• TABLE OF CONTENTS
HIDE
 Title Page
 Table of Contents
 Overview
 The new technologies
 The changing character of the U.S....
 Economic impacts of emerging technologies...
 Economic impacts of emerging technologies...
 Agricultural research and extension...
 Appendix A: Summary analysis tables...
 Appendix B: Summary analysis tables...
 Reference
 Office of technology assessmen...






Group Title: Technology, public policy, and the changing structure of American agriculture : a special report for the 1985 Farm Bill.
Title: Technology, public policy, and the changing structure of American agriculture
CITATION PAGE IMAGE ZOOMABLE PAGE TEXT
Full Citation
STANDARD VIEW MARC VIEW
Permanent Link: http://ufdc.ufl.edu/UF00053865/00001
 Material Information
Title: Technology, public policy, and the changing structure of American agriculture a special report for the 1985 Farm Bill
Alternate Title: Special report for the 1985 Farm Bill
Physical Description: vii, 90 p. : ill. ; 26 cm.
Language: English
Creator: United States -- Congress. -- Office of Technology Assessment
Publisher: Congress of the United States, Office of Technology Assessment :
For sale by Supt. of Docs., U.S. G.P.O.
Place of Publication: Washington D.C
Publication Date: [1985]
 Subjects
Subject: Agriculture -- Economic aspects -- United States   ( lcsh )
Agriculture and state -- United States   ( lcsh )
Agricultural innovations -- United States   ( lcsh )
Genre: federal government publication   ( marcgt )
non-fiction   ( marcgt )
 Notes
General Note: "OTA-F-272."
General Note: "OTA reports."
Funding: Electronic resources created as part of a prototype UF Institutional Repository and Faculty Papers project by the University of Florida.
 Record Information
Bibliographic ID: UF00053865
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: oclc - 11881723
lccn - 85600518

Table of Contents
    Title Page
        Page i
    Table of Contents
        Page 1
        Page 2
    Overview
        Page 3
        Page 4
    The new technologies
        Page 7
        Survey of emerging technologies
            Page 7
            Biotechnology
                Page 8
                Page 9
            Information technology
                Page 10
                Page 11
        Impact of emerging technologies on production
            Page 12
            Projections of agricultural yield
                Page 13
            Projections of food production
                Page 14
                Page 15
                Page 16
    The changing character of the U.S. agricultural sector
        Page 19
        The present structure of agriculture
            Page 19
            Changes in farm size and numbers
                Page 20
            Changes in distribution of sales and income
                Page 20
            Changes in sources of income
                Page 21
            Changes in the structure of debt in the farm sector
                Page 22
        Defining structural change in agriculture
            Page 23
            The economic perspective
                Page 23
                Page 24
            Sociological perspective
                Page 25
        Causes of structural change
            Page 26
            Page 27
            Technological forces
                Page 26
            Economies of size
                Page 26
            Institutional forces
                Page 28
                Page 29
                Page 30
            Economic and political forces
                Page 31
        The dynamics of structural changes
            Page 31
            Page 32
    Economic impacts of emerging technologies and selected farm policies for various size crop farms
        Page 35
        The crop farms analyzed
            Page 36
            Corn-soybean farms in the corn belt
                Page 36
            Wheat farms in the southern plains
                Page 37
            General crop farms in the delta region of Mississippi
                Page 38
        Policy and technology scenarios
            Page 39
            Cotton farms in the Texas Southern High plains'
                Page 39
            Farm policy scenarios
                Page 40
                Page 41
                Page 42
                Page 43
                Page 44
            Tax policy scenarios
                Page 45
            Technology scenarios
                Page 46
            Implications for the 1985 farm bill
                Page 46
        Financial stress and new entrants scenarios
            Page 47
            Financial stress scenarios
                Page 47
            Interest subsidy
                Page 47
            Debt restructuring
                Page 47
            New entrants into farming scenarios
                Page 48
            Implications for the 1985 farm bill
                Page 49
    Economic impacts of emerging technologies and selected farm policies for various size dairy farms
        Page 53
        Background
            Page 53
            Page 54
        Technologies and practices
            Page 55
        Policy and technology scenarios
            Page 56
            Farm policy scenarios
                Page 57
                Page 58
            Tax policy scenarios
                Page 59
            Technology scenarios
                Page 60
        Financial stress scenarios
            Page 61
        Implications for the 1985 farm bil
            Page 61
    Agricultural research and extension policy
        Page 65
        Who profits from the technology change
            Page 66
        The effect of agricultural research and extension on farm structure
            Page 66
            Page 67
        Research, private sector, and extension roles
            Page 68
            Private sector involvment
                Page 69
            Research involvment
                Page 70
                Page 71
            Extension roles
                Page 72
                Page 73
        Implications for the 1985 farm bill
            Page 74
    Appendix A: Summary analysis tables for crop farms
        Page 77
        Page 78
        Page 79
        Page 80
        Page 81
        Page 82
        Page 83
    Appendix B: Summary analysis tables for dairy farms
        Page 84
        Page 85
        Page 86
    Reference
        Page 89
        Page 90
        Page 91
    Office of technology assessment
        Page 92
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Contents

Chapter Page
1. Overview .............................. ****...................... 3
2. The New Technologies ..............................***............ 7
Survey of Emerging Technologies ................... ...... ... .. .. 7
Biotechnology ............................................ ... 8
Information Technology ........................................... 10
Impact of Emerging Technologies on Production ............... ...... 12
Projections of Agricultural Yield ................................... 13
Projections of Food Production ..................................... 14
3. The Changing Character of the U.S. Agricultural Sector................. 19
The Present Structure of Agriculture ................................ 19
Changes in Farm Size and Numbers ........... ...................... 20
Changes in Distribution of Sales and Income ....................... 20
Changes in Sources of Income ................................ 21
Changes in the Structure of Debt in the Farm Sector .................. 22
Defining Structural Change in Agriculture .............................. 23
The Economic Perspective ...................................... 23
The Sociological Perspective ....................................... 25
Causes of Structural Change ........................................... 26
Technological Forces ............................................ 26
Institutional Forces ............................................ 28
Economic and Political Forces ..................................... 31
The Dynamics of Structural Change .................................. 31
4. Economic Impacts of Emerging Technologies and
Selected Farm Policies for Various Size Crop Farms .................... 35
The Crop Farms Analyzed ......................................... 36
Corn-Soybean Farms in the Corn Belt ............................. 36
Wheat Farms in the Southern Plains .............................. 37
General Crop Farms in the Delta Region of Mississippi ................ 38
Cotton Farms in the Texas Southern High Plains ...................... 39
Policy and Technology Scenarios.. .................................... 39
Farm Policy Scenarios .......................... .................. 40
Tax Policy Scenarios ............................................. 45
Technology Scenarios ............................................. 46
Implications for the 1985 Farm Bill ................................ 46
Financial Stress and New Entrants Scenarios ............................ 47
Financial Stress Scenarios ...................................... 47
New Entrants Into Farming Scenario ............................... 48
Implications for the 1985 Farm Bill ................................ 49
5. Economic Impacts of Emerging Technologies and
Selected Farm Policies for Various Size Dairy Farms ................... 53
Background ......................................................... 53
Technologies and Practices ............................................ 55
Policy and Technology Scenarios....................................... 56
Farm Policy Scenarios ............................................ 57
Tax Policy Scenarios .............................................. 59
Technology Scenarios .......................................... 60
Financial Stress Scenarios ..... ........... ....... ...... ... .......... 61
Implications for the 1985 Farm Bill........ ...... ....................... 61








Content -continued

Chapter Page
S 6. Agricultural Research and Extension Policy ............................. 65
Who Profits From Technology Change ................................. 66
The Effect of Agricultural Research and Extension on Farm Structure ...... 66
Research, Private Sector, and Extension Roles ........................... 68
Private Sector Involvement .................................... 69
Research Involvement ................................... ....... 70
Extension Roles ...... .................................... ....... 72
Implications for the 1985 Farm Bill ................................... 74
Appendix A.-Summary Analysis Tables for Crop Farms .................... 77
Appendix B.-Summary Analysis Tables for Dairy Farms .................... 84

