Tax Act on Texas High Plains Farmers." Southern Journal of Agricultural Economics, 14(l982): 71-76. Shirley, C. K. "The Structural Impact of Commodity Farm Programs on Farms in the Southern Texas High Plains." Department of Agricultural Economics, Texas A&M University, M. S. thesis, 1981. Smith, E. G. "Economic Impact of Current and Alternative Farm Programs on Farm Structure in the Southern High Plains of Texas." Department of Agricultural Economics. Texas A&M University, Ph.D. Dissertation, 1982. Stark, P. A. Introduction to Numerical Methods. New York: Macmillan Pub. Co., Inc., 1970. U.S. Department of Agriculture. Economic Indicators of the Farm Sector: Income and Balance Sheet Statistics. ERS-ECIFS, 2-2, 1982. U.S. Department of Agriculture. Farm-Operator Fa/nily Living Expenditures for 1973. SRS, SPSY6 (9-75). U.S. Department of Agriculture. Farm Real Estate Market Developments. ESCS, CD-84, issues in 1970-1984. U.S. Department of Agriculture. Implementing the Agricultural Adjustment Act of I980. ASCS, PA-742, PA-743, PA-744 and PA-745, March. 1980. U.S. Department of Commerce. I982 Census of Agriculture: Part 43 - Texas State and County Data. USDC-Bureau of Census, AC82-A-43, 1984. Van Horn, R. L. "Validation of Simulation Results." ‘Management Science. I7(I971): 247-57. 49 Appendix A: Coding Instructions for all Input Data Card O -- Number of Data Sets The first card in the data deck indicates the number of representative farms (or complete data sets) the analyst has provided information for in the data set. The value can range from l to 99. The model processes the first data set, then proceeds to the next data set, and so on, until it encounters an input error or completes all data sets. An example card for processing the data for three data sets (representative farms) is: Card Columns 1-2 Code the card number, ’00’. 3-4 Code the number of data sets included in the data stream, as '03’ for three farms. 5-80 Blank. Core Data Cards -- Cards 1-30 Card 1.1-1.5 -- Simulation Name Card The name of the data set to be run is entered on Card 1. To provide sufficient space to enter a discriptive name for the simulation, the program assumes the first five cards of each data set are for the name. See Appendix B for a sample set of data card images for simulating a representative farm. (20A4) Card Columns l—80 Code a 400 character alphanumeric name for the simulation. Use five cards (l.'l-1.5) for the name and enter up to 8O characters per card. Card 2 -- Program Options Card The model has a large number of options the analyst may select from. The analyst must specify the number of years to simulate. which farm policies are in effect, whether the simulation is deterministic or stochastic. and whether the farm is allowed to grow. Additionally, the analyst must specify the number of crop and livestock enterprises on the farm and the depreciation methods to be used. The default value for each option is ’0'. All values on the Program Options Card must be right justified. 5O Card Columns 2-3 4-6 l0 ll Option N0. 49 26 50 Option Code the card number ’2’. Number of years to be simulated from ’01’ to ’l0’. Deterministic or stochastic: ’0’ if the program is to be run deterministically; ’050’ if the program is to be run stochastically for 50 iterations. (The model will simulate a maximum of 300 iterations.) Summary of input data and results: ’0’ to print all input data and all output for a deterministic analysis; ’l’ to print all input data and summary table for a deterministic analysis; ’2’ to print minimum input data and all output for a deterministic analysis; ’3’ to print minimum input data and summary table for a deterministic analysis. Summary of stochastic results: ’0’ for a statistical summary of all output variables including annual crop yields, prices. and acreages; ’l’ for a statistical summary of 189 key output variables; ’2’ for a statistical summary of 89 key output variables; ‘3’ for a statistical summary of 39 key output variables; '4’ for a statistical summary of 23 key output variables. (A description of the first 89 variables is provided in the PV matrix and a list of the remaining output variables (89-189 and 190-489) are provided in the S matrix.) Summary of each insolvent iteration: ’0’ to not print a summary table for each insolvent iteration; ’l’ to print a summary table for each insolvent iteration. Cumulative probability distributions: ’0’ to calculate and print cumulative probability distributions for all output variables, including annual crop prices. yields, and acreages; (This value may be used only if Option 26 equals zero.) ’l’ to calculate and print cumulative probability distributions for the first 189 output variables: ’2' to calculate and print cumulative probability distributions for 89 key output variables: ’3’ to calculate and print cumulative probability distributions for 39 key output variables; ‘4’ to print no cumulative probability distributions. Expand or contract yield and price probability distributions: ’0’ to use the same relative variation (coefficient of variation’) for crop yields and prices over time; ’l’ to increase or decrease the relative variability in crop yields and prices over time. This option is only operational for empirical probability distributions. (When this option is used the analyst must provide annual fractional changes in the distributions on Card 53.) 51 12 13-14 16 18 19-21 23 24 1O Z2 31 Probability distributions for yields and prices: ’0’ for multivariate normal probability distributions; (The factored covari- ance matrices are provided on Cards 27, 48, and 79.) ’1’ for independent normal probability distributions; (Standard deviations are provided on Cards 27, 48, and 79.) ’2’ for multivariate triangular probability distributions; (Code optional data Cards 51 and 52 as well as the factored correlation matrices on Cards 27 and 48.) ’3’ for independent triangular probability distributions; (Code optional data Cards 51 and 52 as well as the own correlation coefficients on Cards 27 and 48.) ’7’ for multivariate empirical probability distributions; (Code optional data Cards 50 and 80 as well as the factored correlation matrices on Cards 27, 48, and 79.) ’8‘ for independent empirical probability distributions. (Code optional data Cards 5O and 80 as well as the own correlation coefficients on Cards 27, 48, and 79.) Number 0f crop enterprises on the farm, from ’01’ to ‘l0’. The farm must have at least one crop enterprise, even if it is a confinement dairy farm. If the farm is allowed to grow, this value must be the larger of the number of crops for the initial farm and the number of crops for the most diversified farm. Number of non-dairy livestock enterprises on the farm, from ‘l’ to ’5’. (See Card 44 for a list of alternative livestock enterprises. When this option is used, information for livestock must be provided on Cards 44-49.) Constant or variable crop mix: ’0’ for a crop mix that remains the same over time; ’1’ for a crop mix that changes over time using an LP; ’2’ for a crop mix that changes over time using a QP. (lf this option is selected, code Card 54.) Number of farm machinery items to be depreciated (cost recovered), from ’OO1’ to ’O99’. (This value determines the number of Card 30’s pro- vided by the analyst.) Machinery replacement method for all farm machinery: ’0’ if machinery is sold after it passes its useful life; ’1’ if machinery is traded-in after it passes its useful life. Depreciation method for farm machinery and purchased breeding stock placed into use before 1981: ’0’ to use a straight line depreciation schedule; ’1’ to use a declining balance schedule. Capital recovery method for farm machinery placed into use after 1980: '0’ to use a straight line recovery method; ‘l‘ to use an accelerated recovery method. 52 29 31 .35 38-39 41 32 33 34 35 27 36 Capital recovery method for breeding and dairy stock purchased after 1980: ’0’ to use straight line depreciation schedule; ’1’ to use an accelerated depreciation schedule. Capital recovery method for regular buildings placed into use before 1981: ’0’ to use a 15-year straight line method; ’1’ to use a 15-year declining balance method. Capital recovery method for special use buildings placed into use after 1980: ’0’ to use a 5-year straight line schedule; ’1’ to use a 5-year accelerated schedule; ’2’ to use a 12-year straight line schedule. First-year expensing for farm machinery and breeding stock pur- chased after 1980: ’0’ if expensing is not elected; ’1’ if expensing is elected. Farm growth (purchase or lease) can be simulated by two different growth strategies. If the option equals 1 or 2, purchased cropland is assumed to be a net increase in total land farmed. When the option equals 3 or 4, it is assumed the operator purchases land which has been previ- ously leased. ’0’ if the farm may not grow through purchasing or leasing additional cropland; (Do not include Cards 32-33 or 34-36 if this option is used.) ’1’ if the farm may grow and the availability of cropland is predetermined by the analyst; (Cropland availability information must be provided on Cards 32 and 33.) ’2’ if the farm may grow and the availability of cropland is a random vari- able; (Cropland availability information must be provided on Cards 34-36.) ‘3’ if the farm may grow and the availability of cropland is predetermined by the analyst, but an equal amount of leased land is turned back when land is purchased: (Cropland availability information must be provided on Cards 32 and 33.) ’4’ if the farm may grow and the availability of cropland is a random vari- able. but an equal amount of leased land is turned back when land is purchased. (Cropland availability information must be provided on Cards 34-36.) Number of larger farms (alternative sizes) the analyst is providing information for on Cards 37-43; this value can range from ’0’ to ’10’. (The analyst may provide information on Cards 37-43 without the farm actually growing by setting Option 8 equal to zero.) Constraints on farm growth: ’0’ if the farm may grow by using equity in long-term assets to meet downpayment requirements for land: ‘l’ if the farm may not leverage existing equity to meet downpayment requirements for land. 53 43 45 47 49 21 23 11 47 Sell cropland to remain solvent: ’O’ if the owner may not sell cropland t0 avoid insolvency; '1’ if the owner may sell cropland to avoid insolvency. (Once cropland is sold, it is assumed the operator leases the cropland in succeeding years.) Cropland lease method -- share or cash: ’O’ if the operator uses a crop share lease; (Terms of the crop share lease are provided on Card 31.) ’1’ if the operator uses a cash lease and the per acre lease cost is escalated at a rate specified by the analyst; (The escalation rate is provided on Card 18.) ’2’ if the operator uses a cash lease, and the per acre lease cost is a func- tion of the market value for cropland. (The necessary capitalization rate for this option is provided on Card 18.) ’3’ if the model is being used for a landowner/share analysis. (Terms for the lease between the landowner and the tenant are provided on Card 31.) Capital gains rate for farmland: ’O’ if the capital gains rate is a function of the return to production assets; ’l’ if the annual capital gains rate is determined exogenously by the analyst on Card 19; ’2’ if the capital gains rate formula in the model is used, but the annual percentage has an upper bound equal to the percentage changes for farmland values entered on Card l9. Price support and farmer-owned reserve (FOR) programs: ’O’ if neither a price support program nor a FOR is in effect; ’l’ if an unlimited nonrecourse loan (price support) program is in effect; ’2’ if a nonrecourse price support program and a FOR program is in effect and stocks from the reserve are released at the "trigger price;" ’3’ if a nonrecourse price support program and a FOR program is in effect and stocks from the reserve are released at the "call price;" ’4’ if a direct FOR program is in effect and stocks from the reserve are released at the "trigger price;" ’5’ if a direct FOR program is in effect and stocks from the reserve are released at the "call price;" ’6’ if a limited nonrecourse loan (price support) is in effect and the remainder of the crop is sold directly; ‘7’ if a limited nonrecourse loan (price support) is in effect and the remainder of the crop is placed in a recourse loan; ’8’ if a recourse loan is in effect; ’9’ if a marketing loan program is in effect. Flexible loan rates: ’O’ if loan rates for the nonrecourse CCC loan and the marketing loan remain at the analyst’s specified values on Policy Cards Pl and P39, respectively: ’l’ if loan rates for the nonrecourse CCC loan and marketing loan are cal- culated for years 2 through n based on moving average formulas specified on Policy Card P35. 54 51 52 55 57 59 12 48 51 15 16 18 Number of years interest is charged for FOR loans: ’O’ if interest is waived for all years of a FOR loan; ’1’ if interest is due in only the first year of a FOR loan; ’2’ if interest is due in only the first 2 years of a FOR loan; ’3’ if interest is due in all years of a FOR loan. Pay interest on CCC forfeited loan: ’O’ to not pay interest on forfeited nonrecourse CCC loan; ’1’ to force producer to pay interest on forfeited nonrecourse CCC loan. Target price program: ’O’ if a target price/deficiency payment program is not in effect; ‘l’ if a deficiency payment subject to the payment limit is in effect and target prices remain at the analyst’s specified values on Policy Card P2 in all years; ’2’ if a deficiency payment subject to the payment limit is in effect and target prices are a function of the loan rate. This option should only be used when loan rates are flexible (Option 47 equals 1). ’3’ if a Findley deficiency payment is in effect. Gramm-Rudman payment reduction: ’O’ if government payments are not reduced by the Gramm-Rudman frac- tions on Policy Card P40; ’l‘ if government payments are reduced by the Gramm-Rudman fractions on Policy Card P40. All-risk crop insurance and disaster programs: ’O’ if neither a disaster program nor an all-risk crop insurance program is in effect: ‘l’ if a prevented-plantings disaster program is in effect; '2‘ if a low-yield disaster program is in effect; ’3‘ if both a prevented-plantings and a low-yield disaster program is in effect: ‘4’ if an all-risk crop insurance program is in effect. Production control farm program: ‘0‘ if an acreage set-aside, an acreage diversion. or an acreage limitation program is not in effect: ‘l’ if an acreage set-aside program or an acreage diversion program is in effect; '2‘ if an acreage limitation program is in effect. (Caution: If any acreage limitation program is in effect. do not use the LP or OP (Option 9) to change the crop mix over time.) Payment limitation: ‘O‘ if there is no payment limitation for deficiency, diversion, and disaster payments: '1‘ if there is a payment limitation for deficiency payments and diversion payments; ‘ if there is a payment limitation for disaster payments; (‘No limit on federal crop insurance indemnities.) '3‘ if there is a payment limitation for deficiency payments. diversion pay- ments. and disaster payments: ‘4‘ if the deficiency payment limitation is based on a percent of the value of base production. 55 rd 61 65 67 68-69 70-71 19 20 28 14 29 Marketing quota which provides a two-tiered loan program but works with the set-aside option to reduce production: ’O’ if a marketing quota program is not in effect; ’1’ if a marketing quota program is in effect. Acreage allotment program: ’O’ if an acreage allotment program is not in effect; ’1’ if an acreage allotment program is in effect. Target farm program benefits: ’O’ if all size farms are eligible to participate in all farm programs; ’1’ if farms having more than a specified number of acres are not eligible to participate in all farm programs; (The acreage level is specified on Policy Card 30.) ’2’ if farms having more than a specified number of acres are eligible to participate only in the Federal Crop Insurance program; (The acreage level is specified on Policy Card 30.) ’3’ if farms producing more than a specified value of farm program crops (loan rate times production) are not eligible to participate in farm programs; (The level of crop sales is specified on Policy Card 30.) ‘4’ if farms producing more than a specified value of farm program crops (loan rate times production) are eligible to participate only in the Federal Crop Insurance program. (The level of crop sales is speci- fied on Policy Card 30.) Marketing certificate farm program: ’O’ if there is not a marketing certificate farm program in effect for any crop; ’1’ if there is a marketing certificate farm program in effect for at least one crop. Depreciation of purchased breeding stock: ’O’ if no beef cattle are raised on the farm or none of the beef cattle are eligible for depreciation or cost recovery; ‘ otherwise enter the number of beef cattle units to be depreciated or cost recovered, i.e., the number of Card 46‘s provided by the analyst. 7 The number of pieces of machinery leased on a variable length lease. The value entered (from 0 to 99) must equal the number of Card 55’s entered. Federal income tax provisions: ’O’ if the farm operator is subject to only the 1983 federal income tax pro- visions: '1' if the farm operator is subject to only the 1984 federal income tax pro- visions; '2 if the farm operator is subject to only the 1985 federal income tax pro- visions after 1984; '3’ if the farm operator is subject to each income tax provision as it was implemented; '4‘ if the farm operator is subject toonly the 1981 federal income tax pro- visions: '5' if the farm operator is only subject to the 1982 federal income tax pro- visions: if the farm operator is only subject to the 1975 federal income tax pro- vlSlOflS. w .0 56 nhuauautscn- -.tt~.....tm..t..'.mna..s,.mn.t.unfiiidfl 73 74 75 76 77 78 79 44 42 4O DJ O0 Crop marketing strategies: all five strategies make use of the CCC loan if it is available, however. some overtly use it t0 carry stocks across the crop year. ’0’ if the operator sells a fixed portion of the crop in the year it is har- vested and the remainder in the next tax year; ’1’ if the operator sells a fixed portion of the crop in the year it is har- vested and the remainder in the next tax year, using the CCC loan to carry the crop in storage; (Avoid this strategy if the recourse CCC loan is in effect.) ’2’ if the operator sells a minimum amount of the crop in the year it is harvested and stores the remainder until the following tax year; (The desired taxable income level must be specified on Card 13.) ’3’ if the operator sells a minimum amount of the crop in the year it is harvested and places the remainder in the CCC loan to be sold in the next tax year; (Avoid this strategy if a recourse CCC loan is in effect.) (The desired taxable income level is on Card 13.) ’4’ if the farm operator uses an accrual accounting system and does not spread crop sales across tax years to reduce federal income taxes. Financial bailout strategies: ’0’ if no special financial bailout strategy is available; ’1’ if a 2-year interest moratorium is in effect and the unpaid interest is added to total debt; ’2’ if a 2-year interest rate buydown is in effect, long-term interest rates are reduced 3 percentage points and intermediate-term interest rates are reduced 5 percentage points; ‘3’ if a 10 percent buydown of initial principal is to be simulated; ’4’ if an extended bailout program is simulated which (a) converts 5O per- cent of initial intermediate-term debt to long-term, (b) extends long- term debt to 40 years. (c) postpones all principal payments for 5 years, and (d) increases interest rates 1 percentage point for 5 years. Basis reduction for Investment Tax Credits on machinery and live- stock: ’0’ to reduce basis for investment tax credits; ‘l’ to not reduce basis for investment tax credits. Use surplus cash for early repayment of intermediate and long-term debts: ’0’ to not use surplus cash to retire debts early; ’1’ use surplus cash to retire debts early. Federal Crop Insurance premium adjustment: ’0’ to adjust the FCIC premium schedule based on loss records: ’1’ to not adjust the FCIC premiums based on loss records. Maximum annual interest deduction (excluding interest paid to CCC) a sole proprietor may claim as a federal income tax deduction: ’0’ no maximum interest deduction; ‘l’ to use the maximum interest deduction specified on Card l4. Adjust federal income tax rates for changes in the Consumer Price Index (CPI): ‘O’ to adjust the tax rates for changes in the CPI after 1984: ‘l’ to not adjust the tax rate after 1984. 57 80 41 Dairy enterprise: ’0’ if the farm does not include a dairy enterprise; ’1’ if the farm has a dairy enterprise. Card 3 -- Farmland Owned and Leased The number of acres of cropland and pastureland the farm operator owns and leases at the beginning of the planning horizon. (2I2,6X,7F10.0) Card Columns 1-2 Code the card number ’03’. 3-4 Record number to store net present value cdf in unit 4 and summary sta- tistics in unit 3 after stochastic simulation, such as ’01’, ’10’, ’22’. 5-10 Code a card name, such as ’ACRES’. 11-20 Acres of cropland owned, as 320.0. The farm must have at least 1 acre of cropland, even if it has a zero value. 21-30 Acres of cropland leased, as 160.0. 31-40 Acres of pastureland owned, as 40.0. 41-50 Acres of pastureland leased, as 80.0. 51-60 Fraction of cropland that is tillable. as 0.95. A non-zero value must be provided to obtain values for planted acreage in years 2 through n. 61-70 If all the cropland on the farm is leased, enter the per acre market value for cropland, as 890.0 dollars, otherwise leave this value blank. 71-80 Fraction of the total cropland under irrigation. as 0.45. Card 4 -- Value of Owned Assets The market value of owned cropland, pastureland. and buildings at the beginning of the planning horizon. (2I2.6X.7F10.0) Card Columns 1-2 Code the card, number ’04‘. 3-4 Blank. 5-10 Code a card name. such as ‘ASSETS’. 11-20 Beginning market value of owned cropland and farmstead, as 2848000. 21-30 Beginning market value of owned pastureland, as 14000.0. 31-40 Beginning market value of all off-farm investments, as 10000.0. 41-50 Beginning cash reserves on hand, as 13000.0. 51-60 Nlinimum cash reserve the farm must carry at all times. as 8000.0. 61-70 Value of other livestock held for breeding and other productive intermedi- ate term assets used to produce "other farm income." 58 71-80 Beginning market value of all buildings, wells, and other permanent struc- tures on owned property, as 89000.0. If buildings are inflated at the same rate as land, they are insignificant in value, or they can not be separated from land value, enter a zero here and include buildings with the value of land above. Card 5 -- Depreciation and Cost Recovery of Buildings Buildings placed into service prior to 1981 are depreciated using the straight line method. Special purpose buildings placed into service after 1980 are recovered according to Option 34. (212,ex,71=10.0) Card Columns 1-2 Code the card number ’05’. 3-4 Blank. 5-10 Code a card name, such as ’DEPREC’. 11-20 Salvage value of buildings, wells, and other depreciable improvements purchased before 1981 and eligible for depreciation, as 5000.0. 21-30 Purchase price of buildings, wells, and other depreciable investments pur- chased before 1981 and eligible for depreciation, as 7000.0. 31-40 Economic life of depreciable buildings, etc., purchased before 1981, as 20.0 years. 41-50 Purchase price of regular buildings, wells, etc., purchased after 1981 and eligible for capital recovery, as 50000.0. 51-60 Calendar year regular buildings, purchased after 1980, were placed into service, as 1981.0. 61-70 Purchase price of special purpose buildings purchased after 1980 and eli- gible for capital recovery, as 18000.0. 71-80 Calendar year past 1980 special purpose buildings were placed into service, as 1982.0. Card 6 -- Current Long-Term Debt Current long-term debt is amortized using the information provided on this card. If the farm has more than one long-term mortgage, combine all outstanding long-term debts into one loan. and enter the required information below. The current principal owed on the loan can be entered directly, or the analyst may enter the current ratio of long-term debts to long-term assets. The original amount of the loan can be entered directly or by providing the fraction of the original loan to be repaid. If the original amount of the loan is unknown, leave this particular value blank, and the model will estimate the value. (2I2,6X,7Fl0.0) Card Columns l-2 Code the card number ‘06’. 3-4 Blank. 5-10 Code a card name. such as ‘LTDEBT’. 59 11-20 Outstanding debt on long-term assets, as 1200000; or the current ratio of long-term debts to long-term assets, as 0.50. (Calculate the ratio based on the value of owned land and long-term debts.) The value must be appli- cable for the year preceeding the first year of the planning horizon. User must provide the dollar value of outstanding debt if the farm is to be sim- ulated in terms of real dollars and zero interest rates. 21-30 Loan length for outstanding long-term debt, as 30.0 years. 31-40 Original amount of the long-term loan, as 160000.0; or the fraction of the original loan remaining to be repaid, as 0.75; or leave this field blank if you want the program to estimate the original amount of the long-term loan. User must provide the dollar value of outstanding debt if the farm is to be simulated in terms of real dollars and zero interest rates. 41-50 Minimum ratio of long-term equity to long-term assets for the farm to remain solvent, as 0.25. This value is used to determine the maximum leverage ratio permitted for the farm. 51-70 Blank. Card 7 -- Current Intermediate-Term and Short-Term Debt Current intermediate-term and short-term debt is amortized using the information provided on this card. If the farm has more than one intermediate-term mortgage, combine all of the debts into one loan and enter the required informaton below. Like the long-term debt information, the outstanding intermediate-term debt and the original amount borrowed can be entered several differ- ent ways. (2I2,6X,7F10.0) Card Columns 1-2 Code the card number ’07’. 3-4 Blank. 5-10 Code a card name, as ‘ITDEBT’. 11-20 Outstanding debt on intermediate-term assets, as 20000.0; or the current ratio of the intermediate-term debts to intermediate-term assets. as 0.50. (Calculate the ratio based on the value of farm machinery plus livestock and total intermediate-term debts.) The value must be applicable for the year preceeding the first year of the planning horizon. 21-30 Length of loan for outstanding intermediate-term debt, as 10.0 years. 31-40 Original amount of the intermediate-term loan. as 30000.0; or the fraction of the original loan remaining to be repaid, as 0.66: or leave this value blank and the program will estimate the original amount of the intermedi- ate-term debt. 41-50 Minimum ratio of intermediate-term equity to intermediate-term assets for the farm to remain solvent, as 0.30. 51-60 Fraction of the year the farm uses the operating loan, as 9 months or 0.75. 61-80 Blank. 6O Card 8 -- Terms for New Loans Purchases of cropland and farm machinery are financed using the terms indicated on this card. (2I2,6X,F7.10.0) — Card Columns 1-2 Code the card number ’08’. 3-4 Blank. 5-10 Code a card name, such as ’NEWLON’. 11-20 Loan life for new long-term debts, as 30.0 years. 21-30 Loan life for new intermediate-term debts, as 5.0 years. 31-40 Minimum downpayment required for long-term debts, as 0.48. 41-50 Minimum downpayment required for intermediate-term debts, as 0.60. 51-80 Blank. Card 9 -- Terms for Financing Cash-Flow Deficits When the operator is faced with cash-flow deficits. he can avoid insolvency by borrowing against equity in farmland and machinery. (212,6X,7F10.0) Card Columns 1-2 Code the card number '09’. 3-4 Blank. 5-10 Code a card name, such as ’REFINC’. 11-20 Charge for refinancing a cash-flow deficit, expressed as a fraction of the amount refinanced. as 0.02 or 2 percent. 21-30 Loan life for refinancing long-term debts. as 20.0 years. 31-40 Loan life for refinancing intermediate-term debts. as 4.0 years. 41-80 Blank. Card 10 -- Property Tax and Income Tax Information Property tax is calculated based on the market value of owned cropland and pastureland. Information for computing federal and state income taxes is also provided on this card. In particu- lar, the past 4 years‘ taxable income values after personal exemptions are provided. so the model can use income averaging for computing federal income taxes in years l and 2. (212,6X.10F7.0) Card Columns l-2 Code the card number ’l0’. 3-4 Blank. 5-10 Code a card name. such as TAXES‘. 61 11-17 Annual tax rate for real property expressed as dollar of property tax per dollar of current market value, as 0.00046. This value must be applicable for the year preceeding the first year of the planning horizon. 18-24 Annual personal property taxes, as 1600.0 dollars. This value must be applicable for the year preceeding the first year of the planning horizon. 25-31 Annual cost of any other taxes, excluding state and federal income taxes, as 610.0 dollars. This value must be applicable for the year preceeding the first year of the planning horizon. 32-38 Number of personal income tax exemptions, as 4.0. 39-45 Marginal income tax rate for computing state income taxes, as 0.045. 46-52 Ratio of personal itemized deductions to net farm income for calculating personal itemized deductions, as 0.20. 53-59 Taxable income in tax year t-3, where t is the first year to be simulated, as 11000.0. 60-66 Taxable income in tax year t-2, where t is the first year to be simulated, as 12000.0. 67-73 Taxable income in tax year t-l, where t is the first year to be simulated, as 10000.0. 74-80 Blank. Card 11 -- Self-Employment Tax Rate The annual self-employment tax rates change annually so they are not imbedded in the com- puter program. Enter the annual self-employment tax rates for each year of the planning horizon. (2I2,6X.l0F7.0) Card Columns 1-2 Code the card number ’11'. 3-4 Blank. 5-10 Code a card name. such as ’SELFRT'. ll-l7 Annual self-employment tax rate for year 1, as 0.118, the announced rate for 1984 including available credits. 18-24 Annual self-employment tax rate for year 2, as 0.123. the announced rate for 1985. 25-31 Annual self-employment tax rate for year 3. as 0.123. the announced rate for 1986. 32-38 Annual self-employment tax rate for year 4. as 0.130. the announced rate for 1987. 39-45 Annual self-employment tax rate for year 5. as 0.130. the announced rate for 1988. 62 46-52 Annual self-employment tax rate for year 6, as 0.130. 53-59 Annual self-employment tax rate for year 7, as 0.153. 60-66 Annual self-employment tax rate for year 8, as 0.153. 67-73 Annual self-employment tax rate for year 9, as 0.153. 74-80 Annual self-employment tax rate for year 10, as 0.135. Card 12 -- Maximum Income Subject to Self-Employment Tax The maximum income level that is subject to self-employment taxes changes from year to year so these values are not imbedded in the model. Enter the annual maximum income level for each year of the planning horizon. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’l2’. 3-4 Blank. 5-10 Code a card name, such as ’SELFIN‘. 11-17 Maximum income subject to self-employment tax year 1, as 36800, the announced level for 1984. 18-24 Maximum income subject to self-employment tax year 2, as 36800, the announced level for 1985. 25-31 Maximum income subject to self-employment tax year 3, as 36800, the announced level for 1986. 32-38 Maximum income subject to self-employment tax year 4, as 36800, the announced level for 1987. 39-45 Maximum income subject to self-employment tax year 5. as 36800, the announced level for 1988. 46-52 Maximum income subject to self-employment tax year 6. as 36800. the announced level for 1989. 53-59 Maximum income subject to self-employment tax year 7. as 36800. the announced level for 1990. 60-66 Maximum income subject to self-employment tax year 8. as 36800. 67-73 Maximum income subject to self-employment tax year 9, as 36800. 73-80 Maximum income subject to self-employment tax year l0, as 36800. 63 Card 13 -- Overhead Costs, Accrued Taxes, and Returns to Production Assets Fixed costs other than farm machinery and property taxes are provided on this card. Accrued federal and state income taxes due in year 1 are also provided on Card 13. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’13’. 3-4 Blank. 5-10 Code a card name, such as ’OVCOST’. 11-17 Total annual accountant and legal fees, as 950.0. This value must be applicable for the year preceeding the first year of the planning horizon. 18-24 Total annual unallocated maintenance and repair costs, as 5000.0 This value must be applicable for the year preceeding the first year of the plan- ning horizon. 25-31 Total annual insurance premiums for the farm business, as 900.0. This value must be applicable for the year preceeding the first year of the plan- ning horizon. 32-38 Total annual miscellaneous fixed costs, as 2300.0. This value must be applicable for the year preceeding the first year of the planning horizon. 39-45 Total federal and state income taxes due in year 1, as 2000.0. 46-52 Total self-employment taxes due in year 1, as 500.0. 53-59 Capital gain rate for cropland in the previous year, as -0.04. 60-66 Return to production assets in year t-l expressed as a fraction, as -0.01. 67-73 Desired level of taxable income, if using Option 37, as 25000.0. 74-80 Blank. Card 14 -- Family Consumption Information Information for specifing annual family living expenses is provided on this card. Family liv- ing expenses can be calculated using the analyst's consumption function or an econometric equation estimated for the region being simulated. In addition, off-farm income is provided on this card. (2I2,6X,l0F7.0) Card Columns 1-2 Code the card number ’l4‘. 