B-1505
August 1985

Impacts of Farm Policies and Technology

on the Economic Viability of  

Texas Southern High Plains Cotton Farms

THE TEXAS AGRICULTURAL EXPERIMENT STATION! Neville P. Clarke, Directorl The Texas A&M University System! College Station, Texas

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‘M:

f‘

IMPACTS OF FARM POLICIES AND TECHNOLOGY
ON THE ECONOMIC VIABILITY OF
TEXAS SOUTHERN HIGH PLAINS COTTON FARMS

James W. Richardson
‘ Associate Professor

and

Edward G. Smith
Grain Marketing and Policy Specialist

Agricultural and Food Policy Center
Department of Agricultural Economics
Texas Agricultural Experiment Station

Texas A&M University

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'5»

Table of Contents

Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Representative Farms . . . . . . . . . . . . . . . . . . . . . . . . . .' . . . . . . ." . . . . . . . . . . . . . . . . . . . 1

Simulation Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Policy and Technology Scenarios . . . . . . . . . . . . . . . . . . . . . .  . . . . . . . . . . . . . .8 . . . . . . . . . . . . 7

Farm Policy Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Income Tax Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Financial Stress Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

No New Technology Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Evaluation Criterion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Acreage Reduction Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

No Payment Limitation . . . . . .' . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

No Price and Income Supports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

No Income Supports . . . . . . . . . . . . . . . . . . .- . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

No Farm Program . . . . . . . . . . . . . . . . . . . . . . .~ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

More Restrictive Income Taxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Financial Bailout Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

No New Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Summary of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Impacts of Farm Policies
and Technology on the Economic Viability 0f
Texas Southern High Plains Cotton Farms

Executive Summary

The purpose of this study was to estimate the impacts of alternative government policies and
technology on the growth and economic viability of representative cotton farms in the Texas South-
ern High Plains. The farms initially operated 1,088, 3,383, and 5,570 acres, had debt to asset ratios
typical of farms in the area, owned the necessary machinery complement, and farmed both owned
and leased acreage.

The results indicate that under the most likely technology scenario and continuation of the
provisions of the 1981 Farm Bill, all three farms will have a high probability of remaining solvent
through 1992. All three farms will have an 88% or greater chance of receiving a 3% or greater
return to equity and will be able to grow over the 10-year planning horizon. The greatest percent-
age increase in ending farm size was for the 1,088-acre farm, followed by the 3,383-acre farm, and
the 5,570-acre farm.

Imposing an acreage reduction program (acreage diversion and set aside) increased net farm
incomes and average net present value for all three farms. Acreage reduction programs increased
the annual rate of growth more for the 1,088-acre farm than for the two larger farms.

Removing the deficiency payment program (income supports) reduced the probability of sur-
vival, net farm incomes, and annual growth rates for all three farms. Removing both price supports
(Commodity Credit Corporation loan) and deficiency payments reduced the probability of survival
the most for the 1,088-acre farm (36 percentage points) while the probability of survival for the
5,570-acre farm was reduced by only 2 percentage points. Removing all farm program provisions
reduced the probability of survival for all three farms. The probability of survival declined from
92% to 42% for the 1,088-acre farm, and from 90% to 62% for the 3,383-acre farm. The prob-
ability of survival for the 5,570-acre farm remained above 75%.

Imposing a more restrictive set of federal income tax provisions on the three representative
farms caused a greater reduction of the average annual rate of growth for the two larger farms than
for the 1,088-acre farm. Net farm incomes were also reduced to a greater extent for the larger
farms than for the 1,088-acre farm. Growth occurred from leasing cropland as higher taxes reduced
available cash for down payments.

Yield enhancing technology anticipated over the next 10 years for cotton did not significantly
change the average annual growth rates of the representative farms. Changing the farm program or
federal income tax provisions had a greater impact on farm growth than yield enhancing technology.

The results of analyzing the three farms reveal that the debt restructuring strategies evaluated
here would not greatly benefit these farms. A two-year interest subsidy provided greater benefits to
net present value, net farm income, and ending net worth than a debt restructuring program.

The results of this study indicate that moderate-size (1,088 acre) cotton farms in the Texas
Southern High Plains are more dependent upon farm program provisions than larger farms for their

continued growth and economic viability. Larger farms 6T6 Ufillfif 60/6’ l0 SHIV/Vt’ 14/11/7011! [H117 M0-
gram benefits because of lower production costs ($/lb.), higher average cotton lint prices, and a
greater asset base from which to meet cash flow deficits, lfgrrgs Qt QQ meg Qq qQqbzgflogQg '\<g\$t§\§$

by the loss of any farm program provisions.

Impacts of Farm Policies
and Technology on the Economic Viability of

Texas Southern High Plains Cotton Farms

The economic impacts of farm policy, income tax provisions, and technology have not been
clearly linked to changes in farm structure (Gardner). Numerous economists have suggested that
farm programs have accelerated the growth of large scale farms while other economists suggest that
the link between government programs and increased farm size has never been proven (Quance and
Tweeten; Gardner; Gardner and Pope).

The purpose of this study is to analyze the impacts of selected farm programs, federal income
tax provisions, and technology on the viability of three different size cotton farms in the Texas
Southern High Plains.

Methodology

The first step was to describe three different size representative cotton farms in the study
area. The second step involved a simulation of the representative farms using a Monte Carlo,
whole-farm simulation model (FLIPSIM V) under alternative farm policy, income tax, finance, and
technology scenarios.

Representative Farms

In 1980, Smith conducted a survey of farmers, bankers, input suppliers, cotton gins, and
marketing firms in the Texas Southern High Plains. The survey provided the data necessary to
describe representative farms for eight different size categories. Within each size category, the
farms represented the average characteristics of farms in the region, including volume of cotton
produced, cultural practices, machinery complements, financial position, input costs, and marketing
strategies. For the present study, three of Smith’s representative farms were updated for 1982 costs
and prices. The three farms selected for this study represent a typical size farm in the region (1,088
acres); a large-scale farm (3,383 acres); and a very large-scale farm (5,570 acres). These farms were
selected because they typify the scale of commercial agriculture, accounting for 31% of the farms
and 62% of the cotton lint produced in the Texas Southern High Plains in 1980.

Table 1 provides a summary of the demographic and financial characteristics for the three
representative cotton farms used in this study. The proportion of cropland owned is greater for the
larger farms, ranging from 35% for the smallest farm to 62% for the largest farm. The market
value of machinery for each farm reflects the 1982 market value of the typical machinery comple-
ment for these size farms.

The long- and intermediate-term debt to asset ratios for the 1,088-acre farm were obtained
from USDA’s 1979 Agricultural Finance Survey. These debt ratios are the average for part-owner
cotton ‘farmers in the Texas High Plains who had real estate debts in 1979. The 1979 Agricultural
Finance Survey did not provide information for farms in the two larger size categories so the ratios
reported by Smith were used. Smith’s financial ratios for the 1,088-acre farm were similar to those
reported in the Agricultural Finance Survey.