References ............................................ .............. 89

Tables
Table No. Page
2-1. Emerging Agricultural Production Technology Areas .................... 7
2-2. Estimates of Crop Yields and Animal Production Efficiency .............. 14
2-3. Projection -of Major Crop Production ...................... ........... 15
3-1. Sales Classes of Farms .............................................. 20
3-2. Distribution of Farms, Percent of Cash Receipts, Percent of Farm Income,
and Farm and Off-Farm Income per Farm by Sales Class, 1982 ........... 21
3-3. The Distribution of Farms With High Debt-to-Asset Ratios, by Sales Class
for January 1984 .................................................. 22
3-4. Historical and Projected Percentages of Cropland Harvested by Farms
With Sales in Excess of $200,000 .................................... 24
4-1. Financial Characteristics of Three Representative Corn-Soybean Farms in
East Central Illinois ......................... .... ................ 36
4-2. Financial Characteristics of Three Representative Irrigated Corn Farms in
South Central Nebraska .............................................. 37
4-3. Financial Characteristics of Three Representative Wheat Farms by Size in
the Southern Plains ............................................. 38
4-4. Financial and Resource Characteristics for Three Representative General
Crops Farms in the Delta of Mississippi, 1983 .......................... 38
4-5. Financial Characteristics of Three Representative Cotton Farms by Size in
the Texas Southern High Plains ..................................... 39
5-1. Total Producers and Size Distribution of Herds Selling Milk to
Plants Regulated by Federal Milk Marketing Orders, May 1983 ........... 54
5-2. Representative Dairies by Region and Herd Size ........................ 55
5-3. Financial Characteristics Assumed for Eight Dairy Operations in
Four States ................................................. 56

Figures
Figure No. Page
3-1. Factors Influencing the Structure of Agriculture ........................ 27
5-1. How the Dairying Picture Has Changed ............................... 54





Chapter 1

Overview


I































I


Continuing, rapid advances in biotechnology
and information technology promise to revo-
lutionize agricultural production and to alter
dramatically the structure of the U.S. agricul-
tural sector. In the next 15 years, 1.5 of the esti-
mated 1.8 percent annual growth in produc-
tion needed to balance world agricultural
supply and demand must come from increases
in agricultural yields-yields that will be pos-
sible largely through the development and
adoption of emerging technologies. While it
seems clear that these technologies must be
used if this Nation is to compete in the inter-
national marketplace, it is also clear that the
potential impacts of adopting these technol-
ogies have important policy implications for
Congress as it begins debate on the reauthoriza-
tion of the 1981 farm bill.
One impact will be technology's role, under
the current policy environment, in creating a
surplus of certain commodities in the imme-
diate future. Overall, the agricultural commu-
nity is expected to experience unpredictable
fluctuations in the balance of agricultural
supply and demand. For certain commodities,
however-notably, dairy products-a substan-
tial potential for further U.S. surpluses exists.
The adoption of new technologies coupled with
current farm policy will exacerbate that prob-
lem. The implication for policymakers is the
need for a farm program that more easily
allows for adjustments in periods of shortages
and surpluses rather than remaining fixed.
Another impact of technology will be its con-
tinuing role in changing the structure of the
agricultural sector from a system dominated
by the moderate-size farm to one dominated by
large and very large industrialized farms.,
Technology has provided the technical means
for structural change: mechanization has made
it possible for farmers to operate larger farms,

'For purposes of this study we have defined a moderate-size
farm as having gross sales of $0o0,000 to $199,000; a large farm,
$200,000 to $499,000; and a very large farm, $500,000 and over.


and disease control has made it possible to use
large-scale confinement feeding. Public policy
has provided further incentives, such as price
supports and tax incentives, for farmers to ex-
pand operations.
The technologies a farmer now needs to re-
main competitive are costly and complex.
Farmers who lack the capital and expertise to
adopt new technology early enough to main-
tain a competitive edge must seek supplemen-
tary off-farm income, find some special niche
for their products, or give up farming alto-
gether. This last alternative has become a fa-
miliar picture for the moderate-size farm,
which is fast disappearing from the agricultural
scene. As it drops from the middle of the farm
spectrum, it leaves small and part-time farms
(whose owners earn their primary income
elsewhere) clustered at one end and the large
farms (whose owners can take advantage of
economies of scale) clustered at the other.
This trend has several implications for pub-
lic policy. First, if a decision is made to slow
the decline of the moderate-size farm, policy-
makers must provide ways for: 1) making new
technologies more available to these farms, and
2) providing training in the use of these tech-
nologies. Targeting income support to the oper-
ators of such farms would also be an effective
policy component, although even this measure
may not help dairy farmers in some regions.
Second, despite the apparent advantages of
operators of very large farms, such operators
may need a loan safety net to help them weather
price instabilities and the rigors of the world
marketplace. Unlike most of their moderate-
size counterparts, such farms can survive with-
out income supports.
Third, agricultural policy may have to in-
clude ways to help particular groups and re-
gions make the transition to different endeavors.
For example, programs to retrain agricultural
workers for jobs in other sectors of the econ-
omy may be necessary, or farm operators in






4 A Special Report for the 1985 Farm Bill


a region may need help changing to alterna-
tive kinds of farming. The Lake States region,
for instance, shows some comparative advan-
tages for switching from dairy production to
corn.
Finally, and perhaps most significantly, farm
programs must be considered in the context of
these strong technological, economic, and in-
stitutional forces. Farm programs can merely
speed up or slow down these forces of change
-they cannot reverse the trends.
While the forces influencing change in the
agricultural structure have been identified, they
have not primarily been studied in the overall
context of farm policy decisions. This report
attempts to do just that. It focuses on the fol-
lowing sections of the 1981 farm bill: Title I-


Dairy, Title III-Wheat, Title IV-Feed Grains,
Title V-Cotton, Title VI-Rice, Title VIII-
Soybeans, Title X-Grain Reserves, Title XI-
Payment Limitations, Title XIV-Research and
Extension, and Title XVI-Credit, Rural Devel-
opment, and Family Farms.
Chapters 2 and 3 of this report provide back-
ground information on technology and struc-
tural change and on the procedures followed
in the conduct of this study. The remainder of
the chapters present the results of OTA's anal-
ysis. The long-run impacts of technology, pub-
lic policy, and structural changes on rural com-
munities, the natural resource base, and the
environment will be addressed in detail in the
later full report from this study.





Chapter 2


The New Technologies


Technology has made U.S. agriculture one
of the most productive in the world. Some of
that technology has taken the form of new
products-chemicals to control pests, drugs to
control disease, or sensors and computers that
automatically measure moisture conditions
and irrigate the field. Other technology has
been embodied in new processes-such as the
ability to use a computer, to make better eco-
nomic decisions, or to apply the best combina-
tion of cultural practices. The emerging tech-


nologies encompass both products and processes,
and, like their predecessors, promise to reshape
the practice of agriculture.
This chapter provides a brief survey of the
emerging agricultural production technologies
that could have such an impact and analyzes
the effect of various technology development
and adoption environments on agricultural
food production over the next 15 years.


SURVEY OF EMERGING TECHNOLOGIES


Before the turn of the century, cattle ranchers
in Texas may be able to raise cattle as big as
elephants. California dairy farmers may be able
to control the sex of calves and to increase milk
production by more than 10 percent without
increasing feed intake. Major crops may be
genetically altered to resist pests and disease,
grow in salty soil and harsh climate, and pro-
vide their own fertilizer. And computers and


electronics will be used to increase manage-
ment efficiency. These are only a few of about
150 emerging technologies in the 28 technologi-
cal areas that have been identified and eval-
uated for this study (table 2-1). While it may
sound like science fiction, advances in biotech-
nology and information technology will make
these technologies a reality in the next 10 to
20 years.


Table 2-1.-Emerging Agricultural Production Technology Areas


Animal
Genetic engineering
Animal reproduction
Regulation of growth and development
Animal nutrition
Disease control
Pest control
Environment of animal behavior
Crop residues and animal wastes use
Monitoring and controlling
Communication and information
Telecommunication
Labor-saving technologies


Plant, soil, and water


Genetic engineering
Enhancement of photosynthetic efficiency
Plant growth regulators
Plant disease and nematode control
Management of insects and mites
Weed control
Biological nitrogen fixation
Chemical fertilizers
Water and soil-water-plant relations
Soil erosion, productivity, and tillage
Multiple cropping
Organic farming
Communication and information management
Monitoring and controlling
Telecommunications
Labor-saving technologies
Engine and fuels
Land management
Crop separation, cleaning, and processing


c-JfL :UTC C -llO-yAseset


I


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JuuRncE: urnce or Tecnnology Assessment.





Chapter 2


The New Technologies


Technology has made U.S. agriculture one
of the most productive in the world. Some of
that technology has taken the form of new
products-chemicals to control pests, drugs to
control disease, or sensors and computers that
automatically measure moisture conditions
and irrigate the field. Other technology has
been embodied in new processes-such as the
ability to use a computer, to make better eco-
nomic decisions, or to apply the best combina-
tion of cultural practices. The emerging tech-


nologies encompass both products and processes,
and, like their predecessors, promise to reshape
the practice of agriculture.
This chapter provides a brief survey of the
emerging agricultural production technologies
that could have such an impact and analyzes
the effect of various technology development
and adoption environments on agricultural
food production over the next 15 years.