3-4 Blank. 5-10 Code a card name, as FAMILY’. 11-17 Age of the farm owner/operator at the beginning of the planning horizon. as 38.0 years. a 18-24 Annual taxable off-farm income for the year preceeding the first year in the planning horizon, as 10000.0. Off-farm income is inflated using the Consumer Price Index, Card 20, columns 53-59. If the value changes from year to year, enter this variable on Card 20. 25-31 Annual non-taxable income for the year preceeding the first year of the planning horizon, as 5000.0. If the value changes annually, enter it on Card 20. 32-38 Calendar year for the first year in the planning horizon, as 1982.0. 39-45 Specify the farm production region where the farm is located so the appropriate regional equations for family consumption can be used. The regional codes are: Northeast ’1.0’; Lake States ’2.0’; Corn Belt ’3.0’; Appalachia ’4.0’; Southeast ’5.0’; Delta States ’6.0’; Mountain States ’7.0’; Northern Plains ’8.0’; Southern Plains ’9.0’; Pacific States ’10.0’; and United States ’11.0’. If the analyst wishes to hold real family consumption constant, enter ’12.0’. If the analyst wishes to use his or her own con- sumption function, enter ’13.0’ and fill in values for columns 60-73 below. 46-52 Minimum annual family living expenses for the year preceeding the first year in the planning horizon, as 12000.0. Minimum living expenses are inflated using the Consumer Price Index, from Card 20, columns 61-70. 53-59 Maximum annual family living expenses for the year preceeding the first year in the planning horizon, as 50000.0. Maximum living expenses are inflated using the Consumer Price Index from Card 20. 60-66 Annual family living expenses for the consumption function: consumption = average expenses + MPC * (after tax disposible income - average expenses) 67-73 Marginal propensity to consume (MPC) after-tax disposible income for the analyst’s consumption function. Farm family consumption data for 1973 revealed an MPC of 0.10 for the United States and an MPC of 0.246 for farmers in the corn belt. 74-80 Maximum annual interest payment which can be claimed as a federal income tax deduction, as 25.000.0. This value is used only when Option No. 40 equals l. Card 15 -- Unpaid Family Labor Available to the Farm Total hours of unpaid family labor available to the farm, in each month of the year, are pro- vided on this card. Additional labor required for the farm is assumed to be hired on a full-time and/or part-time basis. (2I2,6X,12F6.0) Card Columns 1-2 Code the card number ‘15’. 3-4 Blank. 5-8 Code a card name. as ‘FLAB’. 9-14 Hours of labor available to the farm in January. as 80.0. l5-20 Hours of labor available to the farm in February. as 80.0. 65 21-26 Hours of labor available to the farm in March, as 80.0. 27-32 Hours of labor available to the farm in April, as 80.0. 33-38 Hours of labor available to the farm in May, as 100.0. 39-44 Hours of labor available to the farm in June, as 120.0. 45-50 Hours of labor available to the farm in July, as 120.0. 51-56 Hours of labor available to the farm in August, as 120.0. 57-62 Hours of labor available to the farm in September, as 100.0. 63-68 Hours of labor available to the farm in October, as 80.0. 69-74 Hours of labor available to the farm in November, as 80.0. 75-80 Hours of labor available to the farm in December, as 80.0. Card 16 -- Monthly Availability of Full-Time Hired Labor Total hours of labor available by month for each full-time employee are provided on this card. This is necessary because full-time employees usually work more hours per month during the summer and fall than during the winter. Enter the information even if the farm does not presently hire a full-time employee since these values are used for larger size farms when a full-time employee is hired. (2I2,6X,12F6.0) Card Columns A 1-2 Code the card number ’16’. 3-4 Blank. 5-8 Code a card name, as ’HLAB’. 9-14 Hours worked per full-time employee in January, as 100.0. 15-20 Hours worked per full-time employee in February, as 100.0. 21-26 Hours worked per full-time employee in March, as 150.0. 27-32 Hours worked per full-time employee in April, as 160.0. 33-38 Hours worked per full-time employee in May, as 180.0. 39-44 Hours worked per full-time employee in June, as 190.0. 45-50 Hours worked per full-time employee in July, as 190.0. 51-56 Hours worked per full-time employee in August. as 190.0. 57-62 Hours worked per full-time employee in September, as 160.0. 63-68 Hours worked per full-time employee in October, as 160.0. 619-74 Hours worked per full-time employee in November. as 140.0. 66 75-80 Hours worked per full-time employee in December, as 100.0. Card 17 -- Hired Labor Costs and Miscellaneous Information The annual salary for full-time employees must be provided if the farm is eligible to grow and alternative size farms hire full-time employees. (2I2,6X,7F10.0) Card Columns 1-2 Code the card number ’17’. 3-4 Blank. 5-10 Code a card name, as ’HLABOR’ 11-17 Annual gross salary for a full-time employee, as 18000.0. This value must be applicable for the year preceeding the first year of the planning hori- zon. 18-24 Number of full-time employees, as 1.0. 25-31 Hourly wage rate for part-time farm labor, as 3.50. This value must be applicable for the year preceeding the first year of the planning horizon. 32-38 After-tax discount rate for calculating net present value and the present value of ending net worth, as 0.075. 39-45 Annual rate of return to off-farm investments, expressed as a fraction of the investment’s current market value, as 0.10 or 10 percent. 46-52 Risk aversion coefficient to be used if a QP is used to change the crop mix over time. as 0.0001. 53-80 Blank. Card 18 -- Cropland and Pastureland Cash Lease Costs When a crop share lease is in effect and no pastureland is leased, columns 11-80 can be left blank. (2I2,6X,7F10.0) Card Columns 1-2 Code the card number '18‘. 3-4 Blank. 5-10 Code a card name. as ’CLEASE’. ll-17 The per acre cash lease cost for cropland, as 80.0. This value must be applicable for the year preceeding the first year of the planning horizon. Leave this value blank if a crop share lease is in effect, i.e.. Option 7 equals 0. 18-24 The per acre cash lease cost for pastureland. as 33.0. This value must be applicable for the year preceeding the first year of the planning horizon. 25-31 Annual escalation rate in per acre cash lease costs expressed as a fraction. as 0.10. i.e.. Option '7 equals l. If the cash lease is to remain constant over time. enter 0.0. 67 32-38 Capitalization rate for determining per acre cash lease costs as a fraction of the market value for cropland (i.e., Option 7 equals 2), as 0.04. In this 4 case, the cash lease rate for cropland equals 4 percent of the per acre value ‘_ of cropland. E 39-80 Blank. Card l9.IYEAR -- Annual Percentage Changes in Costs The model adjusts the initial values of farm assets and production costs annually to arrive at updated market values and costs over the planning horizon. Since the rate of change in these prices 1} can change from year to year, the analyst must enter annual percentage changes over the full plan- ‘A ning horizon. Values for 10 different variables are entered on this card. Code a separate Card 19 for each year (IYEAR) of the planning horizon. (2I2,6X,7F10.0) Card Columns 1-2 Code the card number ’19’. 3-4 Code the year number, IYEAR, as ’01’, ’02’, and so on, until a separate 1, card has been coded for each year of the planning horizon. 5-10 Code a card name, as ’INFLAA’. 11-17 Annual capital gains rate for farmland (fraction), as 0.10. Enter values for this variable if Option 23 equals 1 or 2. x 18-24 Annual percentage change in the price of new farm machinery (fraction), as 0.10. 25-31 Annual percentage change in the price of used farm machinery (fraction), as 0.01. " 32-38 Annual percentage change in fixed costs such as insurance (fraction), as 0.10. 39-45 Annual percentage change in seed costs (fraction), as 0.10. j 46-52 Annual percentage change in fertilizer and lime (fraction), as 0.10. 53-59 Annual percentage change in farm chemicals (fraction), as 0.10. 60-66 Annual percentage change in fuel and lube costs (fraction), as 0.10. 67-73 Annual percentage change in repair costs (fraction), as 0.10. 74-80 Annual percentage change in other production costs (fraction). as 0.10. Card ZOJYEAR -- Annual Percentage Changes in Costs This card serves the same purpose as Card 19 by providing annual percentage changes in prices for a second set of variables. Code a separate Card 20 for each year (IYEAR) of the plan- ning horizon. (2I2,6X.7F10.0) 68 Card Columns 1-2 Code the card number ’20’. 3-4 Code the yearnumber, IYEAR, as ’01’, ’02’, ,’10’. 5-10 Code a card name, such as ’INFLAB’. 11-17 Annual percentage change in variable harvesting costs (fraction), as 0.10. 18-24 Annual percentage change in hired labor costs (fraction), as 0.10. 25-31 Annual percentage change in the market value of off-farm investments (fraction), as 0.10. 32-38 Annual percentage change in the cost of variable inputs purchased for livestock (fraction), as 0.08. 39-45 Annual percentage change in the cost of storing commodities in the CCC loan program, as 0.05. 46-52 Amount of new capital invested from off-farm sources in year I, as 1500.0 dollars. This income is not subject to federal or state taxes. 53-59 Consumer Price Index (1967 = 100), as 240.0. 60-66 Other farm income, net of expenses. as 2000.0 dollars. 67-73 Annual percentage change in the market value of buildings on the initial farmstead if separated from cropland on Card 4, as 0.01. 74-80 Blank. Card 21.IYEAR -- Annual Interest Rates This card serves a similar purpose as Cards 19 and 20; however, annual interest rates for nine types of financial instruments are entered on this card. Code a separate Card 21 for each year (IYEAR) of the planning horizon. (2I2,6X.7Fl0.0) Card Columns 1-2 Code the card number ‘21’. 3-4 Code the year number. IYEAR, as ’01'. ’02’, .’10’. 5-10 Code a card name. as TNTERE‘. 11-17 Annual interest rate for outstanding livestock debts. as 0.0909. 18-24 Annual interest rate for outstanding long-term debts, as 0.085. 25-31 Annual interest rate for outstanding intermediate-term debts, as 0.130. 32-38 Annual interest rate for new long-term debts, as 0.095. 39-45 Annual interest rate for new intermediate-term debts. as 0.150. 46-52 Annual interest rate for refinancing long-term debts. as 0.100. 53-59 Annual interest rate for refinancing intermediate-term debts. as 0.160. 69 60-66 Annual interest rate for operating loans, as 0.180. 67-73 Annual interest rate received for ending year cash balances, as 0.170. 74-80 Blank. Card ZZJCROP -- Crop Enterprise Information - Production Costs For each crop enterprise (JCROP), code a separate Card 22. The total number of Cards coded must equal the value in columns 13-14 of Card 2. The order of the crops used for the Card 22’s must be maintained throughout the remainder of the input cards. If the initial farm does not produce a particular crop, leave columns 17-80 blank on the crop’s Card 22. The analyst must pro- vide information for at least one crop enterprise, even if the farm produces no crops. Information for the crop enterprises is entered on Core Data Cards 22-29 and Policy Data Cards P1-P33. (2I2,3A4, 1X,9F 7.0) Card Columns 1-2 Code the card number ’22’. 3-4 Code the crop enterprise number, JCROP. as ’01’, ’02’, etc. Assign a crop enterprise number even if the rest of the card is left blank due to the ini- tial farm not producing the particular crop. 5-16 Code an alphanumeric name for the crop, such as ’COTTON#IRRIG’. 17 Blank. 18-24 Seed cost per planted acre in previous crop year (Si/acre). 25-31 Fertilizer and lime cost per planted acre in previous crop year (S/acre). 32-38 Chemical cost per planted acre in previous crop year (S/acre). 39-45 Fuel and lube cost per planted acre in previous crop year ($/acre). 46-52 Machinery repair cost per planted acre in previous crop year (S/acre). 53-59 Qther production costs per planted acre in previous crop year ($/acre). 60-66 Variable harvesting costs per yield unit in previous crop year (S/yield unit). This cost can be any cost that is calculated as a function of yield. 67-80 Blank. Card 23.JCROP -- Crop Enterprise Information - Crop Mix The crop mix for the first year of the planning horizon is provided on Card 23. Additionally, information necessary to change the crop mix over time or to allow double cropping is also pro- vided on this card. Code a separate Card 23 for each crop enterprise (JCROP). (2I2.3A4,1X.9F7.0) Card Columns 1-2 Code the card number ’23’. 3-4 Code the crop enterprise number, JCROP. as ’0l'. etc. 5-16 Code an alphanumeric name for the crop. such as "COTTON IRRIG". 70 17 18-24 25-31 32-38 39-45 60-66 67-80 Blank. Planted acres for the crop in year 1 of the planning horizon and remaining years if the crop mix is constant (tillable acres) and there is no set aside, as 400.0. These two values must be entered as total acres regardless of the set aside requirements. Harvested acres for the crop in year 1 of the planning horizon and remaining years if the crop mix is constant (tillable acres) and there is no set aside, as 380.0. These two values must be entered as total acres regardless of the set aside requirements. Minimum proportion of the crop in the crop mix if the crop mix can change over time (fraction), as 0.80. (Leave this value blank if Gption 9 equals zero.) Maximum proportion of the crop in the crop mix if the crop mix can change over time (fraction), as 0.95. (Leave this value blank if Option 9 equals zero, or if the crop is not produced on the initial farm.) If the enterprise is a byproduct of another crop or double cropped with a second crop, indicate the enterprise number for the primary crop, as 1.0. Average fraction of planted acres that are harvested. as 0.98. Code for irrigation or non-irrigation; enter ’0.0’ if the crop enterprise is not irrigated; ’1.0’ if the crop is irrigated. Blank. Card 24.JCROP -- Crop Enterprise Information - Labor Requirements Monthly labor requirements are provided for the crops on this card. Code a separate Card 24 for each crop enterprise (JCROP). (2I2,4X.12F6.~0) Card Columns Code the card number ’24'. Code the crop enterprise number, JCROP. as ’0l’. I02’, etc. Code a card name. as ‘LABC’. Hours of labor per planted acre required for the enterprise in January. as 0.10. Hours of labor per planted acre required for the enterprise in February, as 0.15. Hours of labor per planted acre required for the enterprise in March, as 0.20. Hours of labor per planted acre required for the enterprise in April. as 0.30. Hours of labor per planted acre required for the enterprise in Nlay. as 1.40. 71 39-44 Hours of labor per planted acre required for the enterprise in June, as 1.50. 45-50 Hours of labor per planted acre required for the enterprise in July, as é 1.50. 51-56 Hours of labor per planted acre required for the enterprise in August, as 1.00. 57-62 Hours of labor per planted acre required for the enterprise in September, as 1.90. 63-68 Hours of labor per planted acre required for the enterprise in October, as 0.0. 69-74 Hours of labor per planted acre required for the enterprise in November, as 4.0. 75-80 Hours of labor per planted acre required for the enterprise in December, as 0.0. Card ZSJCROP -- Crop Yields Average (or modal) annual crop yields (units/harvested acre) are entered for each crop enter- prise (JCROP). The values are used as the actual yields in a deterministic simulation and the mean of a multivariate normal or Beta distribution in a stochastic simulation if Option 24 equals 0, 1, 4, or 5. If Option 24 is equal to 2 or 3, yield values are the modal values for a triangular distribution. If Option 24 is equal to 7 or 8, yield values are means for the empirical distributions. "Code a sepa- rate Card 25 for each crop enterprise. Be sure crop yields, prices, loan rates, and target prices use the same units, e.g., bu. or cwts. (2I2,6X,1OF7.0) Card Columns 1-2 Code the card number ’25’. 3-4 Code the crop enterprise number, JCROP, as ’0l ’, etc. 5-10 Code a card name, such as ‘YIELDS’. 11-17 Average yield per harvested acre in year 1 (unit/acre). 18-24 Average yield per harvested acre in year 2 (unit/acre). 25-31 Average yield per harvested acre in year 3 (unit/acre). 32-38 Average yield per harvested acre in year 4 (unit/acre). 39-45 Average yield per harvested acre in year 5 (unit/acre). 46-52 Average yield per harvested acre in year 6 (unit/acre). 53-59 Average yield per harvested acre in year 7 (unit/acre). 60-66 Average yield per harvested acre in year 8 (unit/acre). 67-73 Average yield per harvested acre in year 9 (unit/acre). 74-80 Average yield per harvested acre in year l0 (unit/acre). 72 Card 26JCROP -- Crop Prices Season average (or modal) crop prices in each year of the planning horizon are entered for each crop enterprise (JCROP). Enter the crop price in terms of dollars per unit of yield. Like crop yields, prices are used as actual values in a deterministic simulation and as the mean or modal values if the model is run stochastically. Code a separate Card 26 for each crop enterprise. (2l2,6X,10F 7.0) Card Columns 1-2 Code the card number ’26’. 3-4 Code the crop enterprise number. JCROP, as ’01’. 5-10 Code a card name, such as ’PRICES’. 11-17 Season average crop price for year 1 (S/unit). 18-24 Season average crop price for year 2 (S/unit). 25-31 Season average crop price for year 3 ($/unit). 32-38 Season average crop price for year 4 ($/unit). 39-45 Season average crop price for year 5 ($/unit). 46-52 Season average crop price for year 6 (S/unit). 53-59 Season average crop price for year 7 (S/unit). 60-66 Season average crop price for year 8 (S/unit). 67-73 Season average crop price for year 9 (S/unit). 74-80 Season average crop price for year 10 (S/unit). Card 27JCROP -- Factored Matrix for Crop Yields and Prices The model is programmed to draw random yields and prices from either independent or multivariate distributions. To draw random values from multivariate distributions. the analyst must provide a factored covariance (or correlation) matrix, R. This procedure has been outlined by Nay- lor (1971), by Clements, Mapp, and Eidman (1971), and by King (1979). The "square-root method" is used to factor a covariance (or correlation) matrix (i.e., calculate R) so that it satisfies: S = RR‘ where S is the covariance (or correlation) matrix and R is a unique upper-triangular matrix. To factor a matrix. it must be positive definite and symmetrical about its main diagonal. To draw random values from a multivariate normal probability distribution (Option 24 equal to 0) the analyst must provide a separate factored covariance matrix for crop yields and prices on Card 27. To draw random livestock prices from a multivariate normal distribution, a factored covariance matrix must be provided on Card 48 for livestock. Similarly, a factored covariance matrix for price and production variables on a dairy farm are entered on Card 78. To draw random values from independent normal probability distributions (Option 24 equal to 1), the analyst must provide only the standard deviations for crop yields - prices, livestock prices. and dairy prices on Cards 27, 48, and 74. When Option 24 equals 2 or 7, a multivariate triangular or empirical prob- ability distribution is used and a separate factored correlation matrix must be provided for crop yields - prices, livestock prices. and dairy prices on Cards 27, 4S. and 74. respectively. If Option 24 equals 3 or 8. independent triangular or empirical probability distributions are used and the analyst need only provide the own correlation coefficients (1.0) on Cards 27. 48. and 74. 73 The order of crop yields and prices in the factored covariance (or correlation) matrix must match the order of crop enterprises on Card 22. Code a separate Card 27 for each row of the matrix and enter only the upper right triangle for the matrix. The analyst must provide two Card 27’s for each of the JCROP enterprises. The matrix must be arranged with the yields for each crop first, followed by the prices for each crop. If there are more than five crop enterprises, a continua- tion card must be provided since only 10 values can be entered on a card. The continuation card must immediately follow the first Card 27, i.e., Card ’2701MATRIX’ must be followed by its con- tinuation card ’2701CONTIN’. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’27’. 3-4 Code the matrix row number I, as ’01’, ‘O2’, and so on. 5-10 Code a card name, such as ’MATRIX’. 11-17 The X(I,I) or main diagonal value of the matrix. (If Option 24 equals 1, 3, or 8 enter the crop’s standard deviation or own correlation coefficient here and leave the remainder of the card blank. If the model is to be run deterministically, columns ll-80 of this card can be left blank.) 18-24 The X(I,I+ 1) value of the matrix, if applicable. 25-31 The X(I,I+2) value of the matrix, if applicable. 32-38 The X(I,I+3) value of the matrix, if applicable. 39-45 The X(I,I+4) value of the matrix, if applicable. 46-52 The X(I,I+5) value of the matrix. if applicable. 53-59 The X(I,I+6) value of the matrix, if applicable. 60-66 The X(I,I+7) value of the matrix, if applicable. 67-73 The X(I.I+8) value of the matrix, if applicable. 74-80 The X(I,I+9) value of the matrix, if applicable. If there are more than l0 observations for row I. enter the remaining val- ues for the lth row on the continuation card described below. The contin- uation card for row I. must immediately follow the initial row I card. Continuation of Card 27 Use a continuation card for Card 27 only if the row being coded has more than 1O values. A second continuation card for row I will never be needed since the model does not permit more than 10 crop enterprises. Card Columns 1-2 Code the card number ’27’. 3-4 Code the matrix row number I. as ’01’, ’02’. and so on. 5-10 Code a card name. such as ‘CONTIN’. 11-17 The .\’(I,1+ 10) value of the matrirt. if applicable. 74 60-66 67-73 74-80 The X(I,I+11) value of the matrix, if applicable. The X(I,I+ 12) value of the matrix, if applicable. The X(I,I+ 13) value of the matrix, if applicable. The X(I,I+ 14) value of the matrix, if applicable. The X(I,I+ 15) value of the matrix, if applicable. The X(I,I+ 16) value of the matrix, if applicable. The X(I,I+ 17) value of the matrix, if applicable. The X(I,I+ 18) value of the matrix, if applicable. The X(I,I+ 19) value of the matrix, if applicable. Card 28.JCROP -- Seasonal Index for Crop Prices Enter the seasonal price index for each crop enterprise on Card 28. Code a separate Card 28 for each crop (JCROP). (2I2,6X,12F6.0) Card Columns 9-14 15-20 21-26 Code the card number ’28‘. Code the crop enterprise number, JCROP, as ’01’. Code a card name, as ’INDX’. Seasonal price index for January. as 1.0148. Seasonal price index for February, as 1.0273. Seasonal price index for March, as 1.0288. Seasonal price index for April, as 1.0181. Seasonal price index for May. as 0.9951. Seasonal price index for June, as 0.9983. Seasonal price index for July, as 0.9516. Seasonal price index for August, as 0.9566. Seasonal price index for September, as 0.9808. Seasonal price index for October. as 1.0016. Seasonal price index for November, as 1.0153. Seasonal price index for December. as 1.0214. 75 Card 29JCROP -- Marketing Strategies for Crops A producer can sell crops during the tax year they are produced or store them for sale in the next tax year. Information on Card 29 is used with Option 37 to model the marketing strategies available to producers. Code a separate Card 29 for each crop enterprise (JCROP). (2I2,6X,10F7.0) Card Column 1-2 Code the card number ’29’. 3-4 Code the crop enterprise number, JCROP, as ’0l’. 5-10 Code a card name, as ’MKTGS’. 11-17 The beginning inventory of the crop to be sold during the first tax year to be simulated, as ’400.5’ bales of cotton. 18-24 Fraction of the crop normally held for sale during the next tax year, as ’0.25’. This value is left blank if Option 37 equals 2 or 3. 25-31 Calendar month the crop is sold during the tax year it is harvested, as ’12.0’ for December. (This month should be after harvest and before the end of the tax year.) 32-38 Calendar month the stored crop is sold during the next tax year, as '3.0’ for March. 39-80 Blank. Card 30.IMACH -- Inventory of Owned Farm Machinery Information for calculating depreciation and the current market value of the owned farm 1 machinery is provided on this card. A separate Card 30 must be coded for each item of machinery (IMACH). The number of cards provided here must equal the value coded in card columns 19-21 of Card 2. The analyst may either lump all machinery items into 5 to 10 categories or identify each item of machinery separately. The model will handle up to 99 separate items of machinery. (212.3A4,9F7.0) Card Columns 1-2 Code the card number '30’. 3-4 A farm machinery item number, IMACH, as ’0l’. ’02‘, and so on. 5-16 An alphanumeric name. such as 'TRACTOR4440’. 17-23 Current market value of the machinery item. as 30000.0. 24-30 Purchase price of the machine when put to use on the farm, as 35000.0. 31-37 Salvage value if machine was purchased before 1981. as 3000.0; otherwise 0.0. 38-44 Depreciation life -- if machine was purchased before 1981 or after 1985. as 7.0 years: otherwise leave blank. Under the 1985 Tax Act this value must be greater than or equal to the economic life of the machine. 45-51 Calendar year the machine was placed into use. as 1981.0. 76 52-58 Economic life of the machine on the farm, as 10.0 years. 59-65 The method of replacing machinery is specified using Option 22, for those machines that can be replaced. The replacement code for each machine is specified as a 0.0, 1.0, or 2.0: ’0.0’ if the machine is replaced at the end of its economic life; ’1.0’ if the machine is kept and replaced at the end of its economic life; and ’2.0’ if the machine is kept and not replaced at the end of its economic life. 66-72 The current market value of a replacement machine, as 39000.0. 73-80 The number of years to recover the cost of a particular machine if placed into use during 1982-85, use 3.0, 5.0, or 12.0 years. For machinery placed in use after 1985, specify the capital cost recovery system asset class of 2.0 for trucks and trailers or 3.0 for tractors and other farm machinery. Optional Data Cards -- Cards 31-80 Cards 31-80 are not required by the program for each farm, unless the analyst has envoked an option on Card 2 which requires data provided on these Optional Data Cards. For example, if the farm includes a beef cattle enterprise. the analyst must provide Optional Data Cards 44-49. Card 31 -- Terms for a Crop Share Lease When Option 7 equals zero, the analyst must provide the crop share lease information on this card. Since the terms for crop share leasing differ by input and crop, the analyst must provide crop share information by input for each crop. Code a separate Card 31 for each crop enterprise. be sure to use the enterprise order established on Card 22. (212,6X,10F7.0) Card Columns 1-2 Code the card number ‘31’. 3-4 Code the crop enterprise number. as ’01'. 5-10 Code a card name, such as ’CSHARE‘. 11-17 Landowner’s share of the crop’s cash receipts (fraction), as 0.30. 18-24 Landowner’s share of seed costs for the crop (fraction), as 0.00. 25-31 Landowner’s share of fertilizer and lime costs for the crop (fraction), as 0.30. 32-38 Landowner’s share of chemical costs for the crop (fraction), as 0.30. 39-45 Landowner’s share of fuel and lube costs for the crop (fraction), as 0.30. 46-52 Landowner’s share of repair costs for the crop (fraction), as 0.00. 53-59 Landowner’s share of other production costs for the crop (fraction) as 0.00. 77 60-66 Landowners share of variable (cash) harvest costs for the crop (fr-action), as 0.30. 67-80 Blank. Cards 32 and 33 -- Predetermined Availability of Cropland If Option 8 equals 1 or 3, the analyst must provide values for the predetermined acreage available for purchase and lease in each year of the planning horizon. Otherwise, skip these optional data cards. (2I2,6X,10F 7.0) Card 32 -- Predetermined Cropland Available for Purchase Enter the number of acres of cropland available for purchase each year. The farm operator must purchase all or none of the available parcels. If the farm may grow only through leasing cropland, leave columns 11-80 blank. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’32’. 3-4 Blank 5-10 Code a card name, such as ’ACRESL’. 11-17 Cropland acres available for purchase in year 1, as 160.0. 18-24 Cropland acres available for purchase in year 2, as 0.0. 25-31 Cropland acres available for purchase in year 3, as 160.0. 32-38 Cropland acres available for purchase in year 4, as 0.0. 39-45 Cropland acres available for purchase in year 5, as 160.0. 46-52 Cropland acres available for purchase in year 6, as 0.0. 53-59 Cropland acres available for purchase in year 7, as 160.0. 60-66 Cropland acres available for purchase in year 8. as 0.0. 67-73 Cropland acres available for purchase in year 9. as 160.0. 74-80 Cropland acres available for purchase in year 10, as 160.0. Card 33 -- Predetermined Cropland Available for Lease Enter the number of acres of cropland that is available for lease each year. The farm opera- tor must lease all or none of the available parcels. If the farm may grow only through purchasing cropland. leave columns ll-80 blank. (2I2,6X.10F7.0) Card Columns l-2 Code the card number '33’. 3-4 Blank. 5-10 Code a card name. such as ‘ACRELE’. 78 11-17 Cropland acres available for lease in year 1, as 160.0. 18-24 Cropland acres available for lease in year 2, as 160.0. 25-31 Cropland acres available for lease in year 3, as 160.0. 32-38 Cropland acres available for lease in year 4, as 320.0. 39-45 Cropland acres available for lease in year 5. as 320.0. 46-52 Cropland acres available for lease in year 6, as 320.0. 53-59 Cropland acres available for lease in year 7, as 0.0. 60-66 Cropland acres available for lease in year 8, as 160.0. 67-73 Cropland acres available for lease in year 9. as 0.0. 74-80 Cropland acres available for lease in year l0, as 160.0. Cards 34-36 -- Random Availability of Cropland If Option 8 equals 2 or 4. the analyst must provide values to determine random availability of cropland. If Option 8 equals 0, l. or 3, skip Cards 34-36. Information as to the size of cropland parcels that are available for purchase or lease, as well as their respective probabilities are provided on Cards 34-36. If the farm may grow only by purchasing cropland, enter zeros for the probabili- ties of leased land being available on Card 36. A similar action taken on Card 35 would permit the farm to grow only through leasing cropland. (2I2,6X,7F10.0) Card 34 -- Random Availability of Cropland, Card A Card Columns 1-2 Code the card number ’34’. 3-4 Blank. 5-10 Code a card name. such as ‘LANDAA’. 11-20 The smallest size parcel available for purchase. as 120.0 acres. 21-30 The next larger size parcel available for purchase. as 160.0 acres. 31-40 The next larger size parcel available for purchase. as 320.0. 41-50 The largest size parcel available for purchase. as 640.0. 51-60 The smallest size parcel available for lease, as 80.0. 61-70 The next larger size parcel available for lease, as 160.0 acres. 71-80 Blank. 79 Card 35 -- Random Availability of Cropland, Card B Card Columns 11-20 21-30 31-40 41-50 51-60 61-70 71-80 Code the card number ’35’. Blank. Code a card name, such as ’LANDAB’ The third largest size parcel available for lease, as 300.0 acres. The largest size parcel available for lease, as 560.0 acres. The probability of the smallest size parcel being available for purchase in a 1-year period, as 0.05. The probability of the next larger size parcel being available for purchase in a 1-year period, as 0.40. The probability of the third largest size parcel being available for purchase in a 1-year period, as 0.25. The probability of the largest size parcel being available for purchase in a l-year period, as 0.15. Blank. Card 36 -- Random Availability of Cropland Card Columns -2 -4 -1 LllbJv-l 0 11-20 31-40 41-50 51-80 Code the card number ’36'. Blank. Code a card name, such as ’LANDLAC’. The probability of the smallest size parcel being available for lease in a l-year period, as 0.10. The probability of the next larger size parcel being available for lease in a 1—year period, as 0.25. The probability of the third largest size parcel being available for lease in a 1-year period. as 0.30. The probability of the largest size parcel being available for lease in a 1—year period, as 0.10. Blank. 80 Cards 37-43 -- Crop Enterprise Information for Alternative Farm Sizes When Option 27 is not equal to zero, the analyst must provide the information on Cards 37-43. lf Option 27 equals zero, skip Cards 37-43. These seven cards are used to input information for the cost of production, crop yields, crop prices, and labor requirements associated with farms that are larger than the initial farm. The order of crop enterprises (JCROP) on Cards 38-43 is the same as for Card 22. If the alternative size farms do not produce some of the crops that the initial farm produced, enter zero for their costs, yields, prices, etc., but be sure to provide the required cards for all crops. Card 37 -- Total Cropland Acreage for Alternative Farm Sizes Enter the total cropland acreage for each alternative size farm. The number of alternatively larger farms is provided as Option 27 on Card 2. This value must include both owned cropland and leased cropland and is used to adjust costs. yields, and prices as the initial farm grows. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’37’. 3-4 Blank. 5-10 Code a card name, such as ’FARMSZ’. 11-17 Cropland acres for the first larger farm, as 560.0. 