Beginning financial positions of representative farms in each of the three size categories
(Table 1) were used rather than hypothetically assigning a common financial position. Using

1

TABLE 1. FINANCIAL CHARACTERISTICS OF THREE REPRESENTATIVE COTTON)
FARMS BY SIZE IN THE TEXAS SOUTHERN HIGH PLAINS

Farm Size (acres)

Characteristics 1,088 3,383 5,570
Age of operator 42 45 51
Acres owned 381 1048 3453
Acres leased 707 2335 2117
Value of owned cropland ($1,000) 222.4 611.7 2,015.4 ‘J
Value of machinery ($1,000) 144.5 420.8 713.9
Value of off-farm investments ($1,000) 59.0 110.0 213.7
Beginning cash reserve ($1,000) 16.7 52.0 85.5
Long-term debt ($1,000) 61.1 120.9 488.7
Intermediate-term debt ($1,000) 98.3 203.6 475.4
Initial net worth ($1,000) 275.0 854.8 2,032.3
Equity ratio (fraction)a i 0.62 0.72 0.67
Leverage ratio (fraction)b 0.61 0.40 0.49
Long-term debt/asset (fraction) 0.27 0.20 0.24
Intermediate term debt/asset (fraction) 0.68 0.48 0.67
Off-farm income ($1,000) 16.0 0.0 0.0
Minimum family living expenses ($1,000) 15.2 29.1 38.0
Maximum family living expenses ($1,000) 50.0 50.0 60.0

“Equity ratio is total net worth by total assets.

bLeverage ratio is the ratio of total debt to total
net worth.

Source: Smith.

(.1

representative financial data required the model to recognize the different risk bearing abilities of
different size farm operations.

Smith’s survey of farmers identified average annual off-farm income and minimum family
living expenses by farm size (Table 1). These values for living expenses were used for the study.
Maximum annual family living expenses were assumed to be $50,000 to $60,000 depending on farm
size. The family would utilize 25 cents of every additional dollar of disposable income over and
above the minimum requirement for family living. In no instance, however, will family living with-
drawals exceed the maximum indicated in Table 1.

Cotton production costs for the three farms were estimated by updating Smith’s 1980 pro-
duction costs to reflect 1982 prices. The two larger farms had a 13% lower total cost per pound of
cotton lint produced than the 1,088-acre farm. The 1982 annual production costs for irrigated and
dryland cotton on the three representative farms assume the same proportional economies in input
procurement reported by Smith. The mix of irrigated and nonirrigated cotton varied by farm size.
The 1,088-acre farm irrigated 32% of its available cotton acreage while the two larger farms irri-
gated only 23%. In the simulation analysis, as the 1,088-acre farm grew in size, its proportion of
irrigated cropland was decreased to 23%.

Simulation Model

The General Firm Level Policy Simulator -- FLIPSIM V (Richardson and Nixon) was used to
simulate the three representative farms for selected policy and technology scenarios. The model is
capable of simulating the annual functions of a crop farm (i.e., production, marketing, financial
growth and decay, machinery depreciation and replacement, family consumption, incurring fixed
and variable costs, and participating in farm programs).

Each representative farm was simulated over the 10-year planning horizon beginning in 1983
and extending through 1992. The planning horizon was then repeated 50 times using a different set
of random cotton prices and yields for each iteration. At the end of each iteration, values for key
output variables were calculated.

The model begins each year of the planning horizon by determining the production costs for
the current size of the farm based on production costs provided for larger farms. The representa-
tive farms were permitted to grow over time so cropmix and per acre production costs were forced
to change to correspond to larger representative farms.

After determining the relevant cropmix and costs for the farm the model selects the random A

crop prices and yields for that year. Random yields for irrigated and nonirrigated cotton and ran-
dom prices for cotton lint and cottonseed were drawn to reflect the historical variability typical of
the study area (Table 2).

FLIPSIM V simulates variable production costs for each crop by multiplying the per acre
input costs by planted acreages for the respective crops. Labor costs are calculated as the sum of
full-time labor charges plus the cost of part-time labor. Part-time labor needs are based on the dif-
ference between hours of monthly labor available from full time employees and non-paid family
members and the monthly labor needs for all crops. Harvesting costs are the product of the per
unit harvest costs, random yield, and harvested acreage. Each farm’s initial production and harvest-
ing costs were expressed in 1982 dollars.

Annual crop yields are selected at random based on the historical yield variability observed
for the study area (Table 2) subject to the technology scenario being evaluated, the year of the

3

TABLE 2. ANNUAL YIELDS AND PRICES FOR TYPICAL COTTON FARMS IN THE I
TEXAS SOUTHERN HIGH PLAINS, 1974-1983

Irrigated N onirrigated Cotton lint Cottonseed
Year Cotton linta 1 Cotton lint Priceb Price°
(lbs/acre) (lbs/acre) ($/lb) ($/ton)

1974 341 83 0.4850 124.0
1975 212 336 0.4756 88.8
1976 553 397 0.6465 100.0
1977 552 355 0.4236 62.0
1978 471 130 0.5566 117.0
1979 369 33 1 0.5859 120.0 a
1980 215 65 0.7465 121.0
1981 419 313 0.4540 90.0
1982 0d 0° 0.4955 95.0
1983 410 276 0.6135 85.0
Means 410 189 0.58 110.3

aCottonseed yield is a linear function of lint yield, averaging
about 0.4 tons per bale (480 lbs) of lint.

bCotton lint prices are average cash prices quoted for 41-30 (graded-
staple) cotton in Lubbock for the second week of December in each year.

°Cottonseed prices are season average prices for Lubbock, Texas
(December-February quotes).

dA hailstorm over most of the Southern High Plains reduced yields to zero
for both irrigated and dryland cotton.

Q.

planning horizon, and the size of farm. Under the base technology scenario, the 5,570-acre farm
would adopt the new technology during years 1 to 3. The 3,383-acre farm was assumed to adopt
this technology in a similar pattern during years 4 to 6 and the 1,088-acre farm would make the
adoption in years 7 to 9. Prior to adoption, mean yields were set equal to historical averages in
Table 2. After full adoption mean yields were held constant at 105% of their historical means.

The model calculates property taxes based on the market value of land and the property tax
rate for the study area. Other fixed costs are determined by the analyst. The model amortizes all
outstanding loans assuming they are simple interest mortgages. Annual interest rates for existing
debt on land, machinery, and operating loans were 8.5, 13.4, and 14.4%, respectively. Annual
interest rates for new debts and refinanced loans on long- and intermediate-term assets were 11.4
and 13.4%, respectively. Cash reserves and off-farm investments were allowed to earn 10% interest
annually. The market value of farm machinery was updated assuming the real market value of used
equipment decreased 1% per year. The market value of cropland was estimated using the historical
relationship between the capital gains rate for cropland and the rate of returns for farms.

The model next depreciates each piece of equipment on the farm for income tax purposes.
Equipment purchased prior to 1981 was depreciated using the double declining balance method and
a 5- to 7-year life. Equipment placed into use after 1980 was cost recovered assuming a 5-year life
and the Accelerated Cost Recovery System (ACRS) rules. Regular purpose and special purpose
buildings were depreciated using ACRS rules or the double declining balance method when applica-
ble. Equipment that has passed its economic life (7 to 10 years) was replaced by trading the existing
piece for a replacement, if sufficient cash was available to cover the required downpayment. The
cost of replacement equipment expressed in 1982 dollars was held constant throughout the planning
horizon. First year expensing and maximum investment tax credit were calculated for all.equipment
purchases.

