I971

  
 
   
     

     
   

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  nnscnoum. comma nay“

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  u: CATTLE FEEDING E om!

M special emphasis on economies of size

1

AIM UNIVERSITY
AGRICULTURAL EXPERIMENT STATION
‘unkel, Acting Director, College Station, Texas

Contents

Highlights ........................................................................ .. 3
Introduction .................................................................... .. 5
Regional Production Characteristics ......................... .. 5
Analytical Model and Data Requirements .............. .. 7
Interregional Competition In The

Cattle Feeding—' Fed-Beef Economy .................. .. 9
Effects of Changes In Feedlot Size On The

Cattle Feeding- Fed-Beef Economy .................. .24

Implications of Interregional Economic
Relationships and Regional

Price Differentials ................................................. --26
Potential Adjustments In The

Cattle Feeding- Fed-Beef Economy ................ .. 28
Conclusions ..................................................................... .32
Appendix A:

Development of Data ............................................ .35

Appendix B:
Regional Transportation Rates ......................... .37

Appendix ‘C:
Optimum Solutions for Models 2, 3 and 4 ...... ..4l

Acknowledgment

This research was conducted by The Texas Agri-
cultural Experiment Station of Texas A8cM Univer-
sity under a cooperative agreement with Marketing
Economics Division, Economic Research Service, U.S.
Department of Agriculture and under Texas Agri-
cultural Experiment Station Project HM-2489, Live-
stock Marketing Efficiency and Pricing in the West,
which was a contributing project to the Western
Regional Livestock Marketing Project WM-48.

-Acknowledgment is also made to J. Rod Martin,
agricultural economist, Farm Production Economics
Division, ERS, USDA, for suggestions offered during
the development of the tableau employed in this
study.

i ights

  
  
  
  
 
   
    
  
  
 
 
   
   
  
   
    
   
  
   
   
 
  
   
  

 gional economic relationships in the cat-
‘g-fed-beef economy have changed dra-
if with the advent of modern commercial
,lot operations and the establishment of
 'alized cattle slaughtering and processing
F concentrated cattle feeding areas. Con-
} ~justments relative to location, size and
rm, volume and type of output, and man-
practices employed are essential if cattle
j» slaughtering firms are to compete in the
' ing — fed-beef economy.

“study utilizes a multi-dimensional tranship-
iel to determine the least-cost location and
levels of cattle feeding and fed-cattle slaugh-
 27 specified regions in the 48 contiguous
»,satisfy the demand for fed beef. Models
' developed to systematically measure the
 specified changes in regional feedlot size
i, ted 1975 regional feedlot sizes on the opti-
'nal location and levels of cattle feeding
ter. In addition, the study shows the least-
ent routes for feeder cattle, feed grains,
V ter cattle, and dressed fed beef to meet
i d requirements in the various sectors of
, feeding- fed-beef economy.

i; showed that readily available supplies of
t and feeder cattle and economies of size
operations are of major importance in
" g the optimum location and levels of cattle
legions with the most favorable competi-
i tage in cattle feeding exist primarily in a
 area encompassing the Texas-Oklahoma
 , New Mexico, ‘Colorado, Kansas-Nebraska,
'is, portions of lhe Eastern Corn Belt, and
Tennessee.

‘ties of size in cattle feedlot operations
A fluence the location and, especially, the
‘vels of cattle feeding. However, the find-
g ed that economies of size in cattle feeding,

by themselves, are generally not sufficient to offset
severe locational disadvantages relative to available
sources of feed grains and feeder cattle. Locational
disadvantages relative to market outlets can be par-
tially offset by economies of size in feedlot operations
provided resource inputs such as feed grains and
feeder cattle are readily available.

Optimum solutions with regard to the cattle
feeding—fed-beef economy suggests the following:

1. Under present conditions, total costs of pro-
ducing and distributing fed beef are minimized when
cattle feeding is concentrated predominantly in the
Southern Plains, New Mexico-Arizona, Colorado,
Kansas-Nebraska and the Central Corn Belt.

2. Increases in minimum regional size to 5,000
head would tend to be most beneficial to cattle feed-
ers in the Corn Belt, the Lake States and the North-
ern Inter-Mountain States; it would have severe
repercussions on some of the current major feeding
areas as Nebraska, Kansas, California, Colorado, New
Mexico and East Texas where most feedlot market-
ings are generally accounted for by feedlots with
one-time capacities in excess of 5,000 head.

3. Total costs are minimized when fed cattle
are slaughtered in the concentrated cattle feeding
areas; but when regional slaughter capacities are
below the regional feeding levels, total costs are
minimized if fed cattle are shipped to states in the
Southeast or the Northeast rather than to the West.

4. Fed-beef distribution costs are minimized
when regions West of a line from the western edge
of the Plains States through the center of the Texas
Panhandle ship surplus beef West and regions east
of this line ship to the deficit Northeast, Southeast
and East South Central markets. The exception of
this pattern is West Texas which is able to ship to
the West and Southeast.

5. When regional feeding and slaughter capa-
cities are assumed to be unlimited and assuming

3

1975 projected regional feedlot sizes-

(a) Almost two-thirds of the U.S. fed cattle
would be finished in the Texas-Oklahoma Pan-
handle, Kansas and Nebraska with Iowa and
Illinois accounting for another one-sixth of the
total.

(b) Kentucky-Tennessee appeared as a ma-
jor cattle feeding area along with New Mexico,
Colorado, Arizona and the Eastern Corn Belt.

6. Under present conditions, regions facing the
highest competitive disadvantage with respect to
feeding cattle and/or slaughtering fed cattle were
located primarily in the Far West, the Inter-Mountain
States, the Lake States, portions of the Corn Belt, the
Northeast, and most of the states in the South.

The rapidly changing economic environment in
the cattle feeding— fed-beef economy during the last
decade suggests numerous additional changes at the
local and regional levels in the fed-cattle production,
cattle slaughter and processing, and fed-beef distri-
bution sectors. Such changes, in turn, signify con-
tinuous adjustments in regional competitive positions
and alignments.

Substantial competitive advantages may accrue to
regions which adjust to a changing competive envir-
onment and are able to realize savings through such
factors as (1) economies of size in feedlot operations,
(2) locationof feeding facilities in or adjacent to
major surplus feed grain producing areas, (3) location
of feeding facilities in or adjacent to major surplus
feed grain producing areas, (4) cost advantages in
acquiring feeder cattle. Realization of regional com-
petitive potential is, of course, also dependent on such
regional factors as wage rates, level of management,
availability of various resource inputs, taxes, the
changing structure of demand and so forth. These
and other factors require constant analyses and sur-
veillance by firms in the highly competitive cattle
feeding — fed-beef economy.

4

  
 
 
  
 
  
  
 
  
 
 
   
  
 
  
 
  
    
 
 
   
 
  
 
  
 
 
  
 
  
 
 
 
  

lgmmercial cattle feeding industry, a highly
A and rapidly expanding industry, is per-
10st dynamic sector of the U.S. agricultural
The modern commercial cattle feeding
resented by large and highly mechanized
rations with large investments in fixed
nd resource inputs and by highly spe-
i nagement and labor. Furthermore, com-
ttle feeding firms compete for available
and market outlets on a regional or na-
 This contrasts with the numerous rela-
ill farmer-feeders who are dependent pri-
p resource inputs and market outlets on a
I basis.

I i rapid expansion of cattle feeding in the
fPIillIlS and other major cattle feeding areas
raged increased competition for resources
 cattle feeding firms and for fed-cattle and
arkets. Important economic considerations
f.» within the cattlefeeding industry include
l'ons as optimum location of feedlot facili-
g e to available resources and market outlets,
‘ regional levels of cattle feeding, and opti-
iional allocation of feeder cattle and feed
Ptisfy the demand for fed beef in the United
j a least-cost basis}

i‘ many of the necessary ingredients for cat-
l» are located in the North Central, the
‘I High Plains and the Western States, about
l; U.S. population is concentrated in the
and the South. In addition, the preva-
large, mechanized cattle feedlot operations
' of the major cattle feeding areas raises
concerning the effects of economies of size
I um location and-f optimum levels of cattle

i study is designed to answer these questions.
nts the third phase of a comprehensive

" to the United States in this study denotes the 48
i states.

INTERREGIONAL COMPETITION
IN THE CATTLE FEEDING ECONOMY

with special emphasis on economies of size

Raymond A. Dietrich, assistant professor,
Department of Agricultural Economics and Rural Sociology,
Texas Al-M University

economic analysis of the cattle feeding industry with-
in the Southern Plains. However, this study includes
analyses for other cattle feeding areas since major
emphasis is placed on the competitive interregional
position of the various cattle feeding regions relative
to the available resources and the market outlets for
fed beef. The first study was a detailed analysis of
management practices and cattle feeding systems in
the Southern Plains? The second study was con-
cerned with costs and economies of size in the Texas-
Oklahoma cattle feeding operations?

REGIONAL PRODUCTION CHARACTERISTICS

Major differences exist within and between
most regions of the United States with respect to
the location and concentration of potential fed-beef
consumers, cattle feedlot operations, and commer-
cial cattle slaughter production. In addition, major
differences are also apparent within and between
most regions in annual calf crops and annual feed
grain production relative to the regional fed-cattle
production.

The majority of the U.S.-fed cattle have been
and are produced in the North-Central region, Table
1. Although the numbers of cattle and calves on
feed on January l increased in the North-Central
region during the 1955-70 period, the proportion of
the U.S. cattle and calves on feed declined from 72
percent in 1955 to 59 percent in 1970. During recent
years the rate of growth of cattle feeding has been
lower in the North-Central region than it has for the
United States. Numbers of cattle and calves on feed
increased 33 percent in the United States from 1965
to 1970; they increased 25 percent in the North-

“Dietrich, R. A., The Texas-Oklahoma Cattle Feeding Industry
--Structure and Operational Characteristics, B-1079, Texas
Agr. Exp. Sta., Texas A8cM University, College Station, Texas,
December 1968.

“Dietrich, R. A., Costs and Economics of Size in Texas-Okla-

homa Feedlot Operations, B4083, Texas Agr. Exp.'S'ta., Texas‘

A8¢M University, College Station, Texas, May 1969.

TABLE 1. CATTLE AND CALves on FEED As A PERCENT or UNITED STATEs ToTALs, sELEcTEn
FEEDING AREAs, JANUARY 1, 1955-70

AREAS 1955 1960 1965 1970 _

_ _ _ _ _ _ _ _ _ _ _ PERCENT _ _ _ _ _ _ _ _ _ _ _ _ _ _ cattle fed. Small feedlots accounted for 11.!

1111:"   a 3 15:1 1°Z§§$2§.?§ 3231225331.? ?.i‘.i‘§.‘§f‘ei‘.2§; 
..2:.:*::::..../  a: a: as" g ' »
‘M 2m I” 1M m, contrast, large feedlots marketed more v_
15:11:31: 13:2 g1? 13:; 1;‘, cent of the fed cattle in Texas, Califor
“Egiggiaggzlgm "Hm     Zonalcllzxrntghlllfigihree-fouréhs of the US i‘
$013301  gig  51g are currentlya roduced in the North-. 
mgzEgrligglN mm 1:: Z33 3:; gig Table 3 Twd) North Central States I0 ‘i
100.0 100.0 100.0 100.0 ' ' V

UNITED STATEs
1

0n|o, luo|AuA, ILLINOIS, MICHIGAN, H|scous|u, MINNESOTA, lowA, M|ssouR|, NORTH
DAKOTA, SOUTH DAKoTA, NEBRASKA AND KAusAs.

_ MouTAnA, |DAHO, Hvonuuc, COLORADO, New MEx|co, AR|zouA, UTAH, HAsu|ucTou, Daecou,
CALIFORNIA AND NEVADA.
3/

DATA FOR GEoRc|A, FLoR|oA, KENTUCKY, Tennessee, ALAaAMA AND MISSISSIPPI wene nor
PUBLISHED UNTIL 1960.

Souncez CATTLE on FEED, U.S. DEPT. Aca|., Cnov RPT. Bo., STAT. RPTG. SERV.,
SELECTED Issues.

Central region, about 200 percent in Texas, 100 per-
cent in Oklahoma and almost 50 percent in Colo-
rado and Arizona. Kansas and Nebraska were the
principal states in the North-Central region with sub-
stantial increases in cattle feeding.

Lots with less than 1,000-head capacity repre-
sented 99 percent of the total feedlots in the l0 lead-
ing cattle feeding states in 1969, Table 2. These
states annuallyaccount for about 80 percent of the
fed cattle marketed in the United States. Numbers
of feedlots with less than 1,000-head capacity declined
12 percent in these states from 1964 to 1969, but mar-
ketings from these small feedlots increased 24 per-
cent. During the same period, numbers of feedlots
with 1,000-head-and-over capacity increased almost
one-third while marketings from these large feedlots
increased more than 85 percent. These data reveal
that the expanding large feedlots have been increas-

TABLE 2.

UNDER l,000 HEAD

1
NUMBER OF FEEDLOTS AND NUMBER OF FED CATTLE MARKETED BY SIZE GROUP TEN LEADING CATTLE FEEDING STATES AND PERCENTAGE CHANGES l969-69-

   
 
   
  
  
   
 
    
  
   
 
  
  
   
 
  
  
  
   
 
 
 
 
 
 
 

ing in size, and small feedlots, although L
numbers, have also increased in size and

nois, account for about one-third of 
grain production. Texas, the principal i?
Central State that produces a substantial“
feed grain annually, accounts for about 
the U.S. production. 

The U.S. calf crop, which increased a 
cent from 1955 to 1970, is produced m‘
South Central and West Central States, y
as, the leading state in terms of cow U
and older, annually accounts for about 
the U.S. calf crop. Almost half of the U _
are currently held on farms and ranches ' 
ern High Plains and the Southeastern "i,
cows accounted for three-fourths of the t‘
numbers on January l, 1970 as compar
more than one-half in 1955. I

Commercial cattle slaughter plants i
Central region account for more than hal
commercial cattle slaughter, Table 5. Sla
in the west North-Central region, alone, 
count for more than 40 percent of the]
slaughter. The western region accounted-v
21 percent of the U.S. cattle slaughter.
compared to 16 percent for slaughter 
South-Central region. Commercial cattle *
increased sharply in Texas since 1960 wi 1

/

 

Oven 1,000 HEAD

|TEM Penceur '

    

PERCENTAGE
1961 1969 CHANGE 1961 1969 cnAl0l'?
1961-69 19: -5;
Nunaen Numaen PERCENT Numsen Nuuaen
Nunaea OF LOTS:

louA 15,919 13,839 - 1.6 51 163
NEBRASKA 21,110 20,719 -11.1 330 189
TExAs 1,527 1,300 -11.7 207 300
CALIFORNIA 281 173 -38.1 323 281
COLORADO 1,152 1,226 6.1 81 120
KAN$A§ 13,111 8,871 -31.0 56 126
ILLINOIS 31,931, 21,961 -21.8 66 36
ARIZONA - 27 ' I 8 -70.1 82 51
MINNESOTA 21,060 19,868 - 5.7 20 32
MISSOURI 17,981 17,968 - 0.1 16 32
ToTAL 157,168 138,939 -11.8 1,232 1,633
CATTLE MARAETED: 1,000 1,000 1,000 1,000
HEAD HEAD I HEAD HEAD

lowA 2,853 1,191 17.0 116 121
NEaRAsKA 1,196 1,552 3.7 910 1,770
TexAs 122 111 - 9.0 819 2,595
CALIFORNIA 50 17 -66.0 2,011 2,010
CoLoRAoo 315 311 - 1.3 636 1,116
KANSAS 376 550 16.3 310 1,121
ILLINOIS 1,139 1,132 - 0.6 101 81
ARIZONA 21 -67.5 576 811
M|nuEsoTA 666 755 13.1 37 18
MISSOURI 135 662 52.2 61 69

ToTAL 7,176 9,287 21.2 5,637 10,111 85

_ Nunsen or FEEDLOTS HITH 1,000 - HEAD - on - none cAPAc|Tv |s NUMBER OF LoTs OPERATING ANY TIME ounauc THE YEAR.
nunaen or ALL FEEDLOTS IS uunaen AT eun or vEAR. ‘ -,
Sounce: Nunaen OF FEEDLOTS BY SIZE Gnouvs AND Nunaea OF FED CATTLE MARKETED 1962-1961, SR8-9, AND CATTLE on FEED, MT. Au. 2-1 (1-70), U.S. DEPT. Acn., CnuP_5
Rwrc. Bo., STAT. RPTG. $ERV., June, 1966 AND JANUARY, 1970. 3.

Numsea unoen 1,000 - HEAD CAPACITY Ann Tali
f.

   
  
  
  
   
   
 
 
  
 
  
 
  
 
 
  
 
 
 
 

5 1mm PaooucT1oN, ANo PEacENTAcE u1sTa1euT1oN, 11v sELEcTEo
~. l E FEEDING sTATEs. 1967-69

1967 1968 1969
- - - - - - - --1,000ToNs------------
176,026 168,902 1711,279
1 l 1
6.3 7.0 6.11
5.8 6.3 5.7
5 .7 .7
77 3 78.8 77.1
17.6 15.11 15.8
16 7 16.2 15.8
7.6 8.3 7.9
7.5 .7.0 9.0
3.6 11.2 11.5
3.5 11.11 3.2
20.8 23.3 20.9
11.9 5.0 5.5
1.8 1.8 1.5
.7 .7 .8
.5 .5 .11
1.9 2.0 2.8
11.5 9.2 11.0
100.0 100.0 100.0

 IANA, lLL1No1s, H1c1-11cAN, N1scoNs1N, M1NNEsoTA, lowA,
DAKOTA, 8oL1T11 DAKOTA, NEaaAsNA ANn KANsAs. Howevea,

1 aAL sTATEs aePoaTeo PRODUCTION FOR EAcw oP THESE caoPs.
 , loAao, NYomNs, CoLoaAoo, New ltxtco, Aa1zoNA, Una,

~ , CAL11=oaN1A Aao NEvAuA. Howevea, NoT ALL sTATEs

 1011 aEPoaTeo PRODUCTION FOR eAcw o1= THESE caoPs.

V, 1 ~ 1011, 0.8. DEPT. Aca., CaoP RPTG. 80., STAT. RPTG.

Issues.

n

of large, specialized, shipper-type cattle
 plants near the concentrated cattle feed-
i the Northern Texas Panhandle.

I. MODEL AND DATA REQUIREMENTS

 vtitive regional advantages or disadvant-
tle feeding may occur as a result of re-
 rences in the availability of feeder cattle
 grain supplies, economies of size in
 ations, market outlets, management prac-
jyed, capital and so forth. This study is
‘*1 determine estimates of regional -advant-
dvantages. in cattle feeding due to some
 ferences.

 
 
  
  
   
   
    
 
  
  
  
  

y;

i’ , 0. 8. PaooucnoN, ANo PERCENT n1sTa1auT1oN,aY GEOGRAPHIC

1955 1960 1965 1970
- - - - - - - - - --1,00011EAo-------------
, 112,566 39,353 113,353 115,372
jam: - - - - - - - - - - - - 1 - - - - - - - - - - - - - - -
7.2 7.2 6.0 5.1
L 15.5 111.6 12.7 11.0
£1
l. 26.7 26.2 27.1 27.0
7.7 7.5 7.7 7.8
25.9 26.8 28.3 $1.11
9.9 10.11 10.6 11.7
3.6 3.7 11.3 11.5
12.11 12.7 13.11 111.2
17.0 17.7 18.2 18.7
100.0 100.0 100.0 100.0

1aE, VemowT, HAssAcwusETTs, Rnooe IsLANo, coNNecncuT, New
A1111 PENNsYLVANIA.

 lLL1No1s, H1c111cAN ANo Hiscbwsna.
z , Hlsswal, NoaTN DAaon, 8ouT1-1 0A1<on, NEBRASKA ANn KANsAs.
:3

'1 1n, V1ac1111A, HesT V1ac1N1A, Noam CAaoLlwA, 8ouT11 CAaouNA,
see, ALAaAMA, M1ss|ss1PP1, AaxANsAs, Lou1s1ANA, lkLAwoMA

01011111111, CoLoaAoo, New ltxmo, Aa1zoNA, Una, NevAoA, HAsmNcToN,

lruawn.
‘MAL 81AT1sT1cs ANo CALP CaoP, 0. 8. DEPT. Aca1., sELecTEo 1ssuEs.

TABLE 5. Comeacnt cATTLE SLAUGHTER, AND PEacENT 01sTa1auT1oN, av GEOGRAPHIC
REGIONS, 1960, 1968, ANo 1969

ITEM 1960 1968 1969
- - - - - - --1,00011eAo----------
0. 8. SLAUGHTER 25,2211.3 35,026.11 35,2363
D1sTa1auT1oN BY REGION: - - - - - - - - - - - 1 - - 1- - - - - - - - - -
l/
NORTH ATLANT1c l 7.7 11.8 11.7
2
EAsT Noam CENTRAL-l 19.7 111.7 111.5
3

was: NoaTw 01211111111‘ 311.3 111.2 110.5
8ouT11 ATLANTIC- 5.0 3.9 3.8
8ouT11 CENTRAL- 12.9 15.3 15.6
TExAs 5.9 7.9 8.5
01<LA11oMA 1.3 2.0 2.0
0T11Ea 800111 CENTRAL 5.7 5.11 5.1
11esTEaN' 19.9 20.1 20.9
UNITED STATEs 100.0 100.0 100.0

_ MAINE, New HAMPSHIRE, VERMONT, MAssAcwusETTs, Rwooe IsLAND, CoNNEcT1cuT,
New YORK, New JERSEY, ANo PENNSYLVANIA.

11v
\

01110, INDIANA, 1LL1No1s, M1c111cAN ANo N1scoNs1N.

It»
\

M1NNEsoTA, lowA, Mlssoual, NORTH DA1<on, SOUTH DAKoTA, NEBRASKA AND KANsAs.

14-‘
\

0eLA11AaE, MARYLAND, VIRGINIA, HesT VIRGINIA, NORTH CAaouNA, SOUTH CAa0L1NA,
Geoaen ANo FLORIDA.

lu1
\

KENTUCKY, TENNEssEe, ALABAMA, M1ss1ss1PP1, AaKANsAs, LOUISIANA, tkLAuouA,
Ann TexAs.

lm
\

MONTANA, IDAHO, mamas, CoLoaAoo, New l-‘Exwo, Aa1zoNA, Una, NevAnA,
HASHINGTDN, DREGON ANo CAL11=oaN1A.

Souace: L1vEsToc1< ANn FEAT 8rAT1sT1cs, 0.8. DEPT. Aca1., sELEcTEo ISSUES.

The model developed for this study is a multi-
dimensional transhipment model in which the com-
bined costs of producing and moving fed beef from
the various cattle feeding and slaughtering regions
to consumption centers are minimized. More spe-
cifically, given regional data relative to feeder cattle
and feed grain supplies, feed grain requirements for
non-feeder cattle livestock, feed grain requirements
per head fed, fed-cattle carcass weights, feedlot and
slaughter capacities, and various transfer and produc-
tion costs, the model allocates cattle feeding and fed-
cattle slaughter so that the total costs of producing,
slaughtering and distributing the fresh beef required
by U.S. consumers is minimized. Regions selected for
study along with a central shipping or receiving point
are shown in Figure l. The linear programming
approach was utilized to obtain optimum solutions
for this study. The theory of linear programming
and the "linear restraints and assumptions necessary
for optimal solutions are well documented in other
sources and will not be reviewed in this study.‘

The model developed for this study is shown
in Table 6. An example of the row designations in
this tableau are: -

COST—l 1 —regional transportation costs for

- shipping feeder cattle (FDRCAT),

feed grain (FEEDGR), feed grain

for other livestock (OTGR), fed

cattle on a carcass basis to slaughter

(FCSL), and fed beef to consump-
tion (FBD).

‘For interested readers see Heady, Earl O. and Wilfred Candler,
Linear Programming Methods, Ames, Iowa: Iowa State Press,
1958 and Freeman, B. G. and C. F. Lard, A User's Guide to
Linear Programming and The IBM MPS-360 Computer Rou-
tine, Dept. of Agr. Econ. and Soc., Texas A8cM University, Dept.
Tech. Rpt. No. 70-2, June 1970.

U
9 1
PORTLAND

   
 

LUBBOCK

 
  

HOUSTON
8 Q

 
 
  
  
  
  
    
  
   
  
   
  
      
   
   

* Guymon

Figure l. Regional demarcation and regional shipping and receiving points. 

COST-Q — identical to "COST-l with the ex- An example of the column designations i?

ception of fixed feeding costs leau are as follow: ‘t
(FDLT), and the addition 0f OIFDRCATOI —permits shipment 0t 
slaughter costs to transportation on a per head basis fr y‘
charges for moving fed cattle t0 to feedlots in mgion 1,“
slaughter on a carcass basis (FDSL). OIOTGROI _ permits Shipment of f . F"

OIFDRCATSU —feeder cattle supply in region 1, a hundredweight basisf v
l for feeding to lives
than feeder cattle in r A
OIFEEDGROI —permits shipment of 

_ _ _ _ ' i a hundredweight basis _
OIFEEDGR — feed gram supply 1n region 1, 1 to feedlots in region 1-‘

OIOTGR —feed grain requirements for feed-
ing livestock and poultry other
than cattle in feedlots for region 1,

OILOT F EED - grain requirements per head in 0lFDLT0l — the level of cattle feedi 
region l and shipments of avail- 1 as governed by feed]
able grain/for feeding to region 1, feed grain supplies, fe Pg

OILOTCAT — summation of feeder cattle shipped quirements Per head fedi
to region l feeding costs, 7

OILOTCAP — annual feedlot capacity in region l, OIFCSLO] — ililflgxémrciztiicggs fzleicgziltttle‘

OIFCSLA —fed-cattle shipments to slaughter f§gi°n 1 l0 Slaughter 
from region l on a carcass weight 810T! l, - p‘
basis, 0lFBD0l —carcass shipments fro

OISLACAP —annual slaughter capacity in re- Plamsf“ reglo“ l m cup
gion l’ m region l. 
. . . The sources of data and the meth”

OIOIFBSU _ ted-beef Supply m region l’ ployed for estimating the basic data whic

OIFBD — fed-beef demand in region 1, the cattle feeding—fed-beef economy for
8 

   

A THE TABLEAU EMPLOYED FOR OPTIMIZING CATTLE FEEDING, FED CATTLE SLAUGHTER, AND FED BEEF DISTRIBUTION 

  

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__ IEPRESENTS ONLY A SMALL PORTION OF THE TABLEAU ACTUALLY EMPLOYED.

tppendix A. In order to depict existing
t“ in the cattle feeding—fed-beef economy,
i: models were designed so that shipments
both within and between regions.

W of this study are not intended as precise
 of prevailing conditions for 1968 or as
fictions for the future. Results from the
‘Eu should therefore be interpreted ac-
 Five models or situations were utilized to
v ights and guidelines for decision making
ltle feeding- fed-beef industry:

_odel l was designed to approximate the
_onditions that existed for the cattle feed-
f-beef industry for I968. This model deter-
‘, competitive position of each region in
p; and distributing fed cattle and fed beef.
regional data utilized in this model, with
'on of transfer costs, are shown in Table

A_"0(I€IS 2 and 3 are designed to provide opti-
y‘ tions concerning the effects of econo-
 in feedlot operations on the interregional
g relationships in, cattle feeding and the dis-
{of fed beef. Tlifese models provide insights
1f; changes in interregional economic rela-
‘Ag-and location of cattle feeding as feedlot
systematically increased in regions like the
t and most Southern States where farmer-
sedominate. Models 2 and 3 are similar to

0
YO
\I

1.00 1.92 1.92 1.101 .8! 1.59 1.59 1.11

10.00 10.7a 1.29 2.21 2.20 1.69 .0» 1.59 1.59 1.11
090,000

2,129,000

2ss,e00

231,000

121,000

1373,1100

1,021,910
1.0 0
5,202,620
-6.50 1.0 1.0 0
0,309,500
1.0 1.0 0
1.0 1.0 0
u,aa1,190
922,130

THIS EXAMPLE IS INTENDED TO DEMONSTRATE THE VARIOUS SITUATIONS THAT HERE INCLUDED IN THE BASIC MODEL.

Model 1 with the exception of assumptions concern-
ing regional feedlot size and associated fixed feeding
costs.

3. Models 4 and 5 provide optimum solutions
relative to the location and levels of cattle feeding
as implied by estimated regional feedlot sizes for
1975. Model 4 incorporates all the basic assumptions
of Model l with the exception of projected I975
regional feedlot sizes. Regional capacity restrictions
are not a limiting factor in Model 5.