SURVEY OF EMERGING TECHNOLOGIES


Before the turn of the century, cattle ranchers
in Texas may be able to raise cattle as big as
elephants. California dairy farmers may be able
to control the sex of calves and to increase milk
production by more than 10 percent without
increasing feed intake. Major crops may be
genetically altered to resist pests and disease,
grow in salty soil and harsh climate, and pro-
vide their own fertilizer. And computers and


electronics will be used to increase manage-
ment efficiency. These are only a few of about
150 emerging technologies in the 28 technologi-
cal areas that have been identified and eval-
uated for this study (table 2-1). While it may
sound like science fiction, advances in biotech-
nology and information technology will make
these technologies a reality in the next 10 to
20 years.


Table 2-1.-Emerging Agricultural Production Technology Areas


Animal
Genetic engineering
Animal reproduction
Regulation of growth and development
Animal nutrition
Disease control
Pest control
Environment of animal behavior
Crop residues and animal wastes use
Monitoring and controlling
Communication and information
Telecommunication
Labor-saving technologies


Plant, soil, and water


Genetic engineering
Enhancement of photosynthetic efficiency
Plant growth regulators
Plant disease and nematode control
Management of insects and mites
Weed control
Biological nitrogen fixation
Chemical fertilizers
Water and soil-water-plant relations
Soil erosion, productivity, and tillage
Multiple cropping
Organic farming
Communication and information management
Monitoring and controlling
Telecommunications
Labor-saving technologies
Engine and fuels
Land management
Crop separation, cleaning, and processing


c-JfL :UTC C -llO-yAseset


I


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JuuRncE: urnce or Tecnnology Assessment.




-YrilT~r~-i~~i~--U-CU~-~LUT-~-` uri--il-l--r.--: .._i~(_~_~~_


8 A Special Report for the 1985 Farm Bill


iotclnology
Animal Agricultur
One of the major thrusts of genetic engineer-
ing in animals is the mass production in micro-
organisms of proteinaceous pharmaceuticals,'
including a number of hormones, enzymes, ac-
tivating factors, amino acids, and feed supple-
ments. Previously obtained only from animal
and human organs, these biologicals were ei-
ther unavailable in practical amounts or in
short supply and costly.
Some of these biologicals can be used for
detection, prevention, and treatment of infec-
tious and genetic diseases; some can be used
to increase production efficiency. One of the
applications of these new pharmaceuticals is
the injection of growth hormones into animals
to increase productivity. Several firms, in-
cluding Monsanto and Eli Lilly, are develop-
ing genetically engineered bovine growth hor-
mone to stimulate lactation in cows. In trials
at Cornell University, daily doses of recombi-
nant bovine growth hormone were adminis-
tered to dairy cows. The hormone, produced
naturally by a cow's pituitary gland, was syn-
thesized by Genentech for Monsanto. The
results showed that each cow treated with the
hormone increased milk production by at least
12 percent without increasing feed intake.
Commercial introduction of the new hormone
now awaits approval by the Food and Drug
Administration (FDA) (Bachrach, 1984; Hansel,
1984).
Another new technique arising from the con-
vergence of gene and embryo manipulations
promises to permit genes for new traits to be
inserted into the germ lines2 of livestock and
poultry, opening a new world of improvement
in animal health and productivity. Unlike
genetically engineered growth hormone, which
increases an animal's milk production or body
weight but does not affect future generations,
this technique will allow future animals to be
permanently endowed with traits of other ani-
mals and humans, and probably also of plants.

,Pharmaceuticals that are proteins.
sReproductive cells.


In this technique, genes for a desired trait, such
as disease resistance and growth, are injected
directly into either of the two pronuclei of a
fertilized ovum (egg). Upon fusion of the pro-
nuclei, the guest genes become a part of all of
the cells of the developing animal, and the traits
they determine are transmitted to succeeding
generations.
In 1983, scientists at the University of Penn-
sylvania and University of Washington suc-
cessfully inserted a human growth hormone
gene, a gene that produces growth hormone in
human beings, into the embryo of a mouse to
produce a supermouse that was more than
twice the size of a normal mouse (Palmiter,
1983). In another experiment, scientists at Ohio
University inserted rabbit genes into the em-
bryos of mice. The genetically engineered
mice, which were 2.5 times larger than normal,
ate as much as normal mice (Mintz, 1984).
Encouraged by the success of the super-
mouse experiments, USDA scientists at the
Beltsville Agricultural Research Center are
now conducting a new experiment to produce
super sheep and pigs by injecting human
growth hormone gene into the germ lines of
sheep and pigs (Russell, 1984). In this experi-
ment, USDA scientists provide Ralph Brinster
of the University of Pennsylvania with fer-
tilized eggs from sheep and pigs at their Belts-
ville farms. After injecting the eggs with the
human growth hormone genes, Brinster re-
turns the embryos to Beltsville to be inserted
into the surrogate mother animals.
The experiments of crossing the genetic
materials of different species in general and of
using the human growth hormone in particu-
lar have prompted lawsuits from two scientific
watchdog groups: the Foundation of Economic
Trends, headed by Jeremy Rifkin, and the
Humane Society of the United States. Both
charged that such experiments are a violation
of "the moral and ethical canons of civiliza-
tion," and they sought to halt the experiment.
The researchers argued that they are continu-
ing the experiment cautiously and countered
that the potential scientific and practical bene-
fits far outweigh the theoretical problems
raised by the critics.


S---; c~Lm,, _. -,., .~





Ch. 2-The New Technologies 9


I


The success of the mice experiments in-
dicates that analogous insertion into bovine
germ lines of additional bovine growth hor-
mone genes, or of growth hormone genes from
larger mammals such as sperm whales or
elephants, could yield larger productivity gains
than would somatic injectionss of growth hor-
mones. Moreover, the change in growth would
remain a permanently inheritable characteris-
tic. The expression "a whale of an animal"
would no longer be just a figure of speech.
Probably, however, the growth hormone gene
from any animal may be used (not just hor-
mones from very large animals) as long as
enough of that hormone is injected to do the
job.
Although some scientists may be too op-
timistic when they predict in 2 years the de-
velopment of a 10,000-pound cow and the
growth of a pig 12 ft long and 5 ft high (Mintz,
1984), these developments are certainly within
the realm of possibility in the next 10 to 20
years. However, some of these changes may or
may not be desirable due to economic, envi-
ronmental, anatomical, institutional, and ethi-
cal reasons.
Another technique, embryo transfer in cows,
involves artificially inseminating a super-
ovulated donor animal4 and removing the re-
sulting embryos nonsurgically for implantation
in and carrying to term by surrogate mothers.
Prior to implantation, the embryos can be
treated in a number of ways. They can be
sexed, split (generally to make twins), fused
with embryos of other animal species (to make
chimeric animals or to permit the heterologous
species to carry the embryo to term), or frozen
in liquid nitrogen. Freezing is of great practical
importance because it allows embryos to be
stored until the estrus of the intended recipi-
ent on the farm is in synchrony with that of
the donor. For gene insertions, the embryo
must be in the single-cell stage, having pro-
nuclei that can be injected with cloned foreign
genes. The genes likely to be inserted into cat-
'Injections into body cells rather than into reproductive cells.
'An animal that has been injected with a hormone to stimu-
late the production of more than the normal number of eggs per
ovulation.


38-857 0 85 3 : QL 3


tle may be those for growth hormones, prolac-
tins (lactation stimulator), digestive enzymes,
and interferons, thereby providing both growth
and enhanced resistance to diseases.
While less than 1 percent of U.S. cattle are
involved in embryo transfers, the obvious ben-
efits will push this percentage upward rapidly,
particularly as the costs of the procedure de-
crease (Brotman, 1983). One company, Genetic
Engineering Inc. (GEI), already markets frozen
cattle embryos domestically and abroad and
provides an embryo sexing service for cattle
breeders (Genetic Engineering News, 1983).
Patm Agrkwitw
The application of biotechnologies in plant
agriculture could modify crops so that they
would make more nutritious protein, resist in-
sects and disease, grow in harsh environments,
and provide their own nitrogen fertilizer. While
the immediate impacts of biotechnology will
be greater for animal agriculture, the long-term
impacts may be substantially greater for plant
agriculture. The potential applications of bio-
technology on plant agriculture include micro-
bial inoculums, plant propagation, and genetic
modification.
Microbial Inoculums.-Rhizobium seed in-
oculums are widely used to improve nitrogen
fixation by certain legumes. Extensive study of
the structure and regulation of the genes in-
volved in bacterial nitrogen fixation will likely
lead to the development of more efficient in-
oculums. Research on other plant colonizing
microbes has led to a much clearer understand-
ing of their role in plant nutrition, growth
stimulation, and disease prevention, and the
possibility exists for their modification and use
as seed inoculums.
Recently, Monsanto announced plans to
field-test genetically engineered soil bacteria
that produce naturally occurring insecticide ca-
pable of protecting plant roots against soil-
dwelling insects (Journal of Commerce, Dec.
12, 1984). The company developed a genetic
engineering technique that inserts into soil bac-
teria a gene from a micro-organism known as
Bacillus thuringiensis, which has been regis-