The fraction of cotton marketed in the current tax year was estimated internally based on the
operator’s desired taxable income ($7,400), estimated cash receipts, and income tax deductions. If
the market price is less than the effective loan rate, the crop is placed in the Commodity Credit
Corporation loan when available, rather than being sold. Stocks are released from the loan if the

1 . . . .
The annual capital gain rate for cropland (cgrate) is calculated as a function of the lagged capital gain rate and the real rate of return to
production assets (rret) in the previous period:

cgrate = -0.0559 + 0.0582 Dummy + 0.3673 cgrate + 2.490 rret
(1.37) (1.7s) (1.13) H (3.4s) "1

The Dummy variable is one for 1979 and 1980 and zero otherwise. The student-t ratios are below their respective coefficients. The R

square for this equation was 68.6% and the F ratio was 6.55. The coefficients were estimated using national capital gain rates for farm-
land, 1970-1983 (USDA, Farm Real Estate Market Developments) and national residual returns to farm assets as a percent of total assets
(pages 105-106, USDA, Economic Indicators).

zlncome tax consequences frequently determine the fraction of crops sold during the income tax year they are harvested. The first step in
calculating this fraction is to determine the operator’s expected income tax deductions and cash receipts. Estimated deductions include:
fixed costs, interest payments, variable production and harvesting costs, labor costs, cash rent for land, depreciation, crop insurance pre-
miums, and personal income 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; and other farm income. lf estimated cash receipts are less than estimated tax deductions plus the targeted taxable income
($7,400), all crop production is sold in the current tax year. When cash receipts exceed deductions plus $7,400, the proportion of crops
sold ir. the next tax year equals the percentage of the crop that must be carried over for current cash receipts to equal deductions plus
$7,400.

market price in the following year exceeds the loan rate plus interest. Deficiency payments are paid
if the season average price is less than the target price.‘ The deficiency payment is a function of the
payment rate, farm program yield, and harvested acreage. When an acreage set aside or diversion
program is simulated, the model reduces planted acreage the specified amount and accounts for
increases in production on the more productive land left in production (i.e., slippage). _

After simulating the farm policies specified by the user, the model determines the farm oper-
ator’s year-end financial position, calculates family cash withdrawals,4 and calculates income taxes
payable in the following year. Cash surpluses are deposited in an interest bearing account at 10%
interest. Year-end cash flow deficits are handled in the following order: (a) grant a lien on crops in
storage at the operating loan interest rate, (b) refinance long-term equity, (c) refinance intermedi-
ate-term equity, and/or (d) sell cropland. If the operator is unable to cover the deficit in any one of
these ways, the farm is declared insolvent and the model proceeds to the next iteration after calcu- a
lating the operator’s accrued income and self-employment taxes.

Personal income taxes and self-employment taxes are calculated 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) the stan-
darg tax tables. The model selected the tax strategy which resulted in the lower income tax liabil-

ity.

The farm is permitted to grow at the end of each year by purchasing cropland if the operator
had cash available (after meeting all expenses) to cover a 30% downpayment for land and a 35%
downpayment for any additional machinery necessary for the proposed larger farm. The operator is
permitted to borrow against equity in land to meet up to 50% of the downpayment for land. The
farm operation can also grow by leasing land if the operator has sufficient cash available to cover
the 35% downpayment requirement for purchasing additional machinery required to operate the
larger size farm. If machinery is purchased because of growth, the machinery is depreciated,
investment tax credit calculated, and the operator’s income taxes recomputed.

3The 1981 Farm Bill indicates deficiency payments for cotton shall be based on annual average prices received by farmers. Since weighted
average annual prices received by farmers in the Lubbock area are not available for cotton. the model calculated deficiency payments for
cotton using season average prices. Target prices and loan rates for cotton were scaled down 8.3 cents per pound to account for loca-
tional and quality differentials between Lubbock prices and national average cotton prices used to calculate deficiency payment rates.
This adjustment forced the maximum deficiency payment rate to be equal to the value that one would have used for a national policy

simulation model.

4
A linear family consumption function was assumed for farmers in the Texas Southern High Plains. The function assumed a minimum
level of annual family living expenses was incurred regardless of the farm‘s financial condition. Beyond the minimum, the operator had
a 0.25 marginal propensity to consume out of disposible income. The consumption function was bounded on the top side by a maximum

level of annual family living expenses (Table 1).

sDepreciation recapture, capital gains and losses, investment tax credit, and depreciation allowances are explicitly accounted for in calcu- a‘
lating the sole proprietor‘s accrued income tax liability. If there is a net operating loss from prior years, taxable income in the current
year is appropriately reduced. If there is a net operating loss in the current year, it is automatically carried forward. Net operating loss
earryback is not permitted in the model. I
\y.
6All investment tax credit allowances were deducted from the regular tax liability and the result was compared to the income tax liability 
under the alternative minimum tax. The operator paid the excess of the alternative minimum tax over the sum of the regular income tax
liability and the regular minimum tax. Income tax rate schedules for 1983 and 1984 were included in the model, as well as a procedure
to develop tax rate schedules for 1985-1990 based on changes in the Consumer Price lndex.

6

After checking the farm’s prospects for growth, the model updates the farm operator’s
balance sheet, cash flow statement, and prepares to simulate the next year of the planning horizon.
The steps in the simulation process described above are repeated for 10 years or until the farm is
declared insolvent, whichever comes first. After completing each iteration, the model summarizes
the information for numerous key output variables and returns the farm to its initial economic situ-
ation (year one). This insures that the farm faces the same economic, policy, and physical relation-
ships for each of 5O iterations analyzed.

Policy and Technology Scenarios

The three representative cotton farms were simulated for 10 years under the alternative sce-
narios described below. Seven farm policy scenarios (including a continuation of the 1981 Farm
Bill), one income tax provision scenario, three financial bailout scenarios, and three alternative
technology scenarios were simulated for each farm. These policies represent the current farm pro-
gram and alternative policies which remove some or all program provisions that are thought to
affect farm growth and viability. All policy values associated with each scenario were held constant
across farm sizes to allow direct comparison of their impacts on different size farms. Each scenario
is described in detail in this section of the report.

Farm Policy Scenarios

1. Base Policy -- The Base Policy Scenario involves continuation of the 1981 Farm Bill
through 1992 and continuation of the income tax provisions under the 1982 Tax Act through 1992.
Based on expected adoption of new technology, annual mean crop yields were assumed to increase
as indicated in the previous section. For this scenario, it is assumed the following farm policies
were in effect:

O Commodity Credit Corporation loan program is available to producers.

0 An acreage diversion/set aside program in effect for 1983 to 1985, was utilized, excluding
PIK. No acreage diversion/set aside program was in effect for 1986 to 1992.

0 A target price-deficiency payment program is available for cotton in all years.
I The $50,000 payment limitation for deficiency and diversion payments is in effect.
0 Farms of all sizes are eligible to participate in these farm program provisions.

Values for loan rates, target prices, diversion rates, and diversion payment rates for 1983,

1984, and 1985 were set at their actual values. Loan rates and target prices for 1986 through 1992
were held constant at their 1985 levels. Annual loan rates and target prices for Texas cotton used in
the analysis are summarized in Table 3 for 1983 to 1992. Historical farm policy parameters for the
Texas cotton farms are outlined in Table 4. The average relationship between loan rates and prices
for 1977. to 1982 was used to determine the average annual prices for cotton lint in 1983 to 1992.
(This was done to minimize any bias caused by setting mean prices too close to either the loan rate
or the target price.)

The following options for depreciating machinery and calculating income taxes were used for
the Base scenario:

TABLE 3. LOCALIZED LOAN RATES AND TARGET PRICES FOR A REPRESENTATTJI
COTTON FARM IN THE TEXAS SOUTHERN HIGH PLAINS, 1983 TO 1992 a

Loan Rates Target Price
Years Cotton Lint Cotton Lint j
($/lb) (S/lb) Tj

1983 0.47 0.66

1984 0.46 0.69

1985 0.45 0.68

1986 0.45 0.68

1987 0.45 0.68

1988 0.45 0.68 a
1989 0.45 0.68 ’
1990 0.45 0.68

1991 0.45 0.68

1992 0.45 0.68

aLoan rates and target prices in effect for 1983 to 1984 and announced
for 1984 were localized based on the 1983 to 84 discount for the typical
grade of cotton marketed in Lubbock, Texas in 1982 to 1983.