INTERREGIONAL COMPETITION IN THE
CATTLE FEEDING — FED-BEEF ECONOMY

The competitive environment within the cattle
feeding-fed-beef economy is constantly changing.
Therefore, continuous adjustments in location, size
and type of firm, volume and type of output, and
management practices are essential if firms are to
compete. Given the regional data and consumption
levels, the transhipment model designed for this study
reveals the economic interrelationship and competi-
tive position among regions in the cattle feeding-
fed-beef economy for 1968. In addition, it provides
solutions for determining (1) optimum location and
levels of cattle feeding including least-cost shipment
routes for feeder cattle and feed grain, (2) optimum
location and levels of fed-cattle slaughter and least-
cost shipment routes for fed cattle, (3) least-cost ship-
ment routes for dressed fed beef so that total demand
requirements are met, and (4) the competitive posi-

9

TABLE 7 . ESTIMATED FEEDER CATTLE SUPPLIES, FEED GRAIN SUPPLIES, FEED GRAIN REQUIREPENTS FDR NON-FEEDER CATTLE LIVESTOCK, ANNUAL FEEDLOT CAPACITY, FIXED FEED i
FEED GRAIN REQUIREPENTS PER HEAD FED, FED CATTLE CARCASS HEIGHTS, ANNUAL SLAUGHTER CAPACITY, SLAUGHTER COSTS, AND FED BEEF CONSUMPTION, BY REGION, f

  
  

FEEDER CATTLE FEED GRAIN FEED GRAIN FOR ANNUAL FEEDLOT

FIXED FEEDING FEED GRAIN PER FED CATTLE ANNUAL SLAUGHTER sLA ' 1

 
 

  
  
   
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  

 

R50|011 SUPPLIES SUPPLIES 9711511 uvesrocx CAPACITY cosrs 115110 FED cmcnss 1115131113 CAPACITY 1,; ;
10,000 10,000 Dotuas PER ' Datum ,
151g Eggs gayls H_5/1_0 POUND 01-" c1111 Egg Brigg 100 POUNDS 100 P ,, '
(1) HAsu.,0R5c. 891,000 121,800 269,600 878,137 $.0160 2,679 651 6,262,620
(2) I110u7.,l01111o,1tvo. 2,129,000 373,100 237,000 1,327,911 .0159 2,672 650 1,309,500
(31 UrAn,N5v. 170,000 37,1100 121,100 305,622 .0209 2,110 591 2,073,060
(1) CALIF. 875,000 535,800 977,100 1,137,761 .0121 2,198 606 18,913,260
(5) A1112. 219,000 151,200 69,800 1,209,510 .0129 2,019 572  2,857,110
(6) NJEX. 192,000 88,600 67,1100 607,178 .0135 2,071 577 I 1,923,111
(7) 11.1511. 1_/ 1,119,000 1,253,200 193,000 2,830,151 .0121 2,093 582 11,389,710
(8) E.T5x. _2/ 2,391,000 679,800 156,100 1,137,711 .0117 1,387 111 1,679,760
(91 11 0m. g/ 111,000 129,100 51,100 125,015 .0135 2,311 637 1,363,100
(101 5.01m. 1/ 1,120,000 75,600 103,100 333,060 .0102 1,909 527 2,635,000
(11) 001.0. 790,000 211,100 151,000 1,926,156 .0132 2,021 600 11,655,200
(12) K1111. 1,139,000 1,296,000 183,800 2,338,715 .0151 2,663 6118 10,782,720
(131 N501: 1,552,000 2,100,000 793,200 1,012,520 .0171 2,723 660 27,119,100
(111) N.D.,S.D. 2,213,000 1,793,600 685,800 9113,9112 .0280 2,808 676 6,330,061
(151 M11111.,H|s. 1,602,000 3,609,000 2,260,600 1,563,230 .0322 2,657 617 20,091,065
(16) IOWA 1,057,000 11,911,100 2,559,000 5,113,788 .0302 2,8111 678 31,106,610
(171 111. 559,000 1,721,600 1,399,200 1,129,000 .0331 2,965 707 11,007,990
(101 H1c11.,lu0.,01110 775,000 1,133,000 1,973,100 2,310,705 .0333 2,305 629 17,107,125
(19) M0. 1,191,000 1,355,000 900,200 1,001,663 .0323 2,663 6110 10,303,200
(20) ARK.,LA. 1,053,000 72,200 915,800 33,000 .0373 1,917 530 1,871,960
(21) M|ss.,ALA.,GA. 1,957,000 513,000 2,207,200 297,677 .0269 1,917 530 5,821,700
(22) FLA. 375,000 80,800 361,100 155,110 .0195 2,635 6113 2,615,915
(23) N.C.,S.C. 355,000 553,800 1,016,000 86,900 .0520 2,253 617 1,963,291
(211 1116,1611. 1,313,000 529,000 061,000 176,301 .0302 2,272 622 5,303,110
(25) W.VA.,VA.,I'ID.,DEL. 158,000 110,800 776,100 81,100 .0511 2,761 667 2,770,718
(26) PA. 5/ 107,600 610,200 286,210 .0381 3,151 7113 6,582,980
(27) NORTHEAST fi/ 191,200 1,121,000 25,000 .0555 2,953 705 6,800,130
u. s. 27,100,000 30,151,000 21,793,000 36,522,070 -- -- -- 236,967,312
1/ 115st 15x13 111010053 CROP REPORTING DISTRICTS 1-N, 1-S, 2-N, 2-S, 3, 6 AND 7.
2/ E/(sr TEXAS 111c1.u05s CROP REPORTING DISTRICTS 11, 5-N, 5-S, 8-N, 8-8, 9, 10-11 AND 10-8.
§/ 11537511111 OKLAHOMA |uc1.u05s CROP REPORTING DISTRICTS 1, 1 m0 7._
3/ 9137511111 0011111011111 111010053 CROP REPORTING DISTRICTS 2, 3, 5, 6, 8 11110 9.
5/ P550511 01111.5 SUPPLIES 115125 591111111750 70 05 "0" m 115010113 26 11110 27 00121113 1968. S55 APPENDIX A.

tion and potential of regions in competing for feeder
cattle, feed grains, fed slaughter cattle, and market
outlets for fed beef.

Assumptions in the basic model relative to re-
gional feedlot size were altered in additional models
to determine and analyze changes in the interregional
economic relationships within the cattle feeding-
fed-beef economy as regional feedlot sizes were syste-
matically increased in selected regions.

Regional fixed-feeding costs, which are used in
this study to depict economies of size in cattle feed-
ing, were, derived by applying the estimated average
regional feedlot size to the fixed feeding cost— feed-
lot size function developed in a study of Texas-
Oklahoma cattle feedlot operations.“ Since detailed
fixed feeding cost data were not available for most
regions employed in this study, it was assumed that
the shape of the fixed-cost functions were generally
similar for the various sizes of feedlots in each region.

“See Dietrich. R. A.. reference cited in footnote 3, page 2|. and
Appendix A for a detailed description of the methodology
employed for estimating regional feedlot sizes. The function
used to estimate costs per pound of gain was log Y, : —.932490
— .23l240 log X where Y, is defined as fixed costs per pound
of gain and X represents one-time feedlot capacity.

l0

     
  
   
   
    
  
   
 
  
    
   
   

Further, it was assumed that the rela‘,
the various regional fixed-cost functio
equal, is influenced by fixed invest“
of capacity. ‘

Previous studies have shown th
ments per head of capacity vary from;
the Corn Belt, from $35 to $160 ini-
States, from $50 to $200 in the Sou
and from $30 to $50 per head of 
Southern Plains.“ In order to ensure ti

"Simerl, L. H., “How Feed Supplies Affect
University of Illinois, Urbana, Illinois, pa“ '
Texas Cattle Feeders Association, Amarillo... _
I970; Erickson, D. E., Hinton, R. A. and ‘
Prospects for Cattle Feeding, Illinois Beef ,
sity of Illinois, Urbana, Illinois, I968; Hun I
den, j. P., Economies of Size For Speciali,
Colorado, FPED, ERS, U.S. Department off
Econ. Rpt. 9l, May I966; Walker, W. G. 11 
Costs and Returns From Drylot Feeding of?
sippi, Agr. Exp. Sta., Mississippi State Unf
liam, H. C., Ihen, L. A. and Toussiant, W v
Analysis of Selected Systems for Feeding 
Carolina, A. E. Information Series No. 1~
Agricultural Economics, North Carolina S 
leigh, North Carolina, April I964; and Di ,
ence cited in footnote 3. "

    
   
   
   
   
  
   
  
  
   
  
  
   
   
    
   
   
  
   
  
  
   
   
 
   
  
  
    
   
  
    
  

fficients as shown in Table 7, column 5,
4* existing regional cost situations for all
nal fixed feeding costs were raised 50
‘ceding areas in the Pacific Northwest,
" States, the Corn Belt, the Lake States
g east." Fixed feeding costs in the South
ft were raised 33 percent.

f»: costs were calculated as follows:
i the regional feedlot size in Iowa, as
 marketings, was estimated to be 346
i methodology employed for estimating
g 0t size is described in Appendix A. This
§- when applied to the Texas-Oklahoma
',-; cost function yielded a fixed feeding
it per pound of gain. Adjustments for
l» fixed investments per head of capacity
’ Southern Plains and Iowa resulted in a
.1 cost of $0453 per pound of gain for
el l. Fixed feeding costs for feedlots
nd 5,000-head capacity as estimated from
klahoma fixed feeding cost function were
6.0163 per pound of gain, respectively.
adjusted fixed feeding costs for Iowa in
1d 3 in which minimum regional feedlot
i at 1,000 and 5,000 head are $0355 and
" pound of gain. This compares with a
1g cost in California and West Texas of
_ the one-time regional feedlot size was
“ly 18,400 head.

decision whether to raise regional fixed
w‘ 50 percent or 33 percent for specified
‘estimated from the Texas-Oklahoma fixed
 function, was based on regional fixed
_. per head of capacity, considerations con-
p} atic conditions in the various regions
tion supplied by feeders in some of the
 , the Corn Belt States and Coloradofi
>7 of fixed feeding costs by 50 percent for
feedlots for the Corn Belt, the Lake States
 as compared with the Southern Plains
; regions in the Southwest appears to be
T" This is also generally true for regions
I and Southeast in which fixed feeding
raised 33 percent.

‘K odels employed in this study, in addition

8.; costs were raised 50 percent in regions 1, 2, ll,
_5, l6, l7, l8, l9, 26, and 27. Fixed feeding costs
J 5 percent in regions 8, l0, 20, 21, 22, 23, 24, and

i visited and conferred with three to six feedlot
in Kansas, Colorado, Nebraska, Iowa, Illinois
 concerning feeding costs and management prac-
 a during the summer of 1969. Reasons generally
f» operators for higher fixed investment costs in
l’ compared to the Southern Plains included higher
V. in barns and shelters for protection from inclement
f‘ from two to three times more pen space per head
7o offset potential mud problems. Feed storage fa-
n» often also used for enterprises other than
_»; were also observed to be more substantial in the
l compared to the Southern Plains.

to the basic model, were designed primarily to meas-
ure the effects of economies of size in feedlot opera-
tions. Models 2 and 3, in which minimum regional
feedlot sizes were set at 1,000 and 5,000 head, respec-
tively, were designed to estimate the impact of lower
fixed costs on the cattle feeding- fed-beef economy
as feedlots expand in size.

Variable costs in this study are represented pri-
marily by the regional price differentials for feeder
cattle and feed grain as determined from the opti-
mum solutions of the various models employed. Costs
associated with feed grain and feeder cattle generally
represent more than 90 percent of the total variable
costs in cattle feeding. All other variable costs were
assumed to be similar in all regions. '

A stipulation was also imposed on all models that
the regional feed grain requirements for livestock
other than cattle in feedlots had to be satisfied from
available supplies of feed grain from current produc-
tion.” Wheat and rye, which accounted for approxi-
mately 4 percent of the total grain consumed by U.S.
livestock and poultry in 1968, are not included in
the available supplies of feed grain. Regional feeder
cattle placement and fed-cattle marketing weights,
along with per head feed grain requirements associ-
ated with regional feeding practices, were estimated
and incorporated into each model.

Least-Cost Feeder Cattle
Shipments and Feeding Levels

Model l was designed to depict the basic inter-
regional economic relationship existing for the cattle
feeding-fed-beef economy during 1968. The least-
cost flow patterns for feeder cattle in Model l are
shown in Figure 2. The optimum regional feeding
levels, feeder cattle shipments (the underscored fig-
ures) and opportunity costs are shown in Table 8.
Opportunity costs, which result when shipments do
not occur within or between regions, reflect the de-
crease in f.o.b. delivered price or the reduction in
transportation costs necessary before shipments would
occur. Conversely, opportunity costs may also be in-
terpreted as the penalty or additional costs incurred
for the system when non-optimum shipment routes
are employed. The annual feedlot capacity, the an-
nual surplus feedlot capacity and surplus feeder cattle
are also shown on a regional basis in Table 8.

The regional feeder cattle flow patterns, as shown
in Figure 2, depict both the optimum distribution
patterns and optimum location of cattle feeding for
1968 when total costs in the cattle feeding- fed-beef
economy are minimized simultaneously. The bulk of
the feeder cattle are shipped either West to feedlots
in the Southwest and Southern Plains or North to
Kansas, Nebraska and the Corn Belt. One notable
exception is California, which ships feeder cattle to

“Other livestock are defined to include all grain consuming ani-

mal units other than cattle in feedlots.

ll

Arizona. These results suggest that the cost of mov-
ing feed grain to California along with relatively
high feeding costs places feeders at a competitive dis-
advantage in that state.

Considerations regarding optimum location and
levels of cattle feeding, among others, include avail-
ability of feeder cattle, feed grains and market out-
lets for live fed cattle and dressed fed beef. Table 8
and subsequent table showing the results of Model
l reveal that one or more of these factors had an
important influence, on interregional competition in
cattle feeding. Other important factors such as capi-
tal availability, labor supplies, weather and so forth
were not considered in this study.

Model l shows that although 80 percent of the
cattle feeding was located in eight principal feeding
areas, cattle feeding apparently will take place in
some areas of the South and the East when capacity
restraints on feeding and slaughtering, including the

    
  
  
   
  
   
 
  
  
 
 
 
 
 
 

effects of existing economies of size,
Table 8. Such capacity restrictions aff
patterns in the optimum solutions to the
they place an upper limit on the volum
or slaughter occurring in any one regi
or unused capacity, which did not affect f
solutions of the models employed, refe ,7
nual estimated capacity not utilized in 
solution. While the model employed 1’,
did not assess a penalty for surplus capa,
capacity in the real world context, w,
longer run, suggests inefficiencies and 1_
investment decisions by individual fi 1».
industry. *

Another major observation is tha“
of the available feeding facilities in x
compassing Washington-Oregon (1), M
Wyoming (2), Utah-Nevada (3), Calif
Arizona (5) are unused when cattle fee“

TABLE 8 . MODEL 1 FEEDER CATTLE SUPPLIES, OPTIMUM FEEDING LEVELS, OPPORTUNITY costs, SURPLUS FEEDER CATTLE, FEEDLOT CAPACITIES AND SURPLUS
FEEDLOT CAPACITY, BY REGIONS, 1968
FEEDER UPTIMUM FEEDING LEVELS 1/
$HlPP1NG CATTLE
REc|ous SUPPLY 1 2 3 0 5 6 7 8 9
H5812
(1) 1181s11.,0REc. 890,000 _66;5_31_3 .05 2.12 1.82 2.36 0.62 6.10 10.51 5.35
(2) Mourulmutgmo. 2,129,000 3.05 5.30 0 3.58 2.39 2.30 3.72 8.00 2.97
(3) UTAH,NEV. 078,000 5.37 0 1.05 2.79 1.10 1.66 3.19 7.03 2.78
(0) CALIF. 875,000 6.31 0.61 0.05 £6,827 Qflg 2.110 5.10 9.65 6.93
(5) ARIZ. 209,000 12.06 9.10 8.33 6.12. 212,000 3.88 6.06 10.15 8.17
(6) NJtx. 092,000 12.111 6.97 6.72 6.23 1.60 09_2J_0@ 2.65 7.62 2.92
(7) HJEx. 1,109,000 11.68 6.16 5.99 6.55 2.00 .37 1,109,000 5.00 .76
(8) E.TEx. 2,309,000 8.97 3.87 0.15 0.62 2123;? jligfl Qgifl 1,037,700 .67
(9) H.01<u1. 011,000 12.53 6.67 6.58 9.76 0.97 1.15 1.11 6.70 5_1_,()_00_
(10) E.01<1.11. 1,128,000 10.60 5.32 5.25 6.02 1.60 .93 .811 3.60 LE
(11) 001.0. 790,000 11.211 5.113 5 10 9.13 0.87 2.56 0.10 8.71 3.13
(12) Km. 1,039,000 11.85 5.09 6.26 8.53 3.811 2.59 2.91 6.01 1.12
(13) NEaR. 1,552,000 11.62 5.00 5.92 9.35 0.79 3.59 11.20 7.27 3.05
(10) N.D.,S.D. 2,213,000 8.96 2.11 0.76 9.70 6.90 5.58 8.99 6.96 2.86
(15) Mmr1.,w1s. 1,602,000 10.112 3.83 6.38 9.711 5.30 0.05 11.38 7.05 3.33
(16) 10m 1,057,000 13.58 6.52 7.72 11.20 6.29 0.85 5.10 7.81 3.97
(17) ILL. 559,000 10.96 7.93 8.83 12.03 6.96 5.33 5.05 7.13 0.31
(18) M|c11.,111o.,01-11o 775,000 13.70 7.00 8.116 11.00 6.62 5.30 5.50 7.09 11.52
(19) Mo. 1,091,000 12.53 6.17 6.95 910 11.311 2.02 2.62 11.86 1.69
(20) AR1<.,L11. 1,053,000 9.70 11.96 0.03 5.26 .37 .10 1,053,000 .71 .53
(21) M|ss.,111.11.,G11. 1,957,000 9.37 3.65 11.119 5.81 .93 .65 .55 1.51 .59
(22) FLA. 375,000 15.02’ 8.116 9.25 10.51 5.37 0.27 3.76 11.01 11.23
(23) N.C.,S.C. 355,000 13.711 7.10 8.23 10.18 11.76 11.19 3.72 0.37 3.83
(20) KY.,TEr1u 1,313,000 11.90 5.115 6.90 9.07 3.25 2.35 1.92 2.92 1.811
(25) H.VA.,V11.,1'0.,0E|.. 058,000 15.113 8.110 9.67 12.98 6.97 6.011 7.03 6.12 5.09
(26) P11. 0 18.20 10.83 10.08 15.97 10.70 8.85 8.80 9.75 7.611
(27) NORTHEAST 0 16.83 9.67 11.70 15.16 10.11 8.50 8.62 9.95 7.118
Tout QL188,000 665,313 0 0 836,827 099,500 607,078 2,830,051 1,037,700 025,005
FEEDLOT CAPACITY 878,037 1,327,910 305,622 0,037,761 1,209,510 607,078 2,830,051 1,037,700 025,005 333,060 l‘
SURPLUS FEEDLOT
CAPACITY 213,120 1,327,910 305,622 3,600,930 710,010 0 0 0 0 0

1/ UNDERSCORED NUMBERS ARE FEEDER CATTLE SHIPMENTS.
costs ARE suovm 111 DOLLARS PER HEAD.

l2

OTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FROM NOT HAVING AN ACTIVITY IN THE OPTI I, 

 

 
   
  

   
 
  
  
 
  
 
  
  
 
 
 
 
 
  
  
  
  

‘i, a least-cost basis within the cattle feed-
if economy. The relatively large inship-
eed grain and feeder cattle which are
a much of this area, including the unfav-
g ion of the Northern Inter-Mountain
ifve to large consumption areas, generally
_ adverse competitive situation for feeders
gtes. Other areas with relatively large sur-
5T1; capacities included North Dakota-South
"), Minnesota-Wisconsin (l5), Iowa (16),
diana-Ohio (18) and Missouri (19). Sur-
 1 capacity in the Corn Belt in Model 1
I is due primarily to the predominance of
fer-feeders in that area, who are unable
V t advantages from economies of size, and
associated with importing feeder cattle
uth or the Northwest.

gmplete absence of feeding in Missouri,
 Model 1, suggests that other nearby

regions were able to realize cost advantages in cattle
feeding, primarily economies of size, which were not
available to Missouri feeders. However, Missouri is
also located close to the large deficit feed grain pro-
ducing areas of the Southeast. Since the model was
required to distribute feed grain to areas deficit in
feed. grain production for livestock other than cattle
in feedlots, total costs were minimized when Missouri
feed grain was shipped to the nearby deficit South-
eastern markets. Later models reveal that Missouri
feeders are able to compete in the cattle feeding
economy as regional feedlot sizes are increased.

Major cattle feeding states utilizing their total
feeding capacities included New Mexico, Texas,
Oklahoma, Kansas, Nebraska and Illinois. These
states were able to realize cost advantages resulting
from one or more factors as economies of size in
feedlot operations or favorable locations relative to
feed grain supplies, feeder cattle supplies and market

SURPLUS
T0711. FEEDER
15 16 17 18 19 20 21 22 23 211 25 26 27 311111111120 00171.1:
"Hi ML
6.110 6.55 0.65 0.05 9.01 11.23 12.66 15.51 11.79 12.73 10.12 13.30 10.05 665,313 220,607
3.211 0.12 5.16 5.60 6.01 5.51 9.72 12.27 11.53 9.66 111.91 10.12 11.72 0 2,129,000
5.52 11.10 6.11 6.60 7,211 0,13 5.55 12.10 12.05 10.61 15.56 5.05 16.02 170,000 0
10.07 0.115 10.02 10.00 10.60 10,59 10.07 15.10 15.36 11.09 20.02 15.15 20.32 075,000 0
11.35 9.55 11.06 11.73 11.60 11.10 13.13 15.115 15.55 111.07 19.67 15.07 20.50 215,000 0
0.20 6.30 7.51 0.55 7.52 0.52 10.02 12.11 13.02 11.21 16.91 12.76 17.01 152,000 0
6.30 1.55 6.02 6.72 5.57 5.57 0.311 9.00 10.51 0.77 15.70 10.07 16.00 1,115,000 0
0.33 1.76 2.119 2.79 2.55 1.77 3.90 11.76 5.73 1.611 9.115 6.15 11.13 2,391,000 0
6.31 1.33 5.95 6.03 5.05 7.113 5.111 11.71 11.93 9.71 15.52 11.10 16.60 111,000 0
3.02 2.12 3.311 3.55 3.30 11:07 5.92 7.61 7.00 6.211 11.63 7.03 12.00 1,120,000 0
6.70 5.25 7.36 0.00 7.30 5.111 11.19 11.10 13.72 11.13 17.33 12.06 10.06 790,000 0
11.116 2.56 1.16 1.97 3.72 6.12 7.05 9.97 10.21 7.92 13.52 9.12 11.63 1,139,000 0
1.12 1.01 1.01 5.11 11.91 7.55 0.511 11.19 11.10 0.71 11.21 10.00 15.12 1,552,000 0
.25 .00 3.31 3.50 3.52 7.10 7.92 11.00 9.611 7.11 12.50 0.15 12.52 2,210,000 0
0 1,602,000 2.00 2.03 3.79 6.66 7.36 9.59 0.06 6.00 11.711 7.33 11.92 1,602,000 0
2.30 1,057,000 3.16 1.311 3.63 7.75 0.37 10.02 10.29 7.00 10.37 9.01 111.23 1,057,000 0
11.01 1.65 gy 2.00 1.95 6.12 6.79 9.30 0.61 5.09 11.70 7.62 13.05 555,000 0
0.50 2.115 1.73 _77_5,0@ 1.01 6.17 6.011 0.011 7.01 5.59 9.76 5.56 10.52 775,000 0
2.57 1,262,107 _22_0,y 2.17 0 11.17 5.23 7.110 7.16 11.06 10.53 6.115 11.02 1,191,000 0
2-55 1-111 1-18 1-56 1-95 0 2.35 3.76 1.111 3.15 0.32 5.06 10.23 1,053,000 0
1-63 ~17 ~27 flifi 110B ~75 @1671 1.51 2.17 .32 6.10 2.06 0.01 1,957,000 0
5-30 3-67 3J1“ 3-09 ‘1-35 3-‘15 0.00 155m 3.20 11.20 7.25 1.51 9.91 155,110 219,050
3-9? 2-57 2-27 1-37 3-“3 3-37 2.111 2.56 0 3.03 11.20 2.32 7.65 0 355,000
2-0" -‘15 @1272 ~09 1-23 1-90 .19 3.65 3.12 gray 7.12 3.911 9.111 017,959 155,011
‘1-‘11 3-23 2-92 1-61 ‘1-37 5-11 11.10 1.05 1.63 1.50 3.61 206,50 6.76 206,210 171,760
6-2? 5-10  , ‘1-78 3-68 6-‘11 8-38 7.05 7.57 5.15 7.011 5.10 0 7.72 0 0
5-57 5415i: A ‘1-97 3-15 6-70 8-73 7.50 7.00 5.53 7.01 7.10 2.65 11.65 0 0
0 3.921.118? 1.129.088 1.267.915 0 0 M257,677 155.110 0 176,001 0 206,210 0 20,500,622 3,599,370
_2 1,560,230 5,113,700 1,125,000 2,310,705 1,001,663 30,000 257,677 155,110 06,900 176,301 01,1100 206,210 25,000 36,522,070
1.563.230 1,222,301 0 1,000,760 1,001,663 33,000 0 0 06,900 0 01,1100 0 25,000 -12,5311.256

 

l3

, u-

  

 
 
 
 

7%

~\c

QEEEQB‘

Figure 2.

outlets. Relatively large supplies of feed grain and
proximity to the deficit fed-beef markets in the
Northeast were of special significance to Illinois
which generally was not able to realize competitive
advantages resulting from economies of size in cattle
feeding. Competitive feeding advantages accruing t0
East Texas may be slightly overstated since the model
did not consider export demand for feed grain.

The presence or degree of economies of size in
cattle feeding operations is an important determinant
relative to a region's ability to compete with other
regions for feeder cattle, feed resources and market
outlets as later models will indicate. Table 8 revealed
that regions like West Texas, Western Oklahoma and
Nebraska, where large cattle feeding operations gen-
erally predominate, utilized all available cattle feed-
ing capacities in Model 1. In contrast, California
and Arizona utilized only about 25 percent of their

l4

m,  ..   

Optimum interregionol flows of feeder cattle (Model l).

   
     

,2

i?

‘i

- c
‘a

5

   

H?“

     
  
   

 
   
  
  
 

L.

 

\

     
    
   
   
  
   
 
  

fir”

  

available capacity in Model 1. Relatively f
lot utilization rates occurred in these two I 1
the fact that almost 100 percent of their.
are marketed from feedlots with 1,000-h
capacity and, in addition, the average - i
city for large commercial feedlot operatioi
two states closely approximates that of _
and Western Oklahoma. Furthermore, si'
in California and Arizona have a locatio i
age with respect to market outlets in the:
beef consuming centers of Los Angeleso
Francisco, proximity or availability of sour
grain and feeder cattle clearly is and will
important determinant in future locatio t
feeding facilities. i

Least-Cost Feed Grain Shipments i
Total feed grain production in any?
generally utilized as feed for livestock p

s3

  
   
   
 
  
  
   
  
  
  
    
   
  
  
 
   
  
 
 
  
 
  

i- ots as well as for cattle feeding opera-
A ore, the models developed in this study
g to simultaneously distribute feed grain
 least-cost basis among the various re-
‘ t regional feed grain requirements for
“Vultry other than cattle in feedlots were
" At the same time, feed grain supplies
 feed for non-cattle feedlot enterprises
v to be moved to cattle feeding regions
i_ basis in relation to the region's ability
j feed grain in the cattle feeding— fed-

reveals the optimum regional distribu-
of feed grain required for livestock or
f, than cattle in feedlots. The quantities
opportunity costs and the quantities of
vailable for distribution to the cattle
 are shown in Table 9.

if“ flow patterns, as revealed in Fig-
“nerally from the Plains States to the
5m the ‘Corn Belt States to the South,
i» Northeast. The quantities shipped,
 ty costs and the quantities of feed grain
c; distribution to the cattle feeding indus-
_w in Table 9. Regions with relatively
if of feed grain available for cattle feed-
‘pment to cattle feeding regions include

West Texas (7), Kansas (12), Nebraska (l3), North
Dakota-South Dakota (l4), Minnesota-Wisconsin (l5),
Iowa (16), Illinois (17) and Michigan-Indiana-Ohio
(18).

Figure 4, which reveals the optimum flow pat-
terns of available feed grain for cattle feeding, also
shows the optimum location of cattle feeding as does
Figure 2. Shipments of feed grain for cattle feeding
move predominantly from the Plains States to the
West and from the Corn Belt to the South and East
in the optimum- or least-cost solution.

The quantities of feed grain shipped for cattle
feeding, the opportunity costs resulting from non-
shipments, and surplus feed grain supplies are indi-
cated in Table l0. Major observations from Table
l0 reveal that surplus or unused feed grains are
present in the optimum solution for North Dakota-
South Dakota (14), Minnesota-Wisconsin (l5) and
Iowa (l6). Such surpluses are normally placed in
storage or become available for exports. Surplus feed
grains accrue in these regions primarily because (l)
competing surplus feed grain regions have a more
favorable location relative to deficit feed grain regions
and (2) small scale feedlot operations which result in
competitive disadvantages in feeding. Furthermore,
regions like North Dakota-South Dakota are also
faced with a locational disadvantage in shipping fed

Ere 3. Optimum interregionol flows of feed groin for feeding livestock other than cattle in feedlots (Model l).