18-24 Cropland acres for the second larger farm, as 640.0. 25-31 Cropland acres for the third larger farm. as 960.0. 32-38 Cropland acres for the fourth larger farm, as 1280.0. 39-45 Cropland acres for the fifth larger farm, as 1600.0. 46-52 Cropland acres for the sixth larger farm, as 1920.0. 53-59 Cropland acres for the seventh larger farm. as 2240.0. 60-66 Cropland acres for the eighth larger farm. as 2560.0. 67-73 Cropland acres for the ninth larger farm, as 2880.0. 74-80 Cropland acres for the tenth larger farm, as 3200.0. Card 38.IF ARM -- Farm Machinery Investment for Alternative Farm Sizes Code a separate Card 38 for each alternative farm size (IFARM). Code the first larger farm size on the first Card 38. followed by the second larger farm size on the second Card 38, and so on. (2l2,6X,10F7.0) Card Columns l-2 Code the card number '38’. 3-4 Code the order number for the alternative farm size. IFARM. as '01‘. '02‘, and so on until all farms have been coded. 5-10 Code a card name. such as ‘AMACHI’. 81 11-17 Difference in current replacement cost for all machinery on the farm and the current replacement cost for all machinery on the next larger farm, as 50000.0. 18-24 Annual off-farm income for the alternative farm size, as 3000.0. 25-31 Annual hours of unpaid family labor available to the farm, as 1500.0. 32-38 Total number of full-time employees after the growth, as 3.0. 39-45 Annual salary for a full-time employee, as 12000.0. This value must be applicable for the year preceeding the first year of the planning horizon. 46-80 Blank. Card 39.IFARM-JCROP -- Production Costs for Alternative Farm Sizes Card 39 is repeated for each crop enterprise (JCROP) and each alternative farm size (IFARM). By doing this the analyst enters a separate set of crop enterprise cards for each alterna- tive farm size. Crop enterprises are assumed to be in the order specified for Card 22. Enter all crop data for the first larger farm size first, followed by the crop data for the second larger farm size, and so on. The total number of Card 39’s provided by the analyst must equal the number of crops times the number of alternative size farms. See the Appendix B for a sample of how to code Card 39. (2I2,3A4,1X,9F7.0) Card Columns 1-2 Code the card number ’39’. 3-4 Code the crop enterprise number, JCROP, as ’01’. 5-16 Code a card name, such as ’Alternativel’. 17 Blank. 18-24 Seed costs per planted acre (S/acre). 25-31 Fertilizer and lime costs per planted acre ($/acre). 32-38 Chemical costs per planted acre ($/acre). 39-45 Fuel and lube costs per planted acre (S/acre). 46-52 Repair costs per planted acre (S/acre). 53-59 Other production costs per planted acre (S/acre). 60-66 Custom costs and variable harvesting costs per unit of production (S/yield unit). 67-80 Blank. Card 40.IFARM-JCROP -- Crop Mix Information for Alternative Farm Sizes Card 40 is repeated for each crop enterprise (JCROP) and each alternative farm size (IFARM). By doing this the analyst enters a separate set of crop mix data for each alternative farm size. Crop enterprises are assumed to be in the order specified for Card 22. If a particular crop is 82 not produced for the farm size, indicate that its acreages and maximum proportion of the crop mix are zero. Enter all crop data for the first larger farm size first, followed by the crop data for the second larger farm size, and so on. The total number of Card 40’s provided by the analyst must equal the number of crops times the number of alternative size farms. (2I2,3A4,1X,9F7.0) Card Columns 1-2 Code the card number ’40’. 3-4 Code the crop enterprise number, JCROP, as ’01’. 5-16 Code a card name, as ’Alternative 1’. 17 Blank. 18-24 Planted acres for the crop if the crop mix is constant (tillable acres). 25-31 Harvested acres for the crop if the crop mix is constant (tillable acres). 32-38 Minimum proportion of the crop in the crop mix if the crop mix can change over time (fraction). (Leave this value blank if Option 9 equals zero.) 39-45 Maximum proportion of the crop in the crop mix if the crop mix can change over time (fraction). (Leave this value blank if Option 9 equals zero or the crop is not produced.) 46-52 If the enterprise is a byproduct of another crop or double cropped with a second crop, indicate the enterprise number for the primary crop (the first crop), as 1.0. 53-59 Fraction of planted acres that are normally harvested (fraction), as 0.98. 60-66 Code for irrigation or non-irrigation: enter ‘0.0’ if the crop enterprise is not irrigated, and ’1.0’ if the crop is irrigated. 67-80 Blank. Card 41.IFARM-JCROP -- Labor Requirements for Alternative Farm Sizes Card 41 is repeated for each crop enterprise (JCROP) and each alternative farm size (IFARM). By doing this, the analyst enters a separate set of monthly labor requirements per planted acre for each crop on each alternative farm size. Crop enterprises are assumed to be in the order specified for Card 22. If a particular crop is not produced for the farm size being coded. indicate that its labor requirements are zero. Enter the hourly labor requirements per planted acre for the first larger farm size first, followed by the crop data for the second larger farm size, and so on. The number of Card 41's provided by the analyst must equal the number of crops times the number of alternative size farms. (2l2.4X,12F6.0) Card Columns 1 2 Code the card number ‘41’. 3-4 Code the crop enterprise number. JCROP. as ’01’. 8 5- Code a card name. such as ’F1CC‘. 9-14 Labor required for the enterprise in January. as 2.0. 15-20 Labor required for the enterprise in February as 3.0. 83 21-26 Labor required for the enterprise in March, as 0.0. 27-32 Labor required for the enterprise in April, as 0.0. 33-38 Labor required for the enterprise in May, as 6.0. 39-44 Labor required for the enterprise in June, as 7.0. 45-50 Labor required for the enterprise in July, as 12.0. 51-56 Labor required for the enterprise in August, as 10.0. 57-62 Labor required for the enterprise in September, as 5.0. 63-68 Labor required for the enterprise in October, as 6.0. 69-74 Labor required for the enterprise in November, as 0.0. 75-80 Labor required for the enterprise in December, as 0.0. Card 42.IFARM-JCROP -- Crop Yield Information for Alternative Farm Sizes Card 42 is repeated for each crop enterprise (ICROP) and each alternative farm size (IFARM). By doing this, the analyst enters a separate set of average annual crop yields for each crop on each alternative farm size. Farms larger than the initial farm may experience lower or higher mean crop yields, so the analyst must specify the appropriate mean yields for each alterna- tive farm size. The values entered are assumed to be positive or negative differences from their respective means on Card 25. This enables the analyst to change assumptions regarding weather, and thus crop yields, from one run to the next by changing the values on Card 25. Crop enterprises must be in the order specified for Card 22. Enter yield data in the same order as the Card 39's. (2I2,6X,10F7.0) f Card Columns 1-2 Code the card number ’42’. 3-4 Code the crop enterprise number, JCROP, as ’01’. 5-10 Code a card name, such as "F1—-CD’. 11-17 Difference in the alternative farm’s average crop yield in year 1 and the initial farm's average crop yield in year 1. as -30.0. 18-24 Difference in the alternative farms average crop yield in year 2 and the initial farm’s average crop yield in year 2. as -10.0. 25-31 Difference in the alternative farm’s average crop yield in year 3 and the initial farm’s average crop yield in year 3. as 0.0. 32-38 Difference in the alternative farm’s average crop yield in year 4 and the initial farm’s average crop yield in year 4. as 0.1. 39-45 Difference in the alternative farm’s average crop yield in year 5 and the initial farm's average crop yield in year 5. as -0.l. 84 46-52 Difference in the alternative farm’s average crop yield in year 6 and the initial farm’s average crop yield in year 6, as -0.01. 53-59 Difference in the alternative farm’s average crop yield in year 7 and the initial farm’s average crop yield in year 7, as -0.02. 60-66 Difference in the alternative farm’s average crop yield in year 8 and the initial farm’s average crop yield in year 8, as 0.0. 67-73 Difference in the alternative farm’s average crop yield in year 9 and the initial farm’s average crop yield in year 9, as -0.01. 74-80 Difference in the alternative farm’s average crop yield in year 10 and the initial farm’s average crop yield in year 10, as -0.01. Card 43.IFARM-JCROP -- Crop Price Information for Alternative Farm Sizes Card 43 is repeated for each crop enterprise (JCROP) and each alternative farm size (IFARM). By doing this, the analyst enters a separate set of season average crop prices for each crop on each alternative farm size. Farms larger than the initial farm may experience lower or higher mean crop prices, so the analyst must specify the appropriate prices for each alternative farm size. Values entered here are assumed to be positive or negative differences from their respective means provided on Card 26. This enables the analyst to change assumptions regarding market con- ditions from one run to the next by changing the mean prices on Card 26. Crop enterprises are assumed to be in the order specified for Card 22. Enter price data in the same order as the Card 39’s. (2I2,6X,l0F7.0) Card Columns 1-2 Code the card number '43’. 3-4 Code the crop enterprise number, JCROP, as ’01 ’. 5-10 Code a card name, such as "Fl--CD”. 11-17 Difference in the alternative farm’s average crop price in year 1 and the initial farm’s average crop price in year 1. as 0.02. 18-24 Difference in the alternative farm’s average crop price in year 2 and the initial farm‘s average crop price in year 2, as 0.02. 25-31 Difference in the alternative farm's average crop price in year 3 and the initial farm’s average crop price in year 3. as 0.02. 32-38 Difference in the alternative farm’s average crop price in year 4 and the initial farm's average crop price in year 4. as 0.04. 39-45 Difference in the alternative farm’s average crop price in year 5 and the initial farm’s average crop price in year 5, as 0.04. 46-52 Difference in the alternative farm's average crop price in year 6 and the initial farms average crop price in year 6. as 0.02. 53-59 Difference in the alternative farm's average crop price in year 7 and the initial farms average crop price in year 7. as 0.03. 60-66 Difference in the alternative farm’s average crop price in year 8 and the initial farm’s average crop price in year 8. as 0.03. 85 67-73 Difference in the alternative farm’s average crop price in year 9 and the initial farm’s average crop price in year 9, as 0.05. 74-80 Difference in the alternative farm’s average crop price in year 10 and the initial farm ’s average crop price in year 10, as 0.06. Cards 44-49 -- Livestock Enterprise Information When the farm raises beef cattle (Option 10 not equal to zero), the analyst must provide information for the livestock enterprise on Cards 44-49. If Option 10 is equal to zero, skip Cards 44-49. The number of livestock enterprises is specified by Option 10 on the Option Card. Card 44.ILVSK -- Livestock Enterprise Information The order of livestock data cards is less flexible than for crops. Whereas the analyst may establish his/her own order for crop enterprises, the program has been written to accept all livestock enterprise information in a set order. The first livestock enterprise must be for the mother cow herd. The second enterprise is for the replacement heifer herd which is made up of bred heifers between 1 and 2 years of age. The third enterprise is for herd sires. The fourth enterprise is for stocker steers purchased and sold during the income tax year. The final livestock enterprise is for feeder cattle purchased and sold during the tax year. The number of livestock enterprises is speci- fied by Option l0 on the Options Card. If the farm has a typical cow/calf herd, the number of live- stock enterprises is three. If the farm raises only stocker steers, the analyst must indicate there are four livestock enterprises and enter zero values for the first three livestock enterprises. When the representative farm includes a cow/calf herd with both stockers and feeders, indicate on Option 1O that there are five livestock enterprises. Code a separate Card 44 for each livestock enterprise (ILVSK). (2I2,3A4,1X,9F7.0) Card Columns 1-2 Code the card number ’44’. 3-4 Code the livestock enterprise number, ILVSK, as ’01’, ’02’, ’03’, ’04’, or 5-16 (goscle an alphanumeric name for the enterprise, such as ‘COWS’. 17 Blank. 18-24 Beginning market value for all animals in the enterprise, as 25000.0. 25-31 Average sale weight of livestock in the enterprise, as 1050.0 for cows, 650.0 for replacement heifers sold, 1590.0 for cull bulls, 800.0 for feeder steers sold, or 1100.0 for fat cattle sold. 32-38 Annual per head costs of all purchased inputs (other than labor and inter- est) for livestock in the enterprise. as 46.50. This value must be applicable for the year preceeding the first year to be simulated. 39-45 Annual average death loss (fraction) for animals in the particular enter- prise, as 0.05 for cows, 0. l0 for replacement heifers. etc. 46-52 Average sale weight for heifer" calves sold at weaning, as 450.0 lb, if the card is for the mother cow herd. 86 53-59 Average sale weight for steer calves sold at weaning, as 500.0 lb, if the card is for the mother cow herd, and the average weight of purchased or sold stocker steers. 60-80 Blank. Card 45A -- Herd Replacement Strategies The model permits the simulation of a cow herd which may increase and/or decrease from year to year. In addition, changes in herd size can be achieved by purchasing replacement cows, raising replacement heifers or a combination of these two practices. To accomodate such flexibility, the analyst must provide information for the farm operator’s normal replacement practices and the planned (or desired) herd size, over the 10-year planning horizon. Card 45 specifies the replace- ment strategy information for the herd. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’45’. 3-4 Code a ’01’. 5-10 Code a card name, such as ’REPLMT’. 11-17 Average calving fraction for the herd, as 0.95. 18-24 Average death loss (fraction) of calves after birth and before weaning, as 0.05. 25-31 Average fraction of heifer calves kept for the replacement herd (not sold at weaning), as 0.20. 32-38 Average fraction of replacement heifers sold between 1 and 2 years of age due to sickness or failure to breed, as 0.10. 39-45 Initial number of bred heifers in the replacement herd. as 6.0. 46-52 Average price received for replacement heifers sold due to sickness or failure to breed, as 450.0 dollars. This should be the average price expected for the first year to be simulated. 53-59 Average price paid for replacement cows. as 650.0 dollars. This should be the expected price for the first year to be simulated. 60-66 Average price paid for bulls (herd sires), as 2000.0 dollars. This should be the expected price for the first year to be simulated. 67-73 Average fraction of the cow herd culled each year, as 0.10. 74-80 Blank. 87 Card 45B.ILVSK -- Herd Size Information Card 45 specifies information about the size of the livestock enterprises (number of head) for each year of the planning horizon. The analyst must provide two Card 45B’s if the farm has only a cow calf operation, one Card 45B for the number of cows and one for the number of bulls. If the farm has a herd of stocker steers, code three Card 45B’s and if the farm has a pen of feeder steers, code four Card 45B’s. The model assumes the number of head specified for year 1 on these cards is also the initial herd size. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’45’. 3-4 Code a ’02’ if the card is for the mother cow herd, a ’03’ if the card is for herd sires. a ’04’ if the card is for stocker steers, and a ’05’ if the card is for feeders. 5-10 Code a card name, such as ’HERDSZ’. » 11-17 Number of head for the enterprise in year 1, as 50.0 for cows, or 2.0 for bulls, or 250.0 for stocker steers, or 300.0 for feeder steers. 18-24 Number of head for the enterprise in year 2, as 50.0. 25-31 Number of head for the enterprise in year 3, as 60.0. 32-38 Number of head for the enterprise in year 4, as 70.0. 39-45 Number of head for the enterprise in year 5, as 80.0. 46-52 Number of head for the enterprise in year 6, as 75.0. 53-59 Number of head for the enterprise in year 7, as 70.0. 60-66 Number of head for the enterprise in year 8, as 60.0. 67-73 Number of head for the enterprise in year 9, as 50.0. 74-80 Number of head for the enterprise in year l0, as 60.0. Card 46.ILVSK -- Livestock Depreciation Purchased breeding stock is eligible for depreciation or cost recovery under the 1981 Tax Act. The model permits depreciation of herd bulls and purchased mother cows. The analyst must enter the data for each group of livestock to be depreciated on a separate Card 46. Option 29 on the Options Card indicates how many Card 46’s the analyst will provide. All depreciation data for cows purchased in a given year should be aggregated and entered on one Card 46 to reduce the number of data cards required. (2I2.3A4,9F7.0) Card Columns 1-2 Code the card number "46’. 3-4 Code the consecutive numbers for Card 46s ILVSK. as '01’. ‘02’, and so on. 5-16 Cocle an alphanumeric name for the unit, as ‘Beef Unit l‘ or ‘Bulls 1979’. 17-23 Enter ’l.0' if the data are for cows and ’0.0‘ if the data are for bulls. 88 n“. _....~. .¢_=‘l.\.u..4a.¢....-:j.u4nn,:lh..l._l\.|Za.&.uL_.uL.nLl.Au-ilasm3&i»j " 24-30 Number of head in the unit being coded on this card, as 10.0 or 1.0. 31-37 Purchase price when the livestock entered the herd, as 8000.0 dollars. 38-44 Salvage value if purchased prior to 1981, as 3000.0 dollars; otherwise enter 0.0. 45-51 Depreciation life if purchased prior to 1981, as 5.0 or 12.0. 52-58 Calendar year purchased, as 1981.0. 59-65 Economic life of the livestock coded on this card, as 6.0 years for bulls. 66-72 Number of years to cost recover the set of cattle specified here, as 3.0, 5.0, 12.0, or 15.0. 73-80 Current market value of all livestock in this depreciation category (year and sex), as 7000.0 dollars. Card 47.ILVSK -- Livestock Prices The season average or modal prices for the livestock enterprise are provided for each year of the planning horizon. The analyst must provide two more Card 47’s than the number of livestock enterprises (ILVSI(+2) to insure that the model has prices for heifer and steer calves. The first Card 47 is for the annual prices of culled mother cows. The second Card 47 contains annual prices for heifer calves. The third Card 47 contains annual prices for steer calves. The fourth Card 47 contains annual prices for culled yearling heifers. The fifth Card 47 contains annual prices for culled herd sires. The sixth Card 47, if applicable, contains annual prices for livestock enterprise four, and the seventh Card 47, if applicable, contains annual prices for livestock enterprise five. The price for purchasing stocker steers (enterprise 4) is assumed to be the price received for steer calves which is provided on the third card. In similar fashion. the price for purchasing feeder cattle (enterprise 5) is assumed to be the price received for stocker steers. Thus non-zero prices for weaned bull calves must be provided when simulating stocker steers, and non-zero prices for stocker steers must be provided when simulating feeder cattle. (2I2,6X.10F 7.0) Card Columns 1-2 Code the card number ’47’. 3-4 Code the card number. ILVSK, as '01’, ’02‘. and so on. 5-10 Code a card name, such as ’LPRICE’. 11-17 Season average price in year 1 (ES/lb). 18-24 Season average price in year 2 ($/lb). 25-31 Season average price in year 3 (S/lb). 32-38 Season average price in year 4 (S/lb). 39-45 Season average price in year 5 ($/lb). 46-52 Season average price in year 6 ($/lb). 53-59 Season average price in year 7 (Si/lb). 60-66 Season average price in year 8 (Si/lb). 89 67-73 Season average price in year 9 (S/lb). 74-80 Season average price in year 10 (S/lb). Card 48.ILVSK -- Factored Matrix for Livestock Prices Card 48 is used to enter the factored covariance or correlation matrix (upper triangle) for livestock prices. The order of the livestock enterprises must be the same as the order of livestock prices for Card 47. Code a separate Card 48 for each row of the matrix. (2I2,6X,l0F7.0) Card Columns 1-2 Code the card number ’48’. 3-4 Code the row number (I) of the matrix, as ’0l’, ’02’, and so on. 5-10 Code a card name, such as ’LVSKPR’. 11-17 The X(I,l) value of the matrix. (If Option 24 equals 1, 3. 5, or 8, enter the enterprise’s standard deviation or own correlation coefficient here, and leave the remainder of the card blank. If the model is to run deterministi- cally, this card can be left blank in columns 11-80.) 18-24 The X(I,I+ 1) value of the matrix, if applicable. 25-31 The X(I,I+2) value of the matrix, if applicable. 32-38 The X(l,I+3) value of the matrix, if applicable. 39-45 The X(I,I+4) value of the matrix, if applicable. 46-52 The X(I,l+5) value of the matrix, if applicable. 53-59 The X(I,I+6) value of the matrix, if applicable. 60-80 Blank. Card 49A.ILVSK -- Monthly Labor Requirements for Livestock Monthly labor requirements for each livestock enterprise, excluding young heifers and steers, are provided on this card. Code a separate card for each livestock enterprise (ILVSK). (2l2.4X.l2F6.0) Card Columns 1 2 Code the card number ‘49’. 3-4 Code the livestock enterprise number, ILVSK, as ‘01’. 8 5- Code a card name. such as '49AA’. 9-14 Hours of labor per head required for the enterprise in January. as 0.5. 15-20 Hours of labor per head required for the enterprise in February, as 0.5. 21-26 Hours of labor per head required for the enterprise in Nlarch. as 0.5. 27-32 Hours of labor per head required for the enterprise in April, as 0.5. 90 33-38 Hours of labor per head required for the enterprise in May, as 0.5. 39-44 Hours of labor per head required for the enterprise in June, as 0.5. 45-50 Hours of labor per head required for the enterprise in July, as 0.5. 51-56 Hours of labor per head required for the enterprise in August, as 0.5. 57-62 Hours of labor per head required for the enterprise in September. as 0.5. 63-68 Hours of labor per head required for the enterprise in October, as 0.5. 69-74 Hours of labor per head required for the enterprise in November, as 0.5. 75-80 Hours of labor per head required for the enterprise in December, as 0.5. Card 49B.ILVSK -- Annual Feed Requirements for Livestock To account for the case where crops produced on the farm are fed to livestock, one must provide annual feed requirements per head for each crop. If a crop is not fed to livestock enter the feed requirements for this crop as a zero. The model requires the analyst to code a separate feed requirements card for each livestock enterprise excluding young heifers and steers. All annual feed requirements must be expressed in the yield units for the corresponding crop enterprise, e.g., bush- els of grain or tons of alfalfa fed per year. Surplus feed is sold at prevailing market prices entered on Card 26 and deficit feed requirements are purchased at 110 percent of prevailing market prices. Code a separate Card 49B for each livestock enterprise (ILVSK). (2I2.6X,10F7.0) Card Columns 1-2 Code the card number ’49’. 3-4 Code consecutive numbers for each card, ILVSK, as ’0l',’02’.... 5-10 Code a card name. such as ’49BB’. ll-17 Annual feed requirements per head, for crop enterprise 1, as 50.0 bushels. 18-24 Annual feed requirements per head, for crop enterprise 2. as 20.0 bushels. 25-31 Annual feed requirements per head, for crop enterprise 3, as 3.5 tons. 32-38 Annual feed requirements per head, for crop enterprise 4, as 1.0 tons. 39-45 Annual feed requirements per head, for crop enterprise 5. as 0.0. 46-52 Annual feed requirements per head, for crop enterprise 6, as 0.0. 53-59 Annual feed requirements per head, for crop enterprise 7, as 0.0. 60-66 Annual feed requirements per head, for crop enterprise 8. as 0.0. 67-73 Annual feed requirements per head, for crop enterprise 9, as 0.0. 74-80 Annual feed requirements per head. for crop enterprise l0, as 0.0. 91 Card SOJCROP -- Empirical Probability Distribution Cards When Option 24 is equal to 7 or 8, the analyst must provide information necessary to esti- mate 10 points on the empirical probability distribution for each crop yield, crop price, and non- dairy livestock price. The 10 values for each distribution must be expressed as fractional deviations of their respective mean or trend value (yield or price) for year 1. By providing the fractional devi- ations about the prices and yields for year 1, the model generates an experimental cumulative distri- bution for each annual crop price, crop yield, and livestock price with the same relative variance each year. Code the cards for each crop’s yield distribution first, then code the cards for each crop’s price distribution, and if applicable, code the cards for each livestock enterprise a price was coded for on Card 47. Code a separate Card 50 for each price and yield distribution. The number of Card 50’s must equal to 2 times the number of crop enterprises, plus the number of livestock enterprises plus 2. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’50’. 3-4 Code consecutive numbers for each card, JCROP, as ’Ol’, ’02’,... . After coding a separate card for each crop’s yield, code a separate card for each crop’s price. If the farm has a beef cattle enterprise, enter a separate Card 50 to match each Card 47 and begin numbering the cards ILVSK, ’Ol’, 5-10 gozdeuzi card name, such as ’DEVIAT’. 11-17 The first deviate from trend or mean. as -0.15. 18-24 The second deviate from trend or mean, as -0.13. 25-31 {he third deviate from trend or mean, as -0.10. 32-38 The fourth deviate from trend or mean, as 0.0. 30-45 The fifth deviate from trend or mean. as 0.02. 46-52 The sixth deviate from trend or mean, as 0.04. 53-59 The seventh deviate from trend or mean, as 0.06. 60-66 The eighth deviate from trend or mean, as 0.07. 67-73 The ninth deviate from trend or mean, as 0.09. 74-80 The tenth deviate from trend or mean, as 0.10. Cards 51 and 5" -- Triangular Probability Distribution Cards When Option 24 is equal to 2 or 3, the analyst must provide minimum and maximum values (expressed as fractions of their respective means) for crop yields. crop prices, and livestock prices (if applicable). A triangular probability distribution is completely defined by three values: minimum, mode. and maximum. Modal yields and prices are entered on Cards 25. 26. and 47 when Option 24 is equal to 2 or 3. The minimum and maximum values (expressed as fractions) are provided on Card 51 for each crop enterprise, and similar values for the livestock enterprises are entered on Card 52 (if applicable). Minimum values must be entered in terms of the fraction of the mode in year l. e.g., 0.75 for a minimum that is 75 percent as great as the mode in year l. Similarly, the maximum is entered as the fraction of maximum relative to the mode. e.g.. 1,45 for a maximum which is 45 percent greater than the modal value in year 1. By providing these minimum and 92 maximum values, the distributions can be trended up or down by changing the modal values on Cards 25, 26, and 47, while holding relative variance constant. Card SLJCROP -- Triangular Probability Distribution for Crop Yields and Prices Yield and price units must be expressed as a fraction of their respective mean or modal val- ues for year 1 on Cards 25 and 26. Code a separate card for each crop enterprise (JCROP). (212,6x,101=7.0) Card Columns 1-2 Code the card number ’51’. 3-4 Code the crop enterprise number, JCROP, as ’01’. 5-10 Code a card name, such as ’TRICRP’. 11-17 Minimum crop yield expressed as a fraction of the modal value for year 1 on Card 25, such as 0.50 or 0.90. Be sure to code the negative sign. 18-24 Maximum crop yield expressed as a fraction of the modal value for year 1 on Card 25, such as 1.35 or 1.25. 25-31 Minimum crop price expressed as a fraction of the modal value for year 1 on Card 26, such as 0.58. Be sure to code the negative sign. 32-38 Maximum crop price expressed as a fraction of the modal value for year 1 on Card 26, such as 1.61. 39-80 Blank. Card S2.ILVSK -- Triangular Probability Distributions for Livestock Prices Price units must be expressed as a fraction of their respective mean or modal values for year 1 on Card 47 ($/lb). If the farm has no livestock, skip Card 52. Code a Card 52 to match each of the Card 47’s coded for livestock prices. (2I2,6X.l0F7.0) Card Columns 1-2 Code the card number ’52’. 3-4 Code the livestock enterprise number used on Card 46. as ’01’. 5-10 Code a card name, such as "TRILVSI 11-17 Minimum livestock price expressed as a fraction of the modal value for year 1 on Card 47, such as 0.80 or 0.50. Be sure to code the negative sign. 18-24 Maximum livestock pice expressed as a fraction of the modal value for year 1 on Card 47, such as 1.50 or 1.40. 25-80 Blank. Card 53JCROP -- Expansion Factors for Probability Distributions Empirical price and yield distributions for the crop enterprises can be expanded (or con- tracted) annually by multipling the random fractional deviates about the mean by a fraction, such as 1.30 (or 0.89). This expansion factor option is of use when the yield distribution for a particular 93 crop is expected to increase over time as a result of the introduction of a new variety or due to the reduced effectiveness of chemicals used to control the primary pest affecting the crop. Price distri- butions can also be expanded or contracted over time due to the operator’s subjective expectations of prices or due to changing the farm program parameters (loan rates) during the planning horizon. To use this option, the analyst must enter a ’1’ for Option 43 on the Option Card and code (yield and price) Card 53’s for each crop enterprise. The first JCROP cards must be for the yield distributions and the second set of JCROP cards must be for the price distributions. Enter the yield cards and the price cards in the same order used for Card 22. The fractional adjustments entered for each year of the planning horizon are the fractional increases from year 1, i.e., they do not compound over time. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’53’. 3-4 Code the crop enterprise number, JCROP, as ’01’, ’02’,... 5-10 Code a card name, such as ’FRACTY’. 11-17 Fractional expansion (or contraction) in the probability distribution for the crop in year 1, as 1.00. 18-24 Fractional expansion (or contraction) in the probability distribution for the crop in year 2, as 1.20. 25-31 Fractional expansion (or contraction) in the probability distribution for the crop in year 3, as 1.20. 32-38 Fractional expansion (or contraction) in the probability distribution for the crop in year 4, as 1.30. 39-45 Fractional expansion (or contraction) in the probability distribution for the crop in year 5, as 1.30. 46-52 Fractional expansion (or contraction) in the probability distribution for the crop in year 6, as 1.10. 53-59 Fractional expansion (or contraction) in the probability distribution for the crop in year 7, as 1.00. 60-66 Fractional expansion (or contraction) in the probability distribution for the crop in year 8, as 0.90. 67-73 Fractional expansion (or contraction) in the probability distribution for the crop in year 9, as 0.89. 74-80 Fractional expansion (or contraction) in the probability distribution for the crop in year l0, as 0.80. Card 54.JCROP -- Covariance of Net Returns per Acre for Crop Enterprises When the analyst elects to use a OP solution to determine the crop mix, Option 9 on Card 2, the program requires the upper-triangular covariance matrix of net returns per acre. The order of crop enterprises established for Card 22 must be continued on this Card. Code a separate Card 54 for each row of the covariance matrix (JCROP) and enter only the upper triangle coefficients for the matrix. (2I2,6X,10F7.0) 94 Card Columns 1-2 Code the card number ’54’. 3-4 Code the matrix row number, JCROP, as ’01’, ’02’.... 5-10 Code a card name, such as ’COVARI’. 11-17 The X(I,l) or main diagonal value for row I. 18-24 The X(I,l+ 1) value, if applicable. 25-31 ' The X(I,I+2) value, if applicable. 32-38 The X(I,l+3) value, if applicable. 39-45 The X(I,I+4) value, if applicable. 46-52 The X(I,l+5) value, if applicable. 53-59 The X(I,1+6) value, if applicable. 60-66 The X(I,l+ 7) value, if applicable. 67-73 The X(I,l+8) value, if applicable. 74-80 The X(I,l+9) value, if applicable. Card 55.ILEASE -- Machinery Leasing In addition to owning farm machinery, the operator can lease farm machinery. Information regarding the lease arrangements for each item of farm machinery leased (ILEASE) are coded on a Card 55. Code as many Card 55’s as there are pieces of machinery leased and as indicated for Option 6 on the Option Card. The fraction of the original price paid annually as a lease cost is entered for each piece of machinery. This fraction depends on the current interest rate for buying new machinery (i.e.. for intermediate-run loans) and the expected value of the machine at the end of lease. The analyst should obtain current lease rates for each item to be leased. However. the lease rate can be approx- imated using the following formula estimated from lease rates provided by John Deere in 1983: Annual Intermediate Remaining Lease = 0.1875 + 0.005 Interest - 12.9) + 0.0015 (35.0 - Value ) Rate Rate (percent) Percentage An interest rate of 12.9 percent and a remaining value of 35 percent would yield an 18.75 percent annual lease cost. Code as many Card 55's as Index 6 indicated on the Option Card using the format below: Card Columns 1-2 Card number '55’. 3-4 Machine's number. ILEASE, as '01‘. ‘02’. ’03'.... 5-16 An alphanumeric name for the machinery item. such as ‘TRACTOR4440’. 