I





10 A Special Report for the 1985 Farm Bill


tered as an insecticide for more than two dec-
ades. Plant seeds can be coated with these bac-
teria before planting. As the plants from these
buds grow, the bacteria remain in the soil near
the plant roots, generating insecticide that pro-
tects the plants.
Plant Propagation.-Cell culture methods
for regeneration of intact plants from single
cells or tissue explants have been developed
and are used routinely for the propagation of
several vegetable, ornamental, and tree species
(Murashige, 1974; Vasil, et al., 1979). These
methods have been used to provide large num-
bers of genetically identical, disease-free plants
that often exhibit superior growth and more
uniformity over plants conventionally seed-
grown. Such technology holds promise for im-
portant forest species whose long sexual cycles
reduce the impact of traditional breeding ap-
proaches. Somatic embryos5 produced in large
quantities by cell culture methods can be en-
capsulated to create artificial seeds that may
enhance propagation of certain crop species.
Genetic Modification.-Three major bio-
technological approaches-cell culture selec-
tion, plant breeding, and genetic engineering-
are likely to have a major impact on the pro-
duction of new plant varieties. The targets of
crop improvement via biotechnology manipu-
lations are essentially the same as those of
traditional breeding approaches: increased
yield, improved qualitative traits, and reduced
labor and production costs. However, the
newer technology offers the potential to accel-
erate the rate and type of improvements be-
yond that possible by traditional breeding.
Of the various biotechnological methods that
are being used in crop improvement, plant
genetic engineering is the least established but
the most likely to have a major impact. Using
gene transfer techniques, it is possible to in-
troduce deoxyribonucleic acid (DNA) from one
plant into another plant, regardless of normal
species and sexual barriers. For example, it has
been possible to introduce storage protein
genes from French bean plants into tobacco
plants (Murai, et al., 1983) and to introduce
*Embryos reproduced asexually from body cells.


genes encoding photosynthetic proteins from
pea plants into petunia plants (Broglie, et al.,
1984).
Transformation technology also allows intro-
duction of DNA coding sequences from vir-
tually any source into plants, providing they
are engineered with the appropriate plant gene
regulatory signals. Several bacterial genes have
now been modified and shown to function in
plants (Fraley, et al., 1983; Herrera-Estrella, et
al., 1983). By eliminating sexual barriers to
gene transfer, genetic engineering will greatly
increase the genetic diversity of plants.

Information Technology
Animal Agriuture
The most significant changes in future live-
stock production due to information technol-
ogy will come from the integration of com-
puters and electronics into a modern livestock
production system that will make the farmer
a better manager.
Computers and electronic devices can be
used efficiently in animal feeding, reproduc-
tion, disease control, and environmental con-
trol. The first step toward efficient management
will be with electronic animal identification
(Muehling and Jones, 1983). Positive identifica-
tion of animals is necessary in all facets of man-
agement, including recordkeeping, individual-
ized feed control, genetic improvement, and
disease control. All animals could be identified
soon after birth with a device that would last
the life of the animal. The device would be
readable with accuracy and speed from 5 to 10
ft for animals in confinement and at much
greater distances for animals in feedlots or on
pasture. Research on identification systems for
animals has been in progress for some years,
especially for dairy cows. For example, an elec-
tronic device now used on dairy cows is a
transponder that is worn in the ear or on a neck
chain. A feed-dispensing device identifies the
animal by its transponder and feeds the ani-
mal for maximum efficiency, according to
stage of production. It also permits animals in
different stages of production to be penned to-
gether yet still be fed properly.





Ch. 2-The New Technologies 11


Feeding systems with sensing devices also
detect outdoor temperature so that animals can
be fed accordingly. Since the amount of feed-
energy an animal needs under various weather
situations and at each stage of growth is known,
the ability to sense weather information could
fine-tune diet preparation.
A rapid analysis of the feedstuff going into
the ration will be available at the farm. In for-
mulating a ration, it will be very helpful to get
an instant and accurate reading on the calcium,
phosphorus, and lysine contents of the ration
ingredients. This will permit a feedback con-
trol to adjust the mill and mixer automatically
to provide an optimum feed.
The largest potential use of electronic devices
in livestock production will be in the area of
reproduction and genetic improvement. An in-
expensive estrus detection device, for example,
would prove profitable in several ways:
Animals could be rebred faster after wean-
ing and increase the number of litters per
year.
Animals that did not breed could be culled
from the herd, saving on feeding and
breeding space.
Time would be saved because breeding
would be done faster.
Embryo transplants would be easier be-
cause of better estrus detection.
Another use of information technology is in
disease control and prevention (Osburn, 1984).
Computers and computer programs are being
used at many dairies and swine production
units and in the poultry industry. Herd record-
keeping systems for animal health are being de-
veloped and refined for various production
units. Examples of these programs now in
operation include FARMHX in Michigan and
similar systems in New York and California
(Mather, 1983). These recordkeeping systems
may be linked with animal identification sys-
tems, including radiotransmitters, as indicated
earlier. Examples of the types of information
that can be recorded for each animal include
production records, feed consumption, vacci-
nation profiles, breeding records, conception
dates, number of offspring, listing and dates


of diseases, and costs of medicants for treat-
ment or prevention of disease. A review of
printouts will allow the manager or veterinar-
ian to analyze quickly a health profile for each
animal. Bringing all of this information to-
gether will allow the veterinarian and manager
of the livestock enterprise to plan for more cost-
effective disease control programs and to des-
ignate the duties, such as vaccinations and
pregnancy examinations, that are to be carried
out. These programs are being applied and
refined on a few farms. By 1990 many of the
more progressive livestock producers will be
using these systems, and by 2000 these systems
will be widely applied to nearly all of the cost-
efficient livestock production units.
Environmental control of livestock facilities
is another area where electronic devices can
be used. Microprocessors will be used to alle-
viate odorous gases and airborne dust in ven-
tilation systems.

PMat Agrkslture
One of the applications of information tech-
nology in plant agriculture is in the manage-
ment of insects and mites (Kennedy, 1984). Im-
provements in the design and availability of
computer hardware and software will produce
tremendous changes in insect and mite man-
agement at all levels (research, extension, pest
management, personnel, and farmer). To be
implemented efficiently, as measured by its
contribution to crop profitability, insect and
mite management requires the processing of
voluminous quantities of information, includ-
ing: 1) condition and phenological stage of the
crop, 2) status of the various insect and mite
pests and their natural enemies present in the
crop, 3) production inputs into the crop, 4) in-
cidence of plant diseases and weed pests and
the measures used in their control, 5) weather
conditions, and 6) insect and mite management
options. Further, this information must be up-
dated and reviewed at regular intervals. Com-
puters can help superbly in the effective and
efficient processing of this information as well
as in the design, direction, and analysis of pest
management-related research.





12 A Special Report for the 1985 Farm Bill


The availability at the farm level of micro-
computers equipped with appropriate software
and having access to larger centralized data
bases will greatly speed the transfer of infor-
mation and facilitate pest management deci-
sionmaking. The advantages, simply in terms
of information storage and retrieval, will be
tremendous. The ready storage of and access
to current and historical information on pest
biology, incidence, and abundance; pesticide
use; cropping histories; weather; and the like
at the regional, farm, and even field level will
facilitate the selection of the appropriate man-
agement unit and the design and implementa-
tion of pest management strategies for that
unit.
Centralized, computer-based, data manage-
ment systems for crop, pest, and environmental
monitoring information have been developed
and are being evaluated for use on a regional
scale by a USDA/Animal and Plant Health In-
spection Service regional program. Such sys-
tems will provide rapid analysis, summariza-
tion and access to general crop summaries,
observer reports, pesticide and field manage-
ment information, reports of new or unknown
pests, general pest survey information, and
specified field locations with pest severities.
Other software systems designed to facilitate
directly the implementation of pest manage-
ment programs are in use and are continually
being improved. The Prediction Extension
Timing Estimator (PETE) model (Welch, et al.,
1978) is a generalized model for the prediction
of arthropod phenological events. PETE is suf-
ficiently flexible to be used for management in
many agricultural and nonagricultural systems.