15

beef to most of the major fed-beef consumption
centers. Surplus feed grain producing areas as Illi-
nois, Michigan-Indiana-Ohio and Missouri have a
relatively favorable location with respect to shipments
of feed grain to most of the Southern and East Coast
States.

Another major observation is that the model
allocates feed grain to Washington-Oregon (1) such
that the volume of cattle fed in that region is pre-
cisely equal to the fed-beef demand in that region.
This suggests that although Washington-Oregon is a
surplus feeder cattle producing region, it has a com-
petitive disadvantage compared with West Texas,
Colorado, New Mexico and Arizona in shipping fed
beef to California. Total costs, however, are mini-
mized when the volume of fed beef demanded in the
Washington-Oregon area is supplied by feedlots in
that area.

Given the data and assumptions associated with
Model l, the opportunity costs in Table l0 suggest

11055 9. M0051. 1: 0511mm SHIPMENTS FOR FEED 01211111 FOR uvssrocx 0711511 111m 5550512 01711.5, 05501110111711 0111051110 costs, 11110 FEED 01111111 AVAILABLE PM:
av 11501011, 1968 y.

  
    
  
  
  
  
  
 
 
   
  

that the best potential markets for W’
in addition to the markets to which I
shipped for cattle feeding, in order of 
vantage are California (4), Western Q
and Arkansas-Louisiana (20). Although a
show that feed grains are shipped from,
to feedlots in California and Western O
results from Model l revfeal shipment 
would exist if total 601115111 shipping a)
feed grains, fed cattle and fed beef w,“
for the contiguous 48 states. The least
suppliers of feed grain to Western Okl_
addition to Kansas (l2), are Nebras a
Texas (7) and Eastern Oklahoma (10). v
advantages in shipping to a deficit a 1
tioned not only by location but also byi
surplus quantities in one region comp Q
region. '
Least-Cost Fed-Cattle Shipments

Optimum location is of utmost c0 

.

  

F550 Dssnmruou 1/
81110121110 01111111
11501011 SUPPLY 2/ 1 2 3 11 5 6 7 5 9 11) 11 12 13

(1) HAsn.,0R5c. 121,800 0 .37 .112 .05 .55 .80 1.02 1.21 1.00 1.12 .80 1.09 1.02 -
(2) Pournloauoglvo. 373,000 QQQO .01 .03 01,363 .5 .112 .63 .81 .57 .68 .36 .63 .55 
(3) Ur/111,N5v. 37,1100 .19 .17 .111 3_2,0_65 .18 .35 .57 .77 .56 .68 .35 .66 .60 _
(0) 0111.11‘. 535,800 .03 .75 .61 §£fl0 .112 ‘.77 .99 1.18 1.02 1.12 .96 1.21 1.21 
(5) ARIZ. 151,200 .51 .58 .37 151i .05 .37 .57 .70 .62 .73 .59 .81 .87
(6) N.("£x. 88,600 .111 .00 .19 0 .02 .08 .22 .03 .25 .36 .25 .05 .51
(7) HJEX. 1,253,200 .01 .39 .19 102,03) 69,800 @300 193,000 .13 .05 .11 .16 .25 .31
(8) EJEX. 679,800 .68 .65 .07 .27 .25 .29 .21 fiflj .31 .21 .03 .38 .116
(9) 11.0mm. 129,000 .36 .30 .15 Egg .02 0 .02 .20 20,82 .06 .06 .12 .18 _
(101 0.0m. 75,600 .119 .112 .20 .11 .111 .12 .09 .11 .07 ggg .20 .13 .22 A
(11) 001.0. 211,000 .22 .15 ii 0 .05 .06 .19 .38 .12 .5 .01 .22 .1) 5
(12) 10111. 1,296,000 .00 .211 .10 .07 .09 .00 .10 .15 Ly 1_7_1_,g1g .011 gggg .02
(1a) 1151111. 2,100,000 .211 .111 .05 .00 .13 .12 .111 .21 .011 .07 Edgy EL)» my
(111) N.D.,S.D. 1,793,600 .111 QQQQ .08 .10 .23 .211 .26 .33 .17 .19 .10 .12 .03 y
(15) M|NM.,H1s. 3,689,800 .27 .10 .20 .22 .29 .29 .31 .31 .22 .20 .17 .10 .08 
(16) 1011A 11,910,000 .33 .19 .10 .16 .20 .19 .21 .19 .12 .08 .10 .05 0
(17) (LL. 0,720,600 .09 .36 .30 .27 .29 .28 .28 .22 .21 .15 .23 .10 .17 
(18) M|c11.,|u0.,0111o 11,133,800 .61 .118 .1111 .011 .117 .116 .115 .37 .39 .32 .110 .33 
(19) m. 1,355,000 .117 .37 .28 .21 .20 .23 .23 .19 .15 .09 .20 .09 .16 
(20) Anxqu. 72,200 .77 .71 .56 .37 .36 .38 .30 .12 .37 .26 .50 .112 .51 71
121) M1ss.,ALA.,G1\. 510,000 .06 .76 .66 .50 .51 .52 .115 .26 .10 .06 .50 .119 .55 i
(221 m. 00,000 1.211 1.111 1.011 .05 .011 .07 .79 .56 .06 .75 .96 .07 .911 
(23) N.C.,S.C. 553,800 1.08 .96 .90 .78 .80 .80 .70 .55 .75 .60 .82 .72 .76 (i
(211) KY.,-TENN. 529,800 .80 .69 .61 .50 .52 .51 .116 .33 .07 .36 .53 .113 .119 I
(25) H.VA.,VA.,1'0.,0E|.. 000,800 1.07 .911 .90 .80 .87 .86 .81 .65 .81 .71 .811 .75 .78 i
(26) P1. 007,600 1.011 .91 .00 .05 .00 .07 .05 .73 .00 .72 .00 .711 .75 ‘
(27) 11111111151161 191,200 1.5 1.12 1.09 1.00 1.11 1.10 1.09 .97 1.011 .96 1.05 .97 .96 .-

TOTAL 30,050,800 269,600 237,000 121,000 977,000 69,800 67,000 193,000 056,000 51,000 183,000 151,000 083,800 79 1)]:

1/ UNDERSCORED uumaens m5 10111121151110 (m "r511 THOUSAND POUNDS).
T115s5 costs 11115 snowu 111 ootuns PER 110110115011510111.

OTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FROM NOT HAVING AN ACTIVITY IN 1

2/ 1968 FEED 01111111 PRODUCTION 10.100750 FOR FOOD mousrmr AND s550 REQUIREPENTS.

16

  

  
  
 
  
 
   
  
  
 
 
  
  
 
  
 
  
 

{and processing firms to insure maximum
 ation of available facilities and main-
icecompetitive positions within desired
'~_'onal fed-cattle shipments to slaughter,
jcityand surplus slaughter capacity are
yTable ll. Excess cattle slaughter capa-
udy is defined as total cattle slaughter
i s fed-cattle slaughter. Least-cost ship-
 to slaughtering regions, which are
 p re 5, reveal that almost all live, fed
 in an easterly direction from the
_ rn Belt States. These shipment pat-
ditioned by (1) limited slaughter capa-
 fed-cattle production in some of the
‘le producing regions, (2) the availability
 ghter capacity in the South and North-
deficit cattle feeding levels in the South
 relative to the demand for fed beef
ions, Minnesota-Wisconsin (15) and Cali-
counted for almost 40 percent of the

excess cattle slaughter capacity, Table ll. The least-
cost solution for Model l suggests that unless excess
regional cattle slaughter capacities are utilized for
slaughtering non-fed beef, surplus regional cattle
slaughter capacities would not be utilized for slaugh-
tering fed cattle if total fed-cattle slaughter costs
were minimized. Although the Lake States utilize
substantial slaughter capacity for slaughtering dairy
cattle, these results suggest that excess cattle slaugh-
ter capacity is prevalent in that area. Regions utiliz-
ing less than 50 percent of their available cattle
slaughter capacity, as contrasted by those utilizing 95
per cent or more of their cattle slaughter capacity
for slaughtering fed cattle, are shown in Figure 6.
Regions with excess slaughter capacity generally in-
clude states in the Far West, the Northern Inter-
Mountain and Northern Plains region, the Lake
States and the Northeast.

While the optimum solution indicated that sev-
eral regions in the Southeast utilized their available
cattle slaughter facilities by importing fed cattle for

Tom. SHIPPED F550 0mm
FOR omen AVAILABLE FOR
1g .19 g0 g1 g2 2L 211 2S 26 27 LIVESTOCK onus FEEDING‘
1,30 1,32 1,10 1,31 1,1,0 1,31, 1.33 1.37 1.36 1.36 0 121,800
,80 ,75 ,75 ,6l1 ,93 J35 .85 .87 .86 .86 316,963 56,1137
,90 .80 ,7l1 J33 ,9? ,93 .91 .97 .97 .97 32,065 5,335
1.51 1.31 1.16 1.33 1.39 1.12 1-111 1-52 1-55 1-57 535.000 0
1,12 ,95 ,73 ,9; ,95 1,02 1.01 1.13 1.16 1.18 151,200 0
.76 .59 .10 .50 .611 .67 .65 i .77 .60 .02 0 00,600
.53 .37 .10 .29 .311 .39 .38 .50 .56 .59 132,630 820,570
.53 .111 2_3,28_5 .18 .19 .28 .33 .112 .52 .55 1180,385 199,1115
.1111 .111 .29 .38 .37 .36 .117 .118 .51 129,000 0
.38 .21 .011 .18 .28 .27 .26 .38 .111 .1111 12,019 63,581
.51 .37 .33 J15 .511 .50 .118 .56 .57 .58 121,100 90,000
.26 .08 .07 .18 .27 .22 _.20 .29 .30 .32 573,689 722,311
.22 .13 .11 .22 .32 .26 .211 .30 .29 .29 1,056,231 1,011,566
.23 .22 .23 .31 .110 .30 .32 .31 .30 .30 922,800 870,800
.10 .11 .15 .19 .27 .16 .19 .18 .17 .17 2,268,600 1,1121,200
.05 jflfi .011 .08 .18 .10 .09 .13 .13 .13 2,701,1106 2,212,998
A 1_55_L25_6 $2,103 .02 1,135,371 .09 .01 094% .06 .06 .03 1,203,736 520,361
_, 1,313,111 .19 .15 .07 .111 £2,399 .07 gig 61_0,_QQ 523g 3,751,310» 332,156
l .13 535E 015g .011 .111 .09 .06 .16 17 .20 1,355,000 0
.113 .311 2,200 .09 .15 .20 .23 .311 .1111 .117 72,200 0
.31 .311 .05 12,1 jQ,_60_0 0 .08 .15 .25 .28 1172,129 110,871
.67 .73 .110 .29 QQL .21 .116 .311 .118 .119 80,800 0
.113 .58 .35 .19 .11 ELBQQ .29 .07 .20 .22 553,800 0
.23 .28 .11 529.1119 .09 .02 .07 .13 .22 .25 529,000 0
.39 .61 .15 .30 .20 .03 .36 @013 05 .06 110,300 0
.37 .60 ",1! 61.53 .38 .32 .111 J13 .03 .03 g 107,600 0
.53 .011 " .77 .62 .51 .37 m ,2; ,21 131,10 191,200 0
. .11 90. 1' 1 .8 2,207, 0 1,110 1.016.000 861,000 776.1100 610.200 1,121,000 21,793,000 8561,8115

17

l8

Figure 4.

    

Optimum interregionol flows of feed groin for cattle feeding (Model 1).

 

TABLE t0. M00121. 1 OPTIMUM smmzms OF AVAILABLE ween 12mm FOR c1111.: FEEDING, OPPORTUNITY SHIPPING costs, mo SURPLUS FEED 1mm,
av 1151:1011, 1968
DESTINATION 1/

SHIPPING

REGIONS 1 2 3 11 5 6 7 8 9 10 11 12

(1) WAsH.,0REG. fifi .53 .119 05 .55 .80 1.02 1.21 1.00 1.12 .80 1.09

(2) MONT.,|0A110,WYO. N .17 .10 0 .25 .112 .63 .57 .68 .36 .63

(3) UTAH,NEV. 19 .33 21 LL35 18 .35 .57 .77 .56 .68 .35 .66

(6) N.|“£x. .111 .56 .26 QLQIE .02 .08 .22 .113 .25 .36 .25 115
1711mm. .111 .55 .26 0 1_o_2,g11_a 1_254_8_Q_9_ 53$ .13 .05 .11 .16 .25

(8) E.TEx. 68 .81 511 .27 .25 .29 .21 @115 .31 .21 .113 .38
(10), E.01<1.A. .119 .58 .35 .11 .111 .12 .09 .11 .07 QLI .20 .13
111) Co1_o. .22 ' .31 .07 ggg .05 .06 .15 .312 .12 .25 .01 .22
(12) KAN. .33 110 20 .07 .09 .08 .10 .15 91,1 0 .011 QZJQ
(13) NEBR. 211 .30 12 .08 .13 .12 .111 .21 .011 .07 £01,083 0
(111) N.D.,S.D. .111 .16 .15 .10 .23 .211 .26 .33 .17 .19 .10 .12
(15) M|~N.,H|s. .27 .30 .27 .22 .29 .29 .31 .31 .22 .20 .17 .111
(16) lowA .33 .35 .21 .16 .20 .19 .21 .19 .12 .08 .10 .05
(17) ILL. .119 .52 .37 .27 .8 .28 .28 .22 .21 .15 .23 .111
(18) M|cH.,lND.,01110 .61 .611 .51 .1111 .117 .116 .115 .37 .39 .32 .110 .33
(21) M|ss.,A|_A.,GA. .86 .92 .73 50 .51 .52 .115 .26 .118 .36 .58 .119 t

TOTAL 178,237 0 0 183,935 102,3118 125,809 592,1113 199.1115 99,503 63,581 358,083 622,808 1, 1".

1/ UNOERSOORED NUMBERS ARE SHIPMENTS (IN TEN THOUSAND POUNDS). OTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FROM NOT HAVING AN AOTIV i

SOEUTION. THESE COSTS ARE SHOWN IN DOLLARS PER HUNDREDHEIGHT.

   

NIP 

U

          
     
 
 
 

l?)
\\\'

 

n.

‘1
~0

C‘

 

03“
r

\

 
 
 

   

 
 

f3!

I0

  

   

 

5

\

    
  

.1

   

“#10 0
E

    
  
 
     
   
 

  
 


.\\ .
4  

   

Figure 5. Optimum interregional flows of fed slaughter cattle (Model 1).
SURPLUS
Tonu. FEED
TV 2U 21 22 23 210 25 26 27 SHIPPED can m
1.28 1.18 1.31 1.100 1.67 1.33 1.610 1.36 1.79 121,800 0
.81 .75 .810 .93 1.18 .85 1.110 .86 1.29 56,1037 0
.86 .710 .88 .97 1.26 .91 1.210 .97 1 100 5,335 0
.65 100 .58 .610 1.00 .65 1.010 8O 1 25 88,600 0
.103 .10 .29 .310 .72 .38 .77 .56 1.02 820,570 0
.107 0 .18 .19 .61 .33 .69 .52 .98 199,1015 0
.27 .010 .18 .28 .60 .26 .65 .101 .87 63,581 0
.103 .33 .105 .510 .83 .108 .83 .57 1.01 90,000 0
.110 .07 .18 .27 .55 .20 .56 . .75 722,311 0
.19 .110 .22 .32 .59 .210 .57 .3 .72 1,01010,566 0
.28 .23 .31 .100 .63 .32 .58 .30 .73 0 870,800
.17 .15 .19 .27 .109 .19 .105 ,1? .60 0 1,821,200
.060‘ .010 .08 .18 .103 .09 .100 ,13 ,56 1,727,l075 1085,519
.06" .02 gg .09 .30 @913 .33 ,0; ,51 520,35». o
.25 15 .07 .11» .33 .07 .2? 93,12 4.3 332,055 o
.100 .05 0 m .33 .08 .102 _25 _71 100,871 D
0 " 0 57,065 100,871 0 100,0710 0 90,1910 0 5,888,280 2,777,519

19

Slaughter Capacity Utilization

 over 95 percent

 

under 50 percent

l i 50 to 95 percent

Figure 6.

slaughter, these results are conditioned by the fact
that fed-cattle production in such regions as West
Texas (7), Kansas (l2) and so forth, generally ex-
ceeded regional slaughter capacity. Long run adjust-
ments, as the construction of sufficient slaughter
facilities in the primary areas of fed-cattle produc-
tion, are inevitable. Consequently, states which are
primarily dependent on shipments of fed cattle for
slaughter, as is true for some of the Southeastern
States, will find that much of their processing or
slaughtering facilities will be unused.

The existence of substantial excess slaughter
capacity in Missouri (l9) in Model l is at first glance
somewhat surprising. However, these results suggest
that total costs are minimized when fed cattle are not
shipped into Missouri for slaughter for shipment to
other regions. Furthermore, the optimum solution
revealed that total costs were minimized when Mis-
souri (l) shipped its entire supply of feed grain out-
of-state for feeding to other livestock in the South
and (2) fed no cattle since its locational advantage in
shipping feed grain South was not offset by the
slight competitive advantage it enjoyed in economies
of size in feedlot operations over an adjacent area like
Illinois.

20

Regional slaughter capacity utilization (Model l).

¢ Q Q - - - Q ¢ ¢ u Q ¢ - .-

 
     
  
   
  
   
 
   
 
 
  
  
   
    
  
  

Numerous regions utilizing 95 percent j
of their available cattle slaughter capacity ~71
tering fed beef, in reality, also slaughter s i
volumes of non-fed cattle. These results su,
ever, that such regions enjoy a competitive 
in slaughtering fed cattle when cattle 
located on a least-cost basis. 9

Least-Cost Fed-Beef Shipments ».

The optimum distribution patterns 0f-
fed beef is determined, among other thin
location and levels of production, the con
of population centers and their associated ,
tion levels, and the regional differentials i'
production, transport costs and price of 
products. The two most populous regio ‘
include the Northeast and California) as
Pennsylvania and the Middle Atlantic S_
Southeast and South are huge deficit fed-i
ducing areas. The Northeast and Calif,
example, accounted for more than one-thi,
fed-beef consumption in the contiguous 48 s g
plus fed-beef production, as indicated by
model, is concentrated primarily in the T
homa Panhandle areas, Colorado, Kansas, ._
and Iowa. l

 
  
  
  
 
 
 
  
  
 
  
 
 
 
  
 
  
 
  
  
 
 
  
  
 
 
  

 optimum inter-area flow pattern of dressed
 is readily divisible by a line running from
tern edge of the Plains States through the
if the Texas Panhandle, Figure 7. Regions
5 this imaginary line enjoyed locational advant-
shipping fed beef to the West, especially to
ifornia market. In contrast, regions East of
' were favored with locational advantages in
ts to the deficit Northeast, Southeast, and
 th Central markets. The exception to this
p of shipments was West Texas which shipped
i both West and East.

ifornia, the major deficit fed-beef market in
‘t, supplied about one-third of its require-
v the least-cost solution, Table 12. Primary
tors for the fed-beef market in California
llorado and West Texas with smaller amounts
v pplied by Arizona and New Mexico.

Y». Texas, Western and Eastern Oklahoma
J ational advantage over the Northern Plains
i» shipping fed beef to deficit fed-beef markets
uth as indicated by the optimum shipment
i‘ or the opportunity costs associated with non-
Qt to southern regions. For example, West
7) has a locational advantage over other sur-
'0ns in shipping fed beef to East Texas (8),
-Louisiana (20) and Florida (22) while com-

Figure 7. Optimum interrcgionol flows of fed beef (Model l).

peting with Eastern Oklahoma for shipments to North
Carolina-South Carolina (23). The opportunity costs
in Table 12 revealed that the next best markets for
West Texas, as indicated by the smaller opportunity
costs, are regions 25 and 21, respectively.

Nebraska and Iowa enjoyed a locational advant-
Zlg€ for distributing fed beef to the huge deficit
market in the Northeast (27). Iowa also had a loca-
tional advantage over Nebraska and Kansas for deficit
markets in the Lake States, the Eastern Corn Belt
and Pennsylvania. Kansas competes with Western
Oklahoma for markets in the Middle Atlantic States
and with Iowa in Pennsylvania.

These optimum distribution patterns hold spe-
cial significance relative to management practices
and operational characteristics for cattle feeders and
slaughter plants. For example; West Texas and Colo-
rado, the principal competitors for the California
fed-beef market, must organize their operations to
produce fed beef containing those attributes of qual-
ity, form, weight and sex at a competitive market
price and desired delivery dates if they are to main-
tain their competitive position in that market. The
same is true for surplus fed-beef producing regions
competing for markets in the Northeast, the Lake
States and the South. Nevertheless, with the estab-
lishment and continued growth of large, specialized,

21

  

  
  
    
   
  
  
  
  
  
   
 
   

  

TAaLE 11. ("ODEL 1 ‘= OPTIMuM snmtms OF FED CATTLE (DRESSED EQUIVALENT) FOR SLAUGHTER, OPPORTUNITY SHIPPING costs, SLAUGHTER CAPACITIES, AND so
SLAUGHTER cAPAcmEs, 10v REGIONS, 1968

Snwmuc DESTINATI on 1]

REGIONS 1 2 3 10 5 8 9 10 11
(1) NASHI,OREGI 10,331,190 1.32 1.71 1.01 2.108 3.58 3.92 10.10 3.52 3.72 2.80
(10) CALIF. 1.18 2.0_6 1.73 5,071,172 1.36 2.52 3.19 3.101 3.109 3.06 2.910
(5) ARIZ. 1.73 2.15 1.71 .1010 2,857,1100 1.610 2.32 1.210 2.65 2.16 2.210 ~
(6) ILFEX. 1.23 1.02 .75 1,582,007 .010 1,923,1101 .71 1.08 .59, .73 .59 I
(7) HCIEx. 1.06 .810 .59 .16 .21 .20 11,389,7100 .36 .1035 .010 .103
(8) E-TEX. 2.16 1.90 1.69 1.32 1.18 1.510 1.310 10,679,760 1.100 .75 1.5!
(9) 00.00<LA. 1.11 .89 .73 .91 .99 .53 .108 .88 1,363,180 Em .1010
(10) E.00<LA. 2.12 1.90 1.62 1.30 1.310 1.52 1.35 1.08 .87 1,755,226 1.106 
(11) COL0. .71 .52 .31 .68 .90 .85 1.20 1.310 .76 .93 8,622,101”
(12) KAN. 1.107 1.08 1.13 1.12 1.19 1.36 1.39 1.17 .71 .27 .86 A
(13) NEBR. 1.33 .91 .99 1.26 1.39 1.58 1.69 1.106 1.20 .810 .87 i.
(16) 1000A 2.18 1.68 1.85 2.08 2.110 2.30 2.33 2.01 1.85 1.1010 1.72 
(17) ILL. 2.92 2.109 2.59 2.69 2.75 2.91 2.93 2.35 2.106 1.98 2.105
(18) Mlc00.,1r00.,000l0 3.11 2.66 2.89 3.010 3.10 3.26 3.27 2.66 2.81 2.35 2.75
(21) M|ss.,ALA.,GA. 3.26 2.89 2.93 2.39 2.66 2.98 2.82 1.95 2.610 1.97 2.70 f
(22) FLA. 10.57 10.12 10.17 3.89 3.810 10.03 3.83 2.86 3.76 3.110 3.98 A:
(210) KY.,TENN. 3.33 2.92 3.16 3.11 2.89 3.15 2.99 2.21 2.77 2.11 2.82 ,
(26) PA. 10.72 10.26 10.02 10.63 10.69 10.85 10.85 10.15 10.100 3.910 10.37

TOTAL 10,331,190 0 0 6,653,179_2,857,1100 1,923,1101 11,389,7100 10,679,760 1,3§3,@ 2,635,000 8,6 ""1
SLAUGHTER CAPACITY 0,262,620 0,309,500 2,073,000 10,910,250 2,057,100 1,929,101 11,309,700 0,079,750 1,303,100 2,535,000 11,655,200
SuRPLus sLAucurEn

CAPACITY 1,931,1030 10,309,500 2,073,060 12,260,081 0 0 0 0 0 0 3 032 -

1_/ (Uuoznsconzo NUMBERS ARE SHIPMENTS (100 POUNDS). 0101201 NUMBERS ARE OPPORTUNITY costs 00101000 RESULT FROM NOT HAVING AN ACTIVITY 100 THE 0021004010 I

THESE COSTS ARE SHGAIN IN DOLLARS PER HUNDREDHEIGHT.

  

TAaLE 12. MooEL 1 OPTIMuM smPvenrs FOR DRESSED FED BEEF AND OPPORTUNITY s00|0>0>|00c costs, av aemous, 1968
SHIPPING nssnnAnquzll
REGIONS 1 2 3 10 5 6 7 8 9 10 11
(1) HASHHOREG. 10,331,190 .95 1.100 .55 1.89 2.101 3.11 3.00 3.05 3.21 2.53
(10) CALIF. 1.02 1.61 1.62 6,653,179 1.35 2.09 2.80 2.66 2.85 2.97 2.67
(5) ARIZ. 1.01 1.00 .85 1,867,280 989,860 .96 1.62 1.102 1.71 1.810 1.61
(6) NJtx. .79 .58 .103 1,1056,161 .22 @280 .76 .71 .85 .99 .83
(7) H.IEX. .78 .55 .103 10,163,600 .17 .05 1,319,200 §Q_8_,_2_Q .210 .29 .61
(8) E.TEx. 2.010 1.77 1.69 1.23 1.310 1.37 1.37 10,679,760 1.59 1.19 1.83
(9) H.00<LA. .72 .38 .38 .05 .26 .110 -210 .22 15_3,_5QQ .28 .100
(10) E.00<LA. 1.26 .91 .93 .55 .77 .66 .67 .20 .66 1,206,660 .99
(1.1) CoLo. .33 922,130 926,030 5¥250,520 .29 .25 .710 .59 .53 .710 1,523,381
(12) KAN. 1.07 .68‘ .77 .65 .86 .75 .98 .52 .58 .103 .710
(13) NEBR. .87 .1010 I .58 .67 .910 .85 1.11 .68 .86 .72 .63
(16) 1000A 1.107 .96 1.19 1.27 1.51 1.101 1.65 1.03 1.100 1.17 1.310
(17) ILL. 2.20 1.71 1.91 1.87 2.08 1.97 2.17 1.103 1.98 1.71 1.99
(18) M0c01.,1000.,O000 2.510 2.03 2.30 2.33 2.510 2.1010 2.60 1.83 2.1010 2.110 2.1010
(20) ARK.,LA. 2.16 1.82 1.81 1.38 1.52 1.109 1.51 .37 1.65 1.23 1.90
(22) FLA. 3.70 3.37 3.109 3.06 3.20 3.17 3.18 2.010 3.32 2.93 3.510
(23) N.C.,S.C. 3.57 3.15 3.33 3.08 3. 27 3.19 3.25 2.23 3. 26 2.87 3.39
(210) KY.,TEN00. 2.60 2.15 2.31 2.07 2.28 2.18 2.25 1.35 2.210 1.86 2.37
(26) PA. 3.71 3. 26 3.310 3.107 3.71 3.61 3.76 2.90 3.61 3.31 3.65
TOTAL 10,331,190 922,130 926,030 19,390,700 989,860 066,980 1,319,200 5,287,980 153,500 1,206,660 1,5

1/ Uuosnsconzo NUMBERS ARE snnvnErns 1100 POUNDS).

COSTS ARE SHOHN IN DOLLARS PER HUNDREOHEIGHT.