17 Blank. 95 18-24 Price of the machine when the lease agreement was signed, as 48000.0 dollars. 25-31 Current price of the machine, as 44000.0. 32-38 Current market value of a machine that would replace this machine, as 50000.0. 39-43 Calendar year the lease agreement was signed and the first lease payment was made, as 1982.0. 44-46 Number of years for the lease, as 5.0. 47-50 Specified value of the machine at the end of the lease, expressed as a frac- tion of the price of the machine when it was leased, as 0.25. 51-55 Annual lease cost for the machine, expressed as a fraction of the price of the machine when it was leased, as 0.202. 56-59 Disposition code for the machine at the end of the lease: ’0.0’ turn it back to machinery dealer and neither buy nor lease a replace- ment; ’0.1’ turn it back to the machinery dealer and lease a replacement; ’0.2’ turn it back to the machinery dealer and buy a replacement; ’0.3’ buy it for the specified ending price and keep it for depreciation and later replacement; ’0.4’ buy it for the specified ending price and sell it prior to purchasing a replacement; ’0.5’ buy it for the specified ending price and sell it prior to leasing a replacement; ’0.6’ buy it for the specified ending price and trade it in on a purchased replacement; ’0.7’ buy it for the specified ending price and trade it in on a leased replacement. 60-63 Economic life of the machine, as 10.0 years. 64-67 The number of years to recover the cost of the machine if the operator elects to keep it when the lease ends, as 3.0, 5.0. or 15.0 years. (This value is also used to cost recover the purchase of a replacement.) 68-71 Replacement code for the purchased machine if the operator plans to pur- chase after the lease: ’0.0’ if the machine is replaced at the end of its economic life; ’0.1’ if the machine is kept and replaced at the end of its economic life; and ' ’2.0’ if the machine is kept and no: replaced at the end of its economic life. 72-80 Blank. Cards 56-80 -- Data Cards for Dairy Cows If the farm includes a dairy enterprise (Option 41 equals 1) the analyst must provide data for Cards 56-80. 96 Card 56 -- Number of Cows Milked Each Month The analyst must enter the average number of cows milked each month. By entering monthly totals, the model can accurately reflect any type of dairy production pattern. This value is used to determine milk production and the cost of maintaining milking cows. (I2,6X,12F6.0) Card Columns 1-2 Code the card number ’56’. 3-8 ' Code a card name, such as ’MILKCW’. 9-14 Number of cows milked in January, as 150.0. 15-20 Number of cows milked in February, as 145.0. 21-26 Number of cows milked in March, as 140.0. 27-32 Number of cows milked in April, as 150.0. 33-38 Number of cows milked in May, as 160.0. 39-44 Number of cows milked in June, as 160.0. 45-50 Number of cows milked in July, as 160.0. 51-56 Number of cows milked in August, as 150.0. 57-62 Number of cows milked in September, as 150.0. 63-68 Number of cows milked in October, as 150.0. 69-74 Number of cows milked in November, as 150.0. 75-80 Number of cows milked in December, as 150.0. Card 57 -- Number of Dry Cows Fed Each Month The analyst must enter the average number of dry cows that must be fed each month. This value is used to calculate the cost of maintaining dry cows. (I2.6X,12F6.0) Card Columns 1-2 Code the card number ’57’. 3-8 Code a card name, such as ’DRYCOW’. 9-14 Number of clry cows in January, as 50.0. l5-20 Number of dry cows in February, as 50.0. 21-26 Number of dry cows in March. as 50.0. 27-32 Number of dry cows in April. as 50.0. 33-38 Number of dry cows in Nlay. as 50.0. 39-44 Number of clry cows in June, as 50.0. 97 45-50 Number of dry cows in July, as 50.0. 51-56 Number of dry cows in August, as 50.0. 57-62 Number of dry cows in September, as 50.0. 63-68 Number of dry cows in October, as 50.0. 69-74 Number of dry cows in November, as 50.0. 75-80 Number of dry cows in December, as 50.0. Card 58 -- Number of Replacement Heifers Fed Each Month Enter the number of replacement heifers on the farm that must be fed each month. Replacement heifers are considered to be bred heifers between 1 and 2 years of age. This value is used to calculate the cost of maintaining heifers. (I2,6X,12F6.0) Card Columns 1-2 Code the card number ’58’. 3-8 Code a card name, such as ’REPLAC’. 9-14 Number of replacements fed in January, as 50.0. 15-20 Number of replacements fed in February, as 50.0. 21-26 Number of replacements fed in March. as 50.0. 27-32 Number of replacements fed in April, as 50.0. 33-38 Number of replacements fed in May, as 50.0. 39-44 Number of replacements fed in June, as 50.0. 45-50 Number of replacements fed in July, as 50.0. 51-56 Number of replacements fed in August. as 50.0. 57-62 Number of replacements fed in September. as 50.0. 63-68 Number of replacements fed in October, as 50.0. 69-74 Number of replacements fed in November, as 50.0. 75-80 Number of replacements fed in December. as 50.0. ' 98 Card 59 -- Dairy Calves Fed Each Month Enter the average number of dairy calves on hand (fed) each month for calculating the cost of their feed, etc. (I2,6X,12F6.0) Card Columns 1-2 3-8 9-14 15-20 21-26 27-32 33-38 39-44 45-50 51-56 57-62 63-68 69- 74 75-80 Code the card number ’59’. Code a card name, such as ’CALF’. Number of calves fed in January, as 1.0. Number of calves fed in February, as 10.0. Number of calves fed in March, as 20.0. Number of calves fed in April, as 50.0. Number of calves fed in May, as 30.0. Number of calves fed in June, as 10.0. Number of calves fed in July, as 1.0. Number of calves fed in August, as 0.0. Number of calves fed in September. as 0.0. Number of calves fed in October, as 0.0. Number of claves fed in November. as 0.0. Number of calves fed in December, as 0.0. Card 60 -- Dairy Herd Culling Rate Enter data for the average calving rate, average culling percentage, and other data necessary to calculate the herd dynamics over the planning horizon. (l2.6X,l2F6.0) Card Columns 1-2 3-8 9-14 15-20 21-26 27-32 Code the card number '60’. Code a card name, such as HERD’. Fraction of the milking age cows culled each year, as 0.25. Calving rate for the herd, as 0.85. Fraction of all baby calves born on the farm and sold at birth, as 0.53. Death loss for heifers under 12 months of age kept on the farm for herd replacements (fraction). as 0.20. Initial number of replacement heifers 1 to 2 years of age in the herd. as 20.0. 99 39-44 Fraction of replacement heifers sold after 1 year due to failure to breed or sickness, as 0.10. 45-80 Blank. Card 61 -- Annual Average Milk Price Enter the average annual price of milk received by farmers over the planning horizon. Milk price should be net of hauling costs if hauling costs are omitted for the cost of production value provided in columns 9-14 of Card 67. Enter milk prices in terms of S/cwt. (I2,6X,12F6.0) Card Columns 1-2 Code the card number ’61’. 3-8 Code a card name, such as ’MILKP’. 9-14 Average annual milk price in year 1, as 10.0. 15-20 Average annual milk price in year 2, as 9.0. 21-26 Average annual milk price in year 3, as 9.5. 27-32 Average annual milk price in year 4, as 9.59. 33-38 Average annual milk price in year 5, as 10.00. 39-44 Average annual milk price in year 6, as 11.00. 45-50 Average annual milk price in year 7, as 11.00. 51-56 Average annual milk price in year 8, as 11.50. 57-62 Average annual milk price in year 9, as 11.75. 63-68 Average annual milk price in year 10, as 11.80. 69-80 Blank. Card 62 -- Annual Average Cull Cow Prices Enter the average annual price for culled milk cows over the planning horizon. Enter the price as S/cow. (I2,6X,l2F6.0) Card Columns 1-2 Code the card number ’62‘. ' 3-8 Code a card name, such as ’COWPRI‘. 9-14 Average price received for a cull milk cow in year 1. as 510.0. 15-20 Average price received for a cull milk cow in year 2. as 510.0. 21-26 Average price received for a cull milk cow in year 3. as 510.0. 27-32 Average price received for a cull milk cow in year 4, as 510.0. 100 “Y, mm 33-38 Average price received for a cull milk cow in year 5, as 510.0. 39-44 Average price received for a cull milk cow in year 6, as 510.0. 45-50 Average price received for a cull milk cow in year 7, as 510.0. 51-56 Average price received for a cull milk cow in year 8, as 510.0. 57-62 - Average price received for a cull milk cow in year 9, as 510.0. 63-90 Average price received for a cull milk cow in year 10, as 510.0. 69-90 Blank. Card 63 -- Annual Average Price Paid for Replacement Cows Enter the annual average price paid for a replacement milk cow over the planning horizon. These cows are assumed to be lactating at acquisition. Enter the price as $/cow. (I2,6X,12F6.0) Card Columns 1-2 Code the card number ’63’. 3-8 Code a card name, such as ’REPLAC’. 9-14 Average price paid for a replacement milk cow in year 1, as 1080.0. 15-20 Average price paid for a replacement milk cow in year 2, as 1080.0. 21-26 Average price paid for a replacement milk cow in year 3. as 1080.0. 27-32 Average price paid for a replacement milk cow in year 4, as 1080.0. 33-38 Average price paid for a replacement milk cow in year 5. as 1080.0. 39-44 Average price paid for a replacement milk cow in year 6, as 1080.0. 45-50 Average price paid for a replacement milk cow in year 7, as 1080.0. 51-56 Average price paid for a replacement milk cow in year 8, as 1080.0. 57-62 Average price paid for a replacement milk cow in year 9, as 1080.0. 63-68 Average price paid for a replacement milk cow in year 10, as 1080.0. 69-80 Blank. 101 Card 64 -- Annual Average Price for Baby Calves Enter the annual average price received for baby calves sold by the operator. Enter the price as $/head. (l2,6X,12F6.0) Card Columns 1-2 3-8 9-14 15-20 21-26 27-32 33-38 39-44 45-50 51-56 57-62 63-68 69-80 Code the card number ’64’. Code a card name, such as ’CALFPR’. Average price received for selling calves in year 1, as 50.0. Average price received for selling claves in year 2, as 50.0. Average price received for selling calves in year 3, as 50.0. Average price received for selling calves in year 4, as 50.0. Average price received for selling calves in year 5, as 50.0. Average price received for selling calves in year 6, as 50.0. Average price received for selling calves in year 7, as 50.0. Average price received for selling calves in year 8, as 50.0. Average price received for selling calves in year 9, as 50.0. Average price received for selling calves in year 10, as 50.0. Blank. Card 65 -- Seasonal Price Index for Milk Enter the seasonal price index for milk as a fraction. (I2.6X,12F6.0) Card Columns -2 -s Code the card number ‘65’. Code a card name, such as ’SEASIN’. Seasonal price index for January, as 1.001. Seasonal price index for February. as 1.001. Seasonal price index for March, as 1.001. Seasonal price index for April, as 1.004. Seasonal price index for May, as .990. Seasonal price index for June. as .999. Seasonal price index for July, as .989. Seasonal price index for August. as .979. 102 57-62 Seasonal price index for September. as 1.001. 63-68 Seasonal price index for October, as 1.001. 69-74 Seasonal price index for November, as 1.001. 75-80 Seasonal price index for December, as 1.001. a Card 66 -- Seasonal Milk Production Per Cow Enter the average monthly milk production per cow during each month of the year; enter the values as cwt/month. These values are used to calculate monthly milk production for the herd. (I2,6X,12F6.0) Card Columns 1-2 Code the card number ’66’. 3-8 Code a card name, such as ’MILKPD‘. 9-14 Milk production per cow in January, as 12.0. 15-20 Milk production per cow in February, as 12.5. 21-26 Milk production per cow in March. as 11.0. 27-32 Milk production per cow in April, as 12.0. 33-38 Milk production per cow in May, as 11.1. 39-44 Milk production per cow in June. as 9.0. 45-50 Milk production per cow in July, as 9.0. 51-56 Milk production per cow in August, as 9.0. 57-62 Nlilk production per cow in September, as 9.0. 63-68 Milk production per cow in Qctober, as 10.8. 69-74 Milk production per cow in November, as 11.0. 75-80 Milk production per cow in December. as 12.0. Card 67 -- Annual Cost of Production for the Dairy Herd Enter the total annual cash expense for feed, vet bills, and other cash expenses for the year preceeding the first year to be simulated. Do no: include annual interest and labor expenses or mis- cellaneous repair and fixed costs. as these values are entered for the farm as a whole. Do not include the cost of feed raised on the farm. Enter all costs on a S/head basis. (I2,6X.l2F6.0) Card Columns 1-2 Code the card number '67’. 3-8 Code a card name. such as ’COSTS'. 103 9-14 Annual cost per head for a milking cow, as 900.0. 15-20 Annual cost per head for a dry cow, as 0.0. 21-26 Annual cost per head for a replacement heifer, as 90.50. 27-32 Annual cost per head for a heifer calf under 12 months, as 200.0. 33-38 Annual cost per head for a bull, as 200.0. 39-80 Blank. Card 68 -- Monthly Labor Requirements for Milk Cows Card Columns 1-2 Code the card number ’68’. 3-8 Code a card name, such as ’LAbMILK“. 9-14 Hours of labor per milk cow in January, as 8.0. 15-20 Hours of labor per milk cow in February, as 8.0. 21-26 Hours of labor per milk cow in March, as 8.0. 27-32 Hours of labor per milk cow in April, as 8.0. 33-38 Hours of labor per milk cow in May, as 8.0. 39-44 Hours of labor per milk cow in June, as 8.0. 45-50 Hours of labor per milk cow in July. as 8.0. 51-56 Hours of labor per milk cow in August, as 8.0. 57-62 Hours of labor per milk cow in September, as 8.0. 63-68 Hours of labor per milk cow in October, as 8.0. 69-74 Hours of labor per milk cow in November, as 8.0. 75-80 Hours of labor per milk cow in December, as 8.0. Card 69 -- Monthly Labor Requirements for Dry Cows Card Columns 1-2 Code the card number ‘69’. 3-8 Code a card name, such as ‘LABDRY’. 9-14 Hours of labor per dry cow in January. as 1.5. 15-20 Hours of labor per dry cow in February, as 1.5. 21-26 Hours of labor per dry cow in Nlarch. as 1.5. 104 69-74 75-80 Hours of labor per dry cow in April, as 1.5. Hours of labor per dry cow in May, as 1.5. Hours of labor per dry cow in June, as 1.5. Hours of labor per dry cow in July, as 1.5. Hours of labor per dry cow in August, as 1.5. Hours of labor per dry cow in September, as 1.5. Hours of labor per dry cow in October, as 1.5. Hours of labor per dey cow in November, as 1.5. Hours of labor per dry cow in December, as 1.5. Card 70 -- Monthly Labor Requirements for Replacement Heifers Card Columns 15-20 21-26 27-32 33-38 39-44 45-50 51-56 57-62 63-68 69-74 74-80 Code the card number ’70’. Code a card name, such as ’LABREP’. Hours of labor per heifer in January, as 2.3. Hours of labor per heifer in February, as 2.3. Hours of labor per heifer in March, as 2.3. Hours of labor per heifer in April, as 2.3. Hours of labor per heifer in May, as 2.3. Hours of labor per heifer in June. as 2.3. Hours of labor per heifer in July, as 2.3. Hours of labor per heifer in August. as 2.3. Hours of labor per heifer in September, as 2.3. Hours of labor per heifer in October, as 2.3. Hours of labor per heifer in November, as 2.3. Hours of labor per heifer in December, as 2.3. Card 71 -- Monthly Labor Requirements for Baby Calves Card Columns 3-8 Code the card number ’7l’. Code a card name. such as ‘LABALF’. 105 9-14 15-20 g 21-26 27-32 33-38 39-44 45-50 51-56 57-62 63-63 69-74 75-80 Hours of labor per calf in January, as 0.90. Hours of labor per calf in February, as 0.90. Hours of labor per calf in March, as 0.90. Hours of labor per calf in April, as 0.90. Hours of labor per calf in May, as 0.90. Hours of labor per calf in June, as 0.90. Hours of labor per calf in July, as 0.90. Hours of labor per calf in August, as 0.90. Hours of labor per calf in September, as 0.90. Hours of labor per calf in October, as 0.90. Hours of labor per calf in November, as 0.90. Hours of labor per calf in December, as 0.90. Card 72 -- Cows to be Depreciated - Purchased Pre 1986 Information for cows in the herd that are eligible for cost recovery (ACRS) and were pur- chased after 1980 and before 1986 are entered on this card. (I2,6X,l2F6.0) Card Column 1-2 3-8 9-14 15-20 21-26 27-32 33-38 39-44 45-80 Code the card number ‘72’. Code a card name, such as ’OLDREP’. Purchase price for the cows, as 90000.0. Depreciation (cost recovery) life, 3.0 years. Calendar year they were primarily purchased in, as 1984.0. Economic life of the cows, as 3.0 years. This must be non-zero. Accumulated depreciation, as 20000.0. Number of head bought, as 10.0. Blank. Card 73 -- Cows to be Depreciated - Purchased Post 1985 Enter the data here for the cows that were purchased after 1985 and are eligible for cost recovery. (I2,6X,l2F6.0) 106 Card Columns 1-2 3-8 9-14 15-20 21-26 27-32 33-38 39-44 45-80 Code the card number ’73’. Code a card name, such as ’NEWREP’. Purchase price for all of the cows, as 50000.0. Enter the capital cost recovery system asset class of 1.0 or 2.0. Calendar year purchased, as 1986.0. Economic life of milk cows, as 3.0 years. This must be non-zero. Accumulated depreciation, as 10000.0. Number of head, as 5.0. Blank. Card 74 -- Head Bulls Purchased Prior to 1986 Purchased bulls are eligible for cost recovery (ACRS) so enter the data for bulls purchased prior to 1985 on this card. (I2.6X,12F6.0) 1 2 3-8 39-44 45-50 51-80 Code the card number ’74’. Code a card name, such as ’BULL1’. Number of herd bulls. as 4.0. Economic life of a bull in the herd, as 5.0 years. This must be non-zero. Average purchase price of a bull, as 800.0. Average age of bulls purchased, as 2.0. Average sale price of a cull bull, as 300.0. Calendar year purchased, as 1984.0. Accumulated depreciation, as 5000.0. Blank. Card 75 -- Herd Bulls Purchased After 1985 Card Columns 1-2 3-8 9-14 15-20 21-26 Code the card number "75’. Code a card name. such as ‘BULLZ’. Number of herd sires. as 2.0. Economic life of a bull in the herd. as 5.0 years. This must be non-zero. Average purchase price of a bull. as 800.0. 107 27-32 33-38 39-44 45-50 51-56 57-80 Average age when purchased, as 2.0. Average sale price of an old bull, as 500.0. Calendar year purchased, as 1986.0. Accumulated depreciation, as 300.0. Capital cost recovery system asset class of 1.0 or 2.0. Blank. Card 76 -- Average Milk Production Per Cow Enter the projected annual average production of milk per cow over the planning horizon. If production per cow is expected to trend upward, enter progressively larger values, etc. Enter the milk production per cow in terms of cwts. (I2,6X,12F6.0) Card Columns 15-20 21-26 27-32 39-44 45-50 51-56 57-62 63-68 69-80 Code the card number ’76’. Code a card name, such as ‘MILKPA’. Annual average production of milk in cwts for year 1, as 130.0. Annual average production of milk in cwts for year 2, as 120.0. Annual average production of milk in cwts for year 3, as 140.0. Annual average production of milk in cwts for year 4, as 150.0. Annual average production of milk in cwts for year 5, as 150.0. Annual average production of milk in cwts for year 6. as 150.0. Annual average production of milk in cwts for year 7. as 150.0. Annual average production of milk in cwts for year 8, as 160.0. Annual average production of milk in cwts for year 9. as 160.0. Annual average production of milk in cwts for year 10, as 160.0. Blank. Card 77 -- Size of Milking Herd Enter the desired number of milk cows (all cows over 2 years of age) in the herd. each year of the planning horizon. This option allows the analyst to evaluate alternative herd growth strat- egies. Additional cows required for herd growth are either raised or purchased, depending on the availability of replacements. (I2.6X,12F6.0) Card Columns 1-2 Code the card number ’77‘. 108 3-8 Code a card name, such as ’COWS’. 9-14 Number of milk cows in year 1, as 150.0. 15-20 Number of milk cows in year 2, as 150.0. 21-26 _ Number of milk cows in year 3, as 155.0. 27-32 Number of milk cows in year 4, as 160.0. 33-38 Number of milk cows in year 5, as 165.0. 39-44 Number of milk cows in year 6, as 170.0. 45-50 Number of milk cows in year 7, as 175.0. 51-56 Number of milk cows in year 8, as 175.0. 57-62 Number of milk cows in year 9, as 175.0. 63-68 Number of milk cows in year l0, as 175.0. 69-80 Blank. Card 78.IDAIRY -- Annual Feed Requirements Per Head To account for the case where crops produced on the farm are fed to the dairy herd. the ana- lyst must provide the annual feed requirements per head for each crop. (If a crop is not fed, enter its feed requirements as zero for dairy animals.) The model requires that four separate Card 78’s be provided. The firs! Card 78 contains the annual feed requirements for each crop by a cow over 24 months of age. The second Card 78 contains the feed requirement information for replacement heifers between 12 months and 24 months of age. The third Card 78 contains the feed requirement information for replacement calves under 12 months of age. The fourth Card 78 contains the feed information for herd sires. All feed requirements must be expressed in terms of the yield units for the corresponding crop enterprise, eg., bushels of grain or tons of hay. Surplus feed is sold at pre- vailing market prices entered on Card 26 and deficit feed requirements are purchased at 110 percent of these prices. (2l2.6X,12F6.0) Card Columns 1-2 Code the card number ‘78’. 3-8 Code a card name, such as TEEDRQ’. 9-14 Annual feed requirement per head, for crop enterprise 1. as 85.9 bushels. 15-20 Annual feed requirement per head. for crop enterprise 2, as 4.85 tons. 21-26 Annual feed requirement per head. for crop enterprise 3, as 0.0. 27-32 Annual feed requirement per head. for crop enterprise 4. as 1.82 tons. 33-38 Annual feed requirement per head. for crop enterprise 5. as 3.55 tons. 39-44 Annual feed requirement per head. for crop enterprise 6. as 19.00 bushels. 45-50 Annual feed requirement per head. for crop enterprise 7. as 0.0. I09 51-56 Annual feed requirement per head, for crop enterprise 8, as 0.0. 57-62 Annual feed requirement per head, for crop enterprise 9, as 0.0. 63-68 Annual feed requirement per head, for crop enterprise 10, as 0.0. 69-80 Blank. Card 79.IDAIRY -- Factored Matrix for Dairy This set of six cards is similar t0 Card 27 for crop yields and prices. Values must be provided on this card if the model is to be run using stochastic prices. Enter the factored covariance matrix for prices and milk production if the model is to use normally distributed random numbers, i.e., Option 24 equals 0 or 1. Enter the factored correlation matrix for prices and milk production if the model is to use triangularly or empirically distributed random numbers, i.e., lndex (24) equal to 2,3,7, or 8. The order of the rows in the dairy covariance matrix is predetermined in the model. Rows 1-6 in the factored covariance matrix are: (a) annual milk price, (b) annual cull cow prices, (c) annual replacement cow price, (d) annual calf price, (e) annual milk production, and (f) index of feed costs. Code sLr cards for Card 79. one card for each row of the matrix. Enter only the upper right triangle for the matrix and suppress all values that would have appeared in the lower triangle. The cards call for X(I,J) values in the matrix, where I indicates the row number for the matrix and J indicates the column. The feed cost index has a mean of 1.0 and requires a standard deviation on the magnitude of 0.10. (I2,6X,12F6.0) Card Columns 1-2 Code the card number '79’. 3-8 Code a card name, such as ’DMATRX‘. 9-14 The X(I.I) element of the matrix. 15-20 The X(I,l+ 1) element of the matrix. 21-26 The X(I,l+2) element of the matrix. 27-32 The X(I,I+3) element of the matrix. 33-38 The X(I_I+4) element of the matrix. 39-45 The X(l,l+5) element of the matrix. 46-80 Blank. Card 80.IDAIRY -- Empirical Probability Distributions for Dairy When Option 24 is equal to 7 or 8. the analyst must provide information necessary to esti- mate l0 points on the empirical probability distribution for each of the six random variables associ- ated with the dairy operation. If Option 24 is not equal to either 7 or 8 skip Card 80. The 10 val- ues for each random variable must be expressed as fractional deviations from their respective mean (or trend) value for year 1. By providing the fractional deviations about the means for year l on Cards 61-64 and 76. the model generates an empirical cumulative distribution for each annual price and production variable with the same relative variance each year. Code six cards for Card 80 in the same order used for Card 79, i.e., milk price. cull cow price. replacement cow price, calf price, milk production, and index of feed cost. (The mean oi’ the feed cost index is 1.00.) (2I2.6X.l0F7.0) 110 Card Columns 1-2 Code the card number ’80’. 3-4 Code consecutive numbers for each card, IDAIRY, as ’01’, ’02’,... 5-10 Code a card name, such as ’DEVlAT’. 11-17 _ The first deviate from trend or mean, as -0.15. 18-24 The second deviate from trend or mean, as -0.13. 25-31 The third deviate from trend or mean, as -0.10. 32-38 The fourth deviate from trend or mean, as 0.0. 39-45 The fifth deviate from trend or mean, as 0.02. 46-52 The sixth deviate from trend or mean, as 0.04. 53-59 The seventh deviate from trend or mean, as 0.06. 60-66 The eighth deviate from trend or mean, as 0.07. 67-73 The ninth deviate from trend or mean. as 0.09. 74-80 The tenth deviate from trend or mean, as 0.10. Required Farm Policy Data Cards -- Cards P1-P41 The model is programmed to require 41 types of Farm Policy Data Cards. The analyst must provide all of the policy cards in the order indicated below for the model to operate properly. Since the model was designed to simulate a given farm under many different farm policy options, it was programmed so the analyst must provide all of the policy variables. If a particular set of policy variables are not to be used for the simulation runs planned for a particular farm. the analyst may either leave the policy values blank or turn the policy off on the Option Card, but the Policy Cards ntusz be provided. The model uses only the farm policy variables necessary to simulate the particu- lar farm policy options selected by the analyst on Card 2. Thus policy values that are not used due to the options specified on the Option Card can be left in place for subsequent analyses. Those unfamiliar with the policy variables used in the model are referred to Johnson and Erickson (1977) and by Johnson e1 al. (1982). Policy Cards P1-P24, P32-P36, P39, and P41 provide annual policy data for each of the indi- vidual crop enterprises. These data cards use the same format. The order of crop enterprises must be the same as used for Card 22. Care should be taken to enter the dollar values such as loan rates, target prices, etc., in terms of dollars per yield unit. Card PLJCROP -- CCC Loan Rates or Marketing Loan Repayment Prices CCC loan rates (S/yield unit) are used in the model as the price support level for the Com- modity Credit Corporation (CCC) loan program. When a price support is in effect. the loan rate influences the crop mix if the loan rate exceeds the expected market price. CCC loan rates are used when Option 11 is not equal to zero. If a marketing loan is in effect (Option 11 equal to 9) for a crop, the repayment price is provided on this card rather than the CCC loan rate. Marketing loan rates are entered on Card P39. Annual interest costs are computed for CCC loans based on a 9 month loan using the annual CCC interest rates provided on Card P27. If 111 a crop does not have a loan rate program or its loan program is to be phased out during the plan- ning horizon, enter zeros where loan rates do not apply. Values entered on this card are used unless the loan rate for years 2 through n are determined by the formula provided on Card P35. In that case, only the first loan rate is used in the model. Code a separate Card P1 for each crop enterprise (JCROP), being sure to keep the crop enterprises in the same order as provided on Card 22. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number, ignoring the policy indication (P) as ‘O1’. 3-4 Code the crop enterprise number used on Card 22 (JCROP), as ‘O1’, ’02’, and so on. 5-10 Code a card name, such as ’LOAN’. 11-17 Loan rate for year 1, as 3.00. 18-24 Loan rate for year 2, as 3.05. 25-31 Loan rate for year 3, as 3.10. 32-38 Loan rate for year 4, as 3.15. 39-45 Loan rate for year 5, as 3.20. 46-52 Loan rate for year 6, as 3.25. 53-59 Loan rate for year 7, as 3.25. 60-66 Loan rate for year 8, as 3.25. 67-73 Loan rate for year 9, as 3.25. 74-80 Loan rate for year 10, as 3.25. Card PZJCROP -- Target Prices Target prices (S/yield unit) are used in the model to calculate deficiency payments and disas- ter payments. In addition, when the target price program is in effect (Option 13 not equal to zero) and the crop mix is variable (Option 18 not equal to zero), the expected deficiency payment influ- ences the crop mix. Target prices provided on the P2 Card are not a function of the loan rate and are associated with the national allocation factors specified on the P6 Card. For a crop which has no target price. such as soybeans, enter zeros on its P2 Card. The values on this card are used as the target price whether there is only one deficiency payment or there are two payments (Findley). Code a separate P2 Card for each crop enterprise using the format indicated for Card P1. If the target price is a function of the loan rate (Option 13 equals 2) code the required information on Card P36. Card P3JCROP -- Direct Farmer Owned Reserve Entry Price Q When the Secretary of the USDA announces a direct farmer owned reserve (FOR) for grains. a FOR entry price, not equal to the loan rate, is usually announced. For example. the 1983 FOR entry price for wheat was 120 percent of the wheat loan rate. To analyze direct entry FOR (Index 1 l equals 4 or 5) the analyst must specify the entry price for each crop eligible for the reserve. The annual entry price must be coded as a fraction of the loan rate. i.e.. if the loan rate is $3.00 and the direct entry reserve price is $3.50. the analyst should enter the fraction 1.1666. Since fractions are 112 entered on Card P3 for each year of the planning horizon, the analyst can change the fraction over the planning horizon. Code a separate card for each crop enterprise using the format for Card P1. Card P4.JCROP -- Proven Yield Proven crop yields (yield unit/acre) are used in the model to calculate deficiency payments and disaster payments. Proven yields influence the crop mix if a crop’s expected yield is less than the proven yield and a disaster program is in effect. If a crop does not have a proven yield or the analyst wishes to exclude the crop from the disaster program, or the deficiency payment, enter zeros for its historical yield values. The model calculates annual farm program yield for each crop based on the USDA formula (average of the past 5 years ignoring the high and low). Therefore. the ana- lyst must enter values for each crop’s actual harvested yield over the past 5 years on the P4 Cards. Code a separate card for each crop enterprise using the format indicated for Card Pl. Card P5.JCROP -- Program or Base Acreage Deficiency payments are calculated using program acreage proven yield, national allocation factor, and deficiency payment rate for the particular crop. Program acreages on Card P5 are used to calculate deficiency payments unless the farm is allowed to grow or the crop mix is allowed to vary over time. In these two cases, program acreages are set equal to planted acreage for the respective crop each year. This assumes all cropland added to the farm (purchased or leased) comes with its own program or base acreage. When the crop mix is changed over time. each crop’s annual program acreage is set equal to the lesser of its annual planted acreage or its program acreage. If a crop does not have a target price, enter zeros for its annual program acreage values. Code a sepa- rate card for each crop enterprise using the format indicated for Card P1. Card P6.JCROP -- National Allocation Factor National allocation factors (fractions) are used to calculate deficiency payments. They may differ from year to year for each crop under the target price farm program. In a macro-policy model, the national allocation factor can be endogenously determined based on the formula in the current farm program. However. for a micro-policy model such as F LIPSIM, the analyst must exogenously specify the national allocation factor for each crop in each year of the planning hori- zon. The 1981 Farm Bill specified that the fraction must be less than 1.0 for cotton and between 0.8 and 1.0 for grains. The analyst must provide annual national allocation factors for each crop with a target price. If a crop does not have a target price, enter zeros for its annual national alloca- tion factor. Code a separate Card P6 for each crop enterprise using the format indicated for Card P1. Card P7.JCROP -- Acreage Set-Aside, Diversion, or Limitation The fraction of planted acreage to be set-aside. diverted, or limited (acreage limitation pro- gram) foreach crop enterprise is specified for each year of the planning horizon on the P7 Card. The model does not differentiate between required and voluntary acreage reductions; this is accom- plished by the analyst specifying diversion payment rates on Card P9. Since acreage reductions affect expected net returns per acre, these production controls influence the crop mix. if it is allowed to change over time. The effective amount of production removed by an acreage reduction program equals planted acres times yield times one minus the crops slippage rate. (Slippage is defined as the fraction of diverted production that does not get diverted because of increased use of variable inputs on land in production and the practice of removing the least productive acreage on a farm.) The annual slippage rate for each crop is provided