TABLE 4. NATIONAL LOAN RATES AND TARGET PRICES FOR COTTON AND
ACREAGE SET ASIDE/DIVERSION RATES, 1977 TO 1985

Diversion
Loan Target Set Aside Payment
Year Rate Price Rate Diversion Rate
($/lb) ($/lb) (%) (%) ($/lb) I

1977 0.4463 0.4780 0.00 0.00

1978 0.4800 0.5200 0.00 0.00

1979 0.5023 0.5770 0.00 0.00

1980 0.4800 0.5840 0.00 0.00 0.00

1981 0.5246 0.7087 0.00 0.00 0.00

1982 0.5708 0.7100 0.15 0.00 0.00

1983 0.5500 0.7600 . 0.20 0.05 0.25

1984 0.5500 0.8100 0.25 0.00 0.00

1985 - 0.5500 0.8100 0.20 0.05 0.25

Source: U.S. Department of Agriculture. ASCS Commodity Fact

Sheet: Upland Cotton. May 1983. 1

O Machinery and buildings placed in use prior to 1981 are depreciated using the double
declining balance method.

O Machinery and buildings placed in use after 1980 are depreciated using an accelerated
cost recovery method.

O The operator elects to claim first year expensing for all depreciable items.
O The operator elects to take maximum investment tax credit (ITC) and reduce the basis.
O The operator adjusts crop sales across tax years to reduce current year taxes.

O The operator may use either the regular income tax computation or income averaging to
calculate federal income tax liabilities.

O There is no maximum interest deduction for calculating taxable income.

O The actual self employment tax rates and maximum income levels subject to this tax for
1983 and 1984 are used. Announced values for these variables in 1985 to 1986 were used
and the 1986 values were held constant through 1992.

O The operator elects to trade in old machinery on new replacements at the end of each
item’s economic life.

2. A 20% Acreage Reduction -- The provisions of theBase Policy Scenario were modified by
adding a 15% set aside with a 5% paid diversion for cotton in 1986 to 1992. Reasonable slippage
(70% for cotton) and program participation rates were used to estimate the resulting increase in
mean prices in 1986 to 1992. All other provisions of the Base Scenario were used without change.

3. N0 Farm Program Payment Limitation -- All provisions of the Base Scenario were used
except no limitation was placed on diversion and deficiency payments.

4. No Price Supports and N0 Deficiency Payments -- The Commodity Credit Corporation loan
and target price provisions under the Base Scenario were assumed to have been eliminated for all
years in the planning horizon (1983 to 1992). Annual mean prices for cotton were decreased 2%
based on the expected impact of removing the price and income support programs. Relative vari-
ability in prices about their means was increased based on the work of Morton, Devadoss, and
Heady as to the effects of no farm program on U.S. agricultures To isolate the impact of price and

7
The price response from a 15% acreage set-aside and 5% diversion was calculated assuming the own price flexibility for cotton was -1.75,
slippage was 70%, and program participation was 80%. Based on these assumptions the price response would be about 8.4%, so the
annual mean cottor. prices in Table 3 were increased 8.4% in 1986-1992.

8Morton, Devadoss, and Heady estimated the effect of removing all farm programs on corn and wheat. Their results suggest that the rela-
tive variability in the price of wheat and corn would increase 207% and 131%, respectively, and the mean prices for these crops would
decline 1% and 8%. One would expect that removing price supports (Commodity Credit Corporation loan and FOR) would increase
the variability of wheat price more than that of corn price because these price support mechanisms have influenced the season average
price of wheat more than the corn price over the past decade. Increased relative variability in the price of cotton is assumed to increase
160% or the average of the increases reported for wheat and corn by Morton, Devadoss, and Heady. Cotton farmers have depended on
the loan to establish a floor price less frequently than wheat farmers but more frequently than corn producers over the past decade. The
expected change in the mean price of cotton due to removing the Commodity Credit Corporation loan is to decrease the mean price for
Texas High Plains cotton farmers about 2%. This decrease was estimated by calculating the mean price of cotton in the Southern High
Plains using the empirical distribution for cotton price in Table 3, both with and without the Commodity Credit Corporation loan.

9

income supports on the representative farms, the acreage diversion and set aside programs in the
Base Policy for 1983 to 1985 were assumed to remain in effect.

5. N0 Target Price/Deficiency Payment -- The target price and deficiency payment provision
was assumed to be eliminated for all years of the planning horizon (1983 to 1992). All other provi-
sions of the Base Scenario were used without change to isolate the effects of removing only the
deficiency payment.

6. Target Farm Program Benefits -- All farm program and income tax provisions of the Base
Scenario were used, except that farms with more than $300,000 of sales were not eligible to partici-
pate in farm program provisions. This program restriction excluded the 5,570-acre farm from par-
ticipating directly in the program provisions (Commodity Credit Corporation loan, target price/defi-
ciency payments, and set aside-diversions). Mean prices and relative variability in prices were not
adjusted because sufficient "smaller" farms were assumed to participate in the farm program for the
price support actions of the Commodity Credit Corporation loan to function normally.

7. N0 Farm Program -- All farm program provisions outlined for the Base Scenario were
eliminated for all 10 years of the planning horizon. Mean annual prices and relative variance in
prices for the No Price and Income Supports Scenario (4) were used due to eliminating provisions
of the Commodity Credit Corporation loan.

Income Tax Scenarios

8. Reduced Income Tax Benefits and Base Farm Program -- The federal income tax provisions
in place for the Base Policy Scenario were made more restrictive. All farm policy provisions of the
Base Scenario were left unchanged. The more restrictive federal income tax provisions included:

0 Using the straight line cost recovery method to calculate depreciation on machinery and
buildings.

O Eliminating first year expensing provisions for all depreciable items.

0 Continuing investment tax credit (ITC) provisions but eliminating the maximum ITC
provision.

0 Setting the maximum annual interest expense which could be used to reduce taxable
income at $15,600. This value represents the annual interest expense deductions a con-
sumer might have for a home, automobiles, etc.

0 Making the operator sell obsolete machinery upon disposition rather than trading it in on
new replacements, and thus forcing recapture of excess depreciation deductions.

All other federal income tax provisions for the Base Scenario were used as outlined earlier.
Financial Stress Scenarios

9. Base Finance Scenario -- Each farm’s long-term debt to asset ratio was increased to 0.55
and its intermediate-term debt to asset ratio was increased to 0.60 to represent a highly leveraged
farm. Annual long- and intermediate-term interest rates were increased to their average values for
1980 to 1983 (.1139 and .1343, respectively) to represent a farm which had been forced to refinance

10

its assets during the past 4 years. The farm program provisions associated with the Base Policy
Scenario (1) were continued for this scenario.

10. Debt Restructure -- The length of intermediate-term loans was increased by 1 year, and a
portion of intermediate debt was converted to long-term debt. The conversion of intermediate-term
debt was permitted if the long-term debt to asset ratio did not exceed 0.65. For some farms, this
allowed all intermediate-term debt to be converted to long-term debt. For other farms, this con-
straint substantially restricted debt conversion. Total debt loads and farm program provisions were
the same as those used for the Base Finance Scenario (9).