22

OTHER NAMBERS ARE OPPORTUNITY COSTS WHICH RESULT FRCH NOT

HAVING AN ACTIVITY IN THE OPTIHII 1”‘

  
  
  
  
  
  
  
  
  
  
  
  
  
  
  

' ‘L

TOTAL

15 16 17 18 19 20 21 22 23 28 25 26 27 SHIPPED
2,52 g_97 2_g7 g_31 3_33 3_55 3.35 3.63 3.28 3.20 3.11 2.73 2.59 8,33L
3.08 3,08 2,81 2,91 3,11 3,03 3.03 3.12 3.00 3.15 3.16 2.81 2.82 5,071,
2,27 2,15 1,95 2;05 2,25 1,97 1.97 2.15 1.95 2.01 2.00 1.95 1.96 2,857
,a3 ,71 ,51 ,51 ,53 ,70 .68 .78 .70 .67 .68 .51 .52 3,505
,35 ,2; ,02 ,11 ,11 l§§,l§Z 0 .03 1,963,298 2,708,613 .38 283,881 .02 16,873
,99 ,90 ,11 ,1; ,51 1 703 323 .09 .02 .10 .19 .10 .25 .38 6,383
.32 .23 0 .10 .12 .83 .26 .81 .29 .23 .18 868,583 .01 2,707
.77 .68 .37 .89 .87 .56 .88 .62 .86 .82 .82 .37 .80 1,755
.00 .112 .01 .36 .111 .05 .66 .55 .65 .60 .51 .25 .27 0,622,
.25 .22 gfi .05 .01 .60 .30 .117 .01 _ .211 .10 0,160,010 0 15,155,
.17 11,010,205 .111 .17 .00 .05 .50 .73 .52 .111 .25 .05 .06 01,762,
.17 26,587,688 .15 .32 .81 1.35 .83 1.00 .70 .61 .82 .28 .21 26,587,
1.13 .99 10,103,652 .32 .60 1.88’ .98 1.13 .80 .68 .58 .81 .81 9 10,103,
1.25 1.81 .57 7,975,378 1.31 1.77 1.05 1.15 .69 .83 .33 .28 .11 7,975,
1.60 1.59 .90 .72 1.26 1.01 0 .26 .10 1,577,688 .18 .27 .35 1,577,
2.78 2.73 2.02 1.79 2.39 2.05 1.23 291,351 .69 1.87 .66 .90 .96 997,
1.52 1.53 .76 .66 1.22 1.29 .13 .66 .32 1,097,108 .29 .80 .87 1,097,
2.86 3.02 2.35 1.97 2.87 3.23 2.29 1.95 1.35 2.26 .35 2,126,763 .87 2,126,
1 1,911,969 11,007,990 7,975,318 0' 1,871,960 0 997,357 1,963,298 5,383,809 0 6,302,797 0 189,090,

f1;',898,865 31,106,680 11,007,990 17,187,825 10,303,200 1,871,960 5,828,700 2,685,985 1,963,298 5,383,810 2,770,718 6,302,797 6,800,830 236,967,

0511 065 205,671 0 5,212,051 10,000,200 0 5,021,700 1,610,500 0 1 2,770,710 200,100 6,000,100 07,077,
TOTAL
16 YT 10 15 20 21 722 20 211 25 26 27 01110050
2.00 2. 71 2. 51 2. 07 2. 50 2. 00 2. 05 2. 65 2. 011 2. 50 2. 10 2. 22 11,001,150
0.06 2.05 2.00 2.51 2.67 2.71 2.60 2.60 2.70 2.60 2.66 2.51 6,650,175
1.55 1.71 1.66 1.70 1.116 1.52 1.117 1.117 1.611 1.50 1.55 1.62 2,057,110
1.11 .06 .02 .50 .65 .70 .70 .65 .00 .65 .71 .77 1,520,111
.611 .05 .27 .110 1,505,710 .01 2,501,750 @211 .16 .01 .15 .22 11,005,710
1.05 .50 .07 1.12 .20 .05 .20 .05 .60 .112 .66 .72 11,675,760
.05 .16 .11 .20 .11 .05 .111 .01 .15 1,205,600 0 .07 1,060,100
.511 .27 .15 .20 .10 .00 .10 g5,1_m .15 1,000,101 .00 .111 2,605,000
.116 .00 .211 .1111 .52 .10 .15 .27 .111 .17 .17 .21 0,622,100
.211 .10 .11 0,075,170 .05 .25 .01 .07 .21 5,160,105 gbfi .07 10,702,720
I .00 .17 .011 .25 .56 .06 .112 .17 .01 .00 0 25,710,250 27,115,100
12,160,190 13,523 11,503,196 .26 .71 .1111 .50 .20 .07 .00 1,716,622 5,006,610 00,500,560
.111 11,007,990 .06 .81 .99 -58 .62 1 .00 .06 .15 .15 .211 11,007,550
1.32 .57 7,975,371 1.20 1.98 .80 .75 .05 .66 .12 .05 .11 7,575,071
1.21 .60 .56 .00 122g 1,115,620 .06 .06 .20 .11 .07 .1111 1,071,560
2.67  1' 1.611 2.81 1.73 1-10 my .62 1.05 .65 1.00 1.02 557,057
2.811 1-76 1-27 2-18 1-80 1-03 .69 1,963,298 1.19 .07 .511 .57 1,963,298-
1-115 .63 .112 1-07 -B6 2.195.880 .00 .00 2,000,000 .00 .21 .00 5,000,110
2.80 1.98 1.37 2-1111 2-117 1-73 1.110 .50 1.76 .20 602,757 .27 6,002,757

,0'0'0'

 

-I, '1 11,051,610 19,878,870 3,079,170 2,22 ,

23

shipper-type fed-cattle slaughtering and processing
plants in the Texas-Oklahoma Panhandle and the
Northern Plains, a substantial volume of fed beef
is currently produced by these states within somewhat
similar weight and quality ranges. This is especially
true for fed-steer beef. The prevalence and increased
growth of these slaughtering plants in the primary
fed-cattle production areas with efficient national sys-
tems of distribution suggests an increasing reliance
on price competition for markets. Consequently,
firms containing the most efficient production and
distribution systems will survive in this increasingly
competitive environment.

While excess regional feeding and slaughtering
capacities may be due to inefficiencies or disecono-
mies in feedlot and slaughter operations, these excess
capacities may also reflect relatively high acquisition
and distribution costs. In the absence of efficiencies
to offset regional cost disadvantages resulting from
higher acquisition, production or distribution costs,
such regions may find it increasingly difficult to com-
pete in the cattle feeding- fed-beef economy. I-Iow-
ever, economic theory suggests that such regions
would be expected to use existing capacities as long
as returns exceed associated fixed costs.

EFFECTS OF CHANGES IN FEEDLOT SIZE
ON THE CATTLE FEEDlNG-—FED-BEEF ECONOMY

Interregional competition in the cattle feeding
industry is affected by, among other things, avail-
ability and cost of resource inputs, market outlets,
level of management and weather. With the advent
and continued expansion of large commercial cattle
feedlots, questions have arisen concerning the effect
of economies of size in feedlot operations on the opti-
mum location and levels of cattle feeding. For exam-
ple, given the regional resource supplies, regional
feedlot and slaughter capacities, transport costs and
regional demand for fed beef as specified in Model
l, potential changes in the regional location and
levels of cattle feeding may be determined when
minimum sizes of feedlot operations are arbitrarily
set at l,000- and 5,000-head capacity in those regions
where the existing average feedlot sizes are below
such minimum levels.

Therefore, to provide insights regarding poten-
tial changes in optimum location and levels of cattle
feeding as feedlots increase. in size, minimum one-
time feedlot capacities were increased to 1,000 head
in Model 2 and 5,000 head in Model 3 for those
regions where average feedlot sizes were below these
specified levels. Regional feedlot sizes, as represented
by markctings, were not altered for those regions
exceeding these minimum levels. Models 2 and 3
differ from Model l only with respect to regional
feedlot size and fixed costs associated with the speci-
fied minimum regional feedlot size.

Substantial change, apparently, would occur in
the location and, especially, regional levels of cattle
feeding when minimum regional feedlot capacities

24

   
   
  
   
    
   
  
 
   
    
  
   
   
  
  
  
 
 
  
  
 
   
   
  
   
 
 
    
    
   
   

are increased." The optimum solution f y
as compared to Model l, reveals that C A
New Mexico (6), Colorado (ll) and 
would be affected most severely when 
lot sizes are increased to 1,000 head, Tag
clines in the number of cattle fed in N
ranged from 19 percent in New Mexico e
in Colorado. Numbers of cattle fed inf
Indiana-Ohio (18), on the "other hand, n»
and substantial increases were also no e-f
(l6). Regions feeding cattle in Model 2,,
Model 1, were Missouri (19), North C
Carolina (23) and West Virginia-Maryl 
(25). Feeding levels in all other regions '
to those indicated for Model 1.

Model 3 reveals that numbers of cat .
increase substantially in Iowa (16), Mi o 
Minnesota-Wisconsin (l5) when regional V
are increased to minimum levels of m1
city, Table 13. Illinois maintains its 1
feeding position, and Michigan-Indian:
continues feeding up to capacity levels l
Model 2. Regions feeding for the first
Utah-Nevada (3), North Dakota-South
and Minnesota-Wisconsin (15)." The o,
tion for Model 3, as compared to Model 
cattle feeding in Nebraska (13) would;
more than 60 percent if nearby com
increased average feedlot capacity to 
Other areas which would experience su
clines include California, New Mexico,
Colorado and Kansas. In addition, catt
Washington-Oregon (1) no longer would
compete in the cattle feeding industry 1
ther increases in feedlot size or other +1,
that area. f

Given the potential changes and sh
feeding when regional feedlot sizes are
imum levels of 1,000 and 5,000 head, an
Model 4, depicts future regional feeding,
on estimated regional sizes for 1975.12 g
capacity levels and all other assumpti
4 are similar to those employed in the I
Model 1, the results for Model 4 refl
changes. 

Comparison of the optimum feedi
Model 4 with Model 1, which depicts t 
feeding-fed-beef economy, suggests ~-
ing activity in California (4), New Mex

“See Appendix C for specific details concemi 
patterns, quantities shipped, opportunity c0581
where applicable, for feeder cattle, feed 
cattle, and dressed fed beef. f

"Feed maintenance requirements for cattle A
cold weather conditions in regions as No 
Dakota and Minnesota-Wisconsin were not M
study. For interested readers the affects of ch 
consumption and performance are referred to y
“Formulating Beef Rations For Improved P 
Environmental Stress," American journal of ~ I
nomics, 53-1:79-91, Feb. 1971. p

"See Appendix A for a detailed description of t
employed in developing these data. f

   
  
  
 
  
 
   
  
 
  
 
  
 
 
 
 
 
  
 
 
 
 
 

-Ohio (l8), Mississippi-Alabama-Georgia
ennsylvania (26), Table l3. Regions with
‘eding levels in Model 4 which are not
1 to capacity levels in Model 1 include
and North Dakota-South Dakota (14).
Tennessee (24) and Florida (22) were the
(in the Southeast able to compete for re-
;1 other cattle feeding regions in Model 4.
.els in all other regions in Model 4 were
l those in Model 1.

Adults from Models 2, 3 and 4 suggest that
f size have important economic and inter-
éplications for the cattle feeding industry.
Solutions for these models revealed that
L of producing and distributing fed cattle
 declined $40 million from Model l to
hey declined $96 million from Model l
i, and $55 million from Model l to Model
igest decline, almost 7 percent, occurred
,1 urn regional feedlot sizes were increased
d capacity. This suggests that increases
ize can substantially reduce total costs of
lifed cattle, especially in those areas where
I and feed r cattle are readily available.
A creases m’ feedlot size may also increase

/

the acquisition cost of feed and feeder cattle since
larger feedlots often tend to reach out further for
adequate supplies of these items. These results, how-
ever, are conditioned by the assumptions and con-
straints imposed on the models and should therefore
be interpreted within that framework.

Results from Model 2, where minimum regional
feedlot capacities were arbitrarily set at 1,000 head,
suggest that regions as lowa (l6), Missouri (l9) and
Michigan-Indiana-Ohio (18) would increase their
competitive feeding position substantially when aver-
age feedlot sizes are increased to 1,000 head. These
regions are characterized by (1) fed-cattle marketings
from feedlots averaging below 350-head capacity, (2)
relatively large diseconomies of size in cattle feed-
lot operations, (3) large surplus production of feed
grains, (4) relatively large regional cattle slaughter
capacities and (5) generally favorable location for
shipments of dressed fed beef to deficit fed-beef
centers on the East Coast. Further increases in re-
gional feedlot size to 5,000 head, as in Model 3,
allow regions as Minnesota-Wisconsin (l5) and North
Dakota-South Dakota (14), which have a locational
disadvantage with respect to markets as well as dis-
economies of size in feedlot operations, to compete

011111.114 11501011“. CATTLE FEEDING LEVELS, BY 1100121., ssrmnso 196B 1111110111. 612601.01 CAPACITY AND AVERAGE 62501.01 3121:, AND ESTIMATED 1975 FEEDLOT 8121:,

   
 
   
  
  

Esrmnso Esrmnso Esrmnso
/ 1968 ANNUAL 1968 1975
R5010» M0011 FEEDLOT g/ FEEDLOT g/ FEEDLOT Z/
CAPACITY CAPACITY CAPACITY
1 2 3 1

V‘ - - - - - - - - - - - - - - - - - - - - - - - - HEAD - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
' , 011:6. 665,313 665,313 0 665,313 878,137 5,381 11,259
., 11111111, 1111111. 0 0 0 0 1,327,911 5,533 22,018
i, , 113v. 0 0 305,622 0 305,622 1,710 2,815
'4 836,827 621,500 621,500 621,500 1,137,761 18,116 22,586
 199,500 199,500 199,500 199,500 1,209,510 13,869 19,363
m1. 607,178 192,000 192,000 192,000 607,178 11,162 31,852
@1611. 2,830,151 2,830,151 2,618,781 2,830,151 2,830,151 18,151 58,205
 1,137,711 1,137,711 1,051,000 1,137,711 1,137,711 7,772 26,091
'. L1. 125,015 125,015 125,015 125,015 125,015 11,210 37,715
m1. 333,060 333,060 333,060 333,060 333,060 3,091 9,103
' 1,268,000 790,000 871,295 1,268,000 1,926,156 12,166 15,937
2,338,715 2,338,715 1,661,000 2,338,715 2,338,715 6,322 16,511
1,812,528 3,585,713 1,723,921 1,812,528 1,812,528 1,053 11,599
g , 3.0. 0 0 203,658 109,339 913,912 179 1,599
, 11131:. 0 0 1,563,230 0 1,563,230 263 667
3,921,187 1,588,001 5,113,788 1,721,383 5,113,788 316 1,110
1,12,088 1,12,088 1,12,088 1,129,088 1,12,088 233 333
, 1110., 01110 1,267,915 2,318,705 2,318,705 1,187,665 2,318,705 229 375
’ ~ 0 139,558 1,081,663 0 1,081,663 261 227
i‘, LA 0 0 0 0 33,000 139 139
( , 1111., 0A. 27,677 297,677 27,677 0 27,677 577 553
 155,110 155,110 155,110 155,110‘ 155,110 2,323 1,321
i, s.c. ;=__ _ 0 86,900 86,900 0 86,900 33 33
'5 131111. i‘ 176,381 176,381 176,381 176,381 176,381 315 291
v., v1.,1'11.,0zt.,0c 0 81,100 81,100 0 81,100 28 28
i 286, 210 286, 210 286, 210 0 286, 210 123 123
0 0 0 0 25,000 25 25
231E622 >23fi1 ,131 23,198,567 23, 505, 855 ---- ---- ----

   
  
 

i1 Ares 10m.

=18 THE 8As1c1100EL As PREVIOUSLY DEFINED; M3051. 2 ASSUMES A 11111111111 REGIONAL 1=1-:1-:o1_or s12: 0F 1,000 HEAD; Monet 3 ASSUMES A 11111111111 112010101. 11:01.01 s12:
~ 11:10; A110 most l1 REFLECTS THE 1975 PROJECTED REGIONAL FEEDLOT SIZES.

V- IX A FDR A DETAILED DESCRIPTION OF THE METHODOLOGY EVPLOYED IN DEVELOPING THESE DATA.

25

for resources and markets in the cattle feeding— fed-
beef economy.

Such increases in regional feedlot sizes, which
tend to decrease total fed-beef production costs, sug-
gests that feeders with one-time capacities of 1,000
head or 5,000 head in predominant farmer-feeder
areas generally are in a much stronger position to
compete for resources and markets than are the
smaller farmer-feeders in the same area. While nu-
merous farmer-feeders in the Corn Belt States may
have access to surplus seasonal farm labor and gen-
erally large supplies of relatively low-priced feed
grains, such advantages, as suggested by this study,
will generally not be sufficient in the long run to
offset cost advantages available to the larger, more
specialized commercial feedlot operators. The signifi-
cance of these findings are that cattle feedlot opera-
tions in the major surplus grain producing regions,
where farmer-feeders predominate, must increase in
size to either be competitive or to maintain their
competitive position in the cattle feeding-fed-beef
economy. .

The findings further suggest that, when and if,
feedlot operators increase the size of cattle feeding
operations in Iowa, Missouri, Michigan-Indiana-Ohio
and Minnesota-Wisconsin, major cattle feeding re-
gions as Nebraska, Kansas, Colorado, "California and
New Mexico would be affected most severely. For
example, Iowa, the Eastern Corn Belt States, and the
Lake States have a locational advantage over Nebras-
ka and Kansas in shipping fed beef to the deficit fed-
beef markets in the Northeast and along the East
Coast. Nebraska and Kansas, consequently, would
have to look to deficit markets in the South and
Southeast for their surplus fed beef. West Texas
would become the major supplier for California with
Colorado looking primarily to the Inter-Mountain
States and Washington-Oregon for its surplus output.

IMPLICATIONS OF INTERREGIONAL ECONOMIC
RELATIONSHIPS AND REGIONAL
PRICE DIFFERENTIALS

Regional changes in the location and levels of
cattle feeding as a result of changes in regional feed-
lot size also affect the regional price structure for
feeder cattle, feed grains, fed cattle and dressed fed
beef. Such regional price structures are the result of
regional differences in surplus and deficit situations
and regional ability to compete for resources and
market outlets.

Table l4 shows that feeder cattle prices were
generally lowest in the Southeastern States, East Tex-
as, the Inter-Mountain States and the Pacific North-
west. These regions are large surplus producers of
feeder cattle which are shipped relatively long dis-
tances. Highest prices were generally noted for Ari-
zona (5), Iowa (16), New Mexico (6), Western Okla-
homa (9) and Illinois (17). While these regional price
differentials reflect existing regional supply-demand

26

  
  
  
  
  
  
  
  
  
  
  
     
  
    
  
   
 
  
   
   
  
  
   
 
   
  
  
   
  

TAaLs 1'1. REGIONAL FEEDER CATTLE PRICE OIFFERENTIALS, av most, a
m REGIONAL FEEDLOT s|ze AND FIXED resume cosrs .

 

Ramon lhoEL
‘I 2 -
- - - - - - - - LLAns/cwr- -‘ - - - - _'

(1) HAsn, Daze -.se ‘nllll -.ss I

(2) Hour, lomo, mo -.59 -.'4I1 -.59

(a) um, Nev -.ss -.s1 -.e1

(h) CALIF -.5 -.38 -.53

(5) Aalz .112  .28 .11

(6) N (EX .21 .15 -.03

(7) H TEX 0 0 0

(B) E TEX -.51 -.51 -.5I

(9) H (MLA .03 .08 -.07
(10) E OKLA -.17 -.10 -.31
(11) CoLo .09 -.05 -.1'I
(12) KAN -.03 .03 -.13
(13) NEBR .01 .06 ~09
m) no, so -.au -.a1 -.s1
(15) Mmu, Hrsc -.22 -.0‘) ~05
he) IONA ' .03 .20 .20
(17) ntt -.os .os .06
(18) Mncn, mo, 0mm -.15 0 0
(19) Mlssounl -.27 -.09 ~09
(20) ARK, LA -.60 -.60 -.60
(21) MISS, ALA, GA -.77 -.57 -.5'I
(22) m -.s1 -.\1s -.s1
(2a) NC, sc -.59 -.I+5 ~60
t2») 1mm» -.ss an)» -.n
(5) u vA,vA,m,nzt,oc -.5u -.1+0 -.5')
(26) PENN -. 28 -. 17 -. 29
(27) u 5 -.1+5 -.02 -.15

conditions, they may also provide insight 1
cattle producers and feedlot operators '
existing and anticipated regional price dif 
the structure of the cattle feeding industry i
change. .A

The Southern Plains, which annuall.’
for about 20 percent of the beef cows 2’
older in the 48 contiguous states, is generall
as a surplus feeder cattle producing area.
with the recent upsurge of large commer
operations in West Texas (7) and Western I
(9), these two regions have become net 1»
feeder cattle as reflected by the price diff‘
Table l4. East Texas (8) and Eastern
(10), in contrast, export substantial volum‘
cattle as demonstrated by the relatively ».__
differentials in these two regions. Price ~11
are somewhat lower in East Texas com
those of Eastern Oklahoma since East V)
mally faced with relatively larger surplus 1
feeder cattle and also ships feeder cattle '1
tant markets. _ i;

The price differentials in Table l4 
strate the sensitivity of regional feeder w’;
to both increasing and decreasing demand,
cattle as regional feedlot structures and >1
cattle fed undergoes change. For example
prices increased 17 cents per hundredw_

   
 
  
 
 
  
 
 
 
  
  
  
 
  
 
 
  
  
  
  
  
  

Model 2, as numbers of cattle fed in-
‘f state when average feedlot capacities
 1,000 head as in Model 2. In contrast,
prices declined l3 cents per hundred-
ifornia when numbers of cattle fed in
 lined 25 percent from Model 1 to

feeder cattle are also sensitive to changes
i-demand situation in nearby competing
iioptimum solution for Model 3 revealed
y would be minimized when Washing-
 feeds no cattle and also does not ship
 0 another region. Presumably such cat-
, ome stockers or would be slaughtered
“tle. Numbers of cattle fed in California
y same from Model 2 to Model 3, but
fprices in California were l5 cents per
I?» lower in Model 3 than Model 2. This
“g1 e to increased surplus feeder cattle sup-
y,“ estern regions which exerted additional
,= ~ ure on prices in that area since
regon's entire supply of feeder cattle
 s in Model 3.

‘n price differentials were highest in the
uth, and the Northeast for all models,
* ese regions are characterized by deficit
‘iproduction relative to feed grains de-

i FEED GRAIN PRICE DIFFERENTIALS, BY MODEL, GIVEN CHANGES IN
AND FIXED FEEDING COSTS

i 2 1111021. 3 l‘

- - - - - - --6oLL11ns/c1rr--------------
.29 .29 .32 .29
1113 .08 .11 .08
.21 .21 .21 .21
.117 .117 .117 .117
.31 .31 .31 .31
.15 .15 .15 .15

0 0 0 0
.011 .011 .08 0

-.01 -.01 -.01 -.01
.01 .01 .01 .01
.01 .01 .01 .01

-.07 -.07 -.07 - 07

...09 -.09 -.09 - 09

-.13 -.13 -.09 -.13

-.13 -.13 - 09 - 13

-.13 -.13 -.09 -.13

-.09 -.09 -.05 -.13

-.011 -.011 0 -.08

-.06 -.06 -.02 -.10
.09 .09 .13 .05
.01 :1“ .01 .11 .03
.21 " .21 .5 .17
.18 .18 .22 .111
.08 .08 .12 .011
.15 .15 .19 .11
.17 .17 .21 .13
.23 .23 .27 19

TABLE 16. REGIONAL LIVE FED CATTLE (oassszo EQUIVALENT) PRICE DIFFERENTIALS,
av noosL, c1vs11 CHANGES 111 112111011111. FEEIJLOT SIZE AND FIXED FEEDING cos1's

115111011 M1051.
1 2 3 11
- - - - - - - --DOLLARS/T1T-------------
(1) 1111811, 011cc 1.35 1.511 1.1a 1.112
12) 1b1rr, IDAHO, 1N0 .511 .72 .86 .50
13) UTAH, NEV .39 .60 .67 .82
111) CALIF 1.37 1.39 1.117 1.311
15) ARIZ 1.05 1.05 1.13 .96
16) 11 DEX .25 .27 .35 .22
17) H TEX 0 0 0 0
181 E Tex .51 .51 .60 .51
19) N OKLA .5 .02 .02 .06
(10) E OKLA .80 .57 .57 .61
111) COLO .311 ’ .36 .1111 ‘ .31
112) KAN . 57 . 36 . 35 . 38
113) NEBR .63 .113 .111 .35
1111) N0, S0 .85 .72 .35 .59
115) M11111, N180 1.111 .81 .51 1.20
116) 1011A 1.12 .80 .59 .711
117) ILL 1.57 1.27 1.19 1.311
118) M1011, 1ND, 0-110 1.59 1.36 1.31 1.111
119) Mlssoum 1.28 .98 .90 1.05
12D) ARK, LA 2.56 1.31 .97 2.65
121) Miss, ALA, GA 1.38 1.38 1.38 1.116
122) FLA 1.82 1.811 1.85 1.79
123) NC, SC 2.03 2.03 1.99 2.03
1211 KY, 151111 1.5a 1.53 1.5a 1.5a
125) HVA, VA, 111,011,116 2.21 1.98 1.92 2.15
1 26) PENN 2. 51 2. 28 2. 22 2. 50
127) N E 2.117 2.25 1.99 2.16

manded by the poultry and livestock industry. Feed
grain prices, in all models, were highest in California
(4) followed by Arizona (5). As expected, feed grain
prices were generally lowest in the "Corn Belt and
Northern Plains states. However, feed grain prices
may have been slightly understated in the Eastern
Corn Belt and regions with grain export facilities
since export demand was not incorporated into the
various models. Prices were slightly higher in the
Eastern Corn Belt than those of the Western Corn
Belt because of locational advantages in shipping to
the deficit Northeast. Regional feed grain price dif-
ferentials generally remained relatively more stable
than did price differentials for feeder cattle when
minimum feedlot sizes were increased to 1,000 and
5,000 head in Models 2 and 3, respectively.

Table 16, which depicts regional differences in
fed-cattle prices at the slaughter level, reveals that
fed-cattle prices were generally highest in Pennsyl-
vania and the Northeast. Generally higher fed-cattle
prices in these two regions can be attributed primari-
ly to the excess demand for fed beef relative to
production along with the availability of surplus
slaughter capacity. Fed slaughter cattle prices were
lowest in West Texas, the base region, which did not
have sufficient slaughter capacity to slaughter all the
cattle fed within that region. Consequently, West
Texas and also Western Oklahoma, the region with

27

the second lowest fed-cattle prices, shipped substan-
tial numbers of fed cattle to the Southeast for
slaughter.

These results suggest that fed-cattle prices will
remain generally lowest in I/Vest Texas and Western
Oklahoma until such time as slaughter facilities are
equal to or exceed local fed-cattle slaughter supplies.
Relatively lower fed-cattle prices in surplus fed-cattle
production areas as the Texas-Oklahoma Panhandle
tends to encourage establishment of additional
slaughter facilities in such areas by slaughtering firms
seeking to minimize fed-cattle acquisition costs. This
is evidenced by the recent construction of large, spe-
(iializeil, shipper-type cattle slaughter plants in and
adjacent to the Texas-Oklahoma Panhandle areas.

Regional price differentials for dressed fed beef
reveals that fed-beef prices were generally highest in
such deficit areas as the Northeast, the South, Cali-
fornia and Washington-Oregon, Table 17. Lowest
fed-beef prices were generally observed for the South-
ern Plains and Colorado. These regions are large
surplus producers of fed beef and are faced with
relatively long distant shipments to major fed-beef
consumption centers.

Higher regional fed-beef price differentials indi-
cate both the relative degree of excess regional de-
mand over production as well as relative distances

TABLE 17. RsciouAi. DRESSED FED BEEF PRICE DIFFERENTIALS, av MODEL, GIVEN
CHANGES IN REGIONAL FEEDLOT SIZE Auo FlXED FEEDING cosrs

REGION 110051.
1 2 3 11
- - - - - - - --Doi.i.ARs/cvrr-------------

(1) HASH, DREG 1.11 1.38 1.1111 1.21

(2) Mom, lnAiio, Hro 70 .611 .69 .611

(3) UTAH, Nev 50 .81 .56 .50

(11) CALIF 1.30 1.30 1.30 1.30

(5) ARiz .72 .72 .72 .72

(6) N (‘EX 35 .35 .35 .35

(7) H TEX 0 0 0 0

(B) E TEX 69 .69 .69 .69

(9) H (XLA .02 -.03 -.03 -.03

(10) E OKLA .30 .17 .13 .22
(11) CoLo .03 .03 .03 .03
(12) KAN .31 .09 -.011 .16
(13) NEBR 27 .02 -.11 .12
(111) N0, SD .611 .119 .011 .111
(15) MINN, Hisc. .83 .118 .10 .60
(16) IONA - .57 .32 ' .19 .112
(17) |LL 1.01 .76 .63 .86
(18) Micii, luo, 0i1|o 1.17 .92 .79 1.02
(19) MISSOURI .65 .113 .30 .50
(20) ARK, LA .72 .69 .65 .72
(21) Miss, ALA, GA 1 1.13 1.01 .93 1.06
(22) FLA 1.53 1.53 1.119 1.53
(23) NC, SC 1.65 1.50 1.37 1.57
(211) KY, TENN 1.07 1.02 .911 1.07
(5) 11 VA,VA,1b,DEL,DC 1.82 1_57 1_i.3 1,79
(26) PENN 1.87 1.62 1.119 1.72
(27) N E 2.211 2.00 1.66 1.77

28

   
 
   
    
   
   
   
  
  
  
 
   
  
    
  
 
 
   
   
  
   
   
  
 
   
    
   
   
  
  

between major deficit consumption centers in '
to major supply areas. For example, dressed 
prices were generally highest in the North
Further analysis of the price differentials
Northeast for the various models in Table
cates that fed-beef prices declined in that r1
cattle feeding increased in the more near
in the Eastern Corn Belt in Models 2 and ,1
competitive interregional relationship is also 
in a lower price differential for the Northea
Model 4 compared with Model 1. In both
1 and 4, Nebraska and Iowa were the sole 
of fed beef to the deficit Northeast. How
least-cost solution for Model 4 revealed a (Ti
increase in cattle feeding in Iowa comp.
Model l, and at the same time North 1f
Dakota initiated cattle feeding up to the i
the required consumption within its own,
Model 4. The overall result was that Neb f
its market in North Dakota-South Dakota j
to seek outlets in the more distant Northeast
Nebraska, one of the major suppliers to f
east, was in a less favorable competitive up’
Model 4 than in Model l. Consequently,
received a lower price for its product as re i
lower fed-beef price differentials in Model 4f;
ilar situation existed for Iowa which shi
stantially greater supplies of fed beef to 1
distant Pennsylvania market in Model 4 --‘
with Model 1. "

The adverse price effects for the North
States resulting from substantial increased f
the neighboring Corn Belt and Lake sta
flected in the declining price differentials f’
(12) and Nebraska (l3) in Models 2 and 3, 
These results revealed that fed-beef prices i’.
to decline in Kansas and Nebraska even thy
decreased fed-cattle production. However, ,
gions retained their regional surplus fed- ;
and competed for the same general mar
Iowa and the Eastern Corn Belt States whi
locational advantage in shipping surplus "-;
the Northeast while at the same time suq
increasing their fed-beef production in ~-

3.