on Card P8. If a particular crop does not have a production control program and Option l6 equals 1 or 2, enter zeros on Card P7. Code a separate card for each crop enterprise using the format for Card Pl. 113 Card PSJCROP -- Slippage Rate for Acreage Reduction Slippage is the fraction of acreage diversion or set-aside which results in no reduced produc- tion due to input substitution and the practice of diverting marginal cropland. The slippage rate for each crop may vary over time and must be entered as a fraction, as 0.40 for 40 percent slippage. Code a separate card for each crop enterprise using the format for Card P1. Card P9JCROP -- Payment Rate for Acreage Diversion The per acre payment rate for acreage diversion ($/acre) is provided on this card. If the pay- ment rate is equal to zero (or blank) and Option 16 equals 1 or 2, the model assumes the analyst has specified a mandatory acreage set-aside with no payments. Payments for acreage diversion are calculated as the product of acres idled based on Card P7 and the per acre payment rate for acreage diversion. If the crop has a mandatory set aside and a voluntary acreage diversion, the diversion payment rate entered on this card must equal the diversion payment rate per diverted acre multi- plied by the ratio of diverted acres to total acres held out of production. For example a $30 per acre diversion payment for 10 percent diversion and 20 percent set aside becomes a $10 per acre effective diversion payment rate. If a particular crop does not have a production control program, enter zeros for its annual payment rate values. Code a separate card for each crop enterprise using the format for Card P1. Card Pl0.JCROP -- Trigger Price for the FOR The farmer owned reserve (FOR) is a multiple-year reserve program which allows farmers to transfer grains from the CCC loan program to a multiple-year reserve program. The number of years interest is charged for stocks in the FOR are specified by Option 12. Annual interest rates for FOR loans are entered on Card P28. The farmer must agree to hold the grain off the market until the market price exceeds the trigger price. Once the market price exceeds the trigger price, the farmer may sell the grain and repay the original government loan against the grain. If the analyst elects to have stocks released from the FOR at the trigger price, Option 11 must equal either 2 or 4. Annual trigger prices for each crop eligible for the FOR are provided on Card P10. Trigger prices are entered in terms of their fraction of the loan rate, e.g.. if the trigger price is 140 percent of the loan rate. enter 1.40. If a crop enterprise is not eligible for the FOR, enter zeros for its trigger price fraction. Code a separate card for each crop enterprise using the format for Card P1. Card P11.JCROP -- Call Price for the FOR The 1977 Agricultural Act provides for a release price (now called a trigger price) and a call price. The option of a call price is continued in the model to allow the analyst to easily evaluate two release levels with the same data set. by merely changing the Option Card. Grains in the FOR are not required to be sold at the trigger price; however, when the market price exceeds the call price farmers are required to pay off the government loan against the grain. If the analyst assumes grains will leave the FOR only at the call price, Option 11 should be set equal to 3 or 5. and call prices should be provided on this card. Call prices are entered in terms of their fraction of the loan rate. e.g., if the call price is 160 percent of the loan rate, enter 1.60. When a crop enterprise is not eligible for the FOR, enter zeros for its call price fraction. Code a separate card for each crop enterprise using the format indicated for card P1. \ 114 Card P12.JCROP -- Storage Payments for Grains in the FOR As long as the market price for a crop remains below the trigger price, the government pro- vides an annual payment to producers holding grain in the FOR to defray storage costs. Total stor- age payments for grain in the FOR are calculated as the product of the net storage payment rate entered on this card and the quantity of grain in the FOR. Net storage payment rates (government payment rate minus farmer’s cost of storing grain) should be entered in terms of $/yield unit per year. If a crop is not eligible for the FOR, enter zeros for its net storage payment rate. Code a separate card for each crop enterprise using the format indicated for Card P1. Card P13.JCROP -- Length of the FOR The FOR has been a 3- or a 5-year reserve program; however, its length could be changed. To add flexibility to the model, the analyst must enter the number of years a .farmer may keep grain in the reserve (for example, 3.0 years). Annual values for length of the FOR are required for each crop eligible for the FOR. If a crop is not eligible for the FOR, enter zeros for the length of the reserve. Code a separate card for each crop enterprise using the format indicated for Card Pl. Card P14.JCROP -- Fraction of Target Price to Compute Low-Yield Disaster Payments Low-yield disaster payments were based on a fraction of the target price and the amount of lost yield eligible for the program. The fraction of the target price used to calculate low-yield pay- ments was 0.50 for grains and 0.33 for cotton. Enter these annual values in terms of a fraction for each of the crop enterprises eligible for the low-yield disaster payment. These values are used when Option 15 equals 2 or 3. If a crop is not eligible for the low-yield disaster payment, enter zeros for its fraction. Code a separate card for each crop enterprise using the format indicated for Card P1. Card PISJCROP -- Fraction of Target Price to Compute Prevented Plantings Disaster Payment Prevented-plantings disaster payments were based on one-third of the respective crop’s target price. The 0.33 fraction was appropriate for both cotton and grains; however. the fraction was sub- ject to change. The fractions ‘provided on this card are used when Option 15 equals 1 or 3. If a crop is not eligible for the prevented-plantings disaster payment enter zeros for its fraction. Code a separate card for each crop enterprise using the format indicated for Card P1. Card P16JCROP -- Fraction of Proven Yield to Compute Low-Yield Disaster Payments Low-yield payments were paid on that portion of the actual crop yield which is less than a specified fraction of the crop’s proven yield (Card P4). The fraction of proven yield used in the calculation for cotton was 0.75, while for grains the fraction was 0.60. Enter the annual values in terms of a fraction for each crop eligible for the low-yield disaster program. These values are used when Option 15 equals 2 or 3. If a crop is not eligible for the low-yield disaster program enter zeros for its fraction. Code a separate card for each crop enterprise using the format indicated for Card Pl. 115 Card P17.JCROP -- Fraction of Proven Yield to Compute Prevented-Plantings Disaster Payment Prevented-plantings disaster payments were paid on that portion of the actual crop yield which was less than a specified fraction of the crop’s proven yield (Card P4). For all eligible crops the fraction was 0.75. Enter the annual values in terms of a fraction for each crop eligible for the prevented-plantings disaster payment. These values are used when option 15 equals 1 or 3. When a crop is not eligible for the prevented-plantings disaster payment enter zeros for its fraction. Code a separate card for each crop enterprise using the format indicated for Card P1. Card Pl8.JCROP -- Production Guarantee for All-Risk Crop Insurance Crop insurance is available through the Federal Crop Insurance Corporation (FCIC) for all commercial crops produced in the United States. To simulate the all-risk crop (or multi-peril) insurance program, the analyst must set Option 15 equal to 4 and provide annual values for each crop’s: (a) production guarantee per acre (Card P18), (b) price election (Card P19), and (c) pre- mium rate per acre (Card P20). If the operator declines crop insurance on certain crops, enter zero for those crops not in the insurance program. Enter the annual production guarantee in terms of the number of yield units (bushels, pounds, tons, etc.) per acre. Code a separate card for each crop enterprise using the format indicated for Card P1. Card P19.JCROP -- Price Election for All-Risk Crop Insurance When Option 15 equals 4, enter annual price election values for each crop enterprise to be insured. The price election level should be entered in terms of S/yield unit. If a crop is not insured enter zero for its price election values. Code a separate card for each crop enterprise using the for- mat indicated for Card P1. Card PZOJCROP -- Premium Rate for All-Risk Crop Insurance The annual premium rate per acre must be entered for each crop under the all-risk insurance program. The analyst must provide the total per acre premium because the model automatically reduces the operator's premium for the landownei-‘s share on rented cropland. It is assumed the landowner pays crop insurance premiums in proportion to his share of the crop. Enter the annual premium rate in terms of iii/acre. If a crop is not insured or the program has a 100 percent subsidy, enter zeros for the per acre premium rate. Code a separate card for each crop enterprise using the format indicated for Card P1. Card PZLJCROP -- Loan Rate for Crops Under Quota When a marketing quota is in effect (Option 19 equal to l) there are two separate price sup- port levels. One price support level is available for that portion of the crop produced under the quota. A slightly lower support level is available for that portion of the crop not produced under a quota. When simulating a marketing quota, enter zeros for the quota crops loan rate on Card Pl and enter the loan rate for that portion of the crop produced under quota on this card. The quota loan rate must be entered in terms of $/yield unit specified on Card P23. Enter zeros for the loan rate values on this card if the quota does not apply to the particular crop. Code a separate card for each crop enterprise using the format indicated for Card P1: 116 ,+..i.m.z.iu Card P22.JCROP -- Loan Rate for Crops Not Under Quota Enter the loan rate for that portion of the crop not produced under a quota in terms of $/yield unit. Enter zeros for the loan rate valuesion this card if the marketing quota does not apply to the particular crop. Code a separate card for each crop enterprise using the format indicated for Card P1. Card P23.JCROP -- Quota The annual quota for crops subject to the quota is provided in terms of yield units per base or allotted acre on this card, e.g., 30.0 bushels per acre for quota when normal yield is 45 bushels per acre. The quota is used when Option 19 equals 1. If the crop is not subject to a quota enter zeros for the quota. Code a separate card for each crop enterprise using the format indicated for Card P1. Card P24.JCROP -- Acreage Allotment When Option 2O equals 1. annual acreage allotment values for the crop subject to the allot- ment must be provided on this card. The model assumes crops with an acreage allotment are eligi- ble for other farm programs (loan, target price, etc.) only on that proportion of the crop produced on the allotted acreage. The model is programmed so allotments set equal to zero are disregarded. This allows the analyst to simulate, say, a rice farm with an allotment on rice but no allotment pro- gram for other crops such as grain sorghum or soybeans. Allotments are entered in terms of acre- ages. If a particular crop does not have an acreage allotment enter zeros. Code a separate card for each crop enterprise using the format indicated for Card P1. Card P25 -- Payment Limitations for Deficiency and Diversion Payments When Option 18 equals 1 or 3 a payment limitation on deficiency and diversion payments is in effect. The payment limitation can be varied from year to year but it is in no way connected to size of farm or value of sales. Code one payment limitation card as indicated below. (2I2.6X,10F7.0) Card Columns 1-2 Code the card number ’25’. 3-4 Blank. 5-10 Code a card name, such as ‘PAYLIM’. 11-17 Payment limitation in year 1, as 50000.0. 18-24 Payment limitation in year 2. as 50000.0. 25-31 Payment limitation in year 3, as 50000.0. 32-38 Payment limitation in year 4. as 60000.0. 39-45 Payment limitation in year 5. as 60000.0. 46-52 Payment limitation in year 6. as 60000.0. 53-59 Payment limitation in year 7. as 60000.0. 60-66 Payment limitation in year S. as 60000.0. 117 67-73 Payment limitation in year 9, as 60000.0. 74-80 Payment limitation in year I0, as 70000.0. Card P26 -- Payment Limitation for Disaster Payments If the analyst specifies a payment limitation on disaster payments (Option 18 equal to 2 or 3) the annual payment limit must be entered on this card. The payment limitation can be changed from year to year or it can be made ineffective in particular years by setting it to a high level. Code one payment limitation card using the format for Card P25. Card P27 -- Annual Interest Rate for CCC Loans Loans for stocks in the Commodity Credit Corporation (CCC) loan program are assessed an annual interest charge. When Option 11 equals 1. 2, 3, 6, 7, or 8, the model uses the annual inter- est rate for CCC loans provided on this card to calculate the CCC interest charge. Annual interest rates for FOR loans are entered on Card P28. Since CCC loans are held for 9 to 12 months, the model computes a farmer’s interest cost assuming the loan is for 9 months. Code the annual inter- est rate card using the format specified for Card P25. Card P28 -- Annual Interest Rate for FOR Loans Loans for stocks in the farmer owned reserve (FOR) may be assessed an annual interest charge. When Option 11 equals 4 or 5. the model uses the annual interest rates on this card to compute interest charges for a FOR loan. Option 12 specifies the number of years for which annual interest payments are made on a FOR loan. Code the annual interest rate card using the format for Card P25. Card P29 -- Storage Cost for the CCC Loan Farmers are responsible for paying storage costs of stocks in the CCC loan program. When Option 11 equals 1, 2, 3, 6, 7, 8, or 9 the model calculates annual storage costs for stocks in the CCC loan, using the off-farm storage cost values provided on this card. Since the loans are gener- ally held for 6 to 12 months, the model computes storage costs assuming the loan is held for 9 months. Storage costs are inflated annually using annual inflation rates provided on Card 20. If the stock is stored on the farm, enter only the additional costs incurred. Storage costs must be entered in terms of S/yield unit per year. Code the storage cost card as indicated below. (2l2,6X,10F7.0) Card Columns 1-2 Code the card number ‘29’. 3-4 Blank. 5-10 Code a card name, such as ‘CCCSTG’. 11-17 Annual storage cost for crop 1, as .025. 18-24 Annual storage cost for crop 2, as .025. 25-31 Annual storage cost for crop 3, as 0.40. 32-38 Annual storage cost for crop 4, as 0.40. 39-45 Annual storage cost for crop 5, as 0.30. 118 46-52 Annual storage cost for crop 6, as 0.30. 53-59 Annual storage cost for crop 7, as 0.40. 60-66 Annual storage cost for crop 8, as 0.40. 67-73 Annual storage cost for crop 9, as 0.40. 74-80 Annual storage cost for crop 10, as 0.40. Card P30 -- Farm Program Benefits Scaled to Farm Size Direct farm program benefits can be scaled to farm size a number of ways. Option 28 pro- vides two ways to scale farm program benefits, so they accrue only to farms less than a specified size. Farms that are smaller than the size limits imposed on this card are eligible to participate in the farm programs the analyst has selected. However, once the farm grows larger than the specified size, it is no longer eligible to participate in farm programs. For farms larger than the specified size no farm program benefits are provided. The farm program benefit card is coded as follows. (2I2,6X,10F7.0) Card Columns 1-2 Code the card number ’30’. 3-4 Blank. 5-10 Code a card name, such as ’SCALE’. 11-17 The farm size in acres at which the farm is no longer eligible to participate in any farm programs, as 960.0 acres. This value is used only if Option 28 equals l. 18-24 The farm size in acres at which the farm is no longer eligible for target price, loan rate, disaster, set-aside, and FOR programs, as 960.0 acres. The farm is eligible to participate in the all-risk crop insurance program, i.e., Option 28 equals 2. 25-31 The value of crop sales in dollars at which the farm is no longer eligible to participate in any farm programs, as l00000.0. This value is used only if Option 28 equals 3. 32-38 The value of crop sales in dollars at which the farm is no longer eligible to participate in target price, loan rate, disaster. set-aside, and FOR pro- grams. as l00000.0. The farm is eligible to participate in the all-risk crop insurance program, i.e., Option 28 equals 4. 39-80 Blank. Card P31 -- Previous History for All-Risk Crop Insurance The farm's previous history in the all-risk crop insurance program must be entered so the premium can be adjusted over time. The law provides for a mechanism to reduce the instirance premiums if experience shows the farm is a low risk. The same mechanism increases premiums if the farm is a high risk. Code Card P31 as indicated below. (2I2.6X.l0F7.0) 119 Card Columns 1-2 Code the card number ’31’. 3-4 Blank. 5-10 Code a card name, such as ’FCICH’. 11-17 The number of years the farm has participated in the FCIC all-risk crop insurance program, as ’3.0’. 18-24 The number of years that the farm has experienced a loss where the indemnity received exceeds premiums paid, as ’1.0’. 25-31 Total FCIC insurance premiums paid by the farm during the time it par- ticipated in the program, as ’8500.0’. 32-38 Total FCIC indemnity payments received by the farm during the time it participated in the program, as ’1500.0’. 39-80 Blank. Card P32JCROP -- Marketing Certificate Price The marketing certificate proposed in the 1985 farm bill works through the CCC price sup- port program. If this type of farm program is to be simulated (Option 14 equal to 1). the analyst must provide annual marketing certificate support prices for the eligible crops on this card. Those crops not eligible for the marketing certificate should have zero values for their marketing certifi- cate prices. If the CCC nonrecourse loan is available for the other crops on the farm, set Option l1 equal to 1 and enter CCC loan rates for the eligible crops on Card P1. Code a separate card for each crop enterprise using the format indicated for Card P1. Card P33.JCROP -- Fraction of Crop Eligible for a Certificate Marketing certificates can be available for all or part of a farm operator’s eligible production. Eligible production is defined as the quantity normally produced on eligible acreage, i.e.. farm pro- gram yield times base acreage times one minus the fraction of cropland to set aside times the frac- tion of the crop eligible for a certificate. This latter value can represent the domestic share of a producer’s crop or some other fraction. Enter a separate value for each year of the planning hori- zon for each crop enterprise eligible for marketing certificates. Code a separate card for each crop enterprise using the format indicated for Card P1. Card P34.JCROP -- Maximum Nonrecourse Loan A maximum limit on the CCC nonrecourse loan for each crop can be entered on Card P34. The maximum dollar value of the nonrecourse CCC loan may change from year to year and may differ from one crop to the next. These values are used by the model if Index ll equals 6 or 7. Code a separate card for each crop enterprise using the format indicated for Card Pl. Card P35.JCROP -- Flexible Loan Rate Formulas Option 47 allows the analyst to use loan rates for the individual crops calculated using the analyst's moving average formula of historical crop prices. The information necessary to specify the loan rate formula for each crop and each crop’s historical prices are entered on Card P35. A sepa- rate card is provided for each crop to allow the analyst to experiment with different formulas for 120 each crop. The model assumes the loan rate will equal some fraction of the 2-, 3-, 4-, or 5-year moving average of past prices. A different number of years of past prices may be used (2 to 5) in calculating the loan rate. Additionally, the high and/or low price(s) can be deleted from the moving average calculation. The loan rate for the first year of the planning horizon must be provided by the analyst on Card P1 for each crop. The model begins calculating loan rates in year 2. based on the observed price in year l and the historical prices provided by the analyst on this card. If a par- ticular crop does not have a flexible loan rate, enter zeros for Card Columns 11-80 on Card P35 and the fixed loan rates on Card P1. Code a separate Card P35 for each crop as follows. Card Columns 1-2 Code the card number, ignoring the policy indication (P), as ’35’. 3-4 Code the crop enterprise number used on Card 22 (JCROP), as ’01', ’02’, ..., and so on. 5-10 Code a card name, such as ’FLEXLN’. 11-17 The maximum number of historical prices to use in calculating the moving average, as ’2.0’, ’3.0’, ’4.0’, or ’05’. Enter a ’0.0’ if the crop has no loan rate or the loan rates on Card P1 are to be used for all years of the plan- ning horizon for the particular crop. 18-24 A code to delete the minimum price in calculating the moving average, enter ’0.0’ to not delete the minimum and enter ’1.0’ to delete the mini- mum. 25-31 A code to delete the maximum price in calculating the moving average, enter ’0.0' to not delete the maximum and enter ’1.0’ to delete the maxi- mum. 32-38 Fraction of the moving average to use in calculating the loan rate, such as ’O.75’ or ’1.0’. 39-45 Maximum fraction that the loan rate may decline each year, such as ’0.05‘. 46-52 Minimum loan rate, such as ’0.50' for cotton. 53-59 Historical market price for year t-4, as ‘0.50'. 60-66 Historical market price for year t-3, as ’0.48'. 67-73 Historical market price for year t-Z. as ’0.60'. 74-80 Historical market price for year t-1, as ’0.70’. Card P36.JCROP -- Target Prices Tied to Loan Rates Annual target prices can be tied to the loan rate by setting Option 13 equal to 2 and provid- ing the appropriate values on this card. Enter the annual ratios of target price to loan rate for each crop enterprise, such as, 1.33, 1.20. 1.15. 1.10, 1.06. 1.0, 1.0, etc. If the loan rate equals 85 percent of a 5-year moving average and the target price is supposed to equal 110 percent of this same mov- ing average. enter 1.294 for the values on this card. If a crop has a loan rate but no target price. such as soybeans. enter 0.0 for each year. Code a separate card for each crop enterprise whether it has a target price or not. using the format indicated for Card P1. 121 Card P37 -- Fraction of Base Production Eligible for Deficiency Payments To simulate a farm program which limits deficiency payments through a fraction of base production (Option 18 equals 4), enter the appropriate fraction for each year on Card P37. For example, if deficiency payments are paid on 50 percent of the base production for the first $200,000 of commodity crops produced, enter 0.50 for each year of the planning horizon. The value of base production eligible for deficiency payments is entered on Card P38. Code only one Card P37 using the format for Card P25. Card P38 -- Value of Base Production Eligible for Deficiency Payments When deficiency payments are paid on only a fraction of base production, say, $200,000 of commodity crops produced (Option 18 equals 4) the trigger level is entered on this card. The trig- ger level can change from year-to-year so the analyst must provide a separate value for each year of the planning horizon when the option is elected. This value is used with the fraction of base pro- duction eligible for deficiency payments, entered on Card P37. Code only one Card P38 using the format for Card P25. Card P39JCROP -- Marketing Loan Rate The marketing loan is a new concept in the 1985 farm bill. The marketing loan does away with the CCC loan program and replaces it with an effective government payment based on the dif- ference between the average market price and the marketing loan rate. This price difference is paid on actual production which is generally less than the maximum eligible production. To use the marketing loan concept in the model, set Option 11 equal to 9, enter annual marketing loan rates for each crop on Card P39. and enter the marketing loan repayment price on Card P1. If loan rates are flexible (option 47 equals 1), the marketing loan is automatically adjusted to maintain its rela- tionship to the repayment price (CCC loan) in year 1. Code a separate Card P39 for each crop using the format indicated for Card P1. Card P40 -- Gramm-Rudman Reductions in Government Payments The annual fractional reduction in deficiency, Findley, and diversion payments under the Gramm-Rudman Act are entered on this card. Enter only one card and enter the values as frac- tions, such as: 0.043, 0.10, 0.12, 0.15, 0.0, etc. Use the format for Card Pl to enter a separate frac- tion for each year of the planning horizon. Card P41.JCROP -- Formula Loan Rate for Findley Payment The 1985 farm bill includes a second deficiency (Findley) payment not subject to the $50,000 payment limit. The original deficiency payment is paid on the difference between the target price and the greater of the market price or the loan rate. The Findley payment is paid only if the Secre- tary of Agriculture adjusts the loan rate below the formula (or base) loan rate and market price falls below the formula loan rate. If this option is selected (Option 13 equals 3), the model: (a) calcu- lates the original deficiency payment based on the target price and the greater of the formula loan rate entered on this card or the market price and (b) calculates the second deficiency payment. if applicable, based on the difference between the formula loan rate entered on this card and the greater of the market price or the CCC loan rate on Card Pl. The second deficiency payment is not subject to the payment limitation entered on Card P25. Formula loan rates for each year of the planning horizon must be entered on Card P41 and a separate Card P41 is required for each crop. lf a crop is not eligible for the second deficiency payment. enter zero’s on this card. Values on this card are not recomputed annually. if loan rates are allowed to vary over time. Code a separate card for each crop enterprise using the format for Card Pl. 122 Appendix B: Sample Set of Input Data This appendix includes a listing of the input lines (cards) for one FLIPSIM data set. The data set contains the information to simulate three farms. The first farm is a Texas High Plains cotton farm, the second farm is a dairy farm in Minnesota, and the third farm is a West Texas cow/calf ranch. 123 0003 3904AFS1ZES1-1P0 0.0 0 0 0 0 0.0 0 0 0.0 0.0 NO 1 40% DESTIASSET INTBASE (S1) CURRENT BILL 3901AFSlZESHF8 00 90 14 07 214 29.65 2.39 0.00 .1237 1000 ACRE COTTON FARM IN THE SOUTHERN HIGH PLAINS 3902AFSIZESHPB 575 9.04 104 0.02 0.57 0.00 .1237 DATA FOR AN ANALYSIS OF THE 1005 FARM 0lLL 3903AFS1ZESHP9 00 0.0 00 0.0 0.0 0.0 0.0 INTBASE 1S1) DATA SET OF COMGEM RESULTS 3004AFSIZESHP9 00 00 00 00 0.0 0.0 0.0 CURRENT FARM PROGRAM INFORMATION 1S THE BASE DATA 3901AFSlZESHPO 00.90 14.07 214 00.65 239 0.00 .1237 206 00030317 4 0 0 33 1 I 1 1 I I 1 1 6 0 1 0 1 11003 0 1 1 0 0 0 0 0 0100010010 3902AFS|ZESH90 575 0.04 104 0.02 0.57 0.00 .1237 03 ACRES 301.0 707.0 0.0 0.0 1.0 0.0 00.32 3903AFSlZESH10 0 0 0.0 0 0 00 00 0.0 0.0 04 ASSETS191262.00 00000.0 00000.0 00000.0 0000 0.0 0 0 3904AFSIZESH10 0.0 0.0 0 0 0.0 0.0 0.0 0.0 05 DEPREC000.00 51294.0 20 0 0.0 0 0 0.0 0.0 4001AFSlZESHP5 422.73 401.59 0.0 0.33 0.95 06 LTDEOT04000000 30.0 00000000 0.30 4002AFS1ZESHP5 050.27 763.06 0.0 1.0 009 07 lTDEOT0.4000000 6.0 00000000 0.35 0.750 4003AFSIZESHP5 422.73 401.59 00 0.33 1.0 0.95 00 NEWLON300 60 0.30 0.25 4004AFSlZESNP5 050.27 763.06 0.0 10 2.0 0.09 00 REFINC0.01 20.0 4.0 4001AFS1ZESHF6 540.30 51320 0.0 0.30 005 10 TAXES 001000 0.0 0.0 4.0 0.0 0.20 ‘10466240710300230 4002AFSIZESHP6 12604011214000 1.0 0.09 11 SELFRTO.1235 0.1300 0.1300 0.1300 0.130 0.1300 0.1300 01300 0.1300 0.1300 4003AFSlZESHP6 540.30 513.20 0.0 0.3 1.0 095 12 SELFIN 36000.36000036000.036000.036000.036000036000036000 0360000360000 4004AFSlZESHP6 12604011214000 1.0 2.0 0.09 13 OVCOST1000.0 0.0 2176.0 1000.0 1500 3000 -.03 -0.01 7400. 4001AFS1ZESHP7 644.23 612.01 00 0.23 005 14 FAMILY 42.0 16000. 0.0000 19050 13.0 15200.0 50000. 15200 0.25 25000.0 4002AFS1ZESHF7 2156.771919.520.0 1.0 0.09 15 FLA0113.0 120.0 90.0 130.0 160.0 160.0 200.0 650 65.0 65.0 200.0 200.0 4003AFSlZESHP7 644.23 612.01 0.0 0.23 1.0 0.95 16 HLA0150.0 200.0 130.0 1730 260.0 260.0 320.0 65.0 165.0 65.0 300.0 300.0 4004AFSIZESHP7 21567719195200 10 2.0 0.09 17 HLABOR 12627. 0.0 3.75 0.0600 0 10 4001AFSIZESNPO 07423003052000 0.23 0.95 10 CLEASE 4002AFSlZES1-1F0 2026 7726040300 1.0 0.09 1901|NFLAA00000 0.020 00.02 0.020 0.020 0.020 0020 0.020 0.020 0.020 4003AFSlZESHPO 07423003052000 0.23 1.0 0.95 19021NFLAA-.022 0.025 0.025 0.003 0.031 0.100 0.100 0.010 0.003 0.003 4004AFS|ZESHPO 2926.772604.0300 1.0 20 0.09 19031NFLAA-.047 0.001 0.001 0001 -.023 -.041 -.041 0.000 0.001 0.001 4001AFSlZESHP9 11032010401200 0.23 0.95 19041NFLAA-.057 0.004 0.004 0.000 0.010 -.057 -.057 -.010 0.000 0.000 4002AFSlZESHF9 36977232909700 10 0.09 1905lNFLAA-.000 0.000 0.000 -.011 0.052 r044 -.044 - 010 -.01I ~.011 4003AF5IZESHP9 1103201040 120.0 0.23 1.0 0.95 1906lNFLAA-.092 0.006 0 006 -.015 0.046 -.025 -.025 2020 - 015 -.015 4004AFS|ZESHP9 3697.723200.970 0 1.0 2.0 0.09 2001INFLA00.020 0.020 0.020 0.020 0.020 0.020 317.60 00 0.0 4001AFS1ZESH10 1334 231267.520.0 0.23 0.95 2002lNFLA00.003 0.003 0.000 0.015 0.003 0.000 323.10 0 0 0.0 4002AFSIZESH10 4466 773075.420.0 1.0 0.09 2003lNFLA00001 0.001 0.000 2007 0.001 0.000 323.20 0.0 0.0 4003AFSIZESH10 1334.231267.520.0 0.23 1.0 095 2004INFLA00.000 0.000 0.000 ~ 005 0.000 0.000 323.60 0.0 0.0 4004AFSIZESH10 4466773975 420.0 1.0 20 0.09 2005lNFLAO-.011 -.011 0000 0.002 ~.011 0.000 323.00 0.0 0.0 4101F4C50.64 0.52 0.13 0.46 0.59 0.61 171 0.13 0.13 013 004 1.06 2006INFLAO-.015 -.015 0.000 0004 -.015 0.000 323.70 0.0 00 4102F4C50 09 0.40 0.23 0.09 0.34 019 074 0.00 0.09 0.00 0.54 0.93 21011NTERE011I 0.115 0111 01150 0.1110 01150 0.1110 01110 0.0010 4103F4C50.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2102lNTEREO 105 0105 0.105 01050 0.1050 01050 01050 0.1050 0.0050 4104F4C5000 000 000 000 0.00 0.00 0.00 000 0.00 0.00 0.00 0.00 2103INTERE0.095 0009 0.095 0.0097 0.0950 00090 0.0950 0.0950 0.0750 410171406067 0.55 013 0.49 063 0.65 1.01 0.13 0.13 013 1.00 1.13 2104INTERE00950 0.009 0.0050 0.0090 0.0950 0.0090 00950 0.0950 0.0750 4102F4C6009 051 0.25 0.09 0.36 0.21 0.70 0.00 0.09 0.00 0.57 0.99 21051NTERE0094 0.000 0.094 0.0000 0.0940 00000 0.0940 00940 0.0740 4103F4C60.00 0.00 0.00 0.00 000 0.00 0.00 000 0.00 0.00 0.00 0.00 21061NTERE0.094 0.000 0094 0.0000 0.0940 00000 0.0040 0.0940 0.0740 4105406000 0.00 0.00 0.00 0.00 0.00 000 0.00 0.00 0.00 000 0.00 2201COTTON IRRIG 00.56 14.07 15 72 33 99 00.72 0.00 0.1237 4101F4C70.57 0.47 0.10 041 054 0.55 1.56 0.10 010 010 0.05 097 2202COTTON DRLND 5.55 9.040 14.93 11.04 04.30 0.00 01237 4102F4C7007 0.44 0.22 0.07 0.31 010 0.60 0.00 0.07 0.00 0.50 0.05 2203CTSEED IRRIG 00 0.0 0.0 0.0 00 00 00 4103F4C70.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2204CTSEED DRLND 0.0 00 0.0 0.0 0.0 0.0 0.0 4104F4C70 00 0.00 0.00 000 0.00 0.00 000 0.00 0.00 000 0.00 0.00 2301COTTON 111010 340.16 330.75 0.0 0.32 095 4101F7C90 57 0.46 011 040 0.53 055 1.52 0.11 011 011 0.04 0.95 2302COTTON DRLND 739.04 650.46 0.0 1.0 0.09 4102F7C90 07 0.43 021 0.07 031 017 0.66 0.00 0.07 000 0.40 0.03 23030TSEEO IRRIG 340.16 330 75 00 0.32 1.0 095 4103F7C90.00 0.00 000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 000 0.00 2304CTSEED DRLND 739.04 650 46 0.0 1.0 20 0.09 4104F7C90.00 0.00 000 0.00 000 0.00 0.00 0.00 0.00 000 0.00 0.00 2401LA000.65 0.53 0.13 047 0.61 0.63 1.74 0.13 0.13 0.13 0.96 1.00 4101F7100.57 0.46 0.11 0.40 0.53 0.55 1.52 0.11 0.11 0.11 0.04 0.95 2402LAOC0.09 0.49 0.24 0.09 0.35 0.20 0.75 0.00 0.09 0.00 055 095 4102F7100 07 0.43 0.21 007 0.31 017 0.66 000 007 0.00 040 0.03 2403LABC0.00 0.00 0.00 000 0.00 0.00 0.00 0.00 0.00 000 0.00 0.00 4103F7100.00 0.00 0.00 0.00 0.00 000 0.00 0.00 000 000 0.00 000 2404LAOC0.00 0.00 0.00 0.00 000 000 000 0.00 0.00 0.00 0.00 000 4104F7100.00 0.00 0.00 000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 000 2501V1ELDS4104 4104 410.4 417.2 424.2 4309 4309 4101F5C00.57 0.46 0.11 0.40 0.53 0.55 1.52 011 011 0.11 0.04 0.95 2502VIELOS100.4 1004 1004 1915 194.7 197.9 197.9 4102F5C00.07 0.43 0.21 0.07 0.31 017 0.66 0.00 0.07 0.00 0.40 0.03 2503VlELDSO.320 0.320 0.320 0.333 0.329 0.345 0345 4103F5C00.00 0.00 0.00 000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 000 2504VlELDSO.152 0 152 0152 0.153 0.156 0.150 0150 4104F6C0000 0.00 000 000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2601FR1CESO.400 0.410 0.4200 0.4400 0.450 0.500 4201VD5 2602PRICESO 400 0.410 0.4200 04400 0.450 0.500 4202VO5 2603P0|CES10500 105.00 105.00 105.00 105.00 105.0 4203VO5 2604PR1CES105.00 105.00 10500 10500 105.00 105.0 4204VD5 2701MATR1X0.7394 0.5666 0.000 0.000 0.0000 0.2603 0000 -0.2455 4201VD6 2702MATR1X0 7550 0.000 0.000 0.000 0.2402 0.000 -0 6101 4202VD6 2703MATR1X07667 0.6420 0.000 0000 0.000 0.000 4203VD6 2704MAT0lX1.0000 0.000 0.000 0000 0.000 4204VD6 2705MATRIX0000 0.0030 0.000 0.4694 4201YO7 2706MATR1X0.0030 0.000 0.4694 4202VD7 2707MATO|X0 000 1.00000 4203YD7 2700MA7R1X1.00000 4204VO7 20011NDX1.0040102731020010101099510 99030951600566090001.00161015310214 4201VD9 2002lNDX1.00401.02731.020010101099510 99030955005660.90001.00161.01531.0214 4202VDO 20031NDX1.00001.00001.00001.0000 I.00001.00001.000010000100001 00001000010000 4203YD9 2004INDX1.000010000100001 00001.00001.00001000010000100001.00001.00001.0000 4204VD9 2901MKTGS 0000 0 0000 12 0 1 0 4201Y10 2902MIOO _g(>5 0. 