11. Interest Subsidy -— The annual interest rates, debt levels, and farm program provisions in

the Base Finance Scenario (9) were simulated but an interest subsidy was provided during the first 2
years. The interest subsidy took the form of an interest rate reduction equal to 3.4 percentage
points for long-term interest rates and 5.4 percentage points for intermediate-term interest rates.
These interest rate reductions were the amounts necessary to reduce the respective interest rates
(.1137 and .1343) to 4%.

No New Technology Scenarios

12. No New Technology and Base Farm Policy -- The federal income tax and farm program
provisions in the Base Policy Scenario (l) were simulated assuming no increase in mean yields over
the planning horizon. For the No New Technology Scenarios, mean irrigated and dryland cotton
yields for all 10 years were set equal to their respective means observed over the period 1974 to
1983 (Table 2).

13. N0 New Technology and No Deficiency Payments -- The farm program provisions in the
No Target Price/Deficiency Payments Scenario (5) were simulated assuming the same average
annual cotton yields used for the base No New Technology Scenario (12).

14. No New Technology and No Farm Program -- All farm program provisions were elimi-
nated (Scenario 7) and annual average crop yields used for the base No New Technology Scenario
(12) were assumed.

Evaluation Criterion

The FLIPSIM V model provides considerable detail about the viability of a representative
farm at the end of each iteration, e.g., ending leverage ratio, ending net worth, ending farm size,
total assets, total debt, net present value, and whether the farm remained solvent for 10 years. By
repeating each scenario for 5O iterations, the model generates the information necessary to estimate
mean values for key output variables. The means of these key output values are used to compare
the economic impacts of selected policy and technology scenarios on representative farms. The fol-
lowing output variables for the model were selected to compare the impacts of the scenarios
described in the previous section.

I Probability of survival is defined as the probability that the representative farm will remain
solvent for 10 years. In other words, it is the probability that the operator would maintain
the minimum financial ratios required by local bankers for all years of the planning hori-
zon (debt to asset ratio less than 0.70).

O Probability of a positive net present value is the probability that the representative farm will

11

have a positive after-tax net present value. An after-tax, real discount rate of 3% was used 

to calculate the farm’s net present value. Thus this statistic indicates the probability of the
representative farm providing at least a 3% real rate of return to the operator’s initial net
worth.

O After-tax net present value (NPV) is the present value of the operator’s annual cash with-
drawals (CW) plus the present value of the change in net worth (NW) minus the present
value of annual off-farm income (OY):

T CW - DY NW
npv = z t t +- T - uw
t:

1 <1.o3>t (1.o3>T °

Cash withdrawals equal family living expenses plus state and federal income taxes and self-
employment taxes. Initial net worth (NW ) and ending net worth (NW ) explicitly con-
sider the value of off-farm investments and accrued taxes. A 3% after-tax, real discount
rate was used to calculate net present value for all representative farms.

O Present value of ending net worth is used to indicate the change in the farm’s real net
worth over the planning horizon. Net worth is affected by increases (or decreases) in asset
(land, machinery, and livestock) value and retained earnings. This value can be compared
directly to initial net worth to indicate the relative magnitude of real financial growth.

O Acres owned, leased, and controlled at the end of the planning horizon for each iteration
indicate the impacts of alternative scenarios on the rate of growth for representative farms.
These three statistics provide an indication of how the farm grew either by purchasing or
leasing land.

O Total long- and intermediate-term debts at the end of the planning horizon provide an
insight into the financial stress of the farm over the planning horizon. Increases in aver-
age ending debt from one scenario to another can be due to either rapid growth through
purchasing land and machinery or the farm operator being forced to refinance large cash
flow deficits. When surplus cash is available, the operator is permitted to first prepay
intermediate-term debts and then prepay new long-term debts. Therefore large ending
intermediate-term debts indicate insufficient cash was available to reduce
intermediate-term debt through prepayment of principal.

O Ending equity ratio is the farm’s ending ratio of total net worth to total assets. This ratio
provides a "bottom-line" measure for comparing the representative farm’s ending financial
position across scenarios.

O Average Annual Net Farm Income is the average net farm income received by the operator
over all years simulated. Net farm income equals total farm receipts plus total government
payments minus all cash production expenses, interest payments, labor costs, fixed cash
costs, and depreciation. This value excludes all non-farm income and interest earned on a
cash reserves.

O Average Annual Government Payment is the average annual government payment (defi-
ciency and diversion payments) received over all years simulated. 

12

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15

Results

The results of simulating Scenarios 1-8 for the three representative cotton farms are summa-
rized in Tables 5 to 7. Under the Base Policy Scenario, all three farms had a 90% or greater chance
of remaining solvent for 1O years and an 88% or greater chance of receiving a positive net present
value. On the average, all three farms were able to increase their real net worth, and two of the
farms increased their average ending equity ratio. In addition, all three farms were able to increase
the average total number of acres they controlled. The 1,088-acre farm grew 470 acres (43%) over
the 10 year planning horizon, while the 3,383- and 5,570-acre farms grew by 26.7% and 7.7%,
respectively.

Acreage Reduction Program

Imposing a 20% acreage reduction program on the three cotton farms (Scenario 2) increased
their probability of survival, their probability of experiencing a positive net present value, average
net present value, and average ending farm size relative to results for the Base Scenario. These
results are to be expected because an acreage reduction program increases mean cotton price and
provides a small diversion payment to defray the costs of participating in the acreage reduction pro-
gram. The increase in average ending farm size due to the 20% acreage reduction program ranges
from 1% for the 5,570-acre farm to 4.9% for the 1,088-acre farm. Average annual government
payments to all three farms are less than under the Base Scenario because higher mean cotton prices
reduce deficiency payment rates and thus total government payments.

No Payment Limitation

Eliminating the $50,000 payment limitation (Scenario 3) resulted in substantial increases in
average annual government payments for the 5,570- and 3,383-acre farms while only marginally
impacting the 1,088-acre farm. Average net present value for the 5,570-acre farm was increased
82% over the Base Scenario as a result of eliminating the payment limitation. In contrast, average
net present value for the 1,088-acre farm was increased 12% by eliminating the $50,000 limitation.
Average ending farm size for the 5,570-acre farm was increased 8.5% over the Base by eliminating
the payment limitation, while ending farm size for the 1,088-acre farm was increased 5.7%. The
incentive exists for larger farms to restructure their operations to obtain maximum benefit of defi-
ciency payments.

No Price and Income Supports

Removing both price and income supports (Scenario 4) reduced the probabilities of survival 2
percentage points for the 5,570-acre farm, 18 percentage points for the 3,383-acre farm, and 36
percentage points for the 1,088-acre farm. Average annual net farm income for the 1,088-acre farm
declined from $8,300 under the Base Policy Scenario to -$28,300, and average net present value
declined 104% to -$16,800. Average net present value for the 5,570-acre farm was reduced about
50% to $811,400. Average ending farm size for the 1,088-acre farm was 21.9% less than the Base
Scenario, while the ending farm size for the 5,570-acre farm was only 3.6% less than the Base.

The loss of price and income supports increased the relative variability (risk) in net present
value more for the 1,088-acre farm than the 5,570-acre farm. These results are to be expected when

16

price supports and deficiency payments are removed. Those farms with higher profit margins,
greater equity, and higher mean yields should be better able to survive if price and income supports
are removed.