POTENTIAL ADJUSTMENTS IN T11
CATTLE FEEDlNG—FED-BEEF ECON’)

To gain insights into the potential 1
adjustments in the cattle feeding-— fed-beef}
a model was developed to incorporate p;
changes in regional feedlot size while regi
feeding and slaughter levels were permit
established in each region on a least-cost i
out capacity restrictions. Unlimited regio" i
and slaughter capacities assume that catt
and slaughtering firms have ample time and
to adjust capacities to optimal levels.

Model 5 incorporates all the assu
Model l with the exception of regional sla

   
   
  
 
 
  
   
  
  
   
 
  
  
  
  
  
  
  
  
   
  
  
    
 
   
   

‘pacities which were unlimited. In addi-
nal feedlot sizes in Model 5 were based
 feedlot sizes for 1975 reflecting changes
gs among various size groups of feedlots
~ to 1968 as reported by the U.S. Depart-
; iculture.

’ 8 and Table l8 revealed that regions with
tcompetitive advantage in cattle feeding
trated in an area encompassing the Texas-
‘Panhandle, New Mexico, Arizona, Colo-
 -Nebraska, Iowa-Illinois, portio-ns of the
V-i Belt and Kentucky-Tennessee. Num-
Title fed in the cattle feeding belt accounted
 nt of the total required to meet the U.S.
~ and in Model 5. According to data re-
l the USDA, states in the cattle feeding belt
for 70 percent of the U.S. fed-cattle mar-
a ring 1968. The lone exception to the pat-
Model 5 was Washington-Oregon where
U cattle fed are equal to that region's fed-
mption. Almost 60 percent of the cattle
v fed in the Texas-Oklahoma Panhandle,
3i Nebraska with Iowa and Illinois account-
f other l6 percent. The potential for East
_,-~ to be overstated in Model 5 since the
‘in for feed grain was not considered.
i tial for the Kentucky-Tennessee area ap-
‘irst glance, somewhat surprising. However,

ure 8. Cattle feeding belt as defined by regions with the highest competitive advantage in cattle feeding (Model 5).

that area enjoys locational advantages with respect
to (l) surplus feed grain supplies in the Corn Belt,
(2) surplus feeder cattle production in the South and
(3) a large deficit fed-beef market in the South.

The concentration of cattle feeding activities
among a relatively few states in model 5 has impor-
tant economic implications for feeder cattle and calf
producers, feed suppliers and manufacturers, and fed-
cattle slaughtering and processing plants. The least-
cost shipment patterns of feeder cattle in Table 18
reveals that feeder cattle producing states in the
Northwest and parts of the deep South would be most
disadvantaged if firms comprising the cattle feed-
ing—fed-beef industry were located on a least-cost
production basis. Regions with unfed feeder cattle,
including states in the Northwest, Florida and North
Carolina-South Carolina, imply a relatively greater
locational (lisadvantage for these areas compared to
competing areas in shipping feeder cattle to feedlots
in the least-cost cattle feeding belt. Such a locational
disadvantage, other things equal, suggests that feeder
cattle prices would be lowest for producers in these
more distant feeder cattle production areas given the
concentration of cattle feeding operations suggested
by Model 5.

The optimum distribution patterns of feed grain
available for cattle feeding show that feed grain
transport costs are minimized when the Southern

   

29

     
 
    
  
  
  
  
  
  
  
  
  
  
  
  
   

n01: 18. M0051 5 F5505): c1111.: supvuss, 01111111111 FEEDING LEVELS, 01111001011111 cosrs 11110 sunwtus FEEDER 01111.5, av REGIONS, 111111 N0 nssnucnous 011 11501 .1
FEEDING CAPACITY AND REGIONAL FEEDLOT s1zs PROJECTED to 1975
F5505): P5501211 c1111.: nssnmnou AND 0011mm REGIONAL 551201110 LEVELS 911101.00 i»
51111101110 c1111.: 1111511., 11.T5x., K11N., 1011/1 111011., |N0., 7177,? T0111. P550511 <
REGIONS SUPPLY 0115c. A1112. N.1'£x. H.0KLA. E.T5x. C01.0. N502. 11.1.. 01110 TENN. s1111>1>50 CATTLE 
5552.. ޤA2__ ߤA2_. f
(1) HAs11.,OR1-:c. 091,000 665,010 665,010 220, 
(2) MoNr.,|0)1110,Hv0. 2,129,000 90,500 90,500 2,000, 
(0) UrAu,N5v. 170,000 170,000 170,000 0 ,}
(1) 011.11. 075,000 075,000 »_o 075,000 0 6-’
(5) ARIZ. 2119,000 209,000  209,000 0 
(6) 11.11511. 192,000 192,000 192,000 o
(7) IALTEX. 1,109,000 1,109,000 1,109,000 0.;
(0) 5.1m. 2,091,000 700,029 1,610,671 2,091,000 of,
(9) H-OKLA. 011,000 011,000 011,000 0 .
(10) 5.0101. 1,120,000 1,120,000 1,120,000 o1
(11) COLO. 790,000 290,135 095,865 790,000 0:
(12) KAN. 1,039,000 80,897 1,350,103 1,039,000 
(13) NEBR. 1,552,000 1,552,000 1,552,000 0 
(11) 11.0.,s.0. 2,210,000 2,210,000 2,210,000 "
(15) 11111100116. 1,602,000 1,602,000 1,602,000
(16) lowA 1,057,000 1,057,000 1,057,000
(17) ILL. 559,000 559,000 559,000
(18) M1011. , 1N0. ,01110 775,000 775,000 775,000
(19) 110. 1,191,000 1,260,512 200,100 1,191,000
(20) ARK. ,LA. 1,053,000 1,053,000 1,053,000
(21) MISS. ,ALA. ,GI1. 1,957,000 1,957,000 1,957,000
(22) FLA. 375,000 0
(23) N.C.,S.C. 355,000 0
(211) KY.,TENN. 1,313,000 262,670 1,050,326 1,313,000
(25) H.VA. ,VA.,("0.,DEL. 058,000 0

   

In“, 27,188,000 665,313 209,000 1,367,000 7,036,860 1,610,671 095,865 6,379,615 3,711,162 775,000 1,050,326

Plains imports most of its feed grain requirement
from Kansas, Table 19.13 The Kansas-Nebraska area,
at the same time, receives most of its feed grain
requirement from Iowa. West Texas ships substantial
quantities of feed grains to New Mexico and Arizona
while Illinois supplies the grain required for cattle
feeding in Kentucky-Tennessee. Regions with sub-
stantial quantities of surplus feed grains in Model 5
"Regional feed grain supplies were distributed on a least-cost

basis among regions in Model 5 as in Model 1 such that grain
requirements for feeding to other livestock were satisfied.

TABLE 19. fbDEL 5 2 OPTIMJM SHIPMENTS OF AVAILABLE FEED GRAIN FOR CATTLE FEEDING AND SURPLUS FEED GRAIN BY REGION, WITH N0 RESTRICTIONS ON REGIONA
FEEDING CAPACITY AND REGIONAL FEEDLOT SIZE PROJECTED TO 1975

2 7110 816

 
 
  
 
  
   
   
  
  

include the Northern Plains States, the
and Iowa.

Economic theory suggests that fed-ca
ter, assuming unlimited regional slaughtj
will be predominantly production orien:
specifically, the combined acquisition, slai
distribution costs are generally expected»?
as slaughter firms locate in the primary
areas. The results in Table 20, which _
97 percent of the slaughter was product)

 
   
  
  
   
  
  
   
   
   
  
   

‘0Esr1u1T10N 1/ Sunwtus
SHIPPING H/(sn. , H.T5x. KAN. , 101111, M1011. , 1N0. , Kv., Tout FEED
REGIONS 0115c. A1112. NJtx. H.01<1.11. E.T5x. 001.0. N500. 11.1.. 01110 TENN. s1111>1=50 0mm
(2) m~1.,11>)11o,m0. 170,207 170,207 0
(7) 11.1111. 51,020 200,106 121,171 750,600 0
(8) E-TEX. 223,000 223,000 0
(9) H.01<1.11. 129,100 129,100 0
(12) KAN. 1,136,800 1,136,800 0
(13) NEBR. 100,032 696,272 836,300 0
(10) N.D.,S.D. 0 918,163
(15) M1NN.,11I1s. 0 1,021,200
(16) 10111 1,025,210 710,210 1,770,150 500,111
(17) ILL. 311,966 238,630 550,600 0
(18) M1c11.,|ND.,01l0 178,637 178,637 118,563
TOTAL W337 51,020 283 106 1,690,670 223,000 100,032 1,721,082 1,060,209 178,637 2 8,6 0 5, 6 ,0 1 2,96, 1

 

1/ 8111111151110 m5 IN TEN THOUSAND P0uN0s.

30

  

  

l‘. F0021. 5 =

UPTIMUM SHIPMENTS or FED CATTLE lonzssso EQUlVALENTl FOR stnucnrzn, av nsc1ou, wurn no RESTRICTION on SLAUGHTER CAPACITY AND REGIONAL reenter
s1z: PROJECTED TO 1975

HAsH.,
Onsc.

H.TEx.,

ARIZ. N.MEX. H.0KLA. E.TEx.

   

1,331,130
1,320,200
7,337,590
05,050,730
7,151,377

EMU.

1,20s,ss0

DESTINATION 1/

TOTAL
SHIPPED

Kv.,
TENN-

KAn.,

Iowa, M1cH.,lN0.,
NEBR. ILL. Oulo

Coto.
0,331,190
1,020,280
7,887,590

06,257,398
7,151,377
3,371,880

M1,791,70h

3,371,330
33,173,375 3,512,029
25,056,001

0,070,750

25,H66,801
h,87N,750

6,533,030 s,53a,00

  
  
   
  
 
  
  
  
 
  
 
  
  
  
 
  
   
  
  
 
  
 
  
  
  
 
 
  
  
 
  
  
 
  

H,331,190 1,%2H,280 7,887,590 N5,050,738 7,151,377

nrs ARE IN 100 POUNDS.

‘5, provide further evidence that costs are
l, when slaughter is production-oriented.
 able 20 shows that costs for some regions
nimized when slaughter is not production-
"The optimum solution reveals that total
inimized when Eastern Oklahoma imports
i: cattle instead of dressed fed beef from
Liklahoma. These results suggest that, given
slaughter facilities, regional alterations in
,s as labor costs, power costs, local taxes,
 ion costs and so forth may affect the form
l in which livestock and meat products are
igHowever, cost disadvantages as well as ad-
 ould be associated with the complete shift
 ghter industry to the primary production

itic changes would occur in the optimum
' routes and associated volumes of dressed
,1» when cattle feeding is concentrated
ile feeding belt, as indicated by Table 21,
,5 available slaughter facilities in the pri-
"uction areas, Table 20. These findings
immarized as follows:

9

0- e West Texas-Western Oklahoma area is
‘shipper of fed beef to the Northeastern
the West Coast and the Southeast. The
 ahoma Panhandle emerges as a strong com-
the deficit Northeast (27) with Kansas-
i“ It is the sole supplier for Pennsylvania
i supplies almost two-thirds of the fed-beef
 ts in California (4). In addition, the Tex-
v0.1a Panhandle ships substantial quantities
k beef to Arkansas-Louisiana (20), Florida
i North Carolina-South Carolina (23).

ansas-Nebraska finds itself shipping pre-
‘ y to markets in the East. The Northeast
f» received more than half the fed beef
l. in Kansas-Nebraska in Model 5. Other
outlets include the Middle Atlantic States,

1,206,660 3,371,880 38,178,875 29,079,630 U,B7N,750

6,533,030 1h9,090,000

the Eastern Corn Belt, Missouri and North Dakota-
South Dakota.

3. Preferred markets for Iowa-Illinois included
the Lake States and the Eastern Corn Belt markets
which were shared with Kansas-Nebraska. Iowa was
a major supplier of fed beef to the Northeast (27) in
Model 1 along with Nebraska. However, as a result
of the increased concentration of cattle feeding in
the Plains States in Model 5, fed-beef prices would
tend to decline in these areas; and therefore, the
Texas-Oklahoma Panhandle is able to compete for

the Northeastern markets with Kansas-Nebraska.

4. Both New Mexico and Arizona compete with
West Texas-Western Oklahoma for the deficit Cali-
fornia (4) fed-beef market. With increased cattle
feeding, the Plains States, Arizona (5) and, especially
New Mexico (6), find it difficult to compete for fed-
beef markets in the South.

5. Kentucky-Tennessee, in addition to supply-
ing its own fed-beef requirements, has a locational
advantage in shipping fed beef to the Mississippi-
Alabama-Georgia markets.

6. Out-of-state shipments from Colorado move
to the Inter-Mountain States of Montana-Idaho-
Wyoming (2) and Utah-Nevada (3). Fed-beef pro-
duction in Washington-Oregon (1) was limited to
consumption within that area.

Regional price differentials in Model 5, although
generally similar to those for the previous models as
shown in Tables 14-17, reveal somewhat greater dif-
ferences between surplus and deficit regions. This
was especially true for feeder cattle. For example,
when cattle feeding is concentrated in the cattle feed-
ing belt, feeder cattle producers in the Far West and
the South are faced with relatively long distance
shipments of feeder cattle. Consequently, prices for
feeder cattle in such areas would be expected to
reflect increased transportation costs as indicated by

31

TABLE 21- MODEL 5- 2 UPTIMUM SHIPMENTS FOR DRESSED FED BEEF, BY REGION, WITH NO RESTRICTIONS ON FEEDING AND SLAUGHTER CAPACITY AND REGIONAL FEEDLOT P‘

  

SHIPPING
REGIONS 1 2 3 H 5

wASH.,UREG. M,331,190

1m. 1131,1120 9a9,0s0

11.11511. 1,120,610 166,900

W.lEX.,W.UKLA. 11,535,710
E.1ex.

E.0KLA.

COLD. 922,130 926,k30

KAN.,NEBR.

IOHA,ILL.

MICH.,IND.,UHl0

KY.,TE~~.

DESTINATION 1/
6 7

1,019,200 152,500

     
 

8 9 10 11 12 ' 13 .

5,207,900 ,
1,206,660
1,520,320 .
1,710,160 999,9

TOTAL %,331,190 922,130 926,N30 19,390,7H0 989,860 566,980 1,319,200 5,287,980 153,500 1,206,660 1,523,320 1,718,160 999ji€

1/ SHIPMENTS ARE IN 100 POUNDS.

substantially lower regional price differentials, Table
22.

Regions importing relatively large numbers of
feeder cattle, in contrast, would be faced with rela-
tively higher prices of feeder cattle. The pattern of
regional price differentials for feed grain, fed slaugh-
ter cattle and fed beef in Model 5 was generally
similar to those developed in earlier models. How-
ever, the regional price differentials for fed beef in
the latter model was generally lower than those devel-
oped in the earlier models.

Lower regional fed-beef price differentials sug- ‘

gest that costs of producing and distributing fed
beef would decline when cattle feeding is concen-
trated in regions with the highest competitive ad-
vantage in cattle feeding. Optimum solutions for
the various models revealed that total costs of pro-
ducing and distributing fed cattle and fed beef de-
clined about $15 million from Model 4 to Model 5.
The decline from Model 1 to Model 5, although due
partly to projected 1975 regional feedlot sizes, was
approximately $70 million dollars.

CONCLUSIONS

The dramatically changing economic environ-
ment in the cattle feeding—fed-beef economy sug-
gests that numerous changes are imperative at the
local and regional levels in the fed-cattle production,
processing and distribution sectors. Factors generat-
ing these dynamic changes include changes in tastes
and preferences, a shifting and growing population
with an increasing per capita income, and continuous
technological innovations in cattle feeding, fed-cattle
slaughter, transportation and distribution systems,
and changes in the production of feeder cattle and
feed. In addition, differences in such regional fac-
tors as capital, level of management, availability of
resources for producing feed and feeder cattle, will-
ingness to adopt technological innovations, and others
contribute to constantly changing regional competi-
tive positions and situations among variously en-

32

  
  
  
   
 
   
  
 
 
 
  
   
  
   
  
   
   
  
  
 
 
  
  
    
   
 
  

dowed regions. Some of the above factors I
directly considered in the models employed.’

The cattle feeding- fed-beef economy
trayed in this study, although oversimpli
vides insights concerning interregional I
relationships and potential change in regi
tionships as a result of changes in region
economies of size. The simultaneous sol 
the various sectors of the cattle feeding 1
economy demonstrate how regional competi 1'
are interwoven and provide guidelines for?
making by firms and individuals associated
livestock and meat industry.

Regions enjoying economies of size g
feedlot operations, other things equal, gen
enjoy competitive advantages in the cattle
fed-beef economy over regions where such _f_
are not so evident. The findings reveal
gional disadvantages resulting from disec 1i
feedlot size and higher transportation and
costs can be partially offset through ecol
size in feedlot operations. However, eco_
size in cattle feeding operations by the
not sufficient to offset severe locational dis__
relative to available sources of feeder cattle;
grains. For example, Table 7 revealed p
feeders in California ranked first along 1
Texas in availability of economies of size °
operations. The least-cost solutions for 1v
models designed in this study, however, sh
most of the California feedlot capacities I
come surplus in a highly competitive eco 
result of relatively high transportation c,"
ated with the importation of feed grain 
extent, feeder cattle. 

Locational disadvantages relative to 1.
lets can be partially offset by economies -_
feedlot operations when resource inputs’
feeder cattle and feed grains are readily f
Even though far removed from major 1f;
ters, North Dakota-South Dakota fed subst L

2,228,050 2,038,753

1,883,397

  

1,108,690 3,079,170

;1,051,s10 10,197,130

5 1,870,750

' 3,615,000

2,988,870

TOTAL

23 211 25 26 27 SHIPPED

0,831,190
1,121,280
7,887,590

8,811,100 15,987,155 15,050,738

7,151,377

1,208,680

3,371,880

7,706,270 19,529,175 38,178,875
29,079,880

1,878,750

2,888,030 6.533.030 _

  
  
  
  
 
 
  
  
  
 
 
  
 
  
 
 
  
 
  
  
 
  
 
 
  
   
  
 
  
 
  
  
  
 
  

_tle in the optimum solution for Model 3
f-ge feedlot capacities were increased to
 resulting in a relatively lower fixed feed-
 that area. This suggests that cattle feed-
gying areas where feed grain and feeder
iggenerally abundant can compete in the
"J-ing-fed-beef economy provided econo-
 in feedlot operations are sufficient to
gtional disadvantages.

"feeders in Corn Belt States like Iowa and
l1 major surplus feed grain producing
 e United States, enjoy competitive ad-
 er most other major cattle feeding areas
om relatively lower feed grain prices. This
 advantage, however, is offset to a large
_ diseconomies in feedlot operations. Such
'es are evident in generally higher fixed
f}: less specialized management and feed-
j!‘ lower degree of feedlot utilization and
hen compared with the large, commercial
ich have adopted big business techniques.
l e implementation of innovative cost sav-
Q ues specifically designed for farmer-feeders
‘nsion of large commercial feedlot opera-
5112C possible economies of size in feeding,
1rators inthe Corn Belt may lag or decline
f1 the rapidly expanding activity in the
‘lies. .

evealed that substantial increases could be
1 in cattle feeding in the Western and
~ n Belt and the Lake States with increases
l feedlot size to 5,000-head capacity or the
f1 regional cost saving techniques to offset
f»- onomies of feedlot size. Such increases
beeding in the 1Com Belt and Lake States
 would have severe repercussions on the
i, especially, Nebraska areas. Competitive
3" accruing to the Corn Belt and Lake States
 and Nebraska, in this situation, stem
‘from locational advantages in shipping fed
j deficit fed-beef markets in the Northeast

'; 1 ,s10 19,878,870 3,079,170 2,228,050 3,815,000 3,902,150 2,918,670 2,888,030 7,708,270 8,881,000 35,518,930 109,090,000

and Middle Atlantic States. The Southern Plains, at
the same time, enjoys a locational advantage over
Kansas and Nebraska in shipments to deficit fed-beef
markets in the South.

The projection of regional feedlot sizes to 1975,
along with unlimited regional capacity restrictions
relative to numbers of cattle fed or slaughtered, re-
sulted in a concentrated cattle feeding belt from the

TABLE 22. REGIONAL PRICE DIFFERENTIALS FOR FEEDER CATTLE, FEED GRAIN, FED
SLAUGHTER CATTLE. AND FED BEEF, “JOEL

Fzenza FEED FED F20
REGION CATTLE GRAIN SLAUGHTER BEEF
- - - - - - - - DoLLARs/0wT- -c:T:LE - - - - - - - ; - -

(1) HAsu, Oazc -.98 .30 1.26 1.92

(2) MDNT, IDAHO, Hvo -.98 .09 .3» .90

(3) UTAH, Nev -.76 .21 .19 .75

(E) CALIF -.92 .k7 .97 1.30

(5) Amz -.52 .31 .67 .72

(6) N HEX -.08 .15 .30 .35

(7) H Tex 0 0 0 0

18) E Tex -.51 .0» .03 V .08

19) H OKLA .11 .02 .01 -.03

(10) E 0KLA -.06 .011 .75 .311
(11) 001.0 -.30 .02 .19 28
(12) KAN -.12 -.0\1 .27 .26
(13) NEBR .10 -.07 .31 29
(110) N0, S0 -.|18 -.11 .68 87
(15) M188. N188 -.05 -.11 1.25 79
(16) |OHA -.18 -.11 .78 .63
(17) ILL -.18 -.11 1.27 1.02
(18) Mlcn, luo, 0N|o -.h2 -.11 1.25 1.23
(19) H1ss0un1 -.01 -.08 .98 .65
(20) ARK, LA -.60 .07 .60 .72
(21) Muss, ALA, GA -.78 .05 1.00 1.05
(22) FLA -1.01 .19 1.17 1.53
(23) NC, $2 -.99 .11 1.73 1.61
(2)6) KY, TENN -.89 .06 1.15 1.06
(25) HVA,VA,DEL,HD,DC -.92 .08 2.12 1.71
(26) PENN -.60 .10 2.17 1.93
(27) N E -.79 .16 2.04 1.9%

33

Texas-Oklahoma Panhandle and New Mexico area
through Kansas and Nebraska, the Western Corn
Belt, portions of the Eastern Corn Belt and down
into Kentucky-Tennessee. The implications of these
findings may be summarized as follows:

l. Substantial competitive advantages, other
things equal, will accrue to regions in the cattle feed-
ing — fed-beef economy with the following attributes:

(a) Economies of size in feedlot operations,

(b) Location of feeding facilities in or adjacent
to major surplus feed grain producing areas,

(c) Location of slaughter facilities in the pri-
mary fed cattle producing areas, and

(d) Cost advantages in acquiring feeder cattle.

2. Location relative to market outlets is not an
overriding factor as costs of transporting dressed beef
to more distant markets can be offset by economies
of size in feedlot operations, lower f.o.b. feed and
feeder cattle costs, lower slaughter cattle acquisition
and slaughtering costs, lower taxes and so forth.

3. Generally greater concentration of cattle
feeding activity in the Texas-Oklahoma Panhandle
and Kansas-Nebraska areas compared with the Corn
Belt suggests that regions which enjoy substantial
advantages in economies of size in cattle feeding
along with generally adequate feeder cattle and feed
grain supplies or accessibility to them can anticipate
relatively greater growth and expansion in feedlot
activity than can regions where diseconomies of size
are generally prevalent. This does not indicate that
the cattle feeding industry in the Corn Belt will
eventually be replaced by cattle feeders in the Texas-
Oklahoma Panhandle or Kansas and Nebraska. How-
ever, it does suggest that farmer-feeders in the Corn

34

  
    
 
   
  
    
   
   
 
    
 
  
  
   
   
   

Belt, who do not adopt cost saving techniq j
ing from economies of size or other facto 
faced with increasingly less favorable cf
positions when competing with regions wh
commercial feedlots predominate. ’

4. Regions like California, which "
moved from available sources of feed grain -_
cattle even though they enjoy economies q
feedlot operations and nearby market on
severe competitive disadvantages and ma 5
increasingly difficult to compete for resou y
cattle feeding——fed-beef economy. Econo 1.
suggests that minimum feeding levels in su 
in the short run, would be at those levels i,
to utilize local surplus feed supplies.

5. With the exception of Kentucky-
cattle feeders in the South face severe 
resulting primarily from deficit feed grain v-jf
and diseconomies of size in feedlot operati)
petitive advantages accruing to Kentucky--
in the cattle feeding- fed-beef economy c
other states in the South stem primarily 
tional advantages in obtaining feed grain’,
Corn Belt. However, compared to other t 
feeding regions, Kentucky-Tennessee is _j
competitive disadvantages as a result of 
of size in feedlot operations. Yet, it enj“
tional advantage in obtaining feeder 
nearby Southeastern States and in shippin
to the deficit fed-beef markets in the So

6. Fed-cattle slaughter and processi,
will continue to locate near concentrated w,
ing areas to realize cost advantages ass»
acquisition costs and to assure adequate
supplies.

  
 
 
 
 
  
 
 
  
 
  
   
 
 
  
 
 
 
  
 
  
 
   
  
 
 
  
  
 
  
 
  
  
 
  
 
  
 
  
  
  
 
 
  
 
  
 
  
 
  

APPENDIX A

Development of Data

ta utilized in this study were developed
,m secondary sources as Texas Agricul-
ent Station publications and from vari-
_ls issued by the U.S. Department of
 The specific sources and estimating
i» ployed are described in the following.
Supplies

3 feeder cattle and calf supplies were
w data published by the USDA in "Live-
 eat Statistics,” “Livestock and Poultry
5 and “Calf Crop." The 1968 regional
" supplies were postulated as follows:

, feeder cattle = calf crop — total cow
_ - bull replacements — commercial and
pughter — deaths.

3 beef cow and bull replacements were
U.S. replacement ratio or replacements -I—
,’ ventory. Replacements were estimated
 lowing equation:

?

ents = Net inventory + deaths — be-
Eng inventory

entory = ending inventory + commercial
I; (CT.

 lacements were defined as heifer calves
 k as reported by the USDA.

(Ional Feedlal Size and

I ing Capacity

'9 regional feedlot size for feedlots with
t’ d-over capacity were based on a weight-
"~ re as represented by 1968 marketings
__ various feedlot size groups as reported
DA in "Cattle on Feed." The average
I in each size group was defined as the
uarter range. The lower one-quarter
(then weighted by the proportion of re-
, ttle marketings from lots with 1,000-
er capacity and aggregated over the
f groups. Data on average regional feed-
feedlots with less than 1,000-head capacity
g d through correspondence with livestock
Q- ‘ sonnel and state statisticians in the vari-
 The estimated regional feedlot sizes for
,000-head-and-over capacity and lots with
DOG-head capacity were then weighted by
 ion of fed-cattle marketings represented
e group to obtain the regional feedlot

"one-time regional feedlot capacities for
 1,000-head-and-over capacity were esti-
ultiplying the number of reported feed-

TABLE 23. ESTIMATED FEEDER CATTLE PLACEMENT AND FAT CATTLE MARKETING HEIGHTS,
ASSUMPTIONS REGARDING LENGTH OF TIME ON FEED, AND PER HEAD FEED GRAIN REQUIRE-
MENTS, BY REGIONS

FEEDER CATTLE FAT CATTLE DAYS PER HEAD FEED
Recnons PLAcsnEuT MARKETING on GRAIN
HEIGHTS HEIGHTS F1220 RE UIREMENTS
£21m E5 114E _°U"_°§
(1) HASH. ,0REG. 618 1,068 165 2,679
(2) M011T. ,1oA11o,HYo. 616 1,066 165 2,672
(3) UTA11,N1-:v. 5711 9711 1115 2,1118
(11) CALIF. 592 992 1115 2,198
(5) ARIZ. 538 938 1115 2,0119
(6) N. MEX. 5116 9116 1115 2,071
(7) H. TEx. 5511 9511 1115 2,093
(s) E. Tex. 1121 711s 125 1,387
(9) H. OKLA. 61111 1,01111 1115 2,3111
(10) E. OKLA. 1187 _ 887 1115 1,909
(11) COL0. 6611 1,1111 165 12,8211
(12) KAN. 613 1,063 165 2,663
(13) NEBR. 1332 1,082 165 2,723
(111) N.0., 8.0. 659 1,109 165 2,808
(15) 1111111., Husc. 611 1,061 165 2,657
11s) IOHA s61 1,111 165 2,811+
(17) ILL. 709 1,159 165 2,965
(18) M1c11.,l11o.,0111o 631 1,031 1115 2,305
(19) MISSOURI 613 1,063 165 2,663
(20) ARK., LA. 1190 890 1115 1,917
(21) M1ss.,A|_A.,GA. 1190 890 1115 1,917
(22) FLA. 6011 1,0511 165 2, 635
(23) N.E., S.C. 612 1,012 1115 2,253
(211) KY., TENN. 619 1,019 1115 2,272
(25) H.VA.,VA.,I)EL.,DC m 1,0911 155 2,161
(26) PENN 768 1,218 165 3,151
(27) N.E. 705 1.155 165 2,953

lots within each size group by the lower one-quarter
range and summing over all size groups, The one-
time feeding capacities of these large lots were then
adjusted by annual turn-over ratios, as reflected by
the average days on feed in Table 23, to obtain
annual feeding capacities. One-time regional feeding
capacities for feedlots with less than 1,000-head capa-
city were obtained through correspondence with live-
stock marketing personnel and state statisticians in
the various regions. The annual turn-over ratio for
these small feedlots was arbitrarily set at 1.0.