1987 1988 1989 1990 97834.4 115804.9 115509.4 115289. 0.0 0.0 0.0 0 0.0 0.0 0.0 0 37924.0 41180.2 42585.8 45408 24974.3 2250.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 150732.7 150245.7 151195.2 15259 95355.4 98550.5 101555.7 104758. 12492.8 13542.1 14815.3 15970. 0.0 0.0 0.0 0.0 0.0 0.0 1972.1 1912.9 1835.4 1744. 4971.1 5189.8 5413.0 5540. 4589.9 3320.4 3554.5 4109. 13038.8 12972.4 11412.5 9250. 10595.1 11527.8 12555.3 9327. 0.0 0.0 0.0 0 0.0 0.0 0.0 0.0 0.0 0.0 0 143015.0 147115.7 151354 S 150820. 17715.7 13130.0 9841.7 11877. "35134.5 '30422.4 '30270 0 '30479 0.0 0.0 0.0 0.0 0.0 0 O O 0 0.0 0.0 0.0 0.0 0.0 -35134.5 -30422 5 '30270.0 -3047 *17418.0 '17292 4 '20425 3 '18502 0.0 0.0 0.0 0.0 0.0 0.0 0 0 0.0 0.0 0.0 0.0 0.0 1987 1988 1985 1990 17498 5 18213.8 18932 9 19642. 5133 1 5245.4 5704 9 5002 0 0 C 0 0.0 0 0.0 0.0 0.0 0 22531.7 23460 2 24537 8 25644. 15545.3 17380.1 18127.0 18885 398.0 127.7 0.0 0 510 5 0.0 0.0 O 17553.5 17507.5 18127.0 18885 25432.7 -7025.2 -8431 5 -11213. '5579 3 -5858.3 -5741.2 -5525. 2109.8 2110.9 2153 7 2194 '8902.2 -10773.7 -12019 1 ~14545 127 7 C.0 0.0 2 0 0 0.0 0 C 0.0 0.0 O 0 0.0 0.0 0.0 5213 7 5157 8 4209.5 7042 31445.2 25815.5 22450 A 22875. 41034.2 0.0 0.0 74013 O 0 0.0 0.0 1987 1988 1985 1990 0 O 2488.7 O C 1912. Q Qaxzxxznxxx Q Qxzzsxxax C 0 0.0 0 C 0 0.€ 0.0 C.C 1259 3 0.0 0 0 1383 127 7 0.0 0.0 29 0 C 0.0 0 C C 0.0 0.0 ‘0.0 0 127.7 0.0 0.0 25 WAS NOT T0 THE OPERATOR"S BENEEIT TO 138 J66-‘M OOIDO OO()N NO1Jw N 0(\n -(10 ~m USE INCOME AVERAGINC CASHFLOW STATEMENT FOR ITERATION DCOTTM.POM NO.1 YEARS 1985 1 1990 INNING CASH ON HAND S T CASH FARM INCOME TAL OFF-FARM INCOME .LE OF CAPITAL GAIN ITEMS .SI5 IN FARMLANO SOLO WS: \WNPAYMENT ' MACHINE REPLACE \WNPAYMENT - GREEOING STOCK \WNPAYMENT ' MACHINERY GROWT \WNPAYMENT ' FARMLAND BOUGHT INCIPAL PAID LONG'TERM DEBT lINCIPAL PAID INTR-TERM OEOT \RCHASE OF LEASEO MACHINERY 1MILY LIYINO EXPENSES RSONAL INCOME TAX PAYMENTS LF EMPLOYMENT TAX PAYMENTS \ING CASH IOEFORE OORROWINGI CASH DEFICIT REFINANCEG OR IVERED 91 SELLING FARMLAND CROPS IN COMMERCIAL STORAG PING CASH (AFTER OORROWING t SELLING CROPLAND 0R ITENSION OF CROP LOANI CURRENT MARKET VALUE BALANCE SHEET ECOTTM POM NO 1 1 IN YEARS 1985 - 1990 1088 ACRE COTTON FARM IN THE SOUTHERN HIGH PLAINS DATA FOR AN ANALYSIS OF THE BASELINE MACRO OF MODERATE DEFICITS AND MONEY GROWTH MARKETING LOAN FOR COTTON; MODERATE DEBT FOR A PART OWNER 15700. 0 30941. 21285. 0. 0. OQJOO OOlDNOlflWO()OO OOIfl¢ 9085. 28333. 19007. 0 3800. 8700. 8700.0 1088 ACRE COTTON FARM DATA FOR AN ANALYSIS OF THE BASELINE MACRO OF MODERATE DEFICITS AND MONEY GROWTH MARKETING LOAN FOR COTTON. MODERATE DEBT FOR A PART OWNER YEARS 1985 - 1990 IETS IASH ON HAND AT END OF YEAR IROPS HELD FOR SALE IROPS UNOER CCC LOAN IROPS IN FARMER HELC RESERVE .IYESTOCI HELO FOR IREEDING .IVESTOCK HELD FOR SALE IEAD ESTATE {ARM MACHINERY )FF'FARV INVESTMENTS TOTAL: IBILITEES: .ONG TERM INTERMEDIATE TERM CROPS UNDER CCC LOAN CROPS IN FARMER HELD RESERVE ACCRUEO FEDERAL, I STATE ACCRUEO SELF EMPLOYMENT TAX CONTINGENT CAPITAL GAINS TAX CONTINGENT DEPREC RECAP TAX TOTAL = T WORTH ADJUSTED FOR NREALIZEO CAPITAL GAINS. EPREC 8 CONTINGENT LIA5 T WORTH UNADJUSTED FOR APITAL GAINS RCENTAGE CHANGE IN OJUSTEO NET WORTH IT TC ASSETS RATIC HG-TERM EOUIT“ RATIO TERMEO-TERN EOUITY RATIC ERALL EOLITY TC ASSETZ RATIC VERAGE RATIC [DEBT TD EOUITV IT SERVICE COVERAGE RATIO RNED EOUITY GROWTH TREND LLATERAL RATIO TAL LOAN RATING SCORE TER-TAX NET PRESENT VALUE FDR THE PERIOD 1985 OO(3OO bOb()OOO(JO0 184785. 209555 43805. 845947 H 4 0 mOIDO<>OOoo1>o LL00}:- O0<>0 Oocnm 1588 180.2 147.1 13 | 13 23. B3 25 ~1 I-I-IIIODOIU\-D 47. 158. 317 515. ZS. 78. -0. 105. A10. JOOJUJ-m .205 .255 S48 .088 545 .000 M00000 40100 _Q(3n 0.002 -0.050 141 OIDOO O0 hb IN THE SOUTHERN HIGH PLAINS USING COMSEM DATA FOR 1585-1891 PAYMENT 1955 h O h on -O~Jhu\uu ISO 343. 504 2!. S0. -0. S9. 41‘ muomq-mnn .177 .215 .857 O52 .505 M00000 ~00!) LIOOO O(>OO 00a: 1550 152 150 '1. IJIQE] 10 25 67 21. 1!. (‘DIDGIIJGDOIIIDQ 40 ~l 145. 355 502 28 A1 55 435. l-lhOOD-JJO 135 15$ B47 052 ASE 750 NOOOOO 51 70 n0\0m 29B. -0.010 -C.070 STATISTICAL ANALYSIS OF S0 ITERATIONS FARM NO. 1 PAGE NO. 100 OCOTTM.POM NO.1 1086 ACRE COTTON FARM IN THE SOUTHERN HIGH PLAINS DATA FOR AN ANALYSIS OF THE 1965 FARM BILL USING COMGEM DATA FOR 1986-1991 IASELINE MACRO OF MODERATE DEFICITS AND MONEY GROWTH MARKETING LOAN FOR COTTON; AND CONVENTIONA TARGET PRICE/DEFICIENCY PAYMENT MODERATE DEBT FOR A PART OWNER THE FARM HAS A 58.00 PERCENT CHANCE OF SURVIVING AND A 36.00 PERCENT PROBABILITY OF AN ECONOMIC SUCESS THE FARM OPERATOR REMAINED IN OPERATION AN AVERAGE‘ OF 6.000 YEARS 2 THE FARM OPERATORS AFTER TAX NET PRESENT VALUE FOR ALL ITERATIDNS MEAN = -2s:12.3ooa STD. DEV. = 53735.1675 COEF. VAR. = -356.4346 MINIMUM = -241356.052 MAXIMUM = 165214.625 3 FARM OPERATORS PRESENT VALUE OF ENDING NET WORTH FOR ALL IERATIONS MEAN = 249057.612 STD. DEV. = 82081.S875 COEF VAR. = 32.5559 MINIMUM = 31025.5531 MAXIMUM = 392411 312 4 TOTAL DEBT AT THE END OF THE LAST YEAR FOR ALL ITERATIONS MEAN = 203727 587 STD. DEV. = 9534A.1B75 COEF VAR = 47.2907 MINIMUM = 21429.0586 MAXIMUM = 445022.500 5 ACRES OWNED AT END OF LAST YEAR SIMULATED FDR ALL ITERATIONS MEAN = l68.2000 STD DEV. = 36.0716 COEF VAR. = 19.2035 MINIMUM = 361.0000 MAXIMUM = 701 0000 6 ACRES LEASEC AT END OF LAST YEAR SIMULATED FOR ALL ITERATIONS MEAN = 873.3999 STD DEV = 151.4752 COEF VAR = 17 3436 MINIMUM = 707.0000 MAXIMUM : 1187.0000 7 ACRES CONTROLLED AT END OF LAST YEAR SIMULATED FOR ALL ITERATIONS MEAN : 1321.S999 STD DEV : 174 7039 COEF VAR : 13.2191 MINIMUM : 1088 0000 MAXIMUM = 1728.0000 6 MARKET VALUE OF REAL ESTATE OWNED AT END OF LAST SOLVENT YEAR FOR ALL ITERATIONS MEAN = 176507.812 STD DEV = 38662 1758 COEF VAR = 2? 8915 MINIMUM = 148984 750 MAXIMUM = 341391 312 9 MARKET VALUE OF MACHINERY OWNED AT END OF LAST SOLVENT YEAR FOR ALL ITERATIONS MEAN : 321765 587 STD. DEV = 34147.433E COEF VAR = 10.5125 MINIMUM = 277737 750 MAXIMUM = 399439.250 10 ENDING CASH RESERVES AT ENS O5 LAST SOLVENT YEAR FOR ALL ITERATIONS MEAN = -20B9E.3047 STD. DEV = 34027.5586 COEF VAR. = -162.8400 MINIMUM = -107427.937 MAXIMUM = 10809 7969 11 LONG-TERM DEBTS AT END OF LAST SOLVENT YEAR FOP ALL ITERATIONS MEAN = 111717 500 STD. DEV = 51206.BS55 COEF VAR. = 45 $356 MINIMUM = C.O MAXIMUM = 183570.875 12 INTERMEDIATE-TERM DEBTS A’ END OF LAST SOLVENT YEAR FOR ALL ITERATIONS MEAN = 920‘0 1250 STD. DEV = 57350.0703 COEF VAR : 62 3302 MINIMUM = -c.0027 MAXIMUM = 269193.250 13 LOAN RATING SCORE AT END OF LAST SOLVENT YEAR FOR ALL ITERATIONS MEAN = 3 8950 STD DEV = 1.2416 COEF VAR. = 31.8713 MINIMUM = 2.2500 MAXIMUM = 6.7500 1A LEVERAGE RATIO AT END OF LAS° SOLVENT YEAR FOR ALL ITERATION5 MEAN = 0.5959 STD DEV = 1,4545 COEF VAR = 163 4595 MINIMUM = 0 0476 MAXIMUM = 10.3927 15 TOTAL EOUIT‘ TD TOTAL ASSETS A" END OF LAST SOLVENT YEAR FOR ALL ITERATIONS MEAN = 0.6244 STD DEV = 0 1838 COEF VAR = 29.4407 MINIMUM 1 0.0878 MAXIMUM = 0 9546 16 PER ACRE LAND PRICE AT END OF LAST SOLVENT YEAR FDR ALL ITERATIONS MEAN = 391 0361 STD DEV : 0.0 COEF VAR = 0.0 MINIMUM = 391.0361 MAXIMUM = 391.0361 17 INTERNAL RATE OF RETURN AT END OF LAST SOLVENT YEAR FOR ALL ITERATIONS MEAN : 0.0063 STD OEV : 0.0695 COEF VAR = 1102.1377 MINIMUM -0.2835 MAXIMUM = 0.1056 AVERAGE ANNUAL MEAN = STD. DEV. = COEF. VAR. = MINIMUM = MAXIMUM = AVERAGE ANNUAL MEAN : STD. DEV. : COEF. VAR. : MINIMUM : MAXIMUM = AVERAGE ANNUAL MEAN : STD. DEV : COEF. VAR. = MINIMUM = MAXIMUM = AVERAGE ANNUAL MEAN = STD. DEV. = COEF. VAR. = MINIMUM = MAXIMUM = AVERAGE ANNUAL MEAN = STD. DEV = COEF. VAR. = MINIMUM = MAXIMUM = AVERAGE ANNUAL MEAN = STD. DEV = COEF VAR. : MINIMUM = MAXIMUM : AVERAGE ANNUAL MEAN : STD DEV = CDEF VAR = MINIMUM = MAXIMUM = .PDM NO.! '0: AN ANALYSIS OF THE TOTAL CASH RECE 155206. 33758. 20. 102552. 242553. TOTAL CASH PROD 153703. 21250. 13. 125121. 199520. NET CASH FARM I 11502. 19500. 170. "24417. 54117. NET FARM -19492. 15525. -95. '52150. 22054. TOTAL A41. 795. 179. 0. 3555. INCOME FOR INCOME TAXES ACCRUED FOR ALL YEARS IPTS FOR YEARS SIMULATED 000 5505 4342 A37 312 UCTION 8 HARVESTING COSTS 575 4905 5551 250 000 FOR YEARS SIMULATED NCOME FOR YEARS SIMULATED 1172 273A A058 A052 3750 YEARS SIMULATED 5359 3555 5958 5758 0525 SIMULTED 9397 I302 9951 0 5551 TOTAL GOVERNMENT PAYMENTS RECEIVED FOR YEARS SIMULATED 54299. 5554. 15. 39215 77554. TAXABLE INCOME 9993. 8773. D7. O. 35117. 2773 7852 7733 .0391 7500 FOR YEARS SIMULATED 7305 7595 7927 O 5515 I055 ACRE Cflffflfi Fnkfi IN IHE SOUTHERN HIJH PLAINS 1985 FARM OILL USING COMGEM DATA FOR 1955-1991 '.NE MACRO OF MODERATE OEFICITS AND MONEY GROWTH 9 OWNED AT '1 VALUE 71:: LOAN won covron, END OF S LEASEO AT S CONTROLLED AI END O I I1 VALUE 0' REAL TE DEIT FOR A PART OWNER ‘(ARM OPERATOR REMAINEO IN OPERATION AN AVERAGE’ OF OPERATORS AFTER TAX NET 5523 5000 872! 052 525 '21923. 99420. -407. '185500. 158214. 253507. 75597. 30. 107055. 392411 AL DEIT AT THE END OF THE LAST YEAR FOR SOLVENT ' 525 3750 5585 0595 .587 195721. 90534 A5. 21525. 353501 A45. 55. 15. 391. 701. ENC OF LAST YEAR SIMULATED FOR SOLVENT 570. 151 17. 707. 1197 F LAS 1315. 172. 13. 1055. 1725 ESTATE OW 175596 38729. 22. 105955 341391. OF MACHINERY OWNED AT 321500. 30481 10. 277737 399439. -19395. 32558. -158 AND CONVENTIONA TARGET PRICE/DEFICIENCY VALUE OF ENDING NET 375 8125 2152 250 .312 .AST YEAR SIMULATED FOR SOLVENT 3059 9015 2479 0000 0000 PAYMENT 5.000 YEARS PRESENT VALUE FOR SOLVENT ITERATIONS IERATION5 WORTH FOR SOLVENT ITERATIONS ITERATIONS ITERATION5 2551 .4015 3972 0000 .0000 T YEAR SIMULATED FOR SOLVENT ITERATIONS 5713 5197 1255 0000 0000 NED AT END OF LAST YEAR FOR SOLVENT ITERATIDNS 750 1541 0154 750 312 ENO OF LAST YEAR FOR SOLVENT ITERATIONS 512 1914 7217 750 250 143 QRIG CASH RESERVES AT END OF LAST YEAR OF SOLVENT ITERATIONS 9905 5955 A225 1-1-1: wuwrv — ' IU!_‘I.§1II MAXIMUM = 10805.7585 34 LONG-TERM DEBTS AT END OF LAST YEAR SOLVENT ITERATIONS MEAN = 110327.500 STD. DEV. = 50775.4505 CDEF VAR. = 45.0225 MINIMUM = 0.0 MAXIMUM = 183570.875 35 INTERMEDIATE-TERM DEBTS AT END OF LAST YEAR FDR SOLVENT ITERATIONS MEAN = 88354.1250 STD. DEV = 51855.8047 COEF. VAR. = 58.5757 MINIMUM = -0.0027 MAXIMUM = 225205.052 35 LOAN RATING SCORE AT END OF LAST YEAR FOR SOLVENT ITERATIONS MEAN = 3.8357 STD. DEV. = 1.1832 COEF. VAR. = 30.8377 MINIMUM = 2.2500 MAXIMUM = 5.5000 37 LEVERAGE RATIO AT END OF LAST YEAR SOLVENT ITERATIONS MEAN = 0.7021 STD. DEV. = 0.5217 COEF VAR. = 74.3004 MINIMUM = 0.0475 MAXIMUM = 2.3204 38 TOTAL EOUITY TO TOTAL ASSETS AT END OF LAST YEAR FOR SOLVENT ITERATIONS MEAN = 0.5354 STD. DEV. = 0 1585 COEF VAR. = 25.5125 MINIMUM = 0.3012 MAXIMUM = 0.5545 35 PER ACRE LAND PRICE AT END OF LAST YEAR FOR SOLVENT ITERATIONS MEAN = _ 351.0351 STD. DEV. = 0.0 COEF VAR. = 0.0 MINIMUM = 351.0351 MAXIMUM = 351 0351 40 INTERNAL RATE OF RETURN AT END OF LAST YEAR FOR SOLVENT ITERATIONS MEAN = 0 0122 STD. DEV. 1 0.0551 COEF VAR = 455.0485 MINIMUM = -0 1058 MAXIMUM = 0 1055 CUMMULATIVE DISTRIBUTIONS FOR THE FOLLOWING VARIABLES BCOTTM.POM NO 1 1088 ACRE COTTON FARM IN THE SOUTHERN HIGH PLAINS DATA FOP AN ANALYSIS OF THE 1585 FARM BILL USING COMGEM DATA FOR 1585-1551 BASELINE MACRO OF MODERATE DEFICITS AND MONEY GROWTH MARKETING LOAN FOR COTTON, AND CDNVENTIONA TARGET PRICE/DEFICIENCY PAYMENT MODERATE DEBT FDR A PART OWNER 2 THE FARM DRERATORS AFTER TAX NET PRESEN' VALUE FOR ALL ITERATIONS 3 FARM OPERATORS PRESENT VALUE OF ENDING NET WORTH FOR ALL IERATIONS 4 TOTAL DEBT AT THE END OF THE LAST YEAR FOR ALL ITERATIONS 5 ACRES OWNED AT END OF LAST YEAR SIMULATED FOR ALL ITERATIONS 5 ACRES LEASED AT ENC OF LAST YEAR SIMULATED FDR ALL ITERATIONS 7 ACRES CONTROLLED AT END OF LAST YEAR SIMULATED FDR ALL ITERATIONS 8 MARKET VALUE OF REAL ESTATE OWNED AT END OF LAST SOLVENT YEAR FOR ALL ITERATIONS 5 MARKET VALUE OF MACHINERY OWNED AT END OF LAST SOLVENT YEAR FOR ALL ITERATIONS I 2 3 4 5 5 1 1 -241355.052 31025 5531 21425.0585 381.0000 707 0000 1088. 2 -188500 052 107045.250 28125.5553 381.0000 707.0000 1088. 3 -154055 375 132855 000 50510 1835 381 0000 707.0000 1088 4 -140577.312 141485 000 50535.3154 381.0000 707.0000 1088 5 -138328.537 151511.500 51187 1552 381.0000 707.0000 1088. 5 -128455 552 152422 552 55155.3S15 381 0000 707 0000 1088 7 -127045.812 154858.000 85517.8750 381.0000 707.0000 1085 8 -125754 812 157715.312 88717 0525 381.0000 707.0000 1088. 5 -118511.250 152555.552 55545.1250 381.0000 707.0000 1248 10 -111113.537 157075.750 114515.375 381.0000 707.0000 1248. 11 -110530.537 178750.525 118051.812 381.0000 707.0000 1248. 12 -105525.187 184431 437 125155 875 381.0000 707 0000 1248. 13 -104232 525 188515 125 144013.312 381.0000 707.0000 1248 14 -103211 187 185540 052 148871 552 381 0000 707.0000 1248 15 '55532 3750 151312.587 145550 052 381.0000 707.0000 1248. 15 -88575 0525 202723 187 154533.500 381 0000 707 0000 1248 17 -81385.3750 203341 500 172525 125 381.0000 857.0000 1248. 18 -73850 0525 204355.052 174782.552 381.0000 857.0000 1248. 15 -71134.1250 213104 125 175357.875 381.0000 857.0000 1248 20 -57555 3125 218755.552 175522 537 381.0000 857.0000 1248 21 -50033 4755 221555.312 175582 500 381 0000 857 0000 1248 22 '55325.5537 227040.500 181224.875 381 0000 857 0000 1245. 23 -43233.0117 240218.750 184034 000 381.0000 857 0000 1248 24 -34230.7070 244535.587 201355 250 381.0000 857 0000 1245 25 '32514 7555 245435.000 205782 187 381.0000 857.0000 1248 25 '32422.3554 248455.587 205500.500 381.0000 857.0000 1248. 27 -21547 4551 258455 500 221520.312 381.0000 857.0000 1248. 28 '15335.3355 255745.552 227745.537 381.0000 857.0000 1248 25 '15438.5015 251447 000 227835.500 381.0000 857.0000 1248 30 -8415.3515 275517.525 230853 500 381 0000 857 0000 1248 31 -522.8540 275555.525 233585.250 541.0000 857.0000 1248 32 13225.5023 287423.187 234271 537 541.0000 857.0000 1248. 33 15581.5585 252552.812 235574 537 541.0000 857.0000 1408. 34 21022 4551 301358 000 243282.250 541.0000 857.0000 1408 35 23745.1328 302108.552 248055 750 541.0000 857.0000 1408. 35 30335 7187 305157 875 255223.875 541.0000 857 0000 1408 37 38311 4102 314483.312 258305 437 541.0000 857.0000 1408. 38 41155.0547 315487.125 257534 750 541.0000 1027.0000 1408 35 55588.0000 315550 500 255122 552 541.0000 1027.0000 1405 40 55011.G575 331085.052 273555 250 541 0000 1027.0000 1568. 41 71075.5000 333053.525 278402 125 541.0000 1027 0000 1558 42 72542 3125 344848 437 '275091 187 541.0000 1027.0000 1558 43 83583.2500 345503 000 285755 000 541.0000 1027 0000 1555 44 50458.5875 345285.875 313255 525 541.0000 1027 0000 1558 45 550S'.5000 353851.375 320307 525 541.0000 1027.0000 1555. 45 105714.875 355555.875 350787.875 541.0000 1187 0000 1558 47 110535 187 352554.552 352344 750 541.0000 1187.0000 1558. 48 115025.552 354730.875 357550 750 541.0000 1187 0000 1558 45 140182.375 381551.525 383501.587 541.0000 1187.0000 1728. 50 158214.525 352411.312 445022.500 701.0000 1187.0000 1728 CUMMULATIVE DISTRIBUTIONS FOR THE FOLLOWING VARIABLES BCOTTM.POM NO.1 1088 ACRE COTTON FARM IN THE SOUTHERN HIGH PLAINS DATA FOR AN ANALYSIS OF THE 1585 FARM BILL USING COMGEM DATA FOR 1585-1551 BASELINE MACRO OF MODERATE DEFICITS AND MONEY GROWTH MARKETING LOAN FOR COTTON. AND CONVENTIONA TARGET PRICE/DEFICIENCY PAYMENT MODERATE DEBT FOR A PART OWNER ENDING CASH RESERVES AT END OF LAST SOLVENT YEAR FOR ALL ‘C ITERATIONS 11 LDNG~TERM DEBTS AT END OF LAST SOLVENT YEAR FDR ALL 12 13 ITERATIONS YEAR FOR ALL ITERATIONS YEAR FOP AL; ITERATIONS INTERMEDIATE-TERM DEBTS AT END OF LAST SOLVENT LOAN RATING SCORE AT END OF LAST SOLVEN' 144 0000 0000 .0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 .0000 0000 0000 0000 0000 0000 .0000 0000 0000 0000 .0000 .0000 0000 0000 0000 .0000 .0000 0000 0000 0000 .0000 0000 0000 0000 .0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 .0000 0000 .0000 FARM ND 8 148584. 148584 148584. 148584. 148584 148584. 148584 148584. 148984 148584. 148584 148584 148584. 148584 148584. 148584 148584 148584 148584 148584 148584 148584 148584. 148584. 148584 148584. 148584 148584. 148584. 148584 211550 211550. 211550 211550. 211550. 211550 211550 211550 211550 211550 211550 211550 211550. 211550 211550 211550. 211550. 211550 211550. 341351. FARM NO. 750 750 750 750 750 750 750 750 750 750 750 750 750 750 750 .750 750 750 750 750 750 750 750 750 750 750 750 750 750 750 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 500 312 1 PAGE 5 277737 277737 275115 275115 281075 281075 281075 281075 282514. 282514. 282514 282514 288004. 285551 258215 300435 301557 301557. 301557 303055 308485 328753. 328753 328753. 328753. 328753. 328753 328753. 328753. 328753 325802 325802. 325844 325844 325844 325844 325844 330440 332132 350325. 350325. 350325 353588. 377515 377515 380500 380500 380500. 384245 355435. 1 PAGE NO 750 750 437 437 437 437 437 437 187 187 187 187 875 875 187 125 875 875 875 525 312 375 .375 375 375 375 .375 375 375 375 187 187 437 437 437 437 437 537 052 875 875 875 525 125 125 .052 .052 052 .750 250 102 LEVERAGE RATIO AT END OF LAST SOLVENT YEAR FOR ALL ITERATIONS TOTAL EOUITY TO TOTAL ASSETS AT END OF LAST SOLVENT YEAR FOR ALL PRICE AT END OF LAST SOLVENT YEAR FOR ALL PER ACRE LAND INTERNAL RATE III -¢-_-_..._- (llll-IN-IOUIJIIUIDIJN-I 10 107527. 105519. '94353. -73941. -57010. '54501 '53559. '52179. '55504. -54597. -45575. -55735. -51112. '37371 -35415. -35154. '31551 ‘Z9294. -25590. -27525. ‘Z5555. '25453. "Z5539. ‘Z3552. -15055. '13547. -7234. -7213. -2221 51 5302. 5305. 10509. 10509. 10509. 10509. 10509. 10509. 10509 10509. 10509. 10509. 10509. 10509 10509. 10509. 10509. 10509. 10509. 10509. OF RETURN AT END OF LAST SOLVENT YEAR FOR 937 500 2500 1250 5250 .9553 5505 9553 1505 5039 5515 9255 2227 .0459 5395 3320 .7227 5550 0075 2145 1552 9553 2305 3251 1992 9553 7109 1719 1953 .2500 1535 2539 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 7959 11 0 0 19455 21429 35505. 39151 40945. 52335. 52391 53000. 50475. 73199. 53095 54553 99353. 100035. 101253. 101535. 105510. 107727. 110752. 115101 119157. 119157 119157. 121150. 121551 123555. 125135. 125195. 125250. 125315. 125405. 125437. 125553. 125452. 125551 153510 157392. 159250. 159240. 171515. 179735. 179529. 179595. 179900. 179905. 179957 179975. 153570 .0 .0 .2227 .0525 1211 .4335 3533 5953 .4141 5352 2517 5525 .0000 0525 2500 500 512 575 157 375 525 .575 750 750 750 512 .000 937 557 937 512 557 437 500 312 437 .375 125 312 375 375 937 375 250 525 375 375 125 375 .575 1 1 1 1 1 1 1 1 1 1 1 1 1 1 193991. 12 -o. 11o. 21:51. 2012s. zasso. ::s11. 4237:. aaoso. cvsov. sos1o. s2oso. s2s1s. sassv. sssaa. sssza. s2s21. scssv. snasv. ssvzz. ss1so. sasvo. sszsz. vszas. vszss. 1152:. vasaz. 1s:1s. aosas. $2111. avsss. as222. o1:sa. osssv. os1s1. ovaza. osozs. oassz. os1s1. 12525. 24054. 32110. ovaaa. szsas. 11os1 vvsas. ase14. 203505. 225205. 259193. 0027 9375 5525 5953 2305 3955 4755 5955 7734 1535 3525 9555_ 7595 5320 2959 9922 0547 0557 1250 3125 5000 5750 5125 7500 5125 5250 7500 2500 5000 3750 1575 000 000 125 525 312 500 750 437 500 500 437 750 .500 375 250 937 052 052 250 1 OGIGIGIOIIIIIUIUIUIbh@lb&bbb)htIJI-JUIJIJIJIJIJIJLIIJIJIJHUIJNNNNNNNNNNMNU ITERATION5 ITERATIONS ITERATIONS ALL .2500 .2500 .2500 .5000 .5000 .5000 .5000 .5000 .7500 .7500 .7500 .7500 .0000 .0000 .0000 .0000 .2500 .2500 .2500 .2500 .2500 .5000 .5000 .5000 .5000 .5000 .7500 .7500 .0000 .0000 .0000 .2500 .2500 .2500 .5000 .5000 .5000 .5000 .7500 .7500 .0000 .2500 .5000 .7500 .7500 .0000 2500 .2500 .5000 .7500 CUMMULATIVE DISTRIBUTIONS FOR THE FOLLOWING VARIABLES lCDTTM.PO lTA FDR AN ANALYSIS OF THE ISELINE MACRO OF MODERATE DEFICITS AND MONEY GROWTH IRKETING LOAN FOR COTTON: AND CONVENTIONA TARGET PRICE/DEFICIENCY PAYMENT M ND.1 1055 ACRE COTTON FARM 1955 FARM 5ILL USING COMGEM DATA FOR DOERATE OE5T FOR A PART OWNER AVERAGE AVERAGE AVERAGE AVERAGE AVERAGE AVERAGE AVERAGE >4 1 2 3 5 5 5 7 5 9 10 ANNUAL ANNUAL ANNUAL ANNUAL ANNUAL ANNUAL ANNUAL 15 102552. 115255. 115901. 121559. 121915. 123929. 124495. 125555. 130337. 130515 134029. 135347. 137125. 137573. 139151. 142725. 143293. 152125. 153954 155413. 155590. 155755. 155904. 157153. 187340. 157553. 155025. 189210. 159215. 172334. 172503 172552. 173325. 173557 173755. 175150 178183. 192459. 193217 193577. 195530 200553. 201883. 202005. 205855. 215997. 220617 232285. 235289. 242863. 1f1n.ron no.1 ~von AN ANALYSIS or THE TOTAL CASH PRODUCTION 5 HARVESTING CASH RECEIPTS FOR YEARS SIMULATED COSTS FOR YEARS SIMULATED NET CASH FARM INCOME FOR YEARS SIMULATED ~t1uc LOAN ran co11ou. ‘A1: niar FOR A want ownsa INCOME TAXES ACCRUED FOR ALL TOTAL NET FARM TOTAL TAXA5LE 19 537 125121.250 525 125057.557 937 127055.575 125 127597.375 375 125015.512 750 130359.750 437 130507.552 375 132055.937 525 132755.525 512 134547 312 052 135252 125 557 135515 537 052 135259.125 375 135755.125 525 135952.157 575 141505.312 525 141721 525 375 142395.552 157 142943 125 437 143075.375 512 143551.250 525 144039.312 937 145955 437 512 157542 750 437 147599.312 525 147951.375 375 145423.312 375 155555.250 250 155599.312 537 150055.157 .052 151107.750 512 153027.525 937 154441 500 512 157558.375 500 155374.500 125 159742.312 525 172241 552 525 174523.512 125 179531.000 512 750356.000 .000 151172.125 125 151355.512 512 151475.525 500 152219.125 500 155915.525 512 155752.000 .000 157157.500 525 157570.000 500 191533.000 312 199520.000 roan owsnarons AFTER {AX us? PRESENT 20 25517. 19541 14073. 11550. 10755. 10253. "9515. -7515. "5219. .5797 .5312 -5159 -5921 -5550 -5259. -5077. -4030 -2137. -524. 3552. 3755. 4305. 5517. 5535. 7112. 9050. 10453. 11525. .4553 11551 14144 14557. 14725. 15541. 19154. 20000. .0505 21511 23575 25500. 25347. 30931 30932. 33575. 34533. 35532. 35575. 37555. 40532. 42395. 53043. 55255. 54117. INCOME FOR YEARS SIMULATED 5052 .7255 14394. 1953 1545 1755 7353 0505 2157 9052 3320 9553 7157 7255 4557 9375 3550 0525 0312 5575 5203 5391 5719 9553 3945 5533 1325 5312 2255 1325 0520 5537 5133 5075 9755 1445 3750 0312 2512 1133 5755 5945 5955 5703 5525 5125 3750 INCOME FDR YEARS SIMULATED YEARS SIMULTED TOTAL GOVERNMENT PAYMENTS RECEIVED FOR YEARS SIMULATED 21 '52150. -59470. -55124. -53113. -51557. -40772. -40250. '39534. -3753? -35155. '35255. -35105. -34935. '35540 '33155. '3291L '32575. -32159. ‘Z5059 -27593. "Z5937. '25721. “Z3510. '22055 -21505. “Z1303. -Z0539. -20524. -17910. -17751. -17519. -15232. -13323 -11158. -10955. -5599. -5126. -4527. -1555. "7544. 1397 3171. 3955. 4195. 7535. 5155. 9918. 10555. 13502. 22554. VALUE FOR SOLVENT 5755 1015 2500 5537 3955 5320 1455 5553 1755 7512 5125 1133 7157 9141 0703 7255 3515 0505 9375 9557 5320 5312 5525 1953 7070 2591 3955 5750 0195 3125 1325 0505 5557 5533 3320 7595 4052 5905 2415 0122 5555 1552 5247 0595 4922 3320 1550 9951 5075 0525 cunnuuntxvs D1STRl5UT1ONS FOR THE FOLLOWING VARIABLES 1oaa ACRE carton FARM 19:5 FARM IILL USING COMGEM DATA FOR .1Iz nncno or MODERATE DEFICITS nun nouzv cnowrn AND couvenwxonn TARGET PRICE/DEFICIENCY wnvneuv 145 S 3 ON-*——~——-¢-OO()0O(JOO(JO0C)00¢)0O<)OO(JOO1DOO(JOO(>OOlDOO<)OO<)Oh IN THE SOUTHERN HIGH PLAINS 1955'1991 W mO()OOOC)00019000()OOO()OO()OOO(3OON 103. 110. 123. 170. 229 275 451 553 572 502 557 704. 955 995. 1157. 1212 1292. 1475. 1557. 1515. 3222. 3555 IN THE SOUTHERN HIGH PLAINS 1955-1991 ITERATIONS O00C)00(>OO()0OOl)O0O()O0()O0()0O .0475 .0555 .1045 .1255 .1394 .1494 .1572 .1955 .2173 .2439 .2740 .2755 .3555 .3525 .3990 .5004 .5050 .4320 .4335 .4514 4507 5511 .5053 .5427 .5453 .5404 5540 .7155 .7277 .7734 .7940 .5122 .5570 .5507 .5512 .5932 .9130 9132 9545 .9595 .0599 .2457 .2905 .3575 4317 7572 .5152 .9415 .3204 3927 GUI HID UN u.‘ 3557 3333 5557 2544 5333 500° 9155 9539 4425 0475 9549 S192 2759 5154 5255 1255 2759 5375 5755 3711 1470 5541 S OO(100(3000()OO()OOl900|DOO(>OO()OO(DOOlDOOlDOO4@OO|DOO()OOC)OO1DOw 2W as21§. 00055. 40557 41232. 42451. 42502. 43554. 45572. 45954. 47240 47547. .5525 45077. 47871 45593 50321. 50545. 50555. 50555. 50729 50534. 5149: 51535. 51524. 52435. 53159. .0075 53513 54229. $4955 55792 55555 55035 55917. .9570 55241 59550 50435. 50552 50825. $1554. svsss. 52138 52575. 53554. 55537 55555. 55310 57215. 57795. .5250 57571 77554. .0575 .3012 .3400 .3552 .3555 .5112 .5241 .4355 .4453 .4755 .5103 .5115 .5227 .5225 .5252 .5402 .5403 .5414 .5515 .5574 .5539 .5755 .5529 .5009 .5095 .5457 .5452 .5539 .5752 .5545 .5590 .5975 .5953 7122 .7141 7155 .7233 7377 .7533 .7549 .5039 .5215 .5355 .5523 .5700 .5775 .5575 9054 .9474 .9555 0391 5325 9597 5575 5953 5325 5203 3533 5320 7591 5437 5541 0391 5437 5525 3533 1552 0195 0937 5453 7591 0312 0520 9755 7070 7353 5075 9755 .2070 3437 3125 0525 5533 5203 3945 5528 2812 1552 3005 0520 3533 7500 5525 5525 4375 7500 15 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 391.0351 FARM ND 3 1D m0l>OOO<>OO<)0u DO()0O(>O0lDOO 4 01 1500. 1959 7375 2207.9535 5155 5234 4954.5759 515E.5945 5272 9727 5594 2227 5335 7157 5447.0703 5540.1357 7055.7157 7110.7353 7119 5297 7215 9951 5544.1502 9105.0937 10350.5430 10555 5405 11571.5325 12070.5541 13049.5533 14759.9141 14555.5533 15027.2353 15274 2812 15303 5325 15427 1552 1$505.8533 15357.501E 18973.0525 19445.7070 19971.0703 22740.5945 23555.5937 25352.5000 25127.5505 27995.1445 35117.5515 N ~| D ~l FARM NO 1 1 .2535 .1095 .0554 .0753 .0715 .0575 .0570 .0547 .0574 .0511 .0395 .0359 .0295 .0259 .0240 .0150 .0174 .0125 .0107 .0075 .0055 .0031 .0001 .0055 .0105 .0152 .0150 .0155 .0192 .0302 .0347 .0350 .0535 .0557 .0515 .0505 .0522 .0537 .0550 .0557 .0592 .0729 0732 0753 0512 .0515 .0523 0927 0947 .1055 OO<)00l@0O(J0010001000()OO()OO()OO1DO PAGE ND PAGE ND 103 104 25 FARM OPERATORS PRESENT VALUE OF ENDING NET WORTH FOR SOLVENT IERATIONS 27 TOTAL DEBT AT THE END OF THE LAST YEAR FOR SOLVENT ITERATIONS 28 ACRES OWNED AT END OF LAST YEAR SIMULATED FOR SOLVENT ITERATIONS 29 ACRES LEASED AT END OF LAST YEAR SIMULATED FOR SOLVENT ITERATIONS 30 ACRES CONTROLLED AT END OF LAST YEAR SIMULATED FOR SOLVENT ITERATIONS 31 MARKET VALUE OF REAL ESTATE OWNED AT END OF LAST YEAR FOR SOLVENT ITERATIDNS 32 MARKET VALUE OF MACHINERY OWNED AT END OF LAST YEAR FOR SOLVENT ITERATIONS I 25 25 27 28 29 30 31 32 1 -188500.052 107045.250 21429.0585 381.0000 707.0000 1088.0000 148984.750 277737.750 2 -154055.375 132895.000 28125.5953 381.0000 707.0000 1088.0000 148984 750 277737 750 3 -140577.312 141488.937 50910 1835 381.0000 707.0000 1088.0000 148984 750 279119.437 4 -138328.937 151911.500 50539.3154 381.0000 707.0000 1088.0000 148984.750 279119.437 5 '128459.552 152422.500 51187.1992 381.0000 707.0000 1085.0000 148984.750 281075.437 5 -127045.812 154858.000 55195.3515 381.0000 707.0000 1088.0000 148984 750 281075.437 7 -125754.812 157715.312 85517.8750 381.0000 707.0000 1088.0000 148984.750 281075.437 8 -118511.250 152559.552 88717.0525 381.0000 707.0000 1088.0000 148984.750 281075.437 9 -111113.937 157075.750 95545.1250 381.0000 707.0000 1248.0000 148984.750 282514.187 10 -110530.937 178750.525 114919.375 381.0000 707.0000 1248.0000 148984.750 282514.187 11 -105925.187 184431.437 118051.812 381.0000 707.0000 1248.0000 148984.750 282514.187 12 -104232.525 188519.125 125155.875 381.0000 707.0000 1248.0000 148984.750 282514.187 13 -103211.187 189540.052 144013.312 381.0000 707.0000 1248.0000 148984.750 288004.875 14 -99532.3750 191312.587 148871.552 381.0000 707.0000 1248.0000 148984.750 289951.875 15 -88575.0525 202723 187 149550.052 381.0000 707.0000 1248.0000 148984.750 298219.187 15 -81385 3750 203341.500 154933.500 381.0000 707.0000 1248.0000 148984.750 300435.125 17 -73890.0525 204355.052 172525.125 381.0000 857.0000 1248.0000 148984.750 301557.875 18 -71134.1250 213104.125 174782.552 381.0000 857.0000 1248.0000 148984.750 301557.875 19 -57559.3125 218799.552 175397.875 381.0000 857.0000 1248.0000 148984.750 301557.875 20 -50033.4755 221555.250 175922.937 381.0000 857.0000 1248.0000 148984 750 303095.525 21 -55325.5937 227040.500 179982.500 381.0000 857.0000 1248.0000 148984.750 308485.312 22 -43233.0117 240218.750 181224.875 381.0000 857.0000 1248.0000 148984.750 328793.375 23 '34230.7070 244539 587 184034.000 381.0000 857.0000 1248.0000 148984.750 328793.375 24 -32914.7959 245435.000 201355.250 381.0000 857.0000 1248.0000 148984.750 328793.375 25 -32422.3594 248459.587 205782.187 381.0000 857.0000 1248.0000 148984.750 328793.375 25 -21947.4951 258455.437 205900.500 381.0000 857.0000 1248.0000 148984.750 328793.375 27 -15335.3359 259745.552 221920.312 381.0000 857.0000 1248.0000 148984.750 328793.375 28 '15438.5015 251445.937 227745.937 381.0000 857.0000 1248.0000 148984.750 328793.375 29 '8419.3515 275517.525 227835.500 381.0000 857.0000 1248.0000 148984.750 328793.375 30 '922.8540 275555.525 230853.500 381.0000 857.0000 1248.0000 148984 750 328793.375 31 13225.9023 287423.187 233585.250 541.0000 857.0000 1248.0000 211550.500 329802 187 32 19581.5585 292552 812 234271.937 541.0000 857.0000 1248.0000 211550.500 329802.187 33 21022.4951 301398 000 235974.937 541.0000 857.0000 1408.0000 211550.500 329844.437 34 23745.1328 302108.552 243282.250 541.0000 857.0000 1408.0000 211550.500 329844.437 35 30339.7187 305157.875 248055.750 541.0000 857.0000 1408 0000 211550.500 329844.437 35 38311.4102 314483.250 255223.875 541.0000 857.0000 1408.0000 211550.500 329844.437 37 41155.0547 315487 125 258305.437 541.0000 857.0000 1408.0000 211550.500 330440.937 38 55988.0000 319950.500 257534.750 541.0000 1027.0000 1408.0000 211550.500 332132.052 39 59011.5875 331088 052 259122.552 541.0000 1027.0000 1408.0000 211550.500 350325.875 40 71075.5000 333053 525 273555.250 541.0000 1027.0000 1558.0000 211550 500 350325.875 41 72542.3125 344848 437 278402.125 541.0000 1027.0000 1558.0000 211550 500 350325.875 42 83983.2500 345503.000 279091 187 541.0000 1027.0000 1558 0000 211550.500 353988.525 43 90498.5875 349288.875 289758.000 541.0000 1027.0000 1558.0000 211550.500 377519 125 44 99051 5000 353851.312 313295.525 541.0000 1027.0000 1558 0000 211550 500 377519.125 45 109714.875 359595.875 320307.525 541.0000 1187.0000 1558 0000 211550 500 380900.052 45 110535 187 352554.552 350787.875 541.0000 1187.0000 1558.0000 211550 500 380900.052 47 119029.552 354730.812 352344.750 541.0000 1187 0000 1558 0000 211550 500 380900 052 48 140182.375 381591.552 357590.750 541.0000 1187.0000 1728.0000 211550.500 384249 750 49 158214.525 392411.312 383501.587 701.0000 1187 0000 1728 0000 341391.312 399439.250 CUMMULATIVE DISTRIBUTIONS FOR THE FOLLOWING VARIABLES FARM NO ' PACE NO 9CDTTM.POM ND.1 1088 ACRE COTTON FARM IN THE SOUTHERN HIGH PLAINS DATA FOR AN ANALYSIS OF THE 1985 FARM BILL USINC CDMGEM DATA FOR 1985-1991 BASELINE MACRO O5 MODERATE DEFICITS AND MONEY OROWTF MARKETING LOAN FOR COTTON; AND CONVENTIONA TARGET PRICE/DEFICIENCY PAYMENT MODERATE DEBT FOR A PART OWNER 33 ENDING CASH RESERVES AT END OF LAST YEAR OF SOLVENT ITERATIDN5 34 LONC~TERM DEBTS AT END OF LAST YEAR SOLVENT ITERATIONS 35 INTERMEDIATE-TERM DEBTS AT END OF LAST YEAR FOR SOLVENT ITERATIONS 35 LOAN RATING SCORE AT END OF LAST YEAR FOR SOLVENT ITERATIONS 37 LEVERACE RATIO AT END OF LAST YEAR SOLVENT ITERATIONS 38 TOTAL EOUITY TC TOTAL ASSETS AT END OF LAST YEAR FOR SOLVENT ITERATION5 39 PER ACRE LANE PRICE AT ENC OF LAST YEAR FOR SOLVENT ITERATION5 40 INTERNAL RATE OF RETURN AT END OF LAST YEAR FOR SOLVENT ITERATIONS I 33 34 35 35 37 38 39 40 - -107427 937 0 0 -0.0027 2.2500 0.0475 0.3012 391.0351 '0.1098 2 -105515.500 0 0 710.9375 2.2500 0.0555 0 3400 391 0351 -0.0884 3 ~73941.1250 19454 2227 21357.8828 2.2500 0.1045 0.3552 391 0351 -0.0783 4 -57010.5250 21429 0525 28125.5953 2 5000 0.1255 0 3588 391.0351 -0.0718 5 -54501.9883 35505 1211 28590 2305 2.5000 0 1394 0 4112 391.0351 -0.0578 5 -53585.5508 39181 4335 33517 3945 2.5000 0 1494 0.4241 391.0351 -0.0570 7 -52775 9883 40948.3533 42378 4755 2.5000 0 1872 0 4355 391.0351 -0.0547 8 -58504 1405 52335.5953 43050.8945 2.5000 0.1955 0 4453 391.0351 ~0.0574 9 '54597.5039 52391 4141 47507 7734 2.7500 0.2173 0 4785 391.0357 -0.0511 10 -45575 8515 53000 5352 50910 1835 2 7500 0.2435 0.5103 391 0351 -0 0398 1? -44735 9258 60475.2517 52090.3828 2 7500 0.2740 0 5115 391 0351 -0.0349 12 -41‘12.2227 73199 5525 52579.9548 2 7500 0.2755 0 5227 391.0351 -0.0298 13 -37371 0459 83095 0000 54597.7595 3 0000 0.3555 0 5228 391.0351 -0 0249 14 "35415 8398 84553 0525 55594.8320 3 0000 0 3825 0 5282 391.0351 -0 0240 15 '35154.3320 99343 2500 55423.2959 3.0000 0.3990 0 5402 391.0351 -0.0180 15 -31551 7227 100035.500 52527.9922 3.0000 0.4004 0 5403 391.0351 -0.0174 17 '29294.5580 101253.812 54897 0547 3.2500 0.4040 C 5414 391 0351 -0.0125 18 -28590 0078 101534.875 54897 0547 3.2500 0.4320 0.5518 391.0351 -0.0107 19 -27425 2148 105410.187 55723.1250 3.2500 0.4335 0 5574 391.0351 -0.0075 20 '25555.1552 107727.375 55150.3125 3.2500 0.4514 0.5539 391.0351 -0.0054 21 -25453.9883 110752 525 58570.5000 3.2500 0 4807 0.5788 391.0351 -0.0031 22 -24539.2305 115101.875 59252.8750 3.5000 0 4811 0.5829 391.0351 0 0001 3 '23552 3281 119187 750 75239.8125 3.5000 0.5053 0.5009 391.0351 0.0088 24 -1504E.1992 119187 750 75255 7500 3 5000 0.5427 0.5095 391.0351 0.0105 25 -13547.9883 119187 750 77523.8125 3.5000 0.5453 0 5457 391.0351 0.0152 25 ~7234 7109 121150.812 78582.5250 3.5000 0.5404 0.5482 391 0351 0.0180 27 -7213 1719 121851 000 79319.7500 3 7500 0.5540 0.5539 391.0351 0.0188 28 '2221.1953 123888 937 80539.2500 3.7500 0.7155 0 5752 391.0351 0 0192 29 41.2500 125138.587 82177.5000 4 0000 0.7277 0.5845 391.0351 0.0302 30 8302 1835 125194 937 87555.3750 4.0000 0.7734 0 5890 391 0351 0.0347 31 8305 2539 125280 812 89222 1875 4 0000 0.7940 O 5975 391.0351 0.0350 2 10805.7959 125315 587 101398.000 4.2500 0.8122 0.5983 391.0351 0.0434 33 10805 7959 125404 437 103857.000 4.2500 0.8470 0.7122 391 0351 0.0487 34 10805.7959 125437.500 105197 125 4.2500 0.8507 0 7141 39‘ 0351 0 0515 35 10802 7959 125443.312 107828.525 4.5000 0 8512 0 7148 391 0351 0.0505 35 10809 7959 125452 437 108025.312 4.5000 0 8932 0 7233 391 0351 0 0522 37 10802 7959 125481 375 108992 500 4.5000 0 9130 0 7377 391 0351 C 0537 38 10805 7559 153810 125 109151.750 4.5000 0.9132 0 7833 391 0351 0.0550 39 10805 7959 157392 312 112525.437 4.7500 0.9545 C 7845 391 0351 0.0557 40 10809 7959 159240 375 124094 500 4.7500 0.9595 0 8039 391.0351 0.0592 41 10805.7959 159240.375 132110.500 5.0000 1 0899 0.8215 391.0351 0.0729 42 10809 7959 171815.937 147384.437 5.2500 1.2457 0 8358 391.0351 0 0732 43 10809.7959 179735.375 152585.750 5.5000 1.2908 0.8423 391 0351 0.0783 44 10805.7959 179895 525 171051.500 5 7500 1.3578 0.8700 391.0351 0.0812 45 1080S.7959 179900.375 177585.375 5.7500 1 4317 0 8775 391.0351 0.0815 45 10809 7959 179905.375 185814.250 5.0000 1.7872 0 8875 391.0351 0.0823 47 10809.7959 ‘79957.125 193991.937 5.2500 1.8152 0.9054 391 0351 0.0927 48 10809 7959 179975.375 203505.052 5.2500 1.9415 0.9474 391.0351 0.0947 49 10809.7959 183570 875 225205.052 5.5000 2 3204 0.9545 391.0351 0.1055 ' 146 SUMMARY OF SURVIVAL STATISTICS BCOTTM.POM NO.1 DATA FOR AN ANALYSIS OF THE 1088 ACRE COTTON FARM IN THE SOUTHERN HIGH PLAINS 1985 FARM BILL USING COMGEM DATA FOR 1985-1991 BASELINE MACRO OF MODERATE OEFICITS AND MONEY GROWTH MARKETING LOAN FOR COTTON, MODERATE DEBT FOR A PART OWNER YEAR 1 THE FARM HAS A NO. OF 0. 