For example, it is used as a part of the broader
biological monitoring scheduling system
(BIOSHED) developed in Michigan by Gage
and others (1982) for a large number of pests
on a wide variety of crops (Croft and Knight,
1983).
Experiences with these and other software
systems have demonstrated their great value
and identified areas where improvements are
needed. It has also pointed out that the data
base from which biological models are devel-
oped is limited. Since all biological models are
only as good as the biological information upon
which they are based, the continued develop-
ment and improvement of such models for use
in integrated pest management (IPM) is con-
tingent on continued high-quality research on
the appropriate aspects of plant and pest bi-
ology and ecology.
The advantages provided by computer soft-
ware are tremendous, in terms of improved
efficiency and accuracy with which pest man-
agement decisions can be made and imple-
mented. There is a great deal of effort currently
being devoted to the development of new soft-
ware and the improvement of existing soft-
ware. This, in conjunction with the rapid ad-
vances being made in computer hardware,
provides a powerful force that will lead to
dramatic changes in the implementation of
IPM and to increases in the level of sophis-
tication of IPM, where such increases are
desirable.
A detailed description of all technologies ex-
amined in this study will be presented in OTA's
full report later this year.


IMPACT OF EMERGING TECHNOLOGIES ON PRODUCTION


To help analyze the impact of emerging tech-
nologies on agricultural productivity, OTA
commissioned leading scientists in each of the
28 technology areas studied to prepare papers
on the state of the art. The papers were valu-
able resources for workshops conducted to
assess the impacts of emerging production


technologies. Participants in the workshops-
on animal and plant agriculture-provided data
on: 1) the timing of commercial introduction
of each technology area, 2) the number of years
needed to adopt the technology (by commod-
ity), and 3) yield increases (by commodity)
expected from the technology. Workshop par-





Ch. 2-The New Technologies 13


ticipants included physical and biological
scientists, engineers, commodity extension
specialists, economists, agribusiness represent-
atives, and experienced farmers.
U Since the impact of a new technology on agri-
culture at a given time depends in part on when
the technology is available for commercial in-
troduction, workshop participants were asked
Sto estimate the probable year of commercial in-
troduction of each technology under four alter-
native environments:
1. Baseline environment-assumes to 2000:
a) a real rate of growth in research and ex-
tension expenditures of 2 percent per year,
and b) the continuation of all other forces
that have shaped past development and
adoption of technology.
2. No-new-technology environment-assumes
that none of the technologies identified in
the study will be available for commercial
introduction by 2000.
3. Less-new-technology environment-as-
sumes to 2000: a) no real rate of growth
in research and extension expenditures,
and b) all other factors less favorable than
those of the baseline scenario.
4. More-new-technology environment-as-
sumes to 2000: a) a real rate of growth in
research and extension expenditures of 4
percent, and b) all other factors more fa-
vorable than those of the baseline scenario.
The year of commercial introduction ranged
from now-for genetically engineered pharma-
ceutical products; control of infectious disease
in animals; superovulation, embryo transfer,
and embryo manipulation of cows; and con-
trolling plant growth and development-to
2000 and beyond-for genetic engineering
techniques for farm animals and cereal crops.
Of the 57 potentially available animal technol-
ogies, it was estimated that 27 would be avail-
able for commercial introduction before 1990,
and the other 30 between 1990 and 2000, under
the baseline environment. In plant agriculture,
50 out of 90 technologies examined were pro-
jected to be available for commercial introduc-


tion by 1990, and the other 40 technologies be-
tween 1990 and 2000.
Historical trend lines of efficiency measure-
ments of crop and livestock production were
provided to the participants as a starting point
for their assessment of impact on productivity.
Through the Delphi process, participants col-
lectively projected the primary impacts of the
technologies on each of the nine commodities
for 1990 and 2000 under the different environ-
ments. Based on the information obtained from
the workshops on the year of commercial in-
troduction, the adoption profile, and the pri-
mary impacts, OTA computed crop yields and
production efficiencies for the nine commod-
ities for 1990 and 2000 (table 2-2).

Projections of Agricultural Yield
Under the baseline environment, major crop
yields are estimated to increase from now un-
til 2000 at a rate ranging from 0.8 percent per
year, for soybeans and cotton, to 1.3 percent
per year, for wheat. Wheat yield, for example,
is projected to increase from 35.6 bushels per
acre in 1982 to 44.8 bushels per acre in 2000
at the rate of 1.3 percent per year under the
baseline environment. However, under the no-
new-technology environment, wheat yield
would increase to 40.8 bushels per acre in 2000
at the rate of 0.8 percent a year. The difference
in wheat yield between the two environments,
4 bushels per acre, represents the impact of
new technologies.
Under the baseline environment, feed effi-
ciency in animal agriculture would increase at
a rate of from 0.4 percent per year for beef to
0.8 percent for poultry. In addition, the repro-
duction efficiency would also increase, at an
annual rate ranging from 0.5 percent, for beef
cattle, to 0.9 percent, for swine. Milk produc-
tion per cow per year would increase from
12,300 pounds (Ibs) to 17,563 Ibs per cow in the
period 1982-2000. Without new technologies,
milk'production per cow per year would in-
crease to only 13,700 lbs in 2000; under the






14 A Special Report for the 1985 Farm Bill


Table 2-2.-Estimates of Crop Yields and Animal Production Efficiency
No-new. More-new.
technology Baseline technology
environment environment environment
1982 1990 2000 1990 2000 1990 2000
Corn bu per acre 115 117 124 119 139 121 150
Cotton Ib per acre 481 502 511 514 554 518 571
Rice bu per acre 105 105 109 111 124 115 134
Soybean bu per acre 30 32 35 32 37 33 37
Wheat bu per acre 36 38 41 39 45 40 46
Beef
Pounds meat per Ib feed 0.070 0.071 0.066 0.072 0.072 0.072 0.073
Calves per cow 0.90 0.94 0.96 0.95 1.0 0.95 1.04
Dairy
Pounds milk per Ib feed 0.94 0.94 0.95 0.95 1.03 0.96 1.11
Milk per cow per year
(thousand Ib) 12.3 13.7 15.7 14.0 17.6 14.2 19.3
Poultry
Pounds meat per Ib feed 0.44 0.52 0.53 0.53 0.57 0.53 0.58
Eggs per layer per year 245 255 260 258 275 257 281
Swine
Pounds meat per Ib feed 0.165 0.167 0.17 0.17 0.176 0.17 0.18
Pigs per sow per year 14.4 14.8 15.7 15.2 17.4 15.5 17.8
aThe value shown for swine feed efficiency for 1982 is the average of national feed efficiencies for the 10 years prior to 1982.
The national aggregate linear trend of swine feed efficiency is slightly negative and gives a value of .157 In 1982.
SOURCE: Office of Technology Assessment.


more-new-technology environment, produc-
tion could reach 19,300 Ibs.

Projections of Food Production
The data obtained from the two technology
workshops were used in an econometric model
developed by the Center for Agricultural and
Rural Development at Iowa State University to
assess the collective impact of the 28 areas of
emerging technologies on the production of va-
rious crop and livestock products.
Table 2-3 shows projections to 2000 of in-
creased production for three major U.S. export
commodities (which comprise 60 percent of
U.S. agricultural food production exports).
Under the baseline environment, corn produc-
tion is projected to increase at the rate of 1.8
percent per year from 1981 to 2000. However,
without the new technologies examined in this
study, the rate of growth would be only 1.2 per-
cent. Under the more-new-technology environ-
ment, corn production would increase at a
much faster rate-2.2 percent per year.
About the same growth rates were obtained
for wheat production, which would increase


at 1.8 percent per year from 1981 to 2000 under
the baseline environment. Under the no-new-
technology environment, wheat production
would increase at only 1 percent per year.
A more drastic increase in soybean produc-
tion is projected from now until 2000 regard-
less of the environment considered. The annual
production of soybeans is projected to increase
under the baseline environment at an annual
rate of 2.8 percent from 1981 to 2000. Without
new technologies, the production is still ex-
pected to increase at 2.4 percent a year. Under
the more-new-technology environment, soy-
bean production would increase at 2.9 percent
per year.
In the world marketplace available informa-
tion points to a series of periodic surpluses and
deficits in agriculture over the next two dec-
ades (Mellor, 1983; Resources for the Future,
1983). A Resources for the Future (RFF) study
indicates that global balance between cereal
production and population will remain quite
close to 2000, indicating vulnerability to annual
shortfalls resulting from weather, wars, or
mistakes in policy. Over the next 20 years the
world will become even more dependent on






Ch. 2-The New Technologies 15


Table 2-3.-Projection of Major Crop Production
2000
No-new- More-new-
technology Baseline technology
Crop Unit 1981 environment environment environment
Corn
Production Million bushels 8,136 10,289.0 11,499.0 12,394.0
Growth rate Percent 1.2 1.8 2.2
Wheat
Production Million bushels 2,704 3,273.0 3,825.0 4,063.0
Growth rate Percent 1.0 1.8 2.2
Soybean
Production Million bushels 1,953 3,067.0 3,311.0 3,351.0
Growth rate Percent 2.4 2.8 2.9
SOURCE: Office of Technology Assessment.