Regional Per Head Feed Grain Requirements

Estimated per head feed grain requirements were
based on regional cattle placement and fat cattle
marketing weights and length of time on feed, Table
23. Fed-cattle marketing weightswere estimated from
available slaughter data and weights of cattle on feed
as reported by the USDA for I968. Regional feeding
periods and total gain per head were based on fat
cattle marketing weights as follows:

Fat cattle Days on Total gain
marketing weights feed per head
(pounds) (days) (pounds)
1,000 8c over 165 450
999 to 800 I45 400‘
799 8c under I25 325

35

Regional placement weights are defined as the
difference between fat cattle marketing weights and
total gain per head. Feed grain consumption was
based on placement weights and daily rates of gain.
Total regional per head feed grain consumption was
set at 1.5 percent of the body weight for the first
30 days on feed and 2.0 percent for every day
thereafter.

Regional feed grain production, food industry
and seed use and consumption by grain-consuming
animal units other than cattle on feed were estimated
from data published by the USDA in “National and
State Livestock — Feed Relationships.”

Fed-Beef Consumption Estimates

Since previous research has indicated that per
capita fed-beef consumption is influenced predom-
inantly by per capita consumer income, fed-beef con-
sumption in this study was postulated as a function
of per capita income. The fed-beef equation utilized
for estimating regional fed-beef consumption was as
followszl“

Y = -69.209220 + .06l772X
(l0.79)**

R2 = .90 F = 116.4?‘
where:
Y = per capita consumption of fed beef,
X = deflated per capita consumer income.

Transportation Rates

Transportation costs used in this study were the
lowest of either truck or rail among all regions. Cost
data on other modes of transportation were not in-
cluded in this study. Four equations were utilized
for developing truck and rail transportation rate
functions for cattle, feed grain and dressed fed beef.
These equations were postulated as follows:

(1) Y = a + bx

(2) Y a + bx + b(x)‘-’

(3) Y = a + bx + b(x)2 + b(x)3
(4) Y=a+bx+b\/x_

where:

Y = shipping cost in dollars per hundredweight
for the specified commodity,

x = miles shipped.

“The t-value of the estimated parameter is directly below the
coefficient in all estimating equations in this study. (‘"') de-
notes statistical significance at the one percent probability
level.

36

   
    
    
  
 
 
    
  
  
  
   
  
 
 
    
   
   
  
  

Truck and rail transportation costs rd
data for cattle and carcass beef were obta’
state and regional tariff bureaus and froi
shipping firms. Transportation cost data
adjusted for backhaul privileges. Intraregi
age was assumed to be equal to one-half 
thest possible shipment from the shipping ._
ing point within each region. Data for 1;
truck and rail transportation functions for _
were supplied by the Texas Transportation ;
Texas A&M University. a

Truck and rail transportation functig
appeared to conform most closely to obs
ping rates for cattle, feed grain and "
were adopted for this study. These are as

Cattle: _
Ye, = .105092 + .001911x + .004
01.41)" (2
R2 = .93 F =11
Yo, = 514954 + .00075sx
(121.s9)** s.
R2 = .89 F = 192.94"
Feed Grain: if
Yfg. = .09062s + .000491x
(50.42)** p  
R2 = .72 F = 2542.59+
Y.” = 205012 + .000715x it

(s.4s)" 9
R2 = .54 F = 41.99" 5

Carcass Beef:
Y,“ = 850828 + .00]097X

(2.2..59)** .

R2 = .75 F = 551.082!

Yb, = -.170010 + .0001s1x + 11
(.58)

R2 = s5 F = sss.s2"f

Yo. = cattle shipping cost in doll _
dredweight by truck, j
Ye, = cattle shipping cost in doll €_
dredweight by rail, g
Yfgt = feed grain shipping cost in p
hundredweight by truck, ”
Y,” = feed grain shipping cost inf
hundredweight by rail, A
YM = carcass beef shipping cost in;
hundredweight by truck, Q
Yb, = carcass beef shipping cost irffl
hundredweight by rail. 

37

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APPENDIX C
Optimum Solutions for Models 2, 3 and 4

TABLE 28.

MooEL 2

FEEDER CATTLE SUPPLIES, OPTIFIM

FEEDING LEvELs, owwonrumtv costs, SURPLUS FEEDER CATTLE, FEEDLOT cAPAcmEs AND SURPLUS FEEDLOT
GAPAGITY, 11v 111231011, 1968

  

   
  
   
  
  
  
   
  
  
  
   
   
   
  
  
   
   
  
  
  
  
  
  
   
  
  
  

   
  

 

FEE0ER 0117111011 FEEDING LEvELs 1_/
Smwmuc CATTLE
REGIONS SUPPLY 1 2 3 1 5 6 7 g 9 , 19 11
!§A2__

(1) HASHHOREG. 891,000 §§_,_3_1_3 1.78 2.80 3.115 3.99 5.82 6.98 11.39 5.90 9.211 1.33

(2) 1b11T.,lDA11o,HYO. 2,129,000 3.15 5.30 .68 5.21 1.02 3.50 11.60 8.88 3.52 6.86 2.08

(3) UTA11,NEv. 178,000 3.611 0 0 2.69 1.00 1.13 2.31 6.58 1.60 11.11 .10

11) CALIF. 875,000 1.68 11.71 3.10 6__2[1_,_5L0_0_ QSLE 2.01 11.35 8.90 5.85 6.86 11.91

(5) ARIZ. 219,000 10.83 9.20 7.38 6.12 Zfifi 3.115 5.71 9.110 7.09,} 8.06 6.78

(s) 11.11511. 152,000 11.22 7.50 6.20 s.“ 2.07 33,00 2.33 7.30 2.27:" 5.35 3.31

(7) H.TEx. 1,119,000 10.80 7.01 5.79 7.30 2.75 .69 1,119,000 5.00 .13 3.15 2.87

(8) E.TEX. 2,391,000 8.09 11.72 3.95 5.37 .75 .32 i 1,137,711 .31 1.06 1.511

(9) H.01<LA. 111,000 11.98 7.85 6.71 10.811 6.05 1.80 1.111 7.03 11l,§0_0 2.90 2.92
(10) E.01<LA. 1,128,000 10.05 6.51 5.38 7.10 2.72 1.58 1.17 3.93 gfi £34060 2.72
(11) COLO- 790,000 9.11 5.33 3.95 8.93 11.67 1.93 3.19 7.76 1.85 5.39 QQQQ
(12) KAN. 11,139,000 11.30 6.67 6.39 9.61 1.92 3.211 3.21 6.311 1.12 2.30 2.81
(13) NEBR. 1,552,000 11.00 6.15 5.98 10.36 5.80 11.17 11.116 7.53 2.98 1.110 2.88
(11) N.0.,S.D. 2,213,000 8.311 3.22 11.82 10.75 7.95 6.16 11.25 7.22 2.79 5.59 11.59
(15) MINN.,HIS. 1,602,000 10.68 5.82 7.32 11.63 7.19 5.51 5.52 8.19 1.11 5.38 1.30
(16) 1011A 1,057,000 13.811 8.51 8.66 13.09 8.18 6.31 6.211 8.95 11.78 5.99 5.116
(17) ILL. 559,000 111.96 9.66 9.51 13.66 8.59 6.53 6.33 8.01 11.86 5.69 6.06
(18) MlcM.,1N0.,011|o 775,000 13.79 8.82 9.23 13.16 8.31 6.59 6.51 8.06 5.16 6.111 6.07
(19) M0. 1,191,000 12.79 8.16 7.89 10.99 6.23 3.88 3.76 6.00 2.50 3.37 3.611
(20) ARK.,LA. 1,053,000 8.82 5.81 11.23 6.01 1.12 .116 7_2541_9_5 .71 .20 .58 1.56
(21) M|ss.,ALA.,GA. 1,957,000 9.116 5.117 5.26 7.53 2.65 1.911 1.52 2.118 1.23 1.76 2.39
(22) FLA. 375,000 15.02 10.19 9.93 12.111 7.00 5.117 11.611 11.89 11.78 5.12 6.69
(23) N.C.,S.C. 355,000 13.711 8.87 8.91 11.81 6.39 5.39 11.60 5.25 11.38 11.58 5.70
(211) KY.,TENN. 1,313,000 11.90 ‘ 7.18 7.58 10.70 1.88 3.55 2.80 3.80 2.39 2.611 3.73
(25) H.VA.,VA.,1“b.,DEL. 158,000 15.113 10.13 10.35 111.61 8.60 7.211 7.91 7.00 5.611 6.22 7.01
(26) PA. 0 18.211 12.56 10.76 17.60 12.33 10.05 9.68 10.63 8.19 8.95 9.39
(27) NORTHEAST O 18.91 13.51 111.119 18.90 13.85 11.81 11.61 12.911 10.11 11.05 11.13

TOTAL 27,188,000 665,313 0 0 6211 ,500 199,500 192,000 2, 830,151 1,137, 7111 125,015 333,060 790,0
FEEDLOT CAPACITY 878,137 1,327,911 305,622 1,137,761 1,209,510 607,178 2,830,151 1,137,711 125,015 333,060 1,926,156
SuRPLus FEEDLOT
CAPACITY 213,121 1,327,911 305,622 3,813,261 710,010 @3178 0 0 0 0 1,136,156

 

l/ UNDERSCORED NUMBERS ARE FEEDER CATTLE SHIPMENTS.
COSTS ARE SHOWN IN DOLLARS PER HEAD.

42

OTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FRGW NOT HAVING AN ACTIVITY IN THE OPTWAJM SOLUTION.

   

  

 

  
  
  
  
  
  
  
  
  
  
  
 
 
   
  
   
  

TAaLE 29. MooEL 2 0P1|m11 smPMEnrs OF AVAILABLE FEED GRAIN FOR cAnLE FEEDING, owvonruuurv 31111211111: costs, AND SURPLUS FEED 01171111, av 11:01 
DESTINATION f
Snwwmc .
REGIONS 1 2 3 1 5 6 7 8 9 10 11 12 13 
(1) HASHHUREG. LE .19 .118 .05 .55 .80 1.02 1.21 1.00 1.12 .80 1.09 1.02
(2) FbNT.,lDA110,HYO. 5L1 .13 .09 1A5 .25 .12 .63 .81 .57 .68 .36 .63 .55
(7) HJEx. .111 .51 .25 o Egg My g9_2,_11_1_3 .13 .05 .11 .15 .25 .31
(8) E.TEx. .68 .77 .53 .27 .25 .29 .21 QLS .31 .21 .13 .38 .116
(9) H.0KLA. .36 ‘.12 .21 0 .02 0 .02 .20 fl,111_3 .06 .06 .12 .18 4
(11) CoLo. .22 .27 .06 fl,@ .05 .06 .19 .38 .12 .25 .01 .22 .20
(12) K111. .33 .36 .19 .07 .05 .00 .10 .15 33g ggg .011 522E .02
(13) NEBR. .21 .26 .11 .08 .13 .12 .11 .21 .01 .07 Qfi 0 825E
(11) N.D.,S.D. .111 .12 .11 .10 .23 .211 .26 .33 .17 .19 .10 .12 .03
(15)Ml1111.,H|s. .27 .26 .26 .22 .29 .8 .31 .31 .22 .20 .17 .11 .08
(16) lowA .33 .31 .20 .16 .20 .19 .21 .19 .12 .08 .10 .05 Lg -
(17) ILL. .19 .118 .36 .27 .29 .28 .28 .22 .21 .15 .23 .111 .17
(18) 111011., luD.,011|0 .61 .60 .50 .111 .117 .116 .115 .37 .39 .32 .10 .33 .31
(19) Mo. .117 .119 .31 .21 .211 .23 .23 .19 .15 .09 .20 .09 .16
(21) M1ss.,ALA.,GA. .86 .88 .72 .50 .51 .52 .115 .26 .18 .36 .58 .19 .55
(23) N.C.,S.C. 1.08 1.08 .96 .78 .80 .80 .71 .55 .75 .61 .82 .72 .78
(25) H.VA.,VA.,I1b.,DEL. 1.07 1.06 .96 .81 .87 .86 .81 .65 .81 .71 .81 .75 .78
TOTAL 178,237 0 0 137,265 102,318 101,893 SQL113 199,115 99,503 63,581 223,096 622.88 976.38
1/ Uuozascoasn NUMBERS ARE SHIPMENTS (m TEN THOUSAND POUNDS). OTHER NUMBERS ARE OPPORTUNITY costs 11111011 assuu FROM not HAVING m ACTIVITY 1i

SOLUTION.

THESE COSTS ARE SHOHN IN DOLLARS PER HUNDREDHEIGHT.

  

SURPLUS

Tom. FEEDER
15 . 17 10 19 20 21 22 23 21 25 25 27 01110000 01m:
ELL H_E*_9__
5,29 0,55 0,75 9,55 12,11 12.57 15.51 11.79 12.73 11.01 13.30 11.29 555,313 220,507
2,05 5,15 5,51 5,55 10,39 9.53 12.27 11.53 9.55 11.30 00.12 7.95 0 2,129,000
2.11 1.30 1.05 5.25 7.20 0.17 10.57 10.32 0.91 10.22 7.52 7.53 0 170,000
5.55 0.39 9.00 0.71 9.01 11.35 13.17 13.73 12.15 111.70 13.52 11.93 075,000 0
7.55 9.13 10.01 9.79 10.35 11.71 13.02 13.92 12.111 111.113 11.21 12.51 219,000 0
11.92 5.71 7.30 5.15 0.20 9.53 11.211 11.02 10.011 12.13 11.55 9.05 192,000 o
3.11 5.11 5.75 1.03 5.97 7.37 9.00 9.63 7.09 11.29 9.99 0.35 1,119,000 0
.52 1.51 1.02 1.01 1.77 3.01 3.00 11.05 3.75 11.95 5.27 3.19 2,391,000 0
3.52 5.10 5.19 5.01 7.75 0.77 11.15 11.30 9.15 11.35 10.05 9.37 111,000 o
1.31 ' 2.79 3.31 2.57 1.10 5.20 7.05 7.33 5.59 7.17 7.20 5.119 1,120,000 0
3.15 3.53 5.15 5.21 0.19 9.27 12.35 11.09 9.5_0 11.09 11.03 9.17 790,000 0
1.75 3.51 1.33 2.91 5.75 7.21 9.12 9.55 7.37 9.35 0.07 7.32 ' 1,139,000 0
.93 11.19 1.70 1.03 7.01 0.23 10.57 10.110 0.12 10.01 9.30 7.71 1,552,000 0
173,213 2.59 2.79 3.01 7.35 7.21 10.15 9.02 5.02 0.75 7.57 5.51 2,213,000 0
1,502,000 3.11 3.00 3.79 7.00 7.53 9.05 9.12 7.11 0.39 7.59 5.12 1,502,000 0
1,057,000 3.112 11.51 3.53 0.09 0.51 11.00 10.55 0.11 10.02 9.30 7.73 1,057,000 0
1.39 52,09 1.91 1.59 7.00 5.70 9.30 0.51 5.09 0.17 7.52 5.29 559,000 0
2-20 1-02 215% 3-07 7-111 5.01 0.13 7.10 5.50 5.211 5.05 3.05 775,000 0
_._._1 351 "'12 ~26 2-3" 149L211 5-01 5.110 7.55 7.12 5.12 7.10 5.75 5.32 1,191,000 0
2_0§,9_55 .30 .59 .01 0 1.112 2.00 3.53 2. 27 3.03 1.10 2. 59 1,053,000 0
1_8g,§1_7 .36 1,170,006 .91 1.72 29;7,5_71 2.00 2.25 .11 2.51 2.95 1.37 1,957,000 0
0-111 0-‘111 2.911 ‘1-09 ‘1-03 2.91 @,_11_0 3.20 1.20 3.51 1.51 3.15 155,110 219,090
2.01 2-27 1-20 3-17 ‘1-25 2.32 2.55 0_5L9@ 3.03 .57 2.32 .09 05,900 250,100
~19 0721M EJ110499 ~97 2-70 .10 3.59 3.12 ggg 3.51 3.911 2.55 1,150,171 152,029
2-97 2-92 1-52 ‘1-11 5-99 11.01 11.05 1.53 1.50 111w @1313 0 357,510 90,350
‘1-00 ‘1-70 3-59 6-10 9-20 5.95 7.57 5.15 7.31 1.57 0 .95 0 0
6-90 7-00 5-17 0-55 11-72 9.50 9.99 0.01 \9.92 5.90 1.00 0 0 0
. .001 1.129.000 2.300.705 139.550 0  ,210 0 23,511,131 3,575,055

5,113,7001,129,000 2,310,705 1,001,553 33,000 297,577 155,110 05,900 175,301 01,1100 205,210 25,000 35,522,070

555,707 0 0 912,105 33,000 0 0 0 0 0 0 25,000 12,911,711
L SURPLUS
T0711. FEED
19 20 21 22 937 2'1 b’ 26 27 s11|1=1=£0 crum
1.22 1.10 1.31 1.10 1.31 1.33 1-37 1-30 1-‘11 121.000 0
.75 .75 .01 .93 .05 .05 ~97 ~96 ~91 199-702 °
.37 .10 .29 .31 .39 .30 ~50 ~55 ~91 795155“ °
.11 0 .10 .19 .20 .33 *2 ~52 ~‘° 1999115 °
.25 .11 .29 .30 .37 .35 ~"7 ~09 ~56 911553 0
.37 .33 .115 .51 .50 .10 ~56 ~57 ~09 901000 0
.00 .07 .10 .27 .22 .20 ~29 ~3° ~97 5951519 0
.13 .11 .22 .32 .25 .211 ~99 -” ~39 111151151 °
.22 .23 .31 .10 .30 .32 ~91 ~99 ~95 0 070-000
.11 .15 .19 .27 .15 .19 ~15 ~17 ~22 0 1.021.200
F0 _0,, m J8 J0 4,9 .13 .13 .10 1,375,397 509,251
i0 m 2&5 m, 1,, Elm .05 .05 .13 957,200 0
95a .19 .15 .07 .11 0 .07 0 £019.! ~05 105.111? 0
film 0 m, m, m, 4,6 .15 .17 .25 37,151 0
_3,, 4,5 o 59am 0 4,8 .15 .25 .33 110,071 0
.50 .35 .19 .11 @579 .29 ~07 ~20 ~27 19.579 0
.51 .15 .30 .20 .03 .35 221L191 ~05 ~11 22.1175 0
7 37,151 0 W055 10,071 19,579 10,071 Q41? 90,191 0 5,050,535 2,001,251

43

(DRESSED EQUIVALENT) FOR SLAUGHTER SHIPPING COSTS, SLAUGHTER CAPACITIES, AND SURPLUS SLAUGHTER OAPA 4

  

   
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 

TABLE 30. Mo05L 2 051000000 s0000>005001s 0F FED cA11L5
BY 00500000, 1968
80000050000 DESTINATION Q
005c0o00s 1 2 3 10 5 6 '1 8 9 10 11 12
(1) HASHHDREG. 10,331,190 1.610 1.66 1.28 2.77 3.85 10.21 10.39 10.03 10.210 3.07
(10) CALIF. .91 2.12 1.102 3,7810,1070 1.38 2.52 3.21 3.103 3.710 3.31 2.910
(5) ARIZ. 1.1010 2.19 1.38 .102 2,857,1100 1.62 2.32 1.20 2.88 2.39 2.22
(6) NJtx. .96 1.08 .1010 LQQ .06 1,923,1101 .73 1.10 .810 .98 .59
(7) 101.1501. .77 .88 .26 .110 .21 .18 11,389,7100 .36 .26  .101
(8) EJEx. 1.87 1.910 1.36 1.30 1.18 1.52 1.310 10,679,760 1.63 .98 1.52
(9) H.00<LA. .59 .70 .17 .66 .76 .28 .25 .65 1,363,180 fiflfl .19
(10) E.00<LA. 1.60 1.71 1.06 1.05 1.11 1.27 1.12 .85 .87 1,755,226 1.21
(11) COL0. .1010 .58 0 .68 .92 .85 1.22 1.36 1.01 1.18 5,372,000
(12) KAN. .97 .91 .59 .89 .98 1.13 1.18 .96 .73 .29 .63
(13) 105810. .810 .75 .106 1.010 1.19 1.36 1.109 1.26 1.23 .87 .65
(16) 1000A 1.56 1.39 1.19 1.73 1.81 1.95 2.00 1.68 1.75 1.310 1.37
(17) ILL. 2.32 2.22 1.95 2.36 2.1010 2.58 2.62 2.010 2.38 1.90 2.12
(18) 111000., 1N0.,000|0 2.59 2.107 2.33 2.79 2.87 3.01 3.010 2.103 2.81 2.35 2.50
(19) 1b. 2.18 2.11 1.79 2.06 2.110 2.10 2.11 1.67 1.90 1.39 1.65
(21) M|ss.,ALA.,GA. 2.97 2.93 2.60 2.76 2.66 2.96 2.82 1.95 2.87 2.20 2.68
(22) FLA. 10.30 10.18 3.86 3.89 3.86 10.03 3.85 2.88 10.01 3.39 3.98
(23) N.C.,S.C. 10.08 3.96 3.72 3.910 3.83 10.16 3.99 3.13 10.06 3.39 3.85
(210) KY.,TE0000. 3.010 2.96 2.83 3.09 2.89 3.13 2.99 2.21 3.00 2.310 2.80
(25) H.VA.,VA.,V0.,D5L. 10.23 10.010 3.85 10.38 10.16 10.102 10.65 3.102 10.19 3.610 3.99
(26) PA. 10.20 10.07 3.106 10.38 10.106 10.60 10.62 3.92 10.100 3.910 10.12
T01AL 10,331,190 0 0 10,700,169 2,857,100 1,923,101 11,389,700 10,679,760 (fijifll 2,635,000 5,372,000 10 1H1‘
SLAUGHTER CAPACITY 6,262,620 10,309,500 2,073,060 18,913,260 2,857,100 1,923,101 11,389,7100 10,679,760 1,363,180 2,635,000 11,655,200 10,782, 3
$25.00)’: lfit-AUGHTER 1,931 ,1030 10 , 309,500 2,073,060 110 , 213,091 0 0 0 0 0 0 6, 283, 200 0 
1/ U00o500sco0050 nunazns A005 s0000>005001s (100 POUNDS). 0100500 0000100500: A005 00050001000010 cos1a 00000000 RESULT FRUM 0001 HAVING AN I

ARE SHOWN IN DOLLARS PER HUNDREDHEIGHT.

ACTIVITY 000 1005 0001mm soLunol.

 

TABLE 31. mozL 2 0010mm SHIPMENTS FOR 0005ss50 FED e555 AND o0=0=o001uu|1v SHIPPING c0s1s, BY 00500000, 1968_
SHIPPING DESTINATIONH
00500000 1 1 3 10 5 6 7 8 9 10 T1
(1) HAsH.,0005c. 10,331,190 1.22 1.67 .82 2.16 2.68 3.38 3.27 3.37 3.61 2.80
(10) CALIF. .75 1.61 1.62 10,700,169 1.35 2.09 2.80 2.66 2.90 3.10 2.67
(5) A0002. .710 1.00 .85 1,867,280 @860 .96 1.62 1.102 1.76 1.97 1.61
(6) N.|1'£x. .52 .58 .103 1,1056,161 .22 £30 .76 .71 .90 1.12 .83
(7) H.TEx. .51 .55 103 8,157,330 .17 .05 1,319,200 §Z&,_2_20 .29 .102 .61
(8) E.TEx. 1.77 1.77 1.69 1.23 1.310 1.37 1.37 10,679,760 1.610 1.32 1.83
(9) H.00<LA. .100 .33 .33 1,209,680 .21 .09 .19 .17 iélfi .36 .35
(10) E.00<LA. .86 .78 .80 .102 .610 .53 .510 .07 .58 1,206,660 .86
(11) COL0. .06 922,130 926.1030 2L000J120 .29 .25 .710 .59 .58 .87 1,523,320
(12) KAN. .58 .106 .55 .103 .610 .53 .76 .30 .101 .310 .52
(13) NEBR. .35 .19 .33 .102 .69 .60 .86 .103 .66 .60 .38
(16) 1000A .96 .71 .910 1.02 1.26 1.16 1.100 .78 1.20 1.05 1.09
(17) ILL. 1.68 1.106 1.66 1.62 1.83 1.72 1.92 1.18 1.78 1.59 1.710
(18) M0c0-0.,l000.,0000o 2.02 1.78 2.05 2.08 2.29 2.19 2.35 1.58 2.210 2.02 2.19
(19111). 1.210 0 1.08 1.22 1.08 1.30 1.19 1.100 .72 1.25 1.00 1.28
(20) ARK.,LA. 1.86 1.79 1.78 1.35 1.109 1.106 1.108 .310 1.67 1.33 1.87
(22) FLA. 3.103 3.37 3.109 3.06 3.20 3.17 3.18 2.010 3.37 3.06 3.510
(23) N.C.,S.C. 3.15 3.00 3.18 2.93 3.12 3.010 3.10 2.08 3.16 2.85 3.210
(210) KY.,150000. 2.28 2.10 2.26 2.02 2.23 2.13 2.20 1.30 2.210 1.910 2.32
(26) PA. 3.19 3.01 3.09 3.22 3.106 3.36 3.51 2.65 3.101 3.19 3.100
To1AL 10,331,190 922,130 926,1030 19,390,700 989,860 066,980 1,319,200 5,287,980 153,500 1,206,660 1,523,320 1

1/ U00o500sco0050 00004005000» ARE s00|0>005001s (100 POUNDS). 0100500 00u0~1e500s A005 00000001000011: cos1s 00000000 RESULT 500000 0001 HAVING AN ACTIVITY 000 1005 0001mm soLu1| i‘

ARE SHOHN IN DOLLARS PER HUNDREDHEIGHT.