0. 58.00 PERCENT PROBABILITY OF THE FARM OPERATOR REMAINED INSOLVENT ITERATIONS 0 0 I \ PROBABILITY OF SURVIVAL .000 .000 .000 .000 .000 .580 SURVIVING AND A IN OPERATION AN AVERAGE‘ OF AND CONYENTIONA TARGET PRICE/DEFICIENCY PAYMENT 38.00 PERCENT CHANCE OF AN ECONOMIC SUCCESS 6.000 YEARS 147 Appendix D: Files and Variable Names in FLIPSIM V 148 SUMMARY OF THE C(I,J) MATRIX THE PRINIARY WORKSPACE FOR THE MODEL Except where noted, annual data are stored in the rows (I) of the C matrix for years 1 through 10. Each column (J) of the C matrix represents a separate variable in the model. J Description of Variables 1 Total acres of cropland owned (acres) 2 Total acres of cropland leased (acres) 3 Total acres of cropland available (acres) 4 Total pastureland acres owned (acres) 5 Acres of cropland purchased at the end of year 1 (acres) 6 Acres of cropland leased at the end of year 1 (acres) 7 Current market value of owned cropland and buildings (S) 8 Current market value of all owned buildings (S) 9 _ Salvage value of all buildings owned (S) 1O Cost of all buildings when purchased (S) 11 Economic life of buildings for depreciation purposes (years) 12 Current market value of all off-farm investments (S) 13 Acres of pastureland leased (acres) 14 Market value of newly purchased cropland (S) 15 Market value of newly purchased farm machinery (S) 16 Ratio of leased cropland to total cropland (fraction) 17 Market value of owned pastureland (S) 18 Total operator withdrawals including taxes (S) 19 Current real estate debt (S) 20 Fraction of crops sold in year after harvest as a tax strategy (fraction) 21 Original loan life on real estate loan (years) 22 Fraction of the original real estate loan yet to be repaid (fraction) 23 Annual principal and interest payment for real estate loan (S) 24 Marginal income tax rate (fraction) 25 Effective capital gains tax rate (fraction) 26 Current intermediate-term debt on machinery and livestock (S) 27 Value of cropland owned (S) 28 Original loan life on intermediate-term debt (years) 29 Fraction of the original intermediate-term debt to be repaid (fraction) 30 Annual principal and interest payment on intermediate-term debt (S) 31 Downpayment for machinery replacements (S) 32 Downpayment for new machinery (S) 33 Downpayment for purchased farmland (S) 34 Terms for financing new long-term debts (fraction) 35 Terms for financing new intermediate-term debts (fraction) 36 Loan life for financing new long-term debts (years) 37 Loan life for financing new intermediate-term debts (years) 38 Years simulated (no.) 39 Beginning cash reserve (S) 40 Minimum allowable long-term equity ratio (fraction) 41 Minimum allowable intermediate-term equity ratio (fraction) 42 Terms for obtaining a second mortgage (down payment, etc.) 43 After-tax discount rate (fraction) 44 Total unrealized capital gains ($) 45 Real property tax rate, dollar of tax per dollar of market value (fraction) 149 46 47 48 49 SO 51 52 53 54 55 56 57 58 59 6O 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 8O 81 82 83 84 85 86 87 88 89 9O 91 92 93 94 95 96 97 98 Total personal property taxes (S) Other taxes (S) Accountant and legal fees (S) Unallocated maintenance (S) Insurance cost on machinery and equipment (S) Miscellaneous fixed costs (S) Value of all crops held for sale at year end (S) Value of crops held under CCC loan at year end (S) Value of crops in farmer owned reserve at year end (S) Value of livestock held for breeding at year end (S) Value of livestock held for sale at year end (S) Annual outside capital invested (exogenously) in the farm (S) Per acre cash rent for cropland (S/acre) and other cash lease information Share rent, landlord’s share of crop receipts (fraction) Share rent, landlord’s share of seed costs (fraction) Share rent, landlord’s share of fertilizer and lime (fraction) Share rent, landlord’s share of chemicals (fraction) Share rent, landlord’s share of fuel and lube (fraction) Share rent, landlord’s share of machinery repairs (fraction) Share rent, landlord’s share of other production costs (fraction) Share rent, landlord’s share of custom work (fraction) Working file to be used for landlord’s share of costs Non-taxable income (S) Hours of unpaid family labor available for different size farms (hours) Minimum cash reserve held by the farm (S) Full-time farm labor annual salary per employee (S) Current age of the operator (years) Taxable income in years t-3 through t-l (S) Number of income tax exemptions (no.) Marginal income tax rate for computing state income taxes (fraction) Hours of unpaid family labor available to the farm each month (hours) Annual off-farm income (S) Total hours of labor required for the farm (hours) Hourly wage rate for part-time labor (S/hour) Minimum annual cash family living expenses (S) Average annual inflation rate for farmland (fraction) Average annual inflation rate for new farm equipment (fraction) Average annual inflation rate for used farm equipment (fraction) Average annual inflation rate for fixed costs such as insurance (fraction) Average annual inflation rate for seed costs (fraction) Average annual inflation rate for fertilizer and lime (fraction) Average annual inflation rate for chemical costs (fraction) Average annual inflation rate for fuel and lube costs (fraction) Average annual inflation rate for machinery repairs (fraction) Average annual inflation rate for other production costs such as ginning, drying, etc. (frac- tion) Average annual inflation rate for custom work (fraction) Consumer Price Index (1967 = 100) Average annual inflation rate for hired labor costs (fraction) Average annual inflation rate for value of off-farm investment (fraction) Average annual inflation rate for purchased inputs for livestock (fraction) Appreciation in the value of owned farmland (S) Appreciation in the value of owned machinery (S) Appreciation in off-farm investments (S) 150 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 Realized capital gains or losses (S) Depreciation and/or cost recovery recapture (S) Value of livestock purchased for resale (stocker steers) (S) Total cash receipts for crops and livestock (S) Off-farm income (S) j Total government deficiency and diversion payments (S) Total government disaster payments (S) Other farm income (S) Total cash receipts (S) Total variable production and harvest costs less labor costs (S) Total hired labor costs (S) Total cash rent for leased farmland (S) Total interest payment on all long-term debts (S) Total interest payment on all intermediate-term debts (S) Total principal payment on all long-term debts (S) Total principal payment on all intermediate-term debts (S) Personal income taxes paid (S) Total property taxes paid (S) Total fixed costs other than property taxes (S) Total family living expenses (S) Total cash expenses (S) Total net farm income (S) Total depreciation (S) Total net income after withdrawals (S) Self-employment tax (S) Total of all inventory adjustments minus depreciation (S) Value of home consumption (S) Total interest earned on cash reserves and dividends (S) Market value of all land and buildings (S) Market value of all farm machinery (S) Cash reserve at end of year (S) Change in the value of crops held for sale (S) Net cash farm income (S) Net farm income after withdrawals with unrealized capital gains (S) Change in the value of livestock held for breeding (S) Change in the value of crops held for resale (S) Total market value of other assets, as off-farm investments (S) Total market value of all assets (S) Total debt on all real property (S) Total debt on all farm machinery (S) Value of marketing certificates paid by the government (S) Total of all debts (S) Total net worth adjusted for unrealized capital gains, depreciation, contingent liabilities (S) Debt to asset ratio (fraction) Equity to assets ratio (fraction) Leverage ratio (fraction) Storage payments for farmer-owned reserve (S) Other adjustments to net farm income (S) Value of loan for the farmer-owned reserve (S) Total investable funds at year end (S) Total other income and off-farm income (S) Interest and storage payments (S) Breakeven cost of production for crop 1 (S/yield unit) Breakeven cost of production for crop 2 (S/yield unit) 151 153 154 155 156 157 15s 159 16o 161 162 165 164 165 166 167 16s 169 17o 171 172 173 174 175 176 177 17s 179 1so 1s1 1s2 1s3 1s4 1s5 1s6 1s7 1ss 1s9 19o 191 192 19s 194 195 196 197 19s 199 .200 201 Breakeven cost of production for crop 3 ($/yield unit) Breakeven cost of production for crop 4 ($/yield unit) Breakeven cost of production for crop 5 (S/yield unit) Breakeven cost of production for crop 6 ($/yield unit) Breakeven cost of production for crop 7 ($/yield unit) Breakeven cost of production for crop 8 ($/yield unit) Breakeven cost of production for crop 9 ($/yield unit) Breakeven cost of production for crop l0 ($/yield unit) Lease costs for farm machinery (S) Cash outlay to purchase equipment leased previously (S) Proceeds from the sale of previously leased machinery ($) Difference between proceeds and cost of selling previously leased machinery ($) Surplus cash used to retire debts ($) Total of other income ($) Total income and cash in cash flow statement ($) Value of farm program crops for scaling farm program benefits ($) Value of machinery purchased for replacement ($) Value of machinery purchased for growth ($) Total production of crop l that can be sold by the operator (yield units) Total production of crop 2 that can be sold by the operator (yield units) Total production of crop 3 that can be sold by the operator (yield units) Total production of crop 4 that can be sold by the operator (yield units) Total production of crop 5 that can be sold by the operator (yield units) Total production of crop 6 that can be sold by the operator (yield units) Total production of crop 7 that can be sold by the operator (yield units) Total production of crop 8 that can be sold by the operator (yield units) Total produciton of crop 9 that can be sold by the operator (yield units) Total production of crop 10 that can be sold by the operator (yield units) Production of crop 1 sold in the year it is produced (yield units) Production of crop 2 sold in the year it is produced (yield units) Production of crop 3 sold in the year it is produced (yield uinits) Production of crop 4 sold in the year it is produced (yield units) Production of crop 5 sold in the year it is produced (yield units) Production of crop 6 sold in the year it is produced (yield units) Production of crop 7 sold in the year it is produced (yield units) Production of crop 8 sold in the year it is produced (yield units) Production of crop 9 sold in the year it is produced (yield units) Production of crop l0 sold in the year it is produced (yield units) Production of crop 1 sold in the next tax year (yield units) Production of crop 2 sold in the next tax year (yield units) Production of crop 3 sold in the next tax year (yield units) Production of crop 4 sold in the next tax year (yield units) Production of crop 5 sold in the next tax year (yield units) Production of crop 6 sold in the next tax year (yield units) Production of crop 7 sold in the next tax year (yield units) Production of crop 8 sold in the next tax year (yield units) Production of crop 9 sold in the next tax year (yield units) Production of crop 10 sold in the next tax year (yield units) Crop enterprise (1) cost information (1) Name of enterprise (2) Name of enterprise (3) Name of enterprise (4) Seed costs per planted acre ($/acre) (5) Fertilizer and lime costs per planted acre (S/acre) 152 202 203 204 205 206 207 208 209 210 21 1 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 (6) Chemical costs per planted acre (S/acre) (7) Fuel and lube costs per planted acre (S/acre) (8) Machinery repair costs per planted acre (S/acre) (9) Other production costs per planted acre (S/acre) (10) Harvesting costs per unit of production (S/production unit) (11) Blank (12) Planted acres for year 1 (acres) (13) Harvested acres for year 1 (acres) (14) Blank (15) Minimum acceptable fraction of crop in the crop mix (fraction) (16) Maximum acceptable fraction of crop in the crop mix (fraction) (17) Link to another crop for double cropping (crop number) (18) Fraction of planted acres that are normally harvested (fraction) (19) Inventory of crop being held for sale in year 1 (yield units) (20) Fraction of crop normally held for sale in the next crop year (fraction) (21) Calendar month sell the new crops production after production, as 11.0, 12.0, 1.0, (22) Calendar month sell portion of crop held in storage for next tax year,as 2.0, 3.0, (23) Total cash cost per acre (S/acre) Crop enterprise (2) cost information Crop enterprise (3) cost information Crop enterprise (4) cost information Crop enterprise (5) cost information Crop enterprise (6) cost information Crop enterprise (7) cost information Crop enterprise (8) cost information Crop enterprise (9) cost information Crop enterprise (10) cost information Planted acres for crop enterprise (1) Planted acres for crop enterprise (2) Planted acres for crop enterprise (3) Planted acres for crop enterprise (4) Planted acres for crop enterprise (5) Planted acres for crop enterprise (6) Planted acres for crop enterprise (7) Planted acres for crop enterprise (8) Planted acres for crop enterprise (9) Planted acres for crop enterprise (10) Harvested acres for crop enterprise (1) Harvested acres for crop enterprise (2) Harvested acres for crop enterprise (3) Harvested acres for crop enterprise (4) Harvested acres for crop enterprise (5) Harvested acres for crop enterprise (6) Harvested acres for crop enterprise (7) Harvested acres for crop enterprise (8) Harvested acres for crop enterprise (9) Harvested acres for crop enterprise (10) Stochastic yield (units/harvested acre) for enterprise (1) Stochastic yield (units/harvested acre) for enterprise (2) Stochastic yield (units/harvested acre) for enterprise (3) Stochastic yield (units/harvested acre) for enterprise (4) Stochastic yield (units/harvested acre) for enterprise (5) 153 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 Stochastic yield (units/harvested acre) for enterprise (6) Stochastic yield (units/harvested. acre) for enterprise (7) Stochastic yield (units/harvested acre) for enterprise (8) Stochastic yield (units/harvested acre) for enterprise (9) Stochastic yield (units/harvested acre) for enterprise (10) Stochastic season average prices (S/unit) for enterprise (1) Stochastic season average prices (S/unit) for enterprise (2) Stochastic season average prices (S/unit) for enterprise (3) Stochastic season average prices (S/unit) for enterprise (4) Stochastic season average prices (S/unit) for enterprise (5) Stochastic season average prices (S/unit) for enterprise (6) Stochastic season average prices (S/unit) for enterprise (7) Stochastic season average prices (S/unit) for enterprise (8) Stochastic season average prices (S/unit) for enterprise (9) Stochastic season average prices (S/unit) for enterprise ( 10) Total farm machinery depreciation (S) Average yield (unit/harvested acre) for enterprise (1) Average yield (unit/harvested acre) for enterprise (2) Average yield (unit/harvested acre) for enterprise (3) Average yield (unit/harvested acre) for enterprise (4) Average yield (unit/harvested acre) for enterprise (5) Average yield (unit/harvested acre) for enterprise (6) Average yield (unit/harvested acre) for enterprise (7) Average yield (unit/harvested acre) for enterprise (8) Average yield (unit/harvested acre) for enterprise (9) Average yield (unit/harvested acre) for enterprise (10) Season average price (S/unit) received by farmers for enterprise (1) and seasonal price index Season average price (S/unit) received by farmers for enterprise (2) and seasonal price index Season average price (S/unit) received by farmers for enterprise (3) and seasonal price index Season average price (S/unit) received by farmers for enterprise (4) and seasonal price index Season average price (S/unit) received by farmers for enterprise (5) and seasonal price index Season average price (S/unit) received by farmers for enterprise (6) and seasonal price index Season average price (S/unit) received by farmers for enterprise (7) and seasonal price index Season average price (S/unit) received by farmers for enterprise (8) and seasonal price index Season average price (S/unit) received by farmers for enterprise (9) andseasonal price index Season average price (S/unit) received by farmers for enterprise (10) and seasonal price index Cash receipts from sale of old equipment, cows, and bulls (S) Total variable cost of production (S) for crop enterprise (l) Total variable cost of production (S) for crop enterprise (2) Total variable cost of production (S) for crop enterprise (3) Total variable cost of production (S) for crop enterprise (4) Total variable cost of production (S) for crop enterprise (5) Total variable cost of production (S) for crop enterprise (6) Total variable cost of production (S) for crop enterprise ( 7) Total variable cost of production (S) for crop enterprise (8) Total variable cost of production (S) for crop enterprise (9) Total variable cost of production (S) for crop enterprise (10) Total cash receipts (S) for crop enterprise (1) Total cash receipts (S) for crop enterprise (2) Total cash receipts (S) for crop enterprise (3) Totaz cash receipts (S) for crop enterprise (4) Total cash receipts (S) for crop enterprise (5) Total cash receipts (S) for crop enterprise (6) Total cash receipts (S) for crop enterprise (7) 154 290 291 292 293 294 29s 296 297 29s 299 300 301 302 303 304 30s 306 307 30s 309 310 311 312 313 314 31s 31s 317 31s 319 320 321 322 323 324 32s 320 327 32s 329 330 331 332 333 334 33s 33s 337 33s 339 340 341 342 343 Total cash receipts (S) for crop enterprise (8) Total cash receipts (S) for crop enterprise (9) Total cash receipts (S) for crop enterprise (10) Work file for insolvent years; 1.0 if insolvent, 0.0 if solvent Contingent liabilities (S) Appreciation, the year machinery is sold (S) Disposable income available for consumption (S) Total interest paid for new long-term debts (S) Total principal paid for new long-term debts (S) Total interest paid for new intermediate-term debts (S) Total principal paid for new intermediate-term debts (S) Amount of new long-term debt in year 1 and principal due (S) Amount of new long-term debt in year 2 and principal due (S) Amount of new long-term debt in year 3 and principal due (S) Amount of new long-term debt in year 4 and principal due (S) Amount of new long-term debt in year 5 and principal due (S) Amount of new long-term debt in year 6 and principal due (S) Amount of new long-term debt in year 7 and principal due (S) Amount of new long-term debt in year 8 and principal due (S) Amount of new long-term debt in year 9 and principal due (S) Amount of new long-term debt in year l0 and principal due (S) Amount of new intermediate-term debt in year 1 and principal due (S) Amount of new intermediate-term debt in year 2 and principal due (S) Amount of new intermediate-term debt in year 3 and principal due (S) Amount of new intermediate-term debt in year 4 and principal due (S) Amount of new intermediate-term debt in year 5 and principal due (S) Amount of new intermediate-term debt in year 6 and principal due (S) Amount of new intermediate-term debt in year 7 and principal due (S) Amount of new intermediate-term debt in year 8 and principal due (S) Amount of new intermediate-term debt in year 9 and principal due (S) Amount of new intermediate-term debt in year 10 and principal due (S) Risk rating value (integers 7-28) Total debits in cash flow table (S) Value of straight-line depreciation of machinery (S) Maximum family living expenses (S) Value of deficit used to calculate leverage ratio when insolvent (S) Total variable production costs for livestock enterprise (1) (S) Total variable production costs for livestock enterprise (2) (S) Total variable production costs for livestock enterprise (3) (S) Total variable production costs for livestock enterprise (4) (S) Total variable production costs for livestock enterprise (5) (S) Average price received for cull cows (S/lb) Average price received for females (heifers) (S/lb) Average price received for males (steers) (S/lb) Average price for valuing replacement females (S/lb) Average price for valuing herd sires (S/lb) Average price received for livestock enterprise (4) (S/lb) Average price received for livestock enterprise (5) (S/lb) Stochastic price for cull cows (S/lb) Stochastic price for females sold (S/lb) Stochastic price for young males sold (S/lb) Stochastic price for value of replacement females (S/lb) Stochastic price for herd sires culled (S/lb) Stochastic price for livestock enterprise (4) (S/lb) 155 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 Stochastic price for livestock enterprise (5) (S/lb) Cash receipts for sale of heifers and steers ($) Cash receipts for sale of culled ‘cows, old herd sires, and culled replacement heifers after 1 to 1.5 years ($) Unadjusted net worth ($) Cash receipts for livestock enterprise (4) (S) Cash receipts for livestock enterprise (5) (S) Stocks placed under quota loan Stocks placed under non-quota loan Risk aversion coefficient Fraction of the original real estate loan to be repaid (fraction) Marginal propensity to consume intercept for consumption function Updated intercept for consumption function (S) Maximum interest deduction per year ($) Working array for availability of crop land (1) After-tax capitalization rate (fraction) (2) Smallest no. of acres available for purchase, as 80.0 (3) Next larger no. of acres available for purchase, as 160.0 (4) Next larger no. of acres available for purchase, as 200.0 (5) Largest no. of acres available for purchase, as 320.0 (6) Smallest no. of acres available for lease, as 80.0 (7) Next larger no. of acres available for lease, as 160.0 (8) Next larger no. of acres available for lease, as 320.0. (9) Largest no. of acres available for lease, as 640.0 (10) Probability for smallest no. of acres available for purchase (fraction) (11) Probability for next larger no. of acres available for purchase (fraction) (12) Probability for next larger no. of acres available for purchase (fraction) (13) Probability for larger no. of acres available for purchase (fraction) (14) Probability for largest no. of acres available for purchase (fraction) (15) Probability for next smallest no. of acres available for lease (fraction) (16) Probability for next larger no. of acres available for lease (fraction) (17) Probability for next larger no. of acres available for lease (fraction) (18) Probability for next largest no. of acres available for lease (fraction) Appreciation in market value of owned pastureland ($) Cash lease cost for pastureland (S) Number of acres available for purchase that the farm can afford to buy (acres) Number of acres available for lease (acres) Per acre value of cropland (S/acre) Bid price for purchasing farmland (S/acre) Opportunity cost of farm machinery (S) Cost of purchased breeding stock ($) Total cost recovery for purchased breeding stock (S) Depreciation for buildings and other improvements on the land ($) Annual value of raised breeding livestock added to the herd (S) Annual inflation rate in the market value of buildings (fraction) Debt service coverage ratio (fraction) Earned equity growth trend (fraction) Collateral ratio (fraction) 1 if parcel no. 1 is available for purchase, 0 otherwise 1 if parcel no. 2 is available for purchase, 0 otherwise 1 if parcel no. 3 is available for purchase, 0 otherwise 1 if parcel no. 4 is available for purchase, 0 otherwise 1 if parcel no. 1 is available for purchase. 0 otherwise 1 if parcel no. 2 is available for purchase, 0 otherwise 156 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 41 1 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 1 if parcel no. 3 is available for purchase, 0 otherwise 1 if parcel no. 4 is available for purchase, 0 otherwise Rate of return on non-farm investments for calculating annual dividend payments (fraction) Dividends from off-farm investments (S) Beginning net worth for the farm (S) Downpayment for breeding stock purchased during the year (S) Net farm income less changes in inventories and raised livestock (S) Depreciation recapture on personal property (S) Value of home consumption of farm production, valued at cost (S) Net section 1231 losses (S) Total taxable off-farm income (S) Total taxable farm income (S) (adjusted gross income) Total personal exemptions (S) Ratio of personal itemized deductions to net farm income ( (fraction) Excess itemized personal deductions (S) Taxble dividends less the S200 exclusion (S) Taxable income for farm operator (S) Base period averagable income (S) Income eligible for income averaging (S) Tax liability calculated using income averaging (S) Tax liability calculated using the regular tax computation (S) ITC for new machinery purchased for growth Estimated tax payments during the year (S) Per acre value of pastureland (S) Investment tax credit for purchase of new machinery (S) Tax preference income on capital gains (S) Alternative minimum tax base (S) Alternative minimum tax (S) Total income tax liability (Federal and State) (S) Total interest paid other than to CCC (S) Total interest deduction if maximum is in place (S) Taxable income in excess of the 50 percent tax bracket (S) Tax on personal service income in excess of the 50 percent tax bracket (S) Minimum of regular tax and income averaging (S) Tax on personal service income (S) Tax on difference between the maximum tax and the regular tax (S) Landlord’s cost for harvesting crops (S) Income tax liability paid in year i and accrued in year j (S) Self-employment tax paid in year i and accrued in year j (S) Income subject to self-employment tax (S) Hours worked per month by full-time hired employees (hours) Total expensing (S) Average marginal tax rate - 3-year moving average (fraction) Investment tax credit on new machinery and livestock (S) Cost recovery on new machinery and livestock (S) First year cost recovery on new machinery and livestock (S) Additional investment tax credit carryforward when alternative minimum tax is used (S) Net operation loss carryforward (S) Total non-business deductions (S) Excess of non-business deductions over non-business income (S) Investment tax credit carryforward (S) Crop mix for year i if Option 9 is equal to 1 (acres) Expected net cash receipts per acre for crop 1 (S) Expected net cash receipts per acre for crop 2 (S) 157 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 Expected net cash receipts per acre for crop 3 (S) Expected net cash receipts per acre for crop 4 (S) Expected net cash receipts per acre for crop 5 (S) Expected net cash receipts per acre for crop 6 (S) Expected net cash receipts per acre for crop 7 (S) Expected net cash receipts per acre for crop 8 (S) Expected net cash receipts per acre for crop 9 (S) Expected net cash receipts per acre for crop 10 (S) Accumulated contingent depreciation recapture taxes (S) Taxable income of farm operator when new machinery is purchased (S) Tax liability after new machinery purchase (S) Self-employment tax rate (fraction) Maximum level of net farm income subject to self-employment tax (S) State income taxes (S) Decrease in taxes when new machinery is purchased (S) Contingent capital gains taxes (S) Contingent depreciation recapture taxes (S) Accumulated contingent recapture taxes (S) Market value of fully cost recovered machinery kept on the farm (S) Total value of crop receipts paid to landlord (S) Expected price of crop (S/unit) Expected yield of crop (S/qnit) Downpayments for additional land and machinery in growth phase (S) Work file for purchasing and leasing cropland Work file for purchasing and leasing cropland Income tax payment, state and federal due in year 1 (S) Self-employment tax payment due in year 1 (S) Acres sold to avoid insolvency (acres) Value of acres sold to avoid insolvency (S) Basis for cropland sold (S) Capital gains tax on sale of land (S) Tillable cropland available to the farm (acres) Fraction of cropland that is tillable (fraction) Predetermined acreage available for purchase (acres) Predetermined acreage available for lease (acres) Premium cost for federal crop insurance program (S) Indemnity payment for the crop insurance program (S) Crop and dairy cash receipts (S) Livestock cash receipts (S) Long-term equity ratio (fraction) Intermediate-term equity ratio (fraction) Current ratio (fraction) Net present value (S) Internal rate of return (fraction) Percentage change in net worth from year to year (percentage) Borrowing to meet cash flow deficits (S) Additional first year depreciation for machinery (S) Average length of a short-term loan (fraction) Interest costs for annual operating loans (S) Linear programming constraint for irrigated land and fraction of cropland irrigated (fraction) Work array for the LP Work array for the LP Work array for the LP First year expensing for the year purchased (S) 158 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 51 1 512 513 514 515 516 51 7 518 519 520 521 Depreciation recapture adjustment when market price is less than original purchase price at sale time (S) Expected capital gains rate for farmland (fraction) Work array for calculating expected capital gains for farmland (fraction) Rate of return to production assets (fraction) Total value of production assets (S) Total return to production assets (S) Net value of a crop share lease (S) Capital gains rate for cropland (fraction) Returns to family labor and management (S) Expected net, after tax cash flows per acre (S) Production costs paid by a landlord for a crop share lease (S) Expected rate of return to production assets (fraction) Annual interest rates for outstanding livestock loans (fraction) Annual interest rates for outstanding long-term debts (fraction) Annual interest rates for outstanding‘intermediate-term debts (fraction) Annual interest rates for new long-term debts (fraction) Annual interest rates for new intermediate-term debts (fraction) Annual interest rates for refinancing long-term debts (fraction) Annual interest rates for refinancing intermediate-term debts (fraction) Annual interest rates for operating loans (fraction) Annual interest rates received for cash reserves (fraction) Reserved for additional interest rates Reserved for additional interest rates Reserved for additional interest rates New buildings to be recovered (purchase price and year purchased) Special buildings to be recovered (purchase price and year purchased) Capital recovery for regular buildings (S) Capital recovery for special purpose buildings (S) Landlord costs by crop enterprise (S) Crop share lease by crop enterprise (S) Cash lease costs by crop enterprise (S) Other fixed costs by crop enterprise (S) Interest and storage costs for government price support programs, by crop (S) Labor costs by crop enterprise (S) First machinery item, rows of each machinery column are: (1). Name of machine (2). Name of machine (3). Name of machine (4). Depreciation life for pre-1980 equipment (no.) (5). Current market value, updated annually (S) (6). Market value at purchase (or basis if traded in) (S) (7). Salvage value for pre-1980 equipment (S) or inflated basis for post—1985 equip- ment (S) (8). Current basis (initial cost less accumulated depreciation) for equipment (S) (9). Amount of first year expensing (or depreciation) (S) (10). Asset value of equipment (S) (11). Updated market value (S) (12). Appreciation or loss in market value during year i (S) (13). Accumulated capital recovery or depreciation (S) (14). Realized capital gain (S) (15). Depreciation recapture (S) (16). Economic life in years (no.) (17). Beginning value of equipment (S) 159 (1s). (19). (20). (21). (22). (23). (24). (25). (26). Annual depreciation or cost recovery ($) Replacement code for equipment (no.) Machinery purchased for investment credit (S) Calendar year equipment is placed into use on farm (no.) Current age for replacement and recovery purposes (no.) F irst-year expensing (S) Value of a replacement in year 0 ($) Number of years for cost recovery (no.) or depreciation class Investment tax credit (ITC) ($) 522 Second machinery item, rows are the same as for 521 523 Third machinery item, rows are the same as for 521 620 One hundredth machinery item 621-640 Files reserved for additional purchases of machinery during the planning horizon for growth 641 First leased farm machinery item, rows of the column are: (1)- (2)- (3)- (4). (5)- (6)- (7)- (s). (9)- (10). (11). (12). (13). (14). (15). (16). (17). (18). (19). (20). (21). (22). (23). (24). (25). Name of the machine Name of the machine Name of the machine Value of machine when lease was initiated ($) Current market value of machine ($) Cost of a machine to replace the machine now ($) The calendar year the lease was initially leased (year) Length of the lease, no. of years (no.) Established market value of machine at end of lease (fraction) Lease cost, as a fraction of total purchase price paid annually to leasor (0.18) Disposition code for the machine (0.0, 1.0, ...) after the lease. Economic life of the machine in years (no.) Number of years to recover if purchased at end of lease (no.) Replacement code if machine is owned and disposed of at end (no.) Number of years for the lease (no.) Updated market value of the machine (S) Expected value of machine at end of lease (5) Annual lease cost (S) Contribution of current machine to downpayment or lease of replacement (S) Accumulated lease payments in simulation period 642 Second leased machine. 