N0 Income Supports

Removing the target price/deficiency payment (Scenario 5) reduced the probability of survival
substantially more for the 1,088-acre farm than for the 5,570- and 3,383-acre farms. This result was
not surprising given the finding under Scenario 3. An effective payment limit of $50,000 suffi-
ciently reduces the benefits derived from the target price/deficiency payment provisions for the
larger farms. Therefore, the elimination of such a program would not be as detrimental. The loss
in deficiency payments reduced average annual government payments $25,000 for the 1,088-acre
farm and $35,400 for the largest farm. On a per-acre basis, this reduction in receipts was 343%
greater for the small farm than the large farm thus, further explaining the significant differences in
the results of this scenario for the two farms.

In the event that farm program provisions were targeted to farms producing $300,000 or less
in cotton (Scenario 4), only the 1,088-acre farm would be able to participate in the farm program
during all years. The 3,383-acre farm would receive only 44% as great an average government pay-
ment as under the Base, due to such a program. In contrast, the 5,570-acre farm would not be able
to participate directly in any farm program provisions if Scenario 4 were enacted. Probabilities of
survival for the 3,383- and 5,570-acre farms fell to 86% and 88%, respectively. They did not fall to
the low levels experienced under Scenario 4 when price and income supports were removed.
Although these large farms could not benefit directly from price supports, they indirectly gain the
benefits of reduced price variability due to other farmers participating in the loan program. This
type of farm program would not reduce the rate of growth in farm size for the 1,088-acre farm;
however, it would substantially reduce the rate of growth for the two larger farms.

No Farm Program

Removing all farm program provisions substantially reduced the probability of survival for all
three farms (Scenario 7). The greatest reduction in the probability of survival was for the
1,088-acre farm and the least reduction was for the 5,570-acre farm. On the average, the 1,088-acre
farm was forced to sell 100 acres to achieve a 42% chance of remaining solvent for 10 years. The
5,570-acre farm was able to remain solvent 78% of the time but only by selling an average of 440
acres over the planning horizon. Average annual net incomes for all three farms fell below zero, by
about $40,000, due to lower mean cotton prices, increased price variability, and the absence of defi-
ciency payments. The only difference between this scenario and Scenario 4 (no price and income
supports) was that Scenario 4 included a set aside and paid diversion from 1983 to 1985, with the
associated price enhancement. Net present value, net worth, and probability of survival for all three
farms were significantly benefitted by price enhancement and diversion payments from 1983 to
1985.

More Restrictive Income Taxes

Imposing a more restrictive set of federal income tax provisions (Scenario 8) reduced the
probability of survival slightly more for the 1,088-acre farm than the 3,383-acre farm and had no
effect on the 5,570-acre farm’s chances for survival. Average net present value was reduced about

17

l) ‘f.
A/

$20,000 for all three farms. Average ending farm size was reduced from the Base about 7.5% for
the 3,383-acre farm and about 4.3% for the 5,570-acre farm. As expected, increasing the federal
income tax burden reduced the propensity of farms to grow through purchasing cropland in favor of
growing through leasing. Total cropland controlled at the end of the planning horizon was about
the same as the Base for the 1,088-acre farm, while ending farm size was 4 to 7% lower than the
Base for the two larger farms. l

Financial Bailout Strategies

To analyze the benefits of alternative financial bailout strategies, the financial positions for

the three representative farms described in Table l were modified to emulate highly levered farms u
and simulated under the Base Policy scenario with alternative bailout strategies in place. The long-

term debt to asset ratio for each farm was increased to 55%, the intermediate-term debt to asset

ratios were set equal to 60%, annual interest rates were increased to their average values for

1980-1983 ( 11.37% for long term and 13.4% for intermediate term), and off-farm investments were

set equal to zero. As a basis for comparison, these highly leveraged farms were simulated for 10

years using the farm policy and income tax provisions in the Base Policy Scenario (1). The results

of simulating this Base Financial Scenario and the two financial bailout strategies are presented in

Tables 8 to 10.

All three highly levered cotton farms have a low probability of remaining solvent for 10 years
(56 to 66%) under the Base Policy Scenario (9). Restructuring debt (Scenario 10) for the three dif-
ferent size cotton farms did not appreciably improve their chances of survival. ln fact, this type of
financial assistance actually encouraged all three farms to grow through land purchases which
resulted in lower probabilities of survival for two larger farms. On the other hand, an interest rate
buydown program moderately increased the probability of survival for the two smaller (1,088 and
3,383 acre) farms and substantially increased the average net present value and ending net worth for
all three.

An interest rate subsidy resulted in an increased average annual net farm income for all three
farms, while the debt restructure actually reduced the average annual net farm income. Overall, the
interest rate subsidy provided a greater benefit than the debt restructure bailout.

N0 New Technology

The simulation results presented thus far assumed the most likely technology scenario for the

10 year planning horizon. This amounted to a 5% increase in cotton yields being fully adopted in

the first three years by the 5,570-acre farm, being adopted in years 4 to 6 for the 3,383-acre farm,

and adopted in years 7 to 9 for the 1,088-acre farm. As a point of comparison, three of the policy

scenarios were re-analyzed assuming no new technology was adopted by the three farms. The

results of these no new technologies scenarios are summarized in Tables 11 to 13. To evaluate the

impact of technology on the three farms, one must compare the results in Tables 11 to 13 to their

respective results in Tables 5 to 7. u

Due to its early adoption, the 5,570-acre farm benefited more from the new technology than
the other two farms. The value of adopting the new technology early was evident in the added net .
present value for the 5,570-acre farm. Under the Base Scenario ( 1), the farm enjoyed a $250,000 
increase in average net present value due to early adoption of the new technology. In contrast, the
1,088-acre farm had a $16,000 higher average net present value (under the Base Policy Scenario)
due to the adoption of new technology.

18

TABLE 8. COMPARISON OF SELECTED FINANCIAL BAILOUT SCENARIOS FOR A
REPRESENTATIVE 1,088-ACRE TEXAS SOUTHERN HIGH PLAINS COTTON FARM

Initial Alternative Scenarios‘

Criteria Farm 9 10 1 l
Probability of

survival (%) -- 64 66 72
Probability of

positive net present

value (%) -- 64 66 72
After-tax net present value

mean ($1 ,000) -- 204.7 212.8 252.5
Average present value of ending

net worth ($1,000) 154.7 303.6 313.6 343.2
Average ending cropland owned

(acres) 381.0 464.3 522.4 492.9
Average ending cropland leased

(acres) 707.0 950.1 911.2 950.3
Average ending cropland controlled

(acres) 1088.0 1414.4 1433.6 1443.2
Average ending long-term debts

($1,000) 122.3 160.3 204.6 170.8
Average ending intermediate-term debts

($1,000) 98.3 68.6 72.7 53.7
Average ending equity ratio

(fraction) 0.40 0.40 0.37 0.51
Average internal rate of return

(fraction) -- 0.00 0.04 0.07
Average annual net farm income

($1,000) -- -5.4 -6.4 1.3
Average annual gov’t payments

($1,000) -- 24.4 24.8 24.7

"9 I-II-- Base Finance Scenario consists of the Base farm program provisions for a highly leveraged farm.

10 -- Restructure debt for a highly leveraged farm.
11 -- Interest rate subsidy (buy-down) in the first two years for a highly leveraged farm.