44

   
  
  
  
  
  
  
  
  
  
  
  
  
  

 

TOTAL

15 15 11 15 19 20 21 22 23 25 25 26 27 SHIPPED
3.15 3.59 3.57 2.33 3.51 3,95 3.75 3.90 3.53 3.59 3.63 3.25 3.10 5,331,190
3.39 3.39 3.15 3.16 3.33 3.05 3.15 3.12 3.02 3.17 3.51 3.06 3.06 3,785,570
2.60 2.51 2.26 2.23 2.55 1.97 2.07 2.13 1.95 2.01 2.23 2.18 2.18 2,857,150
1.18 1.09 .65 .85 .85 .72 .80 .75 .72 .69 .93 .76 .76 2,838,850
.68 .59 .33 .35 .31 1 757 939 .10 .01 1,527,121 1,888,525 .61 .23 .25 16,573,225
1.32 1.23 .72 .69 .85 1g5,gg1 .19 1,599,803 .10 .19 .33 .58 .56 6,383,585
.52 .33 .08 .10 .09 .20 .13 .16 .06 5§5,5§§ .15 0 0 2,707,537
.87 .76 .55 .59 .55 _33 .31 .37 .23 .19 .52 .37 .39 1,755,226
.73 .77 .65 .51 .55 .91 .78 .95 .67 .62 .76 .55 .51 5,372,000
.51 .35 .10 .11 555,555 .52 .22 .25 .13 .03 .15 .02 .01 15,155,067
.30 .13 .25 .20 .30 _59 .58 .51 .32 ‘ .21 .28 .12. .08 23,665,709
.17 31,106,650 .13 1 .22 .28 1.02 .60 .65 .37 .28 .32 .15 .10 31,106,650
1.15 1.01 10,103,652 .25 .59 1.17 .77 .80 .59 .37 .56 .33 .32 10,103,652
1.35 1.51 .65 15 773,355 1.23 1,55 .92 .90 .56 .60 .33 .28 .10 15,773,355
.93 .67 §Q5,§§§ .33 .02 .92 .53 .57 .33 .23 .37 .25 .28 905,338
1.93 1.92 1.21 .95 1.56 1.01 .10 .25 .10 1,511,555 .37 .50 .57 1,577,688
3.09 .3.08 2.35 2.05 2.61 2.07 1.35 551,551 .71 1.59 .91 1.15 1.20 997,357
2.87 2.95 2.19 1.75 2.52 2.21 1.35 .86 5§§,11§ 1.32 - .28 .72 .75 536,173
1.85 1.86 1.07 .89 1.52 1.29 .23 .65 .32 1,097,108 .52 .63 .69 1,097,108
2.82 2.95 2.21 1.67 2.61 2.51 1.67 1.11 .33 1.57 0 552,300 .37 552,938,
3.12 2.53 1.97 2.85 3.00 2.16 1.70 1.12 2.03 .35 2,126,763 .56 2,126,763.
, 1.. - 11 --- /1 , , .656 1,071,960 0 2,597,160 1,960,295 5,027,005 0 2,K9,701 0 159,090,000

120,095,065 01,106,650 11,007,990 17,107,525 10,000,200 1,071,960 5,025,700 2,655,955 1,960,295 5,000,510 2,770,710 6,502,900 6,000,500 206,967,052

A 895 865 0 0 2,515,970 9,715,555 0 5,825,700 58,785 0 355,606 2,770,718 3,913,279 6,800,50 87,877,352

TOTAL
16 17 18 19 20 21 22 23 25 25 26 27 SHIPPED
0.02 0.20 0.06 0.06 0.20 0.15 0.12 0.07 0.16 0.02 2.95 2.75 5,001,190
0.01 0.10 0.05 0.10 2.70 2.76 2.60 2.70 2. 00 2.05 2.91 2.79 5,700,169
2.20 1.96 1.91 2.00 1.59 1.57 1.57 1.62 1.69 1.72 1.00 1.07 2,057,150
1.06 1.11 1.07 1.15 .72 .70 .70 .00 .05 .07 .96 1.02 1,920,151
.09 .60 .52 .65 .00 .09 1,005,990 .15 .21 .20 .50 .57 11,009,750
1.65 1.20 1.12 1.05 .26 .55, .20 .50 .60 .65 .91 .97 5,679,760
.59 .06 .01 .50 .12 .09 .09 .11 .15 .17 .-20 .27 1,060,100
.66 .09 .01 .07 @5030 1,072,250 0 .02 .07 .09 .20 .26 2,605,000,
.71 .55 .59 .66 .55 .50 .59 .52 .56 .09 .52 .56 5,072,000
.27 .10 .15 8,079,170 -20 .00 .09 Egg .05 5,002,015 _ .00 .10 10,702,720
.00 .17 .05 .22 -35 .16 .17 .07 .11 0 0 25,710,290 27,559,500
2._16._._0 590. i _._J_‘1 705 516 i3 ~59 .25 .25 .10 .17 2,550,576 6,171,699 9,006,650 01,106,651
.01 11,007,990 .06 .70 .77 .00 .07 .20 .16 .16 .19 .25 11,007,990
1.02 .57 15,778,855 1-17 1-16 .60 .55 .25 .56 .09 .09 .11 15,770,055
.57 .21 .09 -01 -37 .09 .10 .01 505% 1_§,6_00 .05 .11 500,656
1.50 i, .90 .70 1.07 1,871,960 .02 .00 .10 .00 .00 .59 .66 1,071,960
2.92 952.23 1.89 2.53 1-76 1.15 2,597,160 .77 1.55 .91 1.25 1.27 2,597,160
2.55 1.86 1.37 2.21 1-68 .90 .55 1,960,295 1.09 .15 .60 .67 1,960,295
1.65 .83 .62 1-25 J15 2,572,750 .25 .10 2,555,055 .20 .55 .50 5,027,005
2.60 1.90 1.87 2-51 2-25 1.50 1.10 .00 1.56 .17 2,669,701 .27 2,669,701

2.160.590 11,051,610 19,578,070 0.079.170 2,228,050 0,655,000 0,902,150 2,956,670 2,000,000 7,706,270 0,051,500 05,516,900 159,090,000

45

46

TABLE 32 . moEL_3

FEEDER CATTLE SUPPLIES, OPTIMUM FEEDING LEVELS, OPPORTUNITY COSTS,

BY REGION, 1968

SURPLUS FEEDER CATTLE, FEEDLOT CAPACITIES AND SURPLUS

  

FEEDER OPTIMJM FEEDING LEVELS 1/
SHIPPING CATTLE
REGIONS SUPPLY 1 2 3 l, 5 5 7 8 9 10 11
115i
(1) HASHHUREG. 891,000 0 1.78 2.80 3.19 11.03 5.86 6.08 10.19 6.00 9.31 1.23
(2) 110111., lo1111o,wYo. 2,129,000 3.15 5.30 .68 5.25 11.06 3.51 3.70 7.98 3.62 6.96 1.98
(3) UTAH.,NEV. 178,000 3.611 0 3054632 2.73 1.011 1.17 1.111 5.68 1.70, 11.51 814$
(1) CALIF. 875,000 1.611 11.67 3.06 65500 225% 2.01 3.111 7.96 5119111, 6.92 1.80
(5) A1212. 219,000 10.79 9.16 7.31 6.12 53% 3.115 11.77 8.116 7.15 8.12 6.611
(6) N.MEx. 192,000 11.17 7.116 6.16 6.66 2.07 113000 1.39 6.36 2.33 5.111 3.17
(7) wJEx. 1,119,000 11.70 7.91 6.69 8.211 3.69 1.63 1,119,000 5.00 1.113 11.15 3.67
(8) E.TEX. 2,391,000 8.99 5.62 11.85 6.31 1.69 1.26 1,310,000 1,051,000 1.311 2.06 2.311
(9) w.01<LA. 111,000 11.88 7.75 6.61 10.78 5.99 1.71 .111 6.03 111_1,_00_0 2.90 2.72
(10) E.01<L11. 1,128,000 9.95 6.111 5.28 7.011 2.66 1.52 .17 2.93 @015 QQLO 2.52
(11) CoLo. 790,000 9.51 5.113 11.05 9.07 11.81 2.07 2.39 6.96 2.05 5.59 Q0J0_0Q
(12) Km. 1,139,000 11.20 6.57 6.29 9.55 11.86 3.18 2.211 5.31 1.12 2.30 2.61
(13) NEBR. 1,552,000 10.97 6.12 5.95 10.37 5.81 1.18 3.53 6.60 3.05 11.117 2.75
(11) N.D.,S.D. 2,213,000 9.21 11.12 5.72 11.69 8.89 7.10 1.25 7.22 3.79 6.59 5.39
(I5) M|NN.,IND.,0Hl0 1,602,000 11.58 6.72 8.22 12.57 8.13 6.115 5.52 8.19 5.111 6.38 5.10
(16) 101111 1,057,000 11.71 9.111 9.56 11.03 9.12 7.25 6.211 8.95 5.78 6.99 6.26
(17) ILL. 559,000 15.85 10.56 10.111 111.60 9.53 7.117 6.33 8.01 5.86 6.69 6.86
(18) M|c11., |~o.,011|o 775,000 111.69 9.72 10.13 111.10 9.28 7.53 6.51 8.06 6.16 7.11 6.87
(19) Mo. 1,191,000 13.69 9.06 8.79 11.93 7.17 11.82 3.76 6.00 3.50 1.37 1.1111
(20) ARK.,I.A. 1,053,000 9.72 6.71 5.13 6.95 2.06 1.110 15_9,_78_1 .71 1.20 1.58 2.36
(21) MISS.,ALA.,GA. 1,957,000 10.36 6.37 6.16 8.117 3.59 2.88 1.52 2.118 2.23 2.76 3.19
(22) FLA. 375,000 15.02 10.19 9.93 12.18 7.01 5.51 3.71 3.99 11.88 5.22 6.59
(23) N.C.,S.C. 355,000 13.711 8.87 8.91 11.85 6.113 5.113 3.70 11.35 11.118 11.68 5.60
(211) KY.,IENN. 1,313,000 12.80 8.08 8.118 11.61 5.82 11.119 2.80 3.80 3.39 3.61 11.53
(25) w.V/1.,VA.,1'o.,DEL. 158,000 15.13 10.13 10.35 111.65 8.611 7.28 7.01 6.10 5.711 6.32 6.91
(26) PA. 0 18.211 12.56 10.76 17.611 12.37 10.09 8.78 9.73 8.29 9.05 9.29
(27) NORTHEAST 0 18.91 13.51 111.119 18.91 13.89 11.85 10.71 12.01 10.21 11.15 11.03
T0111. Q3 88,000 0 0 305, 622 621,500 1199,500 192,000 2, 618, 781 1,051,000 1125,0115 333,060 8711, 29
FEenLor CAPACITY 878,137 1,327,911 305,622 1,137,761 1,209,510 607,178 2,830,151 1,137,711 125,015 333,060 1,926,156
Sugfigifigou" 878,137 1,327,911 0 3,813,261 710,010 115,178 181,670 383,711 0 0 1,052,161 1'

   
  
  
  
   
   
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  

 

  

  

1/ UNDERSCORED NUMBERS ARE FEEDER CATTLE SHIPMENTS.

COSTS ARE SHOWN IN DOLLARS PER HEAD.

 

OTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FROM NOT HAVING AN ACTIVITY IN THE OPTIMUM (W

SURPLUS

101711. FEEDER
16 17 10 19 20 21 22 20 20 25 26 27 s01PPE0 001105
H512 9552
5,39 7,75 7,56 5,65 11,31 11,67 15,511 111.79 11.83 10.81 13.38 11.29 0 890,000
1.96 0.56 0.61 5.65 9.09 0.73 12.27 11.53 0.76 11.30 10.12 7.96 0 2,129,000
1.21 3.00 3.96 0.35 6.30 7.27 10.67 10.32 0.01 10.22 7.62 7.53 309,917 00,003
5.62 7.05 0.10 7.00 0.90 10.01 13.03 13.69 11.52 10.70 13.00 11.09 075,000 0
6.72 0.09 9.07 0.05 9.01 10.77 13.70 13.00 11.50 10.39 10.20 12.07 209,000 0 5
3.90 5.77 6.36 5.52 7.26 0.59 11.20 11.70 9.10 12.00 11.52 9.01 092,000 0 1
3.01 5.10 5.75 0.03 5.97 7.37 9.90 10.53 7.09 12.19 10.09 9.26 1,109,000 0 5
- .62 1.61 1.02 1.01 1.77 3.01 0.70 5.75 3.76 5.06 6.17 0.39 2,390,000 0 1
2-52 ".10 5.19 1-00 6-76 7.77 11.06 11.20 0.16 11.26 10.75 9.27 011,000 0
.31 1.79 2.31 1.57 3.00 0.20 6.96 7.23 0.69 7.37 7.10 5.39 1,120,000 ' 0
2.36 M73 5.36 W11 7-69 5J1? 12-‘15 11.99 8.80 11.99 11.13 9.5? 790,000 0
.75 2.61 3.38 1.91 5-75 6.21 9.32 9.56 6.37 9.26 0.77 7.22 1,039,000 0
$912k 3-26 3.77 3-10 6.88 7.30 10-59 10.05 7.19 9.98 9.35 7.71 1,552,000 0 1‘
996,112 2.69 2.79 3-00 7.86 7.21 11.36 9.92 6.02 9.65 0.07 6.00 2.213,o00 0 1
,602,000 3.10 3.00 3.79 7.00 7.53 10.75 10,02 7,10 9,29 _ 0,09 6,32 1,602,000 0 §
31,057,000 3.02 0.51 3.63 0.09 0.50 11.90 11.05 0.10 10.92 10.20 0.63 1,057,000 0 ?
1 1.39 59m 1.91 1.69 7.00 6.70 10.20 9.91 9.09 9.07 0.92 7.19 999,000 0 1
2.28 1.82 1191999 8-B7 7.10 6.00 9-08 0.00 5.60 7.10 6.95 0.75 775,000 0 1
1091111 .26 2.30 1,001,663 5.61 5.00 0.56 0.32 5.12 0.00 7.65 6.22 1,091,000 0 ,“_ Q
999,119 .30 .59 .81 0 1.02 3.78 0.03 2.27 0.73 5.00 3.09 1,053,000 0 Z
‘ -151,116 .36 1,307,177 .91 1.72 191,611 2.90 3.16 .01 3.51 3.05 2.27 1,957,000 0
2-51 2-51 2-0" 3-19 3-*3 2-01 125.119 3.20 3.30 3.60 0.50 3.15 155,110 219,090
1.01 1.37 .30 2.27 3.35 1.02 2.56 06,200 9,10 ,67 9,02 .09 06,900 260,100
-19 §l999§§ 252.229 -97 2-78 -10 "-59 0.02 1161001 0.01 0.00 3.55 1,313,000 0 ,
2.07 2.02 .62 3.21 5.09 3.10 0.05 1,63 3,60 01,100 296,259 0 367,600 90,060 1
0.90 3.00 2.69 5.20 0.36 6.06 7.57 5,15 6,01 1,57 0 ,96 0 0 ,
6.00 6.10 0.27 7.65 10.02 0.70 9.99 0,00 9,02 5,90 0,00 0 0 0 f
,103,700 1,029,000 2,300,705 1,001,663 0 297,677 155,110 06.900 176,300 01,000 206,200 0 23,090,567 3,609,033 1

1 5,103,700 1,029,000 2,300,705 1,001,663 33,000 297,677 155,110 06,900 176,300 01,000 206,200 25,000 36,522,070

0 O 0 0 33,000 0 0 0 0 0 0 25,000 13,020,311

 

.17 , "J

47

111111.: 33. P0011 3 -: OPTIMUM SHIPMENTS or AVAILABLE FEED GRAIN F011 onus FEEDING, OPPORTUNITY sruwpmc costs, AND SURPLUS FEED 111111111, av 11201011, 1968 _

  

SHIPPING
REGIONS 1 2 3 11 5 6 7 8 9 10 11 12 13 111 15
(6) N.1'1~:x. .39 .51 .19 Qfl .02 .08 .22 .39 .25 .36 .25 .115 .51 .65
(7) HJEX. .39 .50 .19 0 jQ_2_,_311_8 §1,1;_1§ 151,390 .09 .05 .11 .16 .25 .31 .115
(8) E.TEx. .70 .80 .51 .31 .29 .33 .25 §§_,_1_9_Q .35 .25 .117 .112 .50 .611
(9) 111.01<1.A. .311 .111 .15 gégg .02 614178 .02 .16 0 .06 .06 .12 _ .18 .33
(10) E.01<1.A. .117 .53 .28 .11 .111 .12 .09 .07 .07 gLFI .20 .13  .22 .36
(11) 001.0. .20 .26 Qflq 0 .05 .06 .19 .311 .12 .25 .01 .22 .20 .32
(12) KAN. .31 .35 .13 .07 .09 .08 .10 .11 194L113 514E .011 @123 .02 .16
(13) NeeR. .22 .25 .05 .08 .13 .12 .111 .17 .011 .07 gLm 0 1_1_6_9_,11_g11_ .05
(111) N.0.,S.0. .16 .15 .12 .111 .27 .28 .30 .33 .21 .23 .111 .16 .07 _5l,@
(15) M11111.,1111s. .29 .29 .211 .26 .33 .33 .35 .31 .26 .211 .21 .18 .12 .02
(16) lowA .35 .311 .18 .20 .211 .23 .25 .19 .16 .12 .111 .09 .011 .12
(17) ILL. .51 .51 .311 .31 .33 .32 .32 .22 .25 .19 .27 .18 .21 .29
(18) M1c11.,l11o.,0111o .63 .63 .118 .118 .51 .50 .119 .37 .113 .36 .1111 .37 .35 .38
(19) 1'0. .119 .52 .32 .25 .28 .27 .27 .19 .19 .13 .211 .13 .20 .31
(22) F1.A. 1.26 1.29 1.08 .89 .88 .91 .83 .56 .90 .79 1.00 .91 .98 1.08
(23) N.C.,S.C. 1.10 1.11 .911 .82 .811 .811 .78 .55 .79 .68 .86 .76 .82 .88
(211) KY.,TENN. .82 .811 .65 .511 .56 .55 .50 .33 .51 .110 .57 .117 .53 .63
(25) 11.VA.,VA.,Mo.,0E1.. 1.09 1.09 .911 .88 .91 .90 .85 .65 .85 .75 .88 .79 .82 .85
1on1. 0 0 65,6118 137,265 102.3118 101,893 5511.390 1116.190 99,503 63,581 2116,901 11113,123 1169,1128 57.187

Des1111AT1 on 1/

    
 

1/

THESE COSTS ARE SHOWN IN DOLLARS PER HUNOREDHEIGHT.

48

Uunensconso uunasrzs ARE SHIPMENTS (m TEN THOUSAND POUNDS).

        
   
 

UTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FRCWI NOT HAVING AN ACTIVITY IN THE 1'

TABLE 311. P001213 OPTIMUM s1111>1~11z1ns 01- FED CATTLE (oasssso EQUIVALENT) FOR SLAUGHTER, OPPORTUNITY s1111>1>111c costs, SLAUGHTER CAPACITIES, A1105‘
CAPACITIES, BY 1212111011, 1968 r
SHIPPING DESTINATION 1/
REGIONS 1 7 3 11 5 6 7 8 9 10
(3) UTAH,NEV. 1,815,395 .19 .211 .18 1.10 1.72 2.17 2.211 2.09 2.15
(11) CALIF. .85 2.07 1.67 3,7811,1170 1.38 2.52 3.29 3.112 3.82 3.39
(5) ARIZ. 1.38 2.111 1.63 .112 2,857,180 1.62 2.110 1.21 2.96 2.117
(6) N.l1'£x. .90 1.03 .69 1 .06 1,923,1111 .81 1.09 .92 1.06
(7) 11.T1=.x. .63 .75 .113 .06 .13 .10 11,389,7110 .27 .26 .27
(8) E.TEX. 1.82 1.90 1.62 1.31 1.19 1.53 1.113 11,679,760 1.72 1.07
(9) 11.01<LA. .115 .57 .311 .58 .68 .20 .25 .56 1,363,180 87_9_,_7111_
(10) E.01<1.A. 1.116 1.58 1.23 .97 1.03 1.19 1.12 .76 .87 1,755,226
(11) 801.0. .38 .53 .25 .68 .92 .85 1.30 1.35 1.09 1.26
(12) KAN. .82 .77 .75 .80 .89 1.011 1.17 .86 .72 .28
(13) NEBR. I .68 .60 .61 .911 1.09 1.26 1.117 1.15 1.21 .85
(111) N.0.,S.0. .116 .311 .80 1.17 2.07 2.23 1.90 1.57 1.65 1.66
(15) M|N11.,H|s. .93 .81 1.27 1.61 1.78 1.92 2.05 1.611 1.80 1.110
(16) 1011A 1.22 1.06 1.16 1.115 1.53 1.67 1.80 1.39 1.55 1.111
(17) 11.1.. 2.11 2.02 2.05 2.21 2.29 2.113 2.55 1.88 2.31 1.83
I18) M1c11.,l11o.,0111o 2.110 2.29 2.55 2.66 2.711 2.88 2.99 2.29 2.76 2.30
(19110, 1.96 1.91 1.89 1.91 1.99 1.95 2.011 1.51 1.83 1.32
(21) MISS.,ALA.,GA. 2.83 2.80 2.77 2.68 2.58 2.88 2.82 1.86 2.87 2.20
(22) FLA. 11.17 11.06 11.011 3.82 3.79 3.96 3.86 2.80’ 11.02 3.110
(23) N.0.,S.0. 3.90 3.79 3.85 3.82 3.71 11.011 3.95 3.00 11.02 3.35
(211) KY.,IENN. 2.90 2.83 3.00 3.01 2.81 3.05 2.99 2.12 3.00 2.311
(25) 11.VA.,VA.,Mo.,DE1.. 11.03 3.85 3.96 11.211 11.02 11.28 11.59 3.27 11.13 3.58
(26) PA. 11.00 3.88 3.57 11.211 11.32 11.116 11.56 3.77 11.311 3.88
Tom. 1J815,395 0 0 11,700,169 2,857,110 1,923,1111 11,389,7110 11,679,760 1,363,180 2,635,000 5,9115.
SLAUGHTER I
CAPACITY 6,262,620 11,309,500 2,073,060 18,913,260 2,857,1110 1,923,1111 11,389,710 11,679,760 1,363,180 2,635,000 11,655,_

SURPLUS SLAUGHTER

CAPACITY 11,11117,225 11,309,500 2.073.060 111,213,091 0 0 0 0 0 0 5.709.

l/ UNDERSCORED NUMBERS ARE SHIPMENTS (I00 POUNDS). OTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FROM NOT HAVING AN ACTIVITY IN THE OPTI

THESE COSTS ARE SHOWN IN DOLLARS PER HUNOREDHEIGHT.

SURPLUS

20,890,865 31,106,600 11,007,990 17,187,025 10,303,200 1,871,960 5,820,700 2,605,905 1,963,290 5,383,010 2,770,718 6,582,980 6,800,030 236,967,302

20 2T 22 23 2'1 25 25 27 0111211550 05111111111
1' .55 .36 .50 .60 .63 .61 .73 .76 .70 00,600 0
.33 .06 .25 .30 .35 .30 .06 .52 .55 690,353 0
.11 0 .10 .19 .20 .33 .12 .52 .55 106,190 0
.22 .10 .25 .31 . .33 .32 .13 .01 .07 112,903 0
, .17 0 .10 .20 .23 1 .22 .31 .37 .00 12,351 0
 .33 .29 .01 .50 .06 .00 .52 .53 .51 65,600 0
f .01 .03 .10 .23 .10 .16 .25 .26 .20 593,056 0
1‘ .09 .10, .18 .28 .22 .20 .26 .25 ,25 716,335 000,275
i, .22 .23 .31 .00 .30 .32 .31 ~30 ~30 57,107 1,005,210
1 .11 .15 .19 .27 .16 .19 .10 -17 ~17 015,350 1,005,050
 11 .00 .06 .10 .10 .09 .13 n3 -13 1,017,062 302.792
0 .02 0 .09 .01 004m .06 -06 -00 910,220 0
.19 .15 .07 .10 0 .07 0 .9L1_9i 0 105,111? 0
017 0 .00 .10 .09 .06 .16 -17 -20 280.0117 0
.73 .10 .29 10,071 .21 .06 .31 J10 J19 100,071 0
.50 .35 .19 .11 9,53 .29 .07 -20 -22 19,579 0
.20 .11 sly .09 .02 .07 .13 ~22 -25 57,065 0
, .61 .05 .30 .20 .03 .36 22g; -05 -06 22,1175 0
51:17 0 57,065 00,071 193W 00,070 22,075 90,190 0 5,873,672 2,700,130
15 16 17 10 19 20 " 21 22 23 20 25 26 1 W 
1.90 1.09 1.60 1.59 1.95 1.00 1.01 1.92 1.60 1.75 1.70 1.00 1.60 1,015,395
3.77 3.67 3.29 3.29 3.06 3.13 3.23 3.19 3.10 3.25 3.55 3.20 3.00 3,700,070
2.90 2.79 2.01 2.01 2.50 2.05 2.15 2.20 2.07 2.09 2.37 2.32 2.52 2,057,100
1.56 1.37 .99 .99 0a ,80 .00 .01 .00 .77 1.07 .90 1.10 2,030,000
.90 .79 .10 .39 .36 1,071,960 .10 1,600,500 .00 50_5,621 1 .67 .29 .50 15,115,909
1.71 1.52 .00 .03 .90 .09 .20 .00 .23 .20 .00 .63 .91 0,679,760
.72 .53 .15 .15 .10 .20 .13 .15 .10 fig .20 .06 .26 2,707,537
1.17 .90 .52 .50 .09 .33 .31 .36 .27 .19 .00 .13 .65 1,755,226
1.11 1.05 .79 .71 .79 .99 .06 1.02 .79 .70 .90 .60 .05 5,905,209
.70 .53 .16 .15 .00 .01 .21 .22 .16 .02 .20 .07 .26 10,702,720
.50 .31 .30 .23 .33 .67 .06 .00 .30 .19 .32 .16 .32 11,377,377
.13 .60 .02 .20 .50 1.05 .60 .09 .03 .35 .06 .16 .21 1,376,726
9,969,062 .33 .30 .07 .55 .90 .57 .61 .29 .23 .21 105,036 .03 10,110,090
.27 31,106,600 0 .07 .13 .02 .10 .00 .21 .00 .10 3,760,203 .16 30,070,003
1.30 1.10 10,103,652 .22 .07 1.10 .70 .72 .06 .30 .05 .32 .51 10,103,652
1.60 1.66 .67 10,773,355 1.20 1.09 5 .07 .00 .15 .55 .30 .29 .31 10,773,355
1.16 .00 gfi .36 6,100,030 .05 .16 .09 .30 .16 .36 .21 .07 7,009,176
2.23 2.12 1.20 1.00 1.51 1.01 .10 .23 .11 1,577,600 .13 .56 .03 1,577,600
3.10 3.29 2.03 2.10 2.67 2.00 1.36 991,33 .76 1.50 .90 1.22 1.07 997,357
3.13 3.111; 1 2.22 1.76 2.53 2.17 1.31 .01 5_3§L17_0 1.20 .30 .70 .97 536,173
2.15 2.06 L‘ 1.10 .91 1.07 1.29 .23 .63 .36 1,097,100 .50 .69 .95 1,097,100
3.06 3.09 2.22 1.66 2.60 2.05 1.61 1.00 .31 1.51 0 513m .57 502,930
3.20 3.26 2.01 1.96 2.03 2.90 2.10 1.63 1.10 1.97 .35 2,126,763 .66 2,126,763
9,969,062 31,106,610 11,007,990 11,773,355 6,100,030 1,071,960 0 2,605,905 536,173 3,605,000 o 6,502,900 0 119,090,000

10,925,803 0 0 2,010,070 0,198,362 0 5,820,700 0 1,027,121 1,738,010 2,770,718 0 6,800,030 87,877,302

n

TABLE 35. Moon 3 UPTIMUM SHIPMENTS FOR DRESSED FED BEEF AND OPPORTUNITY SHIPPING costs, BY REGIONS, 1968
81111-111111; Desrmnnou 1/

REGION 1 2 3 11 5 6 7 8 9 10 . 11
(1) WASH.,UREG. 1,815,395 1.28 1.73 .88 2.22 2.711 3.1111 3.33 3.113 3.71 2.86
(11) CALIF. .69 1.61 1.62 11,700,169 1.35 2.09 2.80 2.66 2.90 3.111 2.67
(5) A1112. .68 1.00 .85 1,867,280 fiLw .96 1.62 1.12 1.76 2.01 1.61
(6) N.MEx. .16 .58 .113 1,156,161 .22 QLO .76 .71 .90 -,__ 1.16 .83
(7) w.TEx. .115 .55 .13 9,162,320 .17 .05 1,319,200 @320 .29 7'1 "11 .16 .61
(8) E.TEX. 1.71 1.77 1.69 1.23 1.311 1.37 1.37 11,679,760 1.611 1.36 1.83
(9) H.01<1.A. .31 .33 .33 1,209,680 .21 .09 .19 .17 155E .10 .35
(10) E.01<LA. .76 .711 .76 .38 .60 .119 .50 .03 .511 1,206,660 .82
(11) COLO. 2,515,795 281,531 926,130 695,130 .29 .25 .711 .59 .58 .91 1,523,320
(12) KAN. .39 .33 .112 .30 I .51 .110 .63 .17 .28 .25 .39
(13) NEBR. 1 .16 .06 .20 .29 .56 .117 .73 .30 .53 .51 .25
(111) N.0.,S.D. .16 fiLi .51 .60 1.05 .99 1.25 .82 1.05 1.10 .81
(15) M111111.,luo.,011|o .53 .36 .85 .91 1.27 1.17 1.113 .83 1.23 1.19 1.05
(16) (ONA .77 .58 .81 .89 1.13 1.03 1.27 .65 1.07 .96 .96
(17) 11.1.. 1.119 1.33 1.53 1.19 1.70 1.59 1.79 1.05 1.65 1.50 1.61
(18) M|c11.,l110.,011|0 1.83 1.65 1.92 1.95 2.16 2.06 2.22 1.115 2.11 1.93 2.06
(19) Mo. 1.05 .95 1.09 .95 1.17 1.06 1.27 .59 1.12 .91 1.15
(20) ARK.,LA. 1.76 1.75 1.711 1.31 1.115 1.112 1.1111 .30 1.63 1.33 1.83
(22) F1.A. 3.33 3.33 3.115 3.02 3.16 3.13 3.111 2.00 3.33 3.06 3.50
(23) N.C.,S.C. 2.96 2.87 3.05 2.80 2.99 2.91 2.97 1.95 3.03 2.76 3.11
(211) KY.,TENN. 2.11 2.02 2.18 1.911 2.15 2.05 2.12 1.22 2.16 1.90 2.211
(26) PA. 3.00 2.88 2.96 3.09 3.33 3.23 3.38 2.52 3.28 3.10 3.27

1on1. 1,331,190 922L130 926,130 19,390,710 989,860 166,980 1,319,200 5,287,980 153,500 1,206,660 1,523, -1

1/ UNDERSCORED NUMBERS ARE SHIPMENTS (100 POUNDS). 0111511 NUMBERS ARE OPPORTUNITY cosTs 11111011 RESULT FROM NOT HAVING AN ACTIVITY m THE oPTImH 

C0§TS ARE SHOWN IN DOLLARS PER HUNDREDHEIGHT.