trade. There will be increasing competition for
U.S. farmers in international markets. Much
of this increased competition will come from
developing countries selling farm commodities
as a source of exchange to pay for imports such
as oil. Despite this increased competition, ex-
ports of grain from North America are pro-
jected to nearly double by 2000.
On the other hand, there is another school
of thought that believes current studies such
as that by RFF have not properly assessed the
magnitude and impact of emerging technol-
ogies on farm'production. Technologies such
as genetic engineering and electronic informa-
tion technology that are available in various
forms could mean rapid increases in yields and
productivity. While such changes may improve
the competitive position of American agricul-
ture, they have the potential for creating sur-
pluses andmajor structural change-favoring,
for example, larger more industrialized farms.
Any conclusion regarding the balance of
global supply and demand requires many as-
sumptions regarding the quantity and quality
of resources available to agriculture in the
future. Land, water, and technology are likely
I to be the limiting factors as far as agriculture's
future productivity is concerned.
Agricultural land that does not require irriga-
tion is becoming an increasingly limited re-
source. In the next 20 years, out of a predicted
1.8 percent annual increase in production to
meet world demand, only 0.3 percent will come


from an increased quantity of land used in pro-
duction (RFF, 1983). The other 1.5 percent will
have to come from increases in yields-mainly
from new technology. Thus, to a very large ex-
tent, research that produces new technologies
will determine the future world supply-de-
mand balance and the amount of pressure
placed on the world's limited resources.
The OTA results indicate that with continu-
ous inflow of new technologies into the agri-
cultural production system, U.S. agriculture
will be able not only to meet domestic demand
but also to contribute significantly to meeting
world demand in the next 20 years. This does
not necessarily mean that the United States will
be competitive or have the economic incentive
to produce. It means only that the United States
will have the technology available to provide
the production increases needed to export for
the rest of this century.
Under the baseline environment, growth
rates in production, which include additional
land resources and new technology, will be
adequate to meet the 1.8 percent needed to bal-
ance world supply and demand in 2000. Under
the more-new-technology environment, pro-
duction could increase at 2.2 percent per year,
which would be more than enough to meet
world demand. This increased production
could, however, point to a future of surplus
production. On the other hand. under the less-
new-technology environment the production
of major crops in 2000 would drop to 1.6 per-






16 A Special Report for the 1985 Farm Bill


cent per year, a growth rate that would not be
able to meet the demand. Under the no-new-
technology environment, the annual rate of
production growth would be reduced further
to 1.1 percent. It should be noted that if the cur-


rent administration proposal to reduce the agri-
cultural research budget is accepted by Con-
gress, the rate of production growth would be
somewhere between 1.1 to 1.6 percent.





Chapter 3

The Changing Character of

the U.S. Agricultural Sector


Who will use a new technology is as impor-
tant a consideration as which technology will
be adopted, for the distribution of technology
has a considerable impact both on agricultural
production and on the structure of the agricul-
tural sector.
The emerging technologies examined for this
study will be introduced within a socioeco-
nomic structure that has undergone consider-


able change in the last 50 years and that pro-
mises to continue to change throughout the
remainder of this century. This chapter pro-
vides a perspective for analyzing technology's
distributional impacts on agricultural structure
by surveying the characteristics of that struc-
ture and noting the past and present factors
that define it.


THE PRESENT STRUCTURE OF AGRICULTURE


The heart of agriculture, the farm, is officially
defined as a place that produces and sells, or
normally would have sold, at least 1,000 dol-
lars' worth of agricultural products per year.
So defined, there were about 2.2 million farms
in 1982. Farms in that year had an average net
income from farming of $9,976 and an aver-
age off-farm income of $17,601, for a total of
$27,577.
Perhaps the best known characteristic of U.S.
agriculture is the trend toward larger but fewer
farms. Currently, about 1 billion acres of land
are in farms, resulting in an average farm size
of about 400 acres. However, this average size
has little meaning, since fewer than 25 percent
of all farms fall within the range of 180 to 500
acres. Almost 30 percent of all U.S. farms have
less than 50 acres, while 7 percent have more
than 1,000 acres.
The number of farms reached a peak of about
6.8 million in 1935 and is now approximately
2.2 million. The rate of decline has slowed
since the late 1960s, with a loss of about 100,000
farms since 1974.
Employment in farming began a pronounced
decline after World War II, when a major tech-
nological revolution occurred in agriculture.


The replacement of draft animals by the trac-
tor began in the 1930s and was virtually com-
plete by 1960, releasing about 20 percent of the
cropland, which had been used to grow feed
for draft animals.
The increased mechanization of farming per-
mitted the amount of land cultivated per farm
worker to increase fivefold from 1930 to 1980.
The amount of capital in nominal terms used
per worker increased more than 15 times in
this period. Total productivity (production per
unit of total inputs) more than doubled because
of the adoption of new technologies such as hy-
brid seeds and improved livestock feeding and
disease prevention. The use of both agricultural
chemicals and fuel also grew very rapidly in
the postwar period. Agricultural production
now relies heavily on the nonfarm sector for
machinery, fuel, fertilizer, and other chemicals.
These, not more land or labor, produced the
growth in farm production. The resultant
changes have also greatly increased the capi-
tal investment necessary to enter farming and
have generated new requirements for operat-
ing credit during the growing cycle.
One of the best ways to look at changes in
the economic structure of U.S. agriculture is


I


[I





Chapter 3

The Changing Character of

the U.S. Agricultural Sector


Who will use a new technology is as impor-
tant a consideration as which technology will
be adopted, for the distribution of technology
has a considerable impact both on agricultural
production and on the structure of the agricul-
tural sector.
The emerging technologies examined for this
study will be introduced within a socioeco-
nomic structure that has undergone consider-


able change in the last 50 years and that pro-
mises to continue to change throughout the
remainder of this century. This chapter pro-
vides a perspective for analyzing technology's
distributional impacts on agricultural structure
by surveying the characteristics of that struc-
ture and noting the past and present factors
that define it.


THE PRESENT STRUCTURE OF AGRICULTURE


The heart of agriculture, the farm, is officially
defined as a place that produces and sells, or
normally would have sold, at least 1,000 dol-
lars' worth of agricultural products per year.
So defined, there were about 2.2 million farms
in 1982. Farms in that year had an average net
income from farming of $9,976 and an aver-
age off-farm income of $17,601, for a total of
$27,577.
Perhaps the best known characteristic of U.S.
agriculture is the trend toward larger but fewer
farms. Currently, about 1 billion acres of land
are in farms, resulting in an average farm size
of about 400 acres. However, this average size
has little meaning, since fewer than 25 percent
of all farms fall within the range of 180 to 500
acres. Almost 30 percent of all U.S. farms have
less than 50 acres, while 7 percent have more
than 1,000 acres.
The number of farms reached a peak of about
6.8 million in 1935 and is now approximately
2.2 million. The rate of decline has slowed
since the late 1960s, with a loss of about 100,000
farms since 1974.
Employment in farming began a pronounced
decline after World War II, when a major tech-
nological revolution occurred in agriculture.


The replacement of draft animals by the trac-
tor began in the 1930s and was virtually com-
plete by 1960, releasing about 20 percent of the
cropland, which had been used to grow feed
for draft animals.
The increased mechanization of farming per-
mitted the amount of land cultivated per farm
worker to increase fivefold from 1930 to 1980.
The amount of capital in nominal terms used
per worker increased more than 15 times in
this period. Total productivity (production per
unit of total inputs) more than doubled because
of the adoption of new technologies such as hy-
brid seeds and improved livestock feeding and
disease prevention. The use of both agricultural
chemicals and fuel also grew very rapidly in
the postwar period. Agricultural production
now relies heavily on the nonfarm sector for
machinery, fuel, fertilizer, and other chemicals.
These, not more land or labor, produced the
growth in farm production. The resultant
changes have also greatly increased the capi-
tal investment necessary to enter farming and
have generated new requirements for operat-
ing credit during the growing cycle.
One of the best ways to look at changes in
the economic structure of U.S. agriculture is


I


[I





20 A Special Report for the 1985 Farm Bill


in terms of value of production as measured
by gross sales per year. Farms can be usefully
classified into the five categories of gross sales
shown in table 3-1.
Small farms generally do not provide a sig-
nificant source of income to their operators.
This class of farms is operated by people liv-
ing in poverty and by people who use the farm
as a source of recreation.
Part-time farms may produce significant net
income but in general are operated by people
who depend on off-farm employment for their
primary source of income.
Moderate-size commercial farms cover the
lower end of the range in which the farm is
large enough to be the primary source of in-
come for an individual or family. Most fami-
lies with farms in this range also rely on off-
farm income. In general, farms in this range
require labor and management from at least
one operator on more than a part-time basis.
Large and very large commercial farms in-
clude a diverse range of farms. The great ma-
jority of these are family owned and operated.
Most farms in these classes require one or
more full-time operators, and many depend on
hired labor on a full-time basis. Five percent
of these farms are owned by nonfamily cor-
porations, a much higher percentage than in
the other three classes. In general, the degree
of contracting and vertical integration is much
higher in these classes.