19

ii

TABLE 9. COMPARISON OF SELECTED FINANCIAL BAILOUT SCENARIOS FOR A REPRESENTATIVE
3,383-ACRE TEXAS SOUTHERN HIGH PLAINS COTTON FARM

Initial Alternative Scenarios‘

Criteria Farm 9 10 11 
Probability of

survival (%) -- 56 50 60
Probability of

positive net present

value(%) -- 56 52 60 U
After-tax net present value

mean ($1,000) -- 429.4‘ 413.1 582.3
Average present value of ending

net worth ($1 ,000) 446.7 604.3 599.6 732.9
Average ending cropland owned

(acres) 1048.0 1029.4 1180.4 1207.8
Average ending cropland leased

(acres) 2335.0 2740.8 2660.2 2613.5
Average ending cropland controlled

(acres) 3383.0 3770.2 3840.6 3821.4
Average ending long-term debts

($1,000) 336.4 353.1 481.7 418.4
Average ending intermediate-term debts

($1,000) _ 286.1 242.3 256.5 218.7
Average ending equity ratio

(fraction) 0.41 0.28 0.40 0.35
Average internal rate of return

(fraction) -- 0.00 0.01 0.04
Average annual net [farm income

($1,000) -- -9.1 -21.2 6.9
Average annual gov’t payments

($1,000) -- 36.8 36.4 37.2 Q

a9 -- Base Finance Scenario consists of the Base farm program provisions for a highly leveraged farm.
10 -- Restructure debt for a highly leveraged farm.
11 -- Interest rate subsidy (buy-down) in the first two years for a highly leveraged farm. 

20

TABLE 10. COMPARISON OF SELECTED FINANCIAL BAILOUT SCENARIOS FOR A REPRESENTATIVE
5,570-ACRE TEXAS SOUTHERN HIGH PLAINS COTTON FARM

Initial Alternative Scenarios‘

Criteria Farm 9 10 1 1
Probability of

survival (%) -- 66 64 66
Probability of

positive net present

value(%) -- 62 60 64
After-tax net present value

mean($1,000) -- 495.3 529.3 834.4
Average present value of ending

net worth ($1,000) 1195.9 1310.2 1356.3 1619.0
Average ending cropland owned

(acres) 3453.0 2443.1 2651.7 2665.7
Average ending cropland leased

(acres) 2117.0 3290.0 3324.7 3105.9
Average ending cropland controlled

(acres) 5570.0 5733.2’ 5976.4 5771.6
Average ending long-term debts

($1,000) 1108.5 830.3 1068.5 858.4
Average ending intermediate-term debts

($1,000) 478.4 348.9 356.7 301.7
Average ending equity ratio

(fraction) 0.42 0.41 0.46 0.44
Average internal rate of return

(fraction) -- 0.09 0.10 0.13
Average annual net farm income

($1,000) -- -41.8 -57.3 -6.3
Average annual gov’t payments

($1,000) -- 41.1 41.3 41.6

‘*9 -- Base Finance Scenario consists of the Base farm program provisions for a highly leveraged farm.
10 -- Restructure debt for a highly leveraged farm.
11 -- Interest rate subsidy (buy-down) in the first two years for a highly leveraged farm.

21

TABLE 11. COMPARISON OF SELECTED FARM POLICY SCENARIOS ASSUMING NO NEW a
TECHNOLOGY SCENARIO FOR A 1,088-ACRE TEXAS SOUTHERN HIGH PLAINS COTTON FARM

Initial Alternative Scenarios‘

Criteria Farm 12 13 14
Probability of

survival (%) -- 92 68 42
Probability of

positive net present

value (%) -- 92 54 30 ‘
After-tax net present value

mean ($1,000) -- 365.4 37.3 -102.2
Average present value of ending

net worth ($1,000) 275.0 551.5 290.4 160.8
Average ending cropland owned

(acres) 381.0 627.2 400.4 283.6
Average ending cropland leased

(acres) 707.0 963.2 879.6 922.8
Average ending cropland controlled

(acres) 1088.0 1590.4 1280.0 1206.4
Average ending long-term debts

($1,000) 61.0 158.4 94.5 70.0
Average ending intermediate-term debts

($1,000) 98.3 25.5 87.0 130.1
Average ending equity ratio

(fraction) 0.62 0.73 0.56 0.26
Average internal rate of return

(fraction) -- 0.08 -0.04 -0. 17
Average annual net farm income

($1,000) -- 7.0 -22.2 -41.0
Average annual gov’t payments

($1,000) -- 26.3 1.1 0.0

a12 -- Base policy, continuation of 1981 Farm Bill, assuming most likely yields.

13 -- No target price/deficiency payments assuming most likely yields.

14 -- No farm program assuming most likely yields.

22

TABLE 12. COMPARISON OF SELECTED FARM POLICY SCENARIOS ASSUMING NO NEW
TECHNOLOGY SCENARIO FOR A 3,383-ACRE TEXAS SOUTHERN HIGH PLAINS COTTON FARM

Initial Alternative Scenarios“

Criteria Farm 12 13 14
Probability of

survival (%) -- 88 78 6O
Probability of

positive net present

value (%) -- 86 76 56
After-tax net present value

mean ($1,000) -- 860.0 432.3 146.4
Average present value of ending

net worth ($1,000) 854.8 1324.5 966.2 738.4
Average ending cropland owned

(acres) 1048.0 1772.4 1423.4 1259.6
Average ending cropland leased

(acres) 2335.0 2500.2 2394.8 2373.0
Average ending cropland controlled

(acres) 3383.0 4272.6 3818.2 3632.6
Average ending long-term debts

($1,000) 120.9 470.3 308.3 286.3
Average ending intermediate-term debts

($1,000) 203.6 107.5 182.6 263.8
Average ending equity ratio

(fraction) 0.72 0.67 0.62 0.48
Average internal rate of return

(fraction) -- 0.07 0.03 -0. 10
Average annual net farm income

($1,000) -- 25.4 -3.6 -45.5
Average annual gov’t payments

($1,000) -- 37.9 3.0 0.0

‘l2  Base policy, continuation of 1981 Farm Bill, assuming most likely yields.

13 -- No target price/deficiency payments assuming most likely yields.

14 -- No farm program assuming most likely yields.

23

TABLE 13. COMPARISON OF SELECTED FARM POLICY SCENARIOS ASSUMING NO NEW w

TECHNOLOGY SCENARIO FOR A 5,570-ACRE TEXAS SOUTHERN HIGH PLAINS COTTON FARM

Initial Alternative Scenarios“

Criteria Farm 12 13 _ 14
Probability of

survival (%) -- 94 90 76
Probability of

positive net present

value (%) -- 86 74 6O Q
After-tax net present value

mean($1,000) -- 1340.8 780.8 210.8
Average present value of ending

net worth ($1 ,000) 2032.0 2806.5 2322.4 1842.6
Average ending cropland owned

(acres) 3453.0 3487.1 3250.4 2988.2
Average ending cropland leased

(acres) 2XI7.0 2473.3 2566.0 2735.4
Average ending cropland controlled a

(acres) 5570.0 5960.4 5816.4 5723.6
Average ending long-term debts

($1,000) 488.7 601.0 624.3 641.6
Average ending intermediate-term debts

($1,000) 475.4 130.3 209.9 324.3
Average ending equity ratio

(fraction) 0.67 0.80 0.71 0.81
Average internal rate of return

(fraction) -- 0.08 0.04 -0.07
Average annual net farm income

($1,000) ' -- 47.0 0.2 -65.9
Average annual gov’t payments

($1,000) -- 40.5 4.8 0.0

‘l2 -- Base policy, continuation of 1981 Farm Bill, assuming most likely yields.
13 -- No target price/deficiency payments assuming most likely yields.
14 -- No farm program assuming most likely yields.