50

TOTAL

16 1? 18 19 20 21 22 23 211 25 26 27 SHIPPED
3,51 3,52 3,25 3,55 3,33 3_29 3.22 3.26 3.35 3.21 3.15 2.93 1,815,395
3,uu 3,23 3,13 3,25 2,71 2,3u 2.72 2.91 2.96 2.98 3.05 2.92 5,700,169
2,33 2,39 2_3u 2_13 1_53 1_55 1.51 1.75 1.82 1.85 1.93 2.00 2,857,150
1,u9 1,2» 1,20 1,23 ,75 ,35 .75 .93 .98 1.00 1.09 1.15 1,923,151
1.02 .73 .65 .78 .07 .17 .05 .28 .35 .36 .53 .60 11,389,750
1.77 1.36 1.25 1.57 .30 .52 .27 .63 .81 .77 1.05 1.10 5,679,760

.72 .59 .55 .53 .16 .17 .13 .25 .28 .30 .33 .50 1,363,180

.75 .118 .50 .56 §fl+90 .05 1,072,250 .11 .16 .18 .29 .35 2,635,000

.85 .68 .62 .79 .59 .56 .53 .55 .59 .52 .55 .59 5,955,209

.27 .13 .15 3,079,170 .11 .03 £3,952 2,510,597 .05 _ 3,390,938 .03 .10 10,782,720

.08 .17 .05 .22 .25 .11 .08 .07 .11 0 0 10,377,897 11,377,877

.55 .53 .30 .76 .71 .56 .52 .51 .53 .26 .25 .25 1,376,726

.23 .25 .02 .58 .59 .35 .29 .16 .30 .01 2,258,520 2,058,552 9,969,062

2,168,590 5_3,i2_0 5,705,516 .23 .50 .19 .16~ .10 .17 1,098,525 0 23,090,591 31,106,651

.81 11,007,990 .06 .78 .68 .33 .28 .23 .16 .16 .19 .25 11,007,990
1.32 .57 15,773,355 1.17 1.07 .55 .55 .25 .56 .09 .09 .11 15,773,355

.57 .21 .09 .01 .28 .05 .01 .01 2,888,030 3,216,808 .05 .11 6,105,838
1.52 .99 .87 1.16 1,871,960 .06 .03 .27 .39 .112‘ .68 .75 1,871,960
3.01 2.32 1.98 2.62 1.76 1.19 2,655,955 .86 1.53 1.00 1.35 1.36 2,655,955
2.55 1.86 1.37 2.21 1.59 .88 .55 536,113 1.09 .15 .65 .67 536,173
1.70 .88 .67 1.29 .80 3,655,000 .21 .18 .05 .25 .59 .55 3,655,000
2.60 1.98 1.37 2.51 2.16 1.58 1.09 .80 1.56 .17 6,582,980 .27 6,582,980

L168,590 11,051,610 19,578,870 3,079,170 2,228,050 3,655,000 3,902,150 2,956,670 2,888,030 7,706,270 8,851,500 35,516,930 159,090,000

.1» , w?

52

 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
   
 
  
  
   
  
  
  
  
  

IABLE 36. ("ODEL II FEEDER CATTLE SUPPLIES, OPTINUM FEEDING LEVELS, OPPORTUNITY COSTS, SURPLUS FEEDER CATTLE, FEEDLOT CAPACITIES AND SURPLUS FEEOLOT

av REGION
‘ FEEDER OPTIMUM FEEDING LEVELS 1/
SHIPPING CATTLE "
REGIONS SUPPLY 1 2 3 H 5 6 2 8 9 10 11
11_Ew_

(1) HAsu.,0REc. 8911,000 ii! .21 2.12 3.81 11.35 5.211 6.60 11.01 5.52 8.86 2.66

(2) M0NT.,|0A110,1IYo. 2,129,000 3.115 5.30 0 5.57 11.38 2.92 11.22 8.50 3.111 6.118 .111

(3) UTA11,NEv. 1178,000 5.21 0 .89 11.62 2.93 2.12 3.53 7.77 2.79 5.60 flflfl

(11) CALIF. ‘ 875,000 11.32 2.78 2.06 Q5000 @1500 1.07 3.61 8.16 5.11 i 6.12 2.91

(5) ARIz. 219,000 10.117 7.27 6.311 6.12 @000 2.51 11.97 8.66 6:351; 7.32 11.75

(6) N.MEx. 592,000 11.79 6.51 6.10 7.60 3.01 000,000 2.53 7.50 2.57 5.55 2.22

(7) HJEx. 1,1119,000 11.18 5.82 5.119 8.011 3.119 .119 1,1119,000 5.00 .113 3.15 1.58

(8) E.TEx. 2,3911,000 8.117 3.53 3.65 6.11 1.119 .12 g2; 1,1137,71111 .311 1.06 .25

(9) W.0KLA. 511,000 12.36 6.66 6.11 11.58 6.79 1.60 1.1% 7.03 1110000 2.90 1.63
(10) E.0I<LA. 1,128,000 10.113 5.32 5.08 7.811 3.116 1.38 1.17 3.93 @010 @1400!) 1.113
(11) CoLo. 790,000 11.08 5.113 11.911 10.96 6.70 3.02 11.118 9.05 3.111 6.68 '79_0,0_00
(12) KAN. 1,539,000 11.68 5.58 6.09 10.35 5.66 3.0% 3.2% 6.35 1.12 2.30 1.52
(13) NEBR. 1,552,000 11.115 5.03 5.75 11.17 6.61 11.011 11.53 7.60 3.05 11.117 1.66
(111) N.D.,S.D. 2,213,000 8.79 2.10 11.59 11.56 8.76 6.03 11.32 7.29 2.86 5.66 3.37
(15) M11111.,H|s. 1,602,000 10.112 3.99 6.38 11.73 7.29 11.67 11.88 7.55 3.50 11.711 2.37
(16) IOWA 1,057,000 13.58 6.68 7.72 13.19 8.28 5.R7 5.60 8.31~ B.1N 5.35 3.51
(17) 11.1.. 559,000 111.96 8.09 8.83 111.02 8.95 5.95 5.95 7.63 11.118 5.31 11.39
(18) 1111011., l110.,011|o 775,000 13.53 6.99 8.29 13.26 8.1111 5.75 5.87 7.112 11.52 5.50 11.111
(19) 1'0. 1,691,000 12.53 6.33 6.95 11.09 6.33 3.011 3.12 5.36 1.86 2.73 1.71
(20) ARK.,LA. 1,053,000 9.20 11.62 3.93 6.75 1.86 .26 25,100 .71 .20 .58 .27
(21) MIss.,ALA.,GA. 1,957,000 9.20 3.611 11.32 7.63 2.75 1.10 .88 1.811 .59 1.12 .116
(22) FLA. 375,000 15.02 8.63 9.25 12.50 7.36 11.89 11.26 11.51 11.110 11.711 5.02
(23) N.C.,S.C. 355,000 13.711 7.30 8.23 12.17 6.75 11.81 11.22 11.87 11.00 11.20 11.03
(211) KY.,TE1IN. 1,313,000 11.90 5.61 6.90 11.06 5.211 2.97 2.112 3.112 2.01 2.26 2.06
(25) H.VA.,VA.,1'10.,0E|.. 1158,000 15.113 8.56 9.67 111.97 8.96 6.66 7.53 6.62 5.26 5.811 5.311
(26) PA. 0 18.211 10.99 10.08 17.96 l 12.69 9.117 9.30 10.25 7.81 8.57 7.72
(27) NORTHEAST 0 16.83 9.83 11.70 17.15 12.10 9.12 9.12 10.115 7.66 8.56 7.35

ToTAI. 27,188,000 665,313 0 0 6211 ,500 1199,500 1192,000 2, 803,151 1,1137,71111 1125,0115 333,060 1, 268,000

12210016111611»: 676,137 1,327,911 305,622 11,137,761 1,209,510 607,176 2,630,151 1,137,711 1125,0115 333,060 1,926,156 2,3,

SURPLUS FEEDLOT

CAPACITY 213,I21I I,327,9111 305,622 3,813,261 710,010 115,178 O 0 0 0 658.1156

l/ UNDERSCOREO NUMBERS ARE FEEDER CATTLE SHIPMENTS. OTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FROM NOT HAVING AN ACTIVITY IN THE OPTIMJH 8O
COSTS ARE SHOWN IN DOLLARS PER HEAD-

IABLE 37. MODEL 11 OPTIMUM SHIPMENTS OF AVAILABLE FEED GRAIN FOR CATTLE FEEDING, OPPORTUNITY SHIPPING COSTS, AND SURPLUS FEED GRAIN, BY REGICIII‘

DESTINATION 1/

SHIPPING
115010113 1 2 3 11 5 6 7 6 9 10 11 12 13 111
(1) WASH.,OREG. @000 .51 .112 .05 .55 .60 1.02 1.25 1.00 1.12 .60 1.09 1.02 .96
(21 I'l)NT.,IDAHO,WYO. 515g .15 .03 0 .25 .112 .63 .65 .57 .66 .36 .63 .55 .17
(11) 01.16. .113 .69 .61 @103 .112 .77 .99 1.22 1.02 1.12 .96 1.21 1.211 1.32
(7)11.Téx. .111 .53. .19 0 10_2,3_116 @3103 59335 .17 .05 .11 .16 .25 .31 .119
(6) E.1Ex. .611 .75 .113 .23 .21 .25 .17 Q§,_11_1_5 .27 .17 .39 .31 .112 .60
(9) 11.0101 .36 .1111 .15 gggg .02 0 .02 .211 11411113 .06 .06 .12 .16 .37
(12) Km. .33 .36 .13 .07 .09 .06 .10 .19 Log 133,501 .011 §2_2,§0_6 .02 .20
(13) NEBR. .211 .26 .05 .06 .13 .12 .111 .25 .011 .07 ggggg 0 @050 .09
(111) N.D.,S.D. .111 .111 .06 .10 .23 .211 .26 .37 .17 .19 .10 .12 .03 005E
(15) MINn.,H|s. .27 .26 .20 .22 .29 .29 .31 .35 .22 .20 .17 .111 .06 .02
(16) IOHA .33 .33 .111 .16 .20 .19 .21 .23 .12 .06 .10 .05 9541,3011 .12
(17) 11.1.. .115 .116 .26 .23 .25 .211 .211 .22 .17 .11 .19 .10 .13 .25
(18) MIcn.,111o.,0I-IIo .57 .56 .110 .110 .113 .12 .111 .37 .35 .26 .36 .5 .27 .311
(22) FLA. 1.20 1.211 1.00 .61 .60 .63 .75 .56 ._82 .71 .92 .63 .90 1.01 .
TOTAL 176,237 0 0 137,261 102.3116 101,693 592,113 199.1115 99,503 63,561 $6,063 622,606 1,310,151 30, 2 I

l/ UNDERSCORED NUMBERS ARE SHIPMENTS (IN TEN THOUSAND POUNDS). OTHER NUMBERS ARE OPPORTUNITY COSTS WHICH RESULT FRG4 NOT HAVING AN ACTIVITY IN
THESE COSTS ARE SHOWN IN DOLLARS PER HUNDREDWEICHT.

   
    

SURPLUS

TOTAL FEEDER
15 17 13 19 39 21 22 23 21 25 26 27 SHIPPED 001102
E&_ HELQ_
6.55 8.65 9.02 9.81 11.73 12.83 15.51 111.79 12.73 18.112 13.38 18.05 665,313 228,687
3.12 5.16 5.77 6.81 10.01 9.89 12.27 11.53 9.66 11.91 10.12 11.72 0 2,129,000
3.911 5.95 6.69 7.08 8.17 10.00 12.21 11.89 10.118 15.10 9.19 15.86 178,000 0
6.16 8.03 8.98 8.611 9.10 11.25 13.11 13.37 12.10 18.03 13.16 18.33 875,000 0
7.56 9.07 9.91 9.69 9.61 11.61 13.16 13.56 12.08 17.67 13.88 18.91 219,000 0
5.76 7.29 8.111 7.30 8.110 10.37 11.82 12.110 10.62 16.32 12.111 17.19 192,000 0
11.05 5.52 6.39 5.117 5.97 8.01 9.38 10.01 8.27 15.28 10.37 15.50 1,119,000 0
1. 26 1.99 2.116 2.115 1.77 3. 65 1. 26 5. 23 11. 11 8.95 5.65 10. 63 2,3911 ,000 0
1.16 5.78 6.83 5.68 7.76 9.11 11.51 11.76 9.51 15.35 11.23 16.51 111,000 0
1.95 3.17 3.95 3.21 1.110 5.92 7.1111 7.71 6.07 11.116 7.66 12.63 1,128,000 0
 5.09 7.20 8.09 7.111 9.78 11.20 111.02 13.55 11.27 17.17 12.70 17.90 790,000 0
' I 2.39 3.99 11.97 3.55 6.75 7.85 9.80 10.011 7.75 13.35 9.25 1 111.16 1,139,000 0
1.61 11.611 5.111 11.711 7.88 8.911 11.02 10.93 8.57 111.07 9.83 111.95 1,552,000 0
I .71 3.111 3.50 3.75 7.113 7.92 10.91 9.117 7.27 12.81 8.02 12.75 2,213,000 0
 602 000 2.00 3.00 3.79 7.16 7.53 9.59 0.06 6.00 11.711 7.33 11.92 1,602,000 0
’ 057m 3"‘ m, 3J3 m; M, mm 10.29 7.aa 13.37 9.01 11.23 1,057,000 0
' m; Lsglgqq 2.]? L95 M; w; 930 0.61 5.09 11.70 7.62 13.05 559,000 o
2_25 L56   3_37 55g Q91, 7.37 6.811 5.112 9.59 5.79 10.35 775,000 0
1555 95g LE 2_31, g 1,_97 53,9 7_1,g 7.16 11.86 10.53 6.119 11.82 1,191,000 0
 .51, $3 L23 13,5 Q 2mg 3_ 25 3.91 2.65 7.82 11.56 9.73 1.053,000 0
 .10 m _g1| L05 Q L71, 2.00 .15 5.96 2.69 7.87 1,957,000 0
1 3J7 3.51, 3_2Q M35 3_95 3J7 m 3.28 11.28 7.25 11.511 9.91 155,110 219,890
2.57 2. 27 1. 51 3.1a 3. a7 2. 50 2. 56 ° 3-03 '1- 2B 2- 32 7-65 0 055.000
_1,5 52% _25 L23 23,0 _35 3J9 3.12 LQQQ! 7.12 3.91 9.111 1,021,132 291,568
3.20 2.92 1.70 1.37 5.61 1.30 1.05 1-62 ‘1-50 9-61 0 6-76 0 150,000
5.10 1. 7a a. 05 6.111 0. aa 7. 22 7. 57 5- '15 7- 3'1 5-10 0 "I; 72 0 0
_ 5.05 11.97 3.32 6.70 9.2a 7.75 7.00 5-93 7-01 7-'10 2-69 11-65 0 0
112‘ . 29.00 1,107,665 0 0 0 155,110 - 0 176,301 0 0 0 23,505,055 3.602.115

113,788 1,129,088 2,318,7051,081,663 33,000 297,677 155,110 86,900 176,381 81,1100 286,2110 25,000 36,522,878

 

1105 0 1.161.011o1.001,66a 33,000 297.677 0 06,900 0 01.100 206,210 25.000 11,153,793
SURPLUS
1 .1 .. .. 71 .6 .2 .1 1312.5... SE51.
1.22 1.35 1.111 1.76 1.37 1.73 1.110 1.911 121,000 o
.79 .00 .97 1.27 .09 1.23 ~90 1-'1'1 56.1137 0
1.20 ’ 1.37 1.113 1.01 1.15 1.0a 1-59 2.15 99.2011 0
.11 .33 .30 .01 .12 .06 .60 1.17 796,651 0
0 .10 .19 .66 .33 .711 -52 1.09 199.1115 0
.10 .33 .12 .79 .110 .03 .52 1.09 129,100 0
.11 .22 .31 .61 .211 .65 -9'1 -90 6911,1119 0
.10 .26 .36 .60 .20 .66 J3 -87 1.115.151 0
.27 .35 .11 .72 .36 .67 .31 .00 30,702 010,090
.19 .23 .31__ 7 .50 .23 .51 .21 .75 0 1,121,200
.00 .12  1' .52 .13 .19 .17 .71 1,001,900 173,120
.02 0 .09 .39 115% .30 .06 .62 510,356 23,350
.15 .07 .111 .30 .07 .32 0 .51 227,200 o
.110 .29 59,03 .59 .16 .66 .110 1.03 110,071 0
- 0 10.071 0 10,0711 0 o 0 7.505.719 2,750,076

53

54

TABLE 36.

PlooEL 11

WTIMJM SHIPMENTS OF FED CATTLE (DRESSED EQUIVALENT) FOR SLAUGHTER, OPPORTUNITY SHIPPING COSTS, SLAUGHTER CAPACITIES, AND 8U 

CAPACITIES, BY REGION

  

s1111>1=1uc DESTINATION 1/

REGIONS 1 2 3 11 6 7 8 9 10 11
(1) HASHUOREG. 11,331,190 1.118 1.81 1.11 2.611 3.68 3.99 11.17 3.78 3.98 2.90
(11) CALIF. 1.08 2.12 1.73 3,7811,1170 1.111 2.52 3.16 3.38 3.65 3.22 2.911
(5) ARlz. 1.57 2.16 1.66 .39 2,857,1110 1.59 2.211 1.22 2.76 2.27 2.19
(6) N.MEX. 1.13 1.08 .75 9l5ji9 .09 1,923,1111 .68 1.05 .75 ._ .89 .59
(7) w.TEx. .99 .93 .62 .19 .29 .23 11,389,7110 .36 .22‘ p15 .23 .116
(8) E.TEx. 2.09 1.99 1.72 1.35 1.26 1.57 1.311 11,679,760 1.59 .911 1.57
(9) H.0KLA. .85 .79 .57 .75 .88 .37 .29 .69 1,363,180 8_79,_7_7_1_1 .28
(10) E.01<LA. 1.86 1.80 1.116 1.111 1.23 1.36 1.16 .89 .87 1,755,226 1.30
(11) COL0. .61 .58 .31 .68 .95 .85 1.17 1.31 .92 1.09 8,622,1100
(12) KAN. 1.21 .98 .97 .96 1.08 1.20 1.20 .98 .71 .27 .70
(13) NEBR. .98 .72 .711 1.01 1.19 1.33 1.111 1.18 1.11 .75 .62
(111) N.0.,S.0. 1.06 .76 1.23 1.811 2.117 2.60 2.111 1.90 1.85 1.86 1.811
(16) IowA 1.73 1.110 1.51 1.711 1.85 1.96 1.96 1.611 1.66 1.26 1.38
(17) ILL. 2.62 2.36 2.110 2.50 2.61 2.72 2.71 2.13 2.113 1.95 2.26
(18) M|c11.,l110.,0111o 2.86 2.57 2.711 2.89 3.00 3.11 3.09 2.118 2.82 2.36 2.60
(22) FLA. 11.66 11.18 11.17 3.89 3.89 . 11.03 3.80 2.83 3.92 3.30 3.98
(211) KY.,IENN. 3.26 3.01 3.19 3.111 2.97 3.18 2.99 2.21 2.96 2.30 2.85

10TAL 11,331,190 0 0 11,700,169 2,857,1110 1,923,1111 11,389,7110 11,679,760 1,363,180 2,635,000 8,622,11
SLAucRTER CAPACITY 6,262,620 11,309,500 2,073,060 18,913,260 2,857,1110 1,923,1111 11,389,71+0 11,679,760 1,363,180 2,635,000 11,655,200
SuRPLus SLAUGHTER

CAPACITY 1,931,130 11,309,500 2,073,060 111,213,091 0 0 0 0 0 0 3,032,800

1_/ UNDERSCORED NUMBERS ARE SHIPMENTS (100 POUNDS).
T11EsE costs ARE s11o1m m DOLLARS PER HUNDREDHEIGHT.

OTHER NUMBERS

ARE OPPORTUNITY COSTS WHICH RESULT FROM NOT HAVING AN ACTIVITY IN THE OPTIHM S v

TAaLE 39. MooEL 11 1 OPTImM SHIPMENTS FOR oREssEo FED BEEF AND OPPORTUNITY s11|1>1>|11c costs, av 1151:1011
SHIPPING DESTINATION 1/
REGIONS 1 2 3 11 5 6 7 8 9 10 11 I
(1) HASHHIREG. 11,331,190 1.05 1.50 .65 1.99 2.51 3.21 3.10 3.20 3.39 2.63 3.11
(11) CALIF. .92 1.61 1.62 11,700,169 1.35 2.09 2.80 2.66 2.90 3.05 2.67 3.06 I
(5) ARlz. .91 1.00 .85 1,867,280 9Q,§6_0 .96 1.62 1.112 1.76 1.92 1.61 1.92 I
(6) N.I"£x. .69 .58 .113 1,1156,161 .22 flQQ .76 .71 .90 1.07 .83 1.07 .
(7) H.TEX. .68 .55 .113 11,906,930 .17 .05 1,319,200 Q8420 .29 .37 .61 .59 ‘
(8) E.TEx. 1.911 1.77 1.69 1.23 1.311 1.37 1.37 11,679,760 1.611 1.27 1.83 1.50 I}
(9) H.01<LA. .57 .33 .33 1,209,680 .21 .09 .19 .17 15_3,@Q .31 .35 .1! 
(10) E.01<LA. 1.08 .83 .85 .117 .69 .58 .59 .12 .63 1,206,660 .91 .31
(11) COLO. .23 @139 flit’) 5,250,520 .29 .25 .711 .59 .58 .82 1,523,320 .58 .‘
1121 m. .32 .53 .s2 .50 .11 .so .33 .37 .13 .3s .59 1,113,159.,‘
(13) NEBR. .62 .29 .113 .52 .79 .70 .96 .53 .76 .65 .118 .07 ;
(111) N.0.',S.D. .76 ,37 .88 .97 1.112 1.36 1.62 1.19 1.112 1.38 1.18 1.02
(16) IOHA 1.23 .81 1.011 1.12 1.36 1.26 1.50 .88 1.30 1.10 1.19 .71 
(17) ILL. 1.95 1.56 1.76 1.72 1.93 1.82 2.02 1.28 1.88 1.611 1.811 1.38 I
(18) M1c11.,|11o.,011|o 2.29 1.88 2.15 2.18 2.39 2.29 2.115 1.68 2.311 2.07 2.29 1.90
(19) Pb. 1.118 1.15 1.8 1.15 1.37 1.26 1.117 .79 1.32 1.02 1.35 .65
(20) ARK.,LA. 2.06 1.82 1.81 1.38 1.52 1.119 1.51 .37 1.70 1.31 1.90 1.51 
(22) FLA. 3.60 3.37 3.119 3.06 3.20 3.17 3.18 2.011 3.37 3.01 3.511 3.10
1231 N.C.,S.C. 3.39 3.01 3.25 3.00 3.13 3.11 3.11 2.15 3.23 2.37 3.31 2.115 I’
(211) KY.,TE1111. 2.50 2.15 2.31 2.07 2.28 2.18 2.25 1.35 2.29 1.911 2.37 1.91 I
I26) PA. 3.115 3.11 3.19 3.32 3.56 3.116 3.61 2.75 3.51 3.211 3.50 3.07 
TOTAL 11,331,190 922,130 926,1130 19,390,7110 989,860 1166,980 1,319,200 5,287,980 153,500 1,206,660 1,523,320 1,718,1 '

1/ UNDERSCORED NUMBERS ARE SHIPMENTS (100 POUNDS).
costs ARE snouu m DOLLARS PER HUNDREDHEIGHT.

OTHER NUMBERS ARE OPPORTUNITY costs 11111c11 REsuLT FROM NOT HAVING AN ACTIVITY m THE OPTIHIQ?

 
   

TOTAL

15 16 17 18 19 20 21 22 20 21 25 26 27 snlPPso
3,95 3,1,3 3,17 3,05 3,57 3,73 3.52 3.73 3.31 3. 27 3. 20 2.99 3.16 11,331,190
3, 37 3, 33 3,00 3,05 3, 3g 3,00 3.10 3.12 2.97 3.12 3.19 2.97 3. 29 3, 7811 ,1170
3,1,5 3,1,7 3,09 3,15 3,35 1,59 1.99 2.10 1.87 1.93 1.98 2.06 2.38 2,857,100
1.06 1.00 .70 .76 .70 .67 .75 .71 .67 .61 .71 .67 .99 2,000,010
' .61 .60 .21 .29 .29 1_6_0,1§1 .10 .06 1,960,291 2,952,051 .11 .19 .52 16,170,225
1.25 1.27 .60 .61 .02 1,700,020 .19 .05 .10 .19 .16 .11 .01 6,000,500
.09 .11 .00 .09 .11 .21 .17 .25 .10 .01 .01 161,30 .02 2,707,507
.01 .06 .10 .10 .16 .07 .05 .16 .27 .20 .29 .07 .71 1,755,226
-61 -76 -50 -51— ~59 -06 .70 .95 .62 .57 .51. .15 .71 0,622,100
-36 ~00 -03 ~00 2.__.__567 Z35 ~11“ .21 .01 .15 .05 0 1,005,112 .01 15,155,067
-1‘5 ~09 -00 -07 -20 -61 .10 .10 .21 5 .10 .00 1,010,205, .20 01,762,605
0 ~69 -51 ~39 ~75 059 .92 1.19 .60 .59 .17 .00 .17 709,100
-05 _31.10__,_6 611.0 225E} ~13 Vi? -99 .56 .66 .00 .21 .11 .06 .01 02,010,970
1-16 1-1" _¢_1__1°1°3 65? ~20 5‘ 1-2‘ .06 .91 .50 .16 .00 .00 .69 10,100,652
1-33 1-50 ~61 _9__¢_7 "70 ‘111 1-31 ‘~59 .97 1.00 .51 .65 .21 .29 .10 7,170,111
2-97 3-07 2-21 1-9" Z5" 2-02 1.00 991097 .66 1.11 .69 1.06 1.10 997,057
1-70 1-90 ~90 11" 1-‘10 1-29 .20 .69 .02 1,097,109 .05 .59 .97 1,097,109
0 31,106,600 11,007,900 7.070.011 2.567.235 1,871,960 0 997,057 1,960,291 1,019,160 - 0 6,502,900 0 119,090,000

8 211,091,065 31,106,600 11,007,990 17,107,025 10,303,200 1,071,960 5,021,700 2,615,915 1,960,291 5,000,110 2,770,710 6,502,900 6,000,100 206,967,012

 

120,090,865 0 0 9,717,010 7,735,965 0 5,820,700 1,608,588 0 1,330,207 2,770,718 0 6,800,030 85,106,620

   
 

17 10 19 30 21 22 20 21 25 26 27 
3,95 3,79 3,13 3,03 3,93 3,95 2.83 2.90 2.78 2.68 2.07 0,331,190
0.00 2.95 0.06 2.67 2.71 2.60 2.71 2.70 2.70 2.01 2.69 1,700,169
1.06 1.01 1.90 1.16 1.52 1.17 1.55 1.61 1.65 1.70 1.77 2,057,110
1.01 .97 1.00 .69 .70 .70 .70 .00 .00 .06 .92 1,920,111
.50 .12 .50 1463,1597 .01 2,901,790 .00 .16 .16 .00 .07 11,009,710
1.10 1.02 1.27 0 .20 .09 .20 .10 .60 .57 .01 .07 1,679,760
.26 .21 .00 .09 .01 .09 .01 .10 .10 .10 .17 1,060,100
.01 .26 .05 .02 1,109,060 .05 309,990 .07 .07 .15 .21 2,605,000
.15 .09 .59 .52 .10 .19 .05 .11 .02 .02 .06 0,622,100
.10 .11 0,079,170 .21 .10 .16 71_1,g .06 5,109,005 113L959 .07 10,702,720
 ..17 .01 .25 .11 .21 .27 .10 .16 .00 0 26,119,120 27,119,100
.67 .11 .90 1.01 .00 .05 .50 .72 .10 .09 .00 709,100
1_0,g2g 12,000,159 .26 .56 .29 .35 .10 .22 .00 2,156,161 9,067,510 01,106,610
1 007 990 -06 -B1 -0'1 J13 -'+7 .26 .21 .19 .19 .21 11.0o7,990
i’ -57 1.91am 1-20 1-23 -65 -611 .20 .51 .12 .09 .11 7,170,111
=10 .06 .01 .11 .11 .17 .01 .02 2,567,205 .02 .00 2,567,205
.00 .71 1.00 511,153 1,291,507 .06 .11 .20 .29 .52 .59 1,071,960
2.13 1-79 a; 2,116 1-73 1-10 2,22 .70 1.09 .01 1.15 1.17 997,057
1.83 1.311 0" 2.21 1-72 -95 -61 1,960,291 1.11 .11 .61 .61 1,960,291
.78 .57 1.22 -86 1.161.133 -90 .11 2,000,000 .10 .09 .15 1,019,160
1.98 1,87 2-1111 2-32 1-58 1-20 .00 1.61 .20 6,502,900 .27 6,502,900

"11.051.610 19,078,370 3,079,170 2.228.050 3.505.000 3,902,150 2,906,670 2,888,00 7,706,270 8,801,000 35,516,930 109,090,000

55

Texas Agricultural Experiment Station

Texas A8cM University
College Station, Texas 77843

H. 0. Kunkel, Acting Director- Publication

wosncs mo 5’

U.S. DEPAR

AGHICUL