Table 3-1.-Sales Classes of Farms


Class
Small ......................
Part-time ..................
Moderate
commercial ..............
Large
commercial ..............
Very large
commercial ...............
SOURCE: Office of Technology Assessment.


Amount of gross
sales per year
Less than $20,000
$20,000 to $99,999
$100,000 to $199,000
$200,000 to $499,999
$500,000 and over


Changesn i arm Size and nMumbrs
Major changes in the structure of U.S. agri-
culture can be seen in the changes in the num-
ber of farms in these classes since the 1969
Census of Agriculture. Inflation in commodity
prices has tended to move large numbers of
farms from lower sales classes into higher sales
classes. Even after the number of farms is
redistributed to counteract these nominal
changes, the real number of small farms has
declined by about 22 percent-a dramatic de-
cline. (Recent reports that the number of small
farms has actually increased since 1978 refer
to farms that are small in acreage, not small
in sales.) The number of part-time farms has
also declined by about 18 percent. The num-
ber of moderate farms has increased substan-
tially, by about 39 percent, and the number of
large and very large commercial farms has in-
creased even more dramatically, by about 43
percent and 53 percent, respectively. Even
though the number of moderate farms has in-
creased, the loss of these farms in share of sales
and net income to large and very large farms,
as shown in the next section, more accurately
indicates the changing character of American
agriculture.

Changes in Distrbvwtion of
Sales and Income
Changes in the number of farms do not alone
give the whole picture. Changes in the distri-
bution of sales and income are more important
and clearly show the direction in which U.S.
agriculture is heading. In the sections that fol-
low, sales and income data presented reflect
redistributions calculated to adjust for the im-
pact of inflation.
Between 1969 and 1982, sales by small farms
declined from 9 to 6 percent. Sales from part-
time farms declined from 43 to 22 percent. The
market share of moderate farms increased from
13 percent of total sales to 19 percent. In the
same period the market share of large and very





20 A Special Report for the 1985 Farm Bill


in terms of value of production as measured
by gross sales per year. Farms can be usefully
classified into the five categories of gross sales
shown in table 3-1.
Small farms generally do not provide a sig-
nificant source of income to their operators.
This class of farms is operated by people liv-
ing in poverty and by people who use the farm
as a source of recreation.
Part-time farms may produce significant net
income but in general are operated by people
who depend on off-farm employment for their
primary source of income.
Moderate-size commercial farms cover the
lower end of the range in which the farm is
large enough to be the primary source of in-
come for an individual or family. Most fami-
lies with farms in this range also rely on off-
farm income. In general, farms in this range
require labor and management from at least
one operator on more than a part-time basis.
Large and very large commercial farms in-
clude a diverse range of farms. The great ma-
jority of these are family owned and operated.
Most farms in these classes require one or
more full-time operators, and many depend on
hired labor on a full-time basis. Five percent
of these farms are owned by nonfamily cor-
porations, a much higher percentage than in
the other three classes. In general, the degree
of contracting and vertical integration is much
higher in these classes.

Table 3-1.-Sales Classes of Farms


Class
Small ......................
Part-time ..................
Moderate
commercial ..............
Large
commercial ..............
Very large
commercial ...............
SOURCE: Office of Technology Assessment.


Amount of gross
sales per year
Less than $20,000
$20,000 to $99,999
$100,000 to $199,000
$200,000 to $499,999
$500,000 and over


Changesn i arm Size and nMumbrs
Major changes in the structure of U.S. agri-
culture can be seen in the changes in the num-
ber of farms in these classes since the 1969
Census of Agriculture. Inflation in commodity
prices has tended to move large numbers of
farms from lower sales classes into higher sales
classes. Even after the number of farms is
redistributed to counteract these nominal
changes, the real number of small farms has
declined by about 22 percent-a dramatic de-
cline. (Recent reports that the number of small
farms has actually increased since 1978 refer
to farms that are small in acreage, not small
in sales.) The number of part-time farms has
also declined by about 18 percent. The num-
ber of moderate farms has increased substan-
tially, by about 39 percent, and the number of
large and very large commercial farms has in-
creased even more dramatically, by about 43
percent and 53 percent, respectively. Even
though the number of moderate farms has in-
creased, the loss of these farms in share of sales
and net income to large and very large farms,
as shown in the next section, more accurately
indicates the changing character of American
agriculture.

Changes in Distrbvwtion of
Sales and Income
Changes in the number of farms do not alone
give the whole picture. Changes in the distri-
bution of sales and income are more important
and clearly show the direction in which U.S.
agriculture is heading. In the sections that fol-
low, sales and income data presented reflect
redistributions calculated to adjust for the im-
pact of inflation.
Between 1969 and 1982, sales by small farms
declined from 9 to 6 percent. Sales from part-
time farms declined from 43 to 22 percent. The
market share of moderate farms increased from
13 percent of total sales to 19 percent. In the
same period the market share of large and very






Ch. 3-The Changing Character of the U.S. Agricultural Sector 21


large farms increased greatly-from 36 to 57
percent.
The most telling changes of all have occurred
in the distribution of net farm income. The
large and very large farms have not only cap-
tured the majority of the market but also con-
trolled or reduced their cost of production. In
1974 these commercial farms had a 47-percent
market share and 35 percent of net farm in-
come after adjustment for inflation. In 1982,
just 8 years later, with their market share at 54
percent, these farms had 84 percent of net farm
income (table 3-2). Very large farms have been
responsible for the majority of this growth. This
class, which accounts for only 1.2 percent of
all farms, increased its real share of net farm
income fourfold-from 16 to 64 percent. By
comparison, small farms in 1982 had a nega-
tive net farm income, and part-time farms had
declined from 39 percent in 1974 to 5 percent
of total net farm income. Moderate farms have
seen a substantial decrease in net farm income,
from 21 percent in 1974 to 11 percent in 1982.
It is clear that if these trends continue, small
and part-time farms are likely to disappear, to
the extent that the operators of these farms de-
pend on them for income. The number of small
recreational, or "hobby," farms may increase.
Large and very large farms will completely
dominate agriculture. The number of moderate
farms may continue to increase, but they will
have a small share of the market and a declin-
ing share of net farm income.


Moderate farms comprise most of the farms
that depend on agriculture for the majority of
their income. Traditionally, the moderate farm
has been viewed as the backbone of American
agriculture. These farms appear to be failing
in their efforts to compete for their historical
share of farm income.

Cblages In SOrces of Inome
Employment and the sources of income of
U.S. farmers have changed greatly in the 20th
century. These changes occurred at a rapid rate
in the 1970s. The largest single source of
change was the tremendous increase in labor
productivity made possible by technological
changes, resulting in a sharp drop in the de-
mand for agricultural labor. During the 1930s
the disposable farm income per capital was less
than 40 percent of disposable nonfarm income.
This income differential resulted in the large
migration of the farm labor force out of agri-
culture and rural areas. This out-migration ac-
celerated after the Great Depression of the
1930s because employment and per capital in-
come opportunities increased considerably
outside of agriculture. In general, the marginal
productivity of labor was higher outside the
agricultural sector from the 1930s to the early
1970s. Therefore, migration of labor from
farming to the nonfarm sector contributed to
national economic growth.
In the 1970s, the average income differential
between farm and nonfarm households nar-


Table 3-2.-Distribution of Farms, Percent of Cash Receipts, Percent of Farm Income,
and Farm and Off-Farm Income per Farm by Sales Class, 1982
Sales Class------
Sales C s Percent of Percent of Average Average Average
Value of farm Number Percent of total cash net farm net farm off-farm total
products sold of farms all farms receipts income income income income
Less than $5,000 814,535 36.4 1.2 -2.0 ($550) $20,396 $19,846
Small ....... $5,000-$9,999 281,802 12.6 1.5 -0.9 (700) 22,498 21,798
10,000-$19,999 259,007 11.6 2.8 -0.9 (780) 18,648 17,868
Part-time .... $20,000-$39,999 248,825 11.1 5.4 0.2 154 14,134 14,288
$40,000-$99,999 332,751 14.9 16.4 5.2 3,451 12,529 15,980
Moderate .... $100,000-1S99,999 180,689 8.1 19.1 14.6 17,810 11,428 29,238
Large....... S200,000-$499,999 93,891 4.2 21.0 20.4 48,095 12,834 60,929
Very Large ...$500,000 and over 27,800 1.2 32.5 63.5 504,832 24,317 529,149
All farms 2,239,300 100.0 100.0 100.0 $9,976 $17,601 $27,578
SOURCES. Adapted from Economic indicators ot the Farm Sector: Income and Balance Sheet Statstics. 1983. USDA Economic Research Service. 1984. Table 59. us-
ing farm number and cash receipts distribution data from the 1982 Census of Agriculture, Dept. of Commerce, Bureau of the Census, 1984.
e