759 Last. machinery item leased. 160 SUMMARY OF THE B(I,J) MATRIX THE BEEF CATTLE WORKSPACE FOR THE MODEL Annual data are stored in the rows (I) of the B matrix for years one through ten. Each col- umn (J) of the B matrix represents a separate variable in the model. J Description of Variables 1 Replacement strategy information for livestock: ( 1). Average calving fraction, as 0.95 (2). Average death loss of calves after birth, as 0.05 (3). Average fraction of heifers kept for replacement herd, as 0.20 (4). Average fraction of replacement heifers sold between 1 and 2 years of age, as 0.10 (5). Average fraction of cows culled each year, as 0.20 2 Average price received for culled replacement heifers ($/head) 3 Average price paid for replacement cows ($/head) 4 Average price paid for herd sires ($/head) 5 Average sale weight of heifer calves (lb) 6 Average sale weight of bull calves (lb) 7 8 Value of mother cows in herd ($) 9 Value of bred heifers in the herd ($) 10 Value of bulls in the herd ($) 11 Number of cows in the herd 12 Number of bred heifers in the replacement herd 13 Number of bulls in the herd 14 Number of stocker steers 15 Number of feeder steers 16 Number of bull calves born and sold 17 Number of heifer calves born 18 Number of heifer calves sold 19 Number of heifer calves to enter replacement herd 20 Number of yearling replacement heifers sold 21 Number of cows culled 22 Number of cows needed to buy or sell to maintain herd size 23 Number of cows bought 24 Number of cows sold or culled 25 Cash receipts for cull bulls ($) 26 Cash receipts for cull cows ($) 27 Cash receipts for replacement heifers sold ($) 28 Cash receipts for heifer calves sold ($) 29 Cash receipts for bull calves sold ($) 30 Cash receipts for stockers sold ($) 31 Cash receipts for feeder steers sold ($) 32 Total beef cattle cash receipts ($) 33 Cost of replacement heifers bought ($) 34 Cost of bulls bought (S) 35 Downpayment for culls and cows purchased ($) 36 Cost of stocker steers purchased ($) 37 Cost of feeder steers purchased ($) 38 Number of bulls adjusted for desired herd size 39 Number of bulls bought 40 Number of bulls sold and culled from herd 161 41 42 43 44 45 46 47 48 49 5O Number of cows sold that had been purchased initially Number of bulls sold that had been purchased initially Larger of number of cows culled and number of cows that had been depreciated and were too old to keep Annual feed requirements for cows Annual feed requirements for heifers Annual feed requirements for bulls Annual feed requirements for stocker steers Annual feed requirements for feeder steers Value of other livestock (S) 51-100 Beef cattle depreciation (cost recovery) (1)- Name of the beef animal and year (2). Name of the beef animal and year (3)- Name of the beef animal and year (4). Depreciation life for pre-1980 cattle (no.) (5)- (6)- (7)- (s). Current market value of animals Market value at purchase (or basis if traded in) (S) Salvage value for the cattle (S) Current basis for the cattle (S) (9). Amount of first year expensing (S) (10). Asset value of cattle (S) (11). Updated market value (S) (12). Appreciation or loss in value during year (S) (13). Accumulated capital recovery or depreciation (S) (14). (15). (16). Realized capital gain (S) Depreciation recapture (S) Economic life in years (no.) (17). Beginning value of cattle (S) (18). Annual depreciation or cost recovery (S) (19). Work file for first year expensing (20). (21). (22). Purchase for investment tax credit (S) Calendar year cattle were put into herd (no.) Current age for replacement and recovery purposes (no.) (23). First year expensing (S) (24). Value of replacement stock based on market value (S) (25). Number of years for cost recovery (no.) (3, 5 or 10) (26). Sex, ’l.0’ if cows, and ’0.0’ if bulls (27). Number of herd in this cost recovery unit (or file) 106-110 Livestock production enterprises (cows, replacements, bulls, stockers and feeders) ( 1). Name (2). Name (3). Name (4). Beginning market value for all animals in the enterprise (S) (5)- (6)- (7). (3)- (9). Average sale weight (lb) Annual herd cash costs (non-labor and interest) for inputs (S/head) Annual death loss (fraction) Inflated cost per head for input costs (S/head) Total cost of production for n head (S) 162 SUMMARY OF THE D(I,J) MATRIX THE DAIRY CATTLE WORKSPACE FOR THE MODEL Annual data are stored in the rows (I) of the D matrix for years one through ten. Each col- umn (J) of the matrix represents a separate variable in the model. J Description of Variables 1-12 Number of cows milked each month in years 1-10 13-24 Number of dry cows fed each month in years 1-10 25-36 Number of replacement heifers each month in years 1-10 37-48 Number of dairy cows fed each month in years 1-10 (1). Fraction of milk cows replaced with purchased cows annually (2). Fraction of milk cows culled annually (3). Fraction of calves that are normally sold each year, 0.50 (4). (5). Calving percentage, as 0.95 (6). Death loss for 0 to 1 calves, as 0.20 (7). Fraction of replacement heifers raised that are sold under 2 years old, as 0.10 49 Number of cows bought as replacements 50 Information for herd replacement strategy 51 Average annual price received for milk (S/cwt) 52 Average annual price received for culled cows (S/head) 53 Average annaul price paid for replacement cows (S/head) 54 Average annual price received for calves (S/head) 55 Seasonal price index received for milk (fraction by month) 56 Average annual production of milk (cwt) 57 Seasonal milk production index (fraction) 58 Feed cost index (1.0) 59 Stochastic annual price received for milk (S/cwt) 60-71 Stochastic monthly average milk prices (S/cwt) 72 Stochastic price received for culled cows (S/head) 73 Stochastic price paid for replacements (S/head) 74 Stochastic price received for calves (S/head) 75 Stochastic milk production per cow by year (cwt/head) 76 Stochastic milk production per cow by month (cwt/head/mo.) 77 Stochastic feed cost index (fraction) 78 79 80 Purchased replacement cows (1). Number purchased (2). Number of years a cow is used (no.) (3). Price per head for replacement cows (S) (4). (5)- (6). Annual depreciation (S) (7). Accumulated depreciation (S) (8). Original purchase price of cows (S) (9)). Salvage value (S) (Basis for 1985 Act) (10 . Calendar year plan to sell the cows (11). Calendar year purchased (12). (13). Replacement value of cows (S) 163 81-91 92-103 104-115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 (14). Receipts from sale of culled cows (S) (15). First year expensing (S) (16). Number of years for cost recovery (no) Replacement cows purchased in years 1-10 Total milk production by year in each month (Jan., Feb., ..., Dec.) Total milk cash receipt by year for each month (Jan., Feb., ..., Dec.) Average production of milk per cow for each month (cwt/head/mo.) Total annual milk production (cwt) Work file Added feed costs for livestock (S) Milk cash receipts (S) Cash receipts from selling calves (S) Cash receipts for culled cows (S) Total cash receipts from milk and calves (S) Receipts from selling old bulls (S) Receipts for old bulls and old cows (S) Downpayments for cows and bulls purchased (S) Cost of replacement cows purchased (S) Cost of replacement bulls (S) Number of heifer calves died Number of 1 1/2-year-old replacements sold Number of replacements raised that entered the herd A milk cows feed costs, vet costs, nonlabor, noninterest costs per head per year (S/head) A dry cow’s feed costs, vet costs, nonlabor, noninterest costs per head per year (S/head) A heifer’s feed costs vet costs, nonlabor, noninterest costs per head per year (S/head) A calf’s feed costs, vet costs, nonlabor, noninterest costs per head per year (S/head) A bull’s feed costs, vet costs, nonlabor, noninterest costs per head per year (S/head) Total nonlabor, noninterest costs of production for dairy (S) Number of cows buy or sell due to growth or contraction of head size (no.) Monthly labor required per head of milking cows (hours) Monthly labor required per head of dry cows (hours) Monthly labor required per head of replacement heifers (hours) Monthly labor required per head of calves (hours) Total labor requirements per month (hours) Number of calves sold (bull calves) Number of calves kept for replacement herd Number of calves born each year Number of heifers in replacement herd Number of cows of milking age Number of cows culled Value of cows over 2 years of age (S) Value of calves kept for replacement (S) Total value of milk stock and bulls (S) Herd sires purchased before 1981 (1). Number of herd sires (2). Number of years a sire is used depreciation life pre-1981 (no.) (3). Average purchase price (S/head) (4). Average age when purchased (no.) (5). Sale price of cull bulls (S/head) 164 (6). Annual depreciation (S) (7). Accumulated depreciation (S) (8). Original purchase price for all bulls (S) (9). Salvage value (S) (Basis for 1985 Act) (10). Year sires are to be replaced (11). Calendar year purchased (12). Updated market value (S) (13). Replacement price of bulls today (S) (14). Receipts from sale of old bulls (S) (15). First year expensing (16). Number of years for cost recovery 157-168 Bulls purchased after 1980 169 Number of bulls 170 Value of bulls (S) 171-180 Intermediate-term debts for replacement of cows and bulls (S) 181-186 Factored covariance (correlation matrix) for dairy enterprises 187 Total dairy receipts (S) 188 Receipts per cow (S/cow) 189 Costs per cow (S/cow) 190 Variable costs breakeven price (S/cwt) 191 Total costs breakeven price (S/cwt) 192 Feed requirements for cows 193 Feed requirements for heifers 194 Feed requirements for calves 195 Feed requirements for bulls 196-205 Annual feed requirements by livestock for crop enterprises 1, 2, 3..., 10. 206-215 Deficit or surplus feed crop enterprise 1, 2, ..., 10. 165 SUMMARY OF THE E(I,J) MATRIX THE FARM POLICY DATA For each of the crops a separate file (column J) is used to hold annual policy data. Years are stored in the rows of the matrix (I) and the crops (J) are in the same order as provided by the user on Card 22. J Description of Variables 1-10 Commodity Credit Corporation (CCC) loan rate (S/unit of yield) 11-20 Target price (S/unit of yield) 21-30 Direct farmer owned reserve (FOR) entry price (S/unit of yield) 31-40 Farm program yields (unit of yield/acre) 41-50 Fraction of planted acres set-aside, diverted, or limited (fraction) 51-60 Program or base acreage used for target price calculations (acres) 61-70 National allocation factor for deficiency payment calculations (fraction) 71-80 Payment rate per acre for voluntary diversion (S/acre) 81-90 Trigger price for farmer owned reserve (S/unit of yield) 91-100 Call price for farmer owned reserve (S/unit of yield) 101-110 Storage payment rates per unit for stocks in the farmer owned reserve (S/unit of yield) 111-120 Fraction of target price to compute low yield payments (fraction) 121-130 Fraction of target price to compute prevented plantings payment (fraction) 131-140 Fraction of proven yield to compute low yield payments (fraction) 141-150 Fraction of proven yield to compute prevented plantings payment (fraction) 151-160 Length of farmer owned reserve (years) 161-170 Quantity of stocks under nonrecourse CCC loan (units) 171-180 Quantity of stocks under farmer owned reserve (units) 181-190 Deficiency payments (S) 191-200 Value of the loan under the nonrecourse CCC loan program (S) 201-210 Disaster payment for low yields (S) 211-220 Voluntary diversion payments (S) 221-230 Disaster payment for prevented plantings (S) 231-240 Storage payments received for farmer owned reserve (S) 241-250 Interest costs for stocks in the farmer owned reserve (S) 251-260 Storage and interest costs for stocks under CCC loan program (S) 261-270 Value of stocks in the regular farmer owned reserve (S) 271-280 Value of the loan in a direct farmer owned reserve (S) 281-290 Ratio of acreage allotment and harvested acreage (S) 291-300 Required acreage removed from production (fraction) 301 Annual income support payment limitation (S) 302 Annual interest rate for CCC stocks (fraction) 303 Annual disaster payment limitation (S) 304 305 Information to scale farm program benefits (acres and S) 306 Annual inflation rate for CCC storage costs (fraction) 307 Annual interest rate for FOR loan (fraction) 308 FCIC history of program participation, rows are: (1). Number of years in the insurance program (no.) (2). Number of loss years in past 15 years (no.) (3). Total insurance premiums paid in past 15 years (S) (4). Total indemnity payments received in past 15 years (S) (5). Loss ratio for previous year (fraction) (6). Adjustment in per acre premium from losses or good yield records (fraction) 166 309 310 311-320 321-330 331-340 341-350 351-360 361-370 371-380 381-390 391-400 401-410 411-420 421-430 431-440 441-450 451-460 461-470 471-480 481-490 491-500 501-510 511-520 521-530 531-540 541-550 551-560 561 562 563 564 565 566-570 571-580 581-590 591-600 601-610 611-620 FCIC loss ratio (fraction) FCIC indemnity payments by crop (S) Loan rate for peanuts produced under quota (S/yield unit) Loan rate for peanuts not produced under quota (S/yield unit) Farm peanut pouridage quota (total yield units) Acreage allotment for crops when payments and price supports apply to alloted acreage (acres) Value of stocks in CCC loan (S) Value of stocks in FOR (S) Value of stocks in direct FOR (S) Base acreage for acreage limitation (acres) Production guarantee for all-risk crop insurance (yield unit/acre) Price election for all-risk crop insurance (S/yield unit) Premium rate for all-risk crop insurance (S/acre) FCIC insurance payment for lost yield (S) Annual storage cost for commodities under CCC loan in commercial storage (S/yield unit) Average crop price for the first 12 months in marketing year (S/yield unit) Slippage rates for each crop (fraction) Price for marketing certificate (S/yield unit) Fraction of crop eligible for marketing certificate (fraction) Eligible production (quantity) Marketing certificate support payment (S) Slippage acres for set aside by crop (acres) Maximum nonrecourse CCC loan for each crop (S) Quantity of stocks under recourse CCC loan Value of stocks under recourse CCC loan Flexible loan rate information Flexible target prices, tied to loan rates Fraction of base production eligible for deficiency payment Maximum value of base production deficiency payment (S) Reduction in government payments (fraction) Total marketing loan payment (S) Total of the unlimited deficiency (Findley) payment (S) Blank Marketing loan rates by crop (S/yield unit) Total production sold for marketing loan by crop (yield units) Marketing loan payment by crop (S) Formula loan rates by crop for Findley payment (S/yield unit) Findley payment by crop (S) 167 SUMMARY OF THE F (I,J) MATRIX COST OF PRODUCTION FOR ALTERNATIVE FARM SIZES J Description of Variables 1-10 Costs of production per acre by crop enterprise for initial farm size ($/acre) 11-20 Costs of production per acre by crop enterprise for first alternative farm size (S/acre) 21-30 Costs of production per acre by crop enterprise for second alternative farm size (S/acre) 31-40 Costs of production per acre by crop enterprise for third alternative farm size (S/acre) 41-50 Costs of production per acre by crop enterprise for fourth alternative farm size (S/acre) 51-60 Costs of production per acre by crop enterprise for fifth alternative farm size (S/acre) 61-70 Costs of production per acre by crop enterprise for sixth alternative farm size (S/acre) 71-80 Costs of production per acre by crop enterprise for seventh alternative farm size ($/acre) 81-90 Costs of production per acre by crop enterprise for eighth alternative farm size ($/acre) 91-100 Costs of production per acre by crop enterprise for ninth alternative farm size (S/acre) 101-110 Costs of production per acre by crop enterprise for tenth alternative farm size (S/acre) 111 Cultivated acreages for initial and alternative farm sizes (acres) 112 Value of additional machinery for alternative farm sizes (S) 113 Hours of family labor available per year for initial and alternative farm sizes (hours) 114 Average annual off-farm income for initial and alternative farm sizes (S) 115 Number of full-time employees for initial and alternative farm sizes (no.) 116 Annual salary for a full-time employee (S) 117-120 Blank 121-130 Actual crop yields for past 5 years on all crops 131-140 Actual crop prices for past 4 years on all crops. 168 SUMMARY OF THE FC, FC2, AND FC3 MATRICES The FCIC all-risk crop insurance program originally contained a provision to increase or decrease a farmer’s premium rate based on past history in the program. The rate schedules for adjusting the premium are data initialized in matrices FC, F C2, and FC3. Each column of a matrix is a separate risk bracket and the matrix rows are for the different years of history in the program. J Description of Variables FC (1) Loss ratio bracket of 0.0 to 0.20 PC (2) Loss ratio bracket of 0.21 to 0.40 PC (3) Loss ratio bracket of 0.41 to 0.60 F C (4) Loss ratio bracket of 0.61 to 0.80 FC (5) Loss ratio bracket of 0.81 to 1.00 FC2(1) Loss ratio bracket of 1.01 to 1.19 FC2(2) Loss ratio bracket of 1.20 to 1.39 FC2(3) Loss bracket ratio of 1.40 to 1.69 FC2(4) Loss bracket ratio of 1.70 to 1.99 FC2(5) Loss bracket ratio of 2.00 to 2.49 FC3(1) Loss bracket ratio of 2.50 to 3.24 FC3(2) Loss bracket ratio of 3.25 to 3.99 FC3(3) Loss bracket ratio of 4.00 to 4.99 FC3(4) Loss bracket ratio of 5.00 to 5.99 F C3(5) Loss bracket ratio of 6.00 and over 169 SUMMARY OF THE H(I,J) MATRIX The hourly labor requirements per acre for each crop enterprise on the initial farm and alternatively larger farm sizes are stored in the H matrix. .1 Description of Variables 1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100 101-110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129-138 139 140 Monthly labor required/acre for each crop on the initial farm size (hours/acre) Monthly labor required/acre for each crop on the first alternative farm size (hours/acre) Monthly labor required/acre for each crop on the second alternative farm size (hours/ acre Mon)thly labor required/acre for each crop on the third alternative farm size (hours/ acre Mon)thly labor required/acre for each crop on the fourth alternative farm size (hours/ acre) Monthly labor required/acre for each crop on the fifth alternative farm size (hours/acre) Monthly labor required/acre for each crop on the sixth alternative farm size (hours/acre) Monthly labor required/acre for each crop on the seventh alternative farm size (hours/ acre) Monthly labor required/acre for each crop on the eighth alternative farm size (hours/ acre) Monthly labor required/acre for each crop on the ninth alternative farm size (hours/ acre) Monthly labor required/acre for each crop on the tenth alternative farm size (hours/ acre) Monthly labor available from family for initial farm size (hours) Monthly labor available from family for first alternative farm size (hours) Monthly labor available from family for second alternative farm size (hours) Monthly labor available from family for third alternative farm size (hours) Monthly labor available from family for fourth alternative farm size (hours) Monthly labor available from family for fifth alternative farm size (hours) Monthly labor available from family for sixth alternative farm size (hours) Monthly labor available from family for seventh alternative farm size (hours) Monthly labor available from family for eighth alternative farm size (hours) Monthly labor available from family for ninth alternative farm size (hours) Monthly labor available from family for tenth alternative farm size (hours) Sum of monthly labor needs for the farm (hours) Hours of part time labor required each month (hours) Monthly labor required/head for mother cow herd (hours) Monthly labor required/head for replacement females herd (hours) Monthly labor required/head for herd sires (hours) Monthly labor required/head for enterprise 4 (hours) Monthly labor required/head for enterprise 5 (hours) Total labor required by month for crops 1-10 (hours) in years l-10 Sum of labor required by month for all crops (hours) Blank 170 option is zero since values for this array are read from Card No. 2. SUMMARY OF THE INDEX(I) ARRAY The index array contains the values for all of the options in the program. Default for each Description of Variables (Options) 1 Number of years to be simulated (1 to 10) 2 Deterministic (0) or stochastic (2 to 300) 3 Number of crop enterprises (1 to 10) 4 Number of farm machinery items (1 to 100) 5 Depreciation schedules for pre-1980 equipment 6 For leasing machinery 7 Cropland leasing arrangements 8 Farm growth by purchase or lease of cropland 9 Crop mix, fixed or variable over time 10 Number of non-dairy livestock enterprises (1 to 5) 11 Price support programs, CCC or FOR 12 Number of years interest is charged for FOR loan 13 Target price program 14 Marketing certificate farm program 15 Low‘ yield disaster program or F CIC crop insurance program 16 Set-aside or diversion program 17 Reserved for a farm policy option 18 Payment limitation for government programs 19 Marketing quota farm program 20 Acreage allotment farm program 21 Sell cropland to avoid insolvency 22 Machinery replacement: trade-in or sale 23 Capital gains rate for farmland 24 Probability distributions selected 25 Reduce basis for ITC 26 Summary of stochastic results 27 Number of alternative farm sizes 28 Scale farm program benefits 29 Depreciation of purchased breeding stock 30 Cummulative probability distributions 31 Capital recovery for farm equipment placed into use after 1980 32 Capital recovery for breeding stock purchased after 1980 33 Capital recovery for regular buildings placed into use after 1980 34 Capital recovery for special purpose buildings built after 1980 35 Expensing election for purchases of equipment after 1980 36 Growth by refinancing equity in long-term debts 37 Marketing strategies 38 Adjust tax schedule for CPI changes after 1984.0 39 Skip the FCIC premium adjustment 40 Maximum annual interest deduction in effect or not 41 Dairy enterprise included or not 42 Pay off loans with surplus cash 43 Expand empirical probability distributions 44 Financial bailout strategies 45 Federal Income Tax provisions 46 Taxes have been calculated 47 Formula loan rates 48 Pay interest on forfeited CCC loan 49 Print deterministic results and input data 50 Print insolvency data 51 Gramm-Rudman 52-59 Blank 60 Record number for storage on Units 3 and 4 from STAT. 171 SUMMARY OF THE P(I,J) MATRIX The seasonal average price for the crops on the initial farm and alternatively larger farms are stored in the P matrix. J Description of Variables 1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100 101-110 Season average crop prices for crops on the initial farm Season average crop prices for crops on the first alternative farm size Season average crop prices for crops on the second alternative farm size Season average crop prices for crops on the third alternative farm size Season average crop prices for crops on the fourth alternative farm size Season average crop prices for crops on the fifth alternative farm size Season average crop prices for crops on the sixth alternative farm size Season average crop prices for crops on the seventh alternative farm size Season average crop prices for crops on the eighth alternative farm size Season average crop prices for crops on the ninth alternative farm size Season average crop prices for crops on the tenth alternative farm size 172 SUMMARY OF THE PV(I,J) MATRIX The PV matrix holds the values for 80 output variables over all iterations in a stochastic analysis. Description of Variables b-ll-Jl-Jiébérilih-lrfib-J \OOO\IO\UI-PUJI\J'—*G\OOO\IO\UIJ>-UJIQ>—* 20 21 22 23 24 25 26 27 28 29 3O 31 32 33 34 35 36 37' 38 39 Calendar year the farm was declared insolvent After-tax net present value for all iterations (S) Present value of ending net worth for all iterations (S) Before-tax net present value for all iterations (S) Acres owned at end of last year simulated for all iterations (acres) Acres leased at end of last year simulated for all iterations (acres) Total acres controlled at end of last year simulated for all iterations (acres) Market value of owned farm land at end of last year simulated for all iterations (S) Market value of machinery at end last year simulated for all iterations (S) Ending cash reserves at end last year simulated for all iterations (S) Total long-term debts year end for last year simulated for all iterations (S) Total intermediate-term debts year end for last year simulated for all iterations (S) . Loan rating score at the end of the last year simulated for all iterations (S) Ending leverage ratio for the last year simulated for all iterations (fraction) Ending equity to assets ratio for the last year simulated for all iterations (fraction) Per acre value of cropland for the last year simulated for all iterations (S/acre) Internal rate of return (fraction) _ Average annual total cash receipts calculated over all solvent years (S) Average annual cash production and harvesting costs calculated over all solvent years ($) Average annual net cash income calculated over all solvent years (S) Average annual net farm income calculated over all solvent years (S) Average annual income taxes, calculated over all solvent years (S) Average annual government payments received, calculated over all solvent years (S) Average annual taxable income, calculated over all solvent years (S) After-tax net present value for only solvent iterations (S) Present value of ending net worth for only solvent iterations (S) Before-tax net present value for only solvent iterations (S) Acres owned at end of last year simulated for only solvent iterations (acres) Acres leased at end of last year simulated for only solvent iterations (acres) Total acres controlled at end of last year simulated for only solvent iterations (acres) Market value of owned farmland at end of last year simulated for only solvent iterations ($) Market value of farm machinery at end of last year simulated for only solvent iterations (S) Ending cash reserves at end of last year simulated for only solvent iterations (S) Total long-term debts year end for last year simulated for only solvent iterations (S) Total intermediate-term debts year end for last year simulated for only solvent iterations (S) Loan rating score at the end of the last year simulated for only solvent iterations (S) Ending leverage ratio for the last year of the planning horizon for only solvent itera- tions (fractions) Ending equity to assets ratio for the last iterations (fraction) Per acre value of cropland. for last year of the tions (S/acre) year of the planning horizon for only solvent planning horizon for only solvent itera- 173 40 41-50 51-60 61-70 71-80 81-90 91-100 Internal rate of return for only solvent iterations (fraction) Debt service coverage ratio for years 1-10 (fraction) Earned equity growth trend for years 1-10 (fraction) Collateral ratio in years 1-10 (fraction) Leverage ratio for years 1-10 (fraction) Loan rating score Blank (available for expansion) 174 SUMMARY OF THE RS(I,J) MATRIX The capital recovery schedules for the 1982, 1983, 1984, and 1985 Tax Acts are included in the model to enable the user complete flexibility in simulating options under the various Income Tax Acts. Data for the RS matrix are data initialized in a Block Data subroutine. (J) Description of Variables 1982 Income Tax Provisions Three-year straight line schedule Five-year straight line schedule Twelve-year straight line schedule Fifteen-year straight line scehdule Three-year accelerated schedule for 1981-84 Five-year accelerated schedule for 1981-84 Fifteen-year accelerated schedule for 1981-84 Three-year accelerated schedule for 1985 Five-year accelerated schedule for 1985 l0 Fifteen-year accelerated schedule for 1985 11 Three-year accelerated schedule for 1986 and on 12 Five-year accelerated schedule for 1986 and on 13 F ifteen-year accelerated schedule for 1986 and on 14 Maximum expensing limits for 1981-83, 1984 & 1985, and 1986 and on \OO0\lO\§I\-PUJI\)*—* 175 SUMMARY OF THE S(I,J) MATRIX The annual data for up to 400 output variables are stored in the S matrix at the end of each iteration. These data are analyzed after the last iteration is simulated. J Description of Variables 1-10 Annual cash receipts (fraction) 11-20 Annual taxable income ($) 21-30 Annual net farm income ($) 31-40 Annual government payments excluding disaster payments ($) 41-50 Annual indemnity payments for crop insurance ($) 51-60 Annual disaster payments ($) 61-70 Annual ending investable funds at year end ($) 71-80 Annual personal income taxes paid ($) 81-90 Annual depreciation deductions paid ($) 91-100 Annual borrowings to meet cash flow deficits ($) 101-200 Annual cash prices for all crops ($/yield unit) 201-300 Annual crop yields for all crops (yield unit/acre) 301-400 Annual harvested acreage for all crops (acres) 176 SUMMARY OF THE TAX81, TAX82, TAX83, TAX84, AND TAX85 MATRICES The 1981 Economic Recovery Tax Act includes four separate tax schedules for the years 1981, 1982, 1983, 1984, and 1985. The tax schedules for a married individual filing a joint income tax return are programmed in FLIPSIM using the matrices TAX81, TAX82, TAX83, TAX84, and TAX85. The schedules are organized in their respective matrices with the rows (I) being alternative income tax brackets and the columns (J) being: J Description of Variables in TAX81, TAX82, TAX83, TAX84, and TAX85 1 The taxable income levels for each bracket (S) 2 The base income tax payment for each bracket (S) 3 The marginal income tax rate for each bracket (fraction) 177 SUMMARY OF THE VC(I,J) MATRIX THE FACTORED COVARIANCE OR CORRELATION MATRIX J Description of Variables 1-20 Factored covariance (correlation) matrix for crop yields and prices 21 Independent standard normal deviates for crop yields and prices 22 Price per unit for culled cows (sows) 23 Price per unit for females sold 24 Price per unit for males sold 25 Price per unit for replacement females 26 Price per unit for herd sires 27 Price per unit for livestock enterprise (4) 28 Price per unit for livestock enterprise (5) 29 Independent standard normal deviates for livestock enterprise prices 30 31 Minimum values for crop yields in a triangular distribution 32 Maximum values for crop yields in a triangular distribution 33-38 Empirical probability density function for dairy enterprise 39 Work file for dairy empirical probability density function 40 Work file for dairy empirical probability density function 41 Minimum values for crop prices in a triangular distribution 42 Maximum values for crop prices in a triangular distribution 43 44 45 46 47 48 49 50 51 Minimum values for livestock prices (deviations from the model value) 52 Maximum values for livestock prices (deviations from the model value) 53 54 55 56 57 58 59 60 Probabilities for a discrete uniform distribution 61-80 Cummulative deviates about the mean (or trend) for crop yields and prices. 81-87 Cummulative deviates about mean prices for the livestock enterprises. 88-100 Blank 101-122 Covariance for expected net returns for crops 123-142 Expansion fractions for empirical distributions for crops 178 SUMMARY OF THE Y(I,J) MATRIX The average annual yield. values for each crop enterprise on the initial farm are stored in the Y matrix. In addition, these values for alternatively larger size farms are stored in the Y matrix. J Description of Variables 1-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100 101-110 Average annual crop yields for crops on the initial farm Average annual crop yields for crops on the first alternative farm size Average annual crop yields for crops on the second alternative farm size Average annual crop yields for crops on the third alternative farm size Average annual crop yields for crops on the fourth alternative farm size Average annual crop yields for crops on the fifth alternative farm size Average annual crop yields for crops on the sixth alternative farm size Average annual crop yields for crops on the seventh alternative farm size Average annual crop yields for crops on the eighth alternative farm size Average annual crop yields for crops on the ninth alternative farm size Average annual crop yields for crops on the tenth alternative farm size 179 [Blank Page in Bulletin] Mention of a trademark 0r a proprietary product does not constitute a guarantee or a warranty of the product by The Texas Agricultural Experiment Station and does not imply its approval to the exclusion of other products that also may be suitable. All programs and informtion of The Texas Agricultural Experiment Station are available to everyone without regard to race, color, religion, sex, age, handicap, or national origin. 2M—7-86