24

Despite the substantial contribution technology made to net present value for the 5,570-acre
farm, average ending farm size was about the same (less than 5O acres greater) due to the early
adoption of new technology. Similarly, for the two smaller farms, average ending farm size was
almost identical for the two different levels of technology. These results suggest that farm programs
have far more impact on a farm’s economic viability and growth than moderate technological
advancements in crop agriculture.

Summary of Results

Base Policy Scenario

O All three representative farms had a high probability of remaining solvent through the 10
year planning horizon.

O All three farms had greater than a reasonable (greater than 88%) chance of having a posi-
tive net present value.

O On the average, all three farms were able to grow by purchasing and leasing cropland.

O The largest percentage increase in ending farm size was for the 1,088-acre farm; however,
the 3,383-acre farm had the greatest absolute increase in acres controlled.

Acreage Reduction Programs

O Average net present value was increased for all three farms as a result of an acreage
reduction program. A

O A 20% acreage reduction program increased average ending farm size about 1% for the
5,570-acre farm and about 5% for the 1,088-acre farm.

O Average ending equity to asset ratios for all three farms were increased 2 to 6 percentage
points by a 20% acreage reduction program.

O Net farm income was increased more than 50% for the three Texas cotton farms.
O Deficiency payments were reduced from 3 to 15% for the three farms.
No Payment Limitation

O The larger the farm, the greater the impacts on growth and income from removing the
$50,000 payment limitation on deficiency and diversion payments. Average net present
value increased 82% for the 5,570-acre farm, 60% for the 3,383-acre farm, and 12% for
the 1,088-acre farm.

O Removing the payment limitation substantially increased the average ending farm size. On
;-_the average, the 5,570-acre farm grew 8.5% more than the Base, while the 3,383- and the
"1,088-acre farms grew 6.7 and 5.7%, respectively.

No Price Supports and No Deficiency Payments
O Removing price and income supports for cotton reduced the probability of survival for all

three farms. The probability of survival for the 1,088-acre farm declined the most.

25

O Average after-tax net present value was decreased 104% for the 1,088-acre farm and 50%
t0 60% for the two larger farms.

O The loss of price and income supports substantially reduced the rate of growth in farm size
for the 1,088-acre farm (22%) while only moderately reducing the rate of growth for the
largest farm (4%). 

O Loss of price and income supports increased risk associated with income more for the
1,088-acre farm than for the larger farms.

O The presence of an effective $50,000 payment limitation causes the income support pro-
gram to benefit the LOSS-acre farm relatively more than larger farms. In contrast, the
price support program results in a greater relative advantage for large and very large
farms.

No Target Price/Deficiency Payment

O Removing the deficiency payment provision reduced the probability of survival considera-
bly more for the 1.088-acre farm than for the 3,383- or 5,570-acre farms. The probability
of survival declined from 94% to 68% for the smallest farm.

O The $50,000 payment limitation, if effective, reduced the current benefits of the deficiency
payment for very large farms, so its loss reduced average ending farm size less than 2.5%.

O The loss of deficiency payments reduced the average net present value of small farms more
than twice as much as for large farms.

O Average ending farm size was reduced more, in percentage terms, for the small farm
(-18%) than for the large farm (-2.5%) if deficiency payments were removed.

Target Farm Program Benefits to Small Farms

O The two larger farms were prevented from participating in the Commodity Credit Corpo-
ration loan, diversion program, and deficiency payment, in most years, due to their value
of production exceeding the maximum of $300,000.

O The 1,088-acre farm was not affected by the program. However, the rate of growth for
the two larger farms was reduced about 50% from the Base.

O Although the two larger farms were unable to place cotton in the Commodity Credit Cor-
poration loan they benefited indirectly from the price stabilizing functions of the loan.

No Farm Program

O Removing all farm program provisions reduced the 1,088-acre farm’s chance of remaining
solvent for 10 years from 92% to 42%, while the chance of remaining solvent for the
5,570-acre farm declined from 94% to 78%.

O The percentage reduction in average net present value was similarly reduced more for the
smallest farm than for the largest farm.

O In the absence of farm programs, all three farms continued to grow but at a much slower
rate than under the Base farm program. The largest farm was able to increase its average

ending farm size 166 acres over its initial 5,570-acres. Average ending farm size increased

26

about 124 acres for the smallest farm; however, it survived only 42% of the time.

The largest farm was forced to sell an average of 441 acres to remain solvent 78% of the
time for 10 years.

Removal of all farm program benefits reduced average ending net worth for all three
farms due to reductions in land values.

More Restrictive Federal Income Tax Provisions

More restrictive federal income tax provisions reduced the average annual rate of growth
to a greater extent for the two larger farms than for the 1,088-acre farm.

Increasing the federal income tax burden on farmers reduced the propensity to grow
through purchasing cropland relative to leasing.

Probability of survival was not significantly affected by a more restrictive set of federal
income tax provisions.

Changes in the tax provisions resulted in reduced annual net farm incomes on all three
cotton farms. Reduction in net farm income was greater for the largest farm than for the
moderate-size farm.

Financial Bailout Strategies

Restructuring initial debt for highly leveraged farms failed to appreciably increase the
probability of survival for the three Texas cotton farms.

Debt restructure resulted in accelerated farm growth in later years, which contributed to
low probabilities of remaining solvent for 10 years.

An interest rate buy-down strategy increased the probability of survival only slightly for
the two smaller farms while not affecting the largest farm’s probability of survival.

Average ending farm size for an interest buy-down program was only slightly greater than
for the Base Financial analysis.

Neither debt bailout strategy provided much hope for highly leveraged Texas Southern
High Plains cotton farmers without substantial off-farm income to subsidize the farm.

Impact of Technology

Increasing average annual cotton yields had no significant impact on the average growth
rate for the three Texas cotton farms. This result was the same for all three farm policies
evaluated.

V, Farm policies and federal income tax provisions had substantially more impact on the

i average growth rate for the three Texas cotton farms than yield differences between the
most likely technology scenario and the no new technology scenario.

27

Literature Cited:

Gardner, B. L. "Public Policy and the Control of Agricultural Production." Amer. J. Agr. Econ.,
60(1978)836-843.

Gardner, B. D., and R. D. Pope. "How is Scale and Structure Determined in Agriculture?" Amer.
J. Agr. Econ., 60(1978):295-302.

Morton, A. S., S. Devadoss, and E. O. Heady. "Potential Grain Price Instability Under Alternative
Farm Policies." Iowa State University, Card Report 129, 1984.

Office of Technology Assessment. Technology, Public Policy, and the Changing Structure of Ameri-
can Agriculture: A Special Report for the 1985 Farm Bill. Congress of the United States,
OTA, February 1985.

Quance, L., and L. G. Tweeten. "Policies, 1930-1970." Size, Structure and Future of Farms, (eds.,
G. Ball and E. O. Heady), Ames: Iowa State University Press, 1972.

Richardson, J. W., and C. J. Nixon. "Description of FLIPSIM V: The General Firm Level Policy
Simulator." Texas A&M University, Department of Agricultural Economics, mimeo, 1985.

Smith, E. G. "Economic Impact of Current and Alternative Farm Programs on Farm Structure in
the Southern High Plains of Texas." Unpublished Ph.D. Dissertation, Texas A&M Univer-
sity, 1982.

U.S. Department of Agriculture. Economic Indicators of the Farm Sector: Income and Balance
Sheet Statistics. ERS-ECIFS, 2-2, 1982. i

U.S. Department of Agriculture. Farm Real Estate Market Developments. ESCS, CD-84, issues in
1970-1984.

U.S. Department of Agriculture. Unpublished data from the 1979 Agricultural Finance Survey
were provided by USDA. July 1984.

28

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