22 A Special Report for the 1985 Farm Bill


rowed to about 88 percent, owing to rapid in-
creases in farm prices and a substantial in-
crease in the number of farm jobs available
from growth in rural industries. These two fac-
tors resulted in a slowing of the rate of out-
migration.
In 1982 the average income of farm and non-
farm households was quite close, $27,577 and
$28,638, respectively. However, two-thirds of
the income of farm households came from off-
farm sources. The majority of farm operators
today have some off-farm employment.
The average income statistics mask eco-
nomic problems that exist in the middle of the
scale of sales classes of farm operations (table
3-2). Farms in the part-time class, with sales in
the range of $20,000 to $99,999, are in serious
trouble. About 580,000 farms in this class in
1982 had an average total income of about
$15,000. Their average net income from farm-
ing was only $2,033. These farms are not large
enough to generate much net farm income and
have lower-than-average off-farm incomes. In
contrast, farmers with sales of less than $20,000
have substantial off-farm incomes and low or
negative net farm income. The average off-farm
income of these individuals enables them to
maintain this way of life.
Those owning moderate farms have suffi-
cient off-farm income to maintain a household.
However, this group may be under the most
stress. To provide an adequate total income,
moderate farm owners must earn almost as
much off-farm as on-farm income. Farmers
with sales in excess of $200,000 have moder-
ate off-farm incomes and moderate-to-very
large net farm incomes. As a group, these
farmers are well-off.

Changes In the Structure of Debt
IM the Farm Sector
At a time when agricultural production has
become more concentrated, the structure of
debt in the farm sector has also become more
concentrated. This process accelerated during
the boom years of the 1970s. The size and con-
centration of farm debt, combined with high


production costs and the continuing likelihood
of low commodity prices, have led to a great
deal of concern about the financial condition
of the farm sector. A substantial proportion of
the U.S. farm sector is under severe financial
stress. Financial stress is defined as the per-
ceived inability of the firm or individual to
meet cash flow commitments in the form of
cash farm expenses, debt repayment require-
ments, tax payments, or family living needs.
This stress can be measured indirectly by use
of the debt-to-asset ratio. In general, the distri-
bution of high debt-to-asset ratios is more im-
portant than the average debt-to-asset ratio of
all farms. The percentage of farms with debt-
to-asset ratios greater than 40 percent and
greater than 70 percent in January 1984 by
gross sales class is shown in table 3-3.
Clearly, debt use is closely related to farm
size. To the extent that debt-to-asset ratios show
potential financial problems, beginning farmers
and operators of larger farms are likely to be
in more difficulty than are other farmers.
An important aspect of outstanding debt is
the risk of default from the lender's standpoint.
If those with the largest proportion of debts to
assets are more likely to suffer losses, then
there are important risk elements facing agri-
cultural lenders. In January 1984, 24 percent
of the total agricultural debt was owed by
farmers with over a 70-percent debt-to-asset
ratio. Another 32 percent was owed by farmers
with debt-to-asset ratios in the range of 40 to

Table 3-3.-Distribution of Farms With High
Debt-to-Asset (dla) Ratios, by Sales Class, January 1984
Highly Very highly
leveraged leveraged
(d/a ratios: (dla ratios:
40 to 70%) over 70%)
% of No. of % of No. of
Sales class class farms class farms
Less than $50,000 ..... 8.3 123,200 5.0 74,800
$50,000 to $99,999..... 14.7 44,000 8.7 26,400
$100,000 to $249,999... 18.1 52,800 9.2 26,400
$250,000 to $499,999... 19.0 17,600 12.6 11,000
$500,000 and over ..... 17.4 5,200 15.3 4,500
All farms ........... 11.1 242,800 6.6 143,100
SOURCE: U.S. Department of Agriculture, 1983 Farm Production Expenditure
Survey.





Ch. 3-The Changing Character of the U.S. Agricultural Sector 23


70 percent. Thus, over one-half of outstanding
debt was owed by operators with debts greater
than 40 percent of their assets. This is a mat-
ter of great concern for lenders, since poor
farm incomes or decreases in asset values will
more quickly erode the equity of highly lever-
aged operators than of high-equity operators
(Brake, 1985).
Another useful way to illustrate increasing
financial stress is through the recent increases
in debt service burdens. This increase can be
measured by the amount of interest expense
as a percentage of cash receipts after payment
of intermediate production expenses, business
taxes, wages, and rents. By this measure, the
debt burden of U.S. farms was 17 percent in
1975. By 1981 it had reached 35 percent and
has been in the range of 34 to 38 percent ever
since. This has resulted in substantial reduc-
tions in the amount of receipts remaining to


pay for the operator's labor, for the owner's
equity in the business, for purchases of capi-
tal durable goods, and for payments of inter-
est and principal.
The consequences of increasing financial
stress can be seen in increasing rates of pay-
ment delinquency and foreclosure. For exam-
ple, Production Credit Association loan charge-
offs were under 0.1 percent in 1978 and 1979.
By 1983 these charge-offs had risen to 1.2 per-
cent of outstanding loans-an elevenfold in-
crease in 4 years. Similarly, the number of
loans in process of liquidation was negligible
in the late 1970s. Data on these loans were not
even kept in the Farm Credit System. By 1982,
loans in process of liquidation approached 1
percent of outstanding loans, and as of March
1984, Production Credit Association loans in
the process of liquidation were over 2.5 per-
cent of all outstanding loans.


DEFINING STRUCTURAL CHANGE IN AGRICULTURE


Traditionally, American agriculture has been
dominated by farms in which the operators and
their families provided most of the labor, made
the management decisions, owned part of the
resources, accepted most of the production and
price risks, bought and sold in the open mar-
ket, and depended on the farm as their major
source of family income. Such farms have been
revered since the days when Thomas Jefferson
argued for national policies of public land dis-
tribution that favored small, independent land-
holders. In recent years, the dispersed, inde-
pendent farm, open market system has become
less dominant in American agriculture. Major
questions are whether this system can compete
for world markets and whether society should
take steps to halt present trends that are grad-
ually diminishing this system's prominence.
Answering these questions entails viewing the
causes of structural change-that is, how farm
resources are organized and controlled-through
economic and noneconomic perspectives.


Tbe Economic Perspectiv
An economic perspective encompasses con-
centration and vertical integration in agri-
culture.

Comncetrcion
Concentration refers to the proportion of pro-
duction controlled by the largest firms. It is im-
portant to consider because the more highly
concentrated the market, the greater the poten-
tial impact of a firm or group of firms on price.
Concentration of total production in agricul-
ture compared to that in many of the other eco-
nomic sectors is generally low. As shown in
chapter 2, concentration has occurred to the
point where in 1982 about 28,000 very large
commercial farms-1.2 percent of all farms-
produced one-third of the total value of U.S.
farm products and accounted for over 60 per-
cent of U.S. farm net income.





Ch. 3-The Changing Character of the U.S. Agricultural Sector 23


70 percent. Thus, over one-half of outstanding
debt was owed by operators with debts greater
than 40 percent of their assets. This is a mat-
ter of great concern for lenders, since poor
farm incomes or decreases in asset values will
more quickly erode the equity of highly lever-
aged operators than of high-equity operators
(Brake, 1985).
Another useful way to illustrate increasing
financial stress is through the recent increases
in debt service burdens. This increase can be
measured by the amount of interest expense
as a percentage of cash receipts after payment
of intermediate production expenses, business
taxes, wages, and rents. By this measure, the
debt burden of U.S. farms was 17 percent in
1975. By 1981 it had reached 35 percent and
has been in the range of 34 to 38 percent ever
since. This has resulted in substantial reduc-
tions in the amount of receipts remaining to


pay for the operator's labor, for the owner's
equity in the business, for purchases of capi-
tal durable goods, and for payments of inter-
est and principal.
The consequences of increasing financial
stress can be seen in increasing rates of pay-
ment delinquency and foreclosure. For exam-
ple, Production Credit Association loan charge-
offs were under 0.1 percent in 1978 and 1979.
By 1983 these charge-offs had risen to 1.2 per-
cent of outstanding loans-an elevenfold in-
crease in 4 years. Similarly, the number of
loans in process of liquidation was negligible
in the late 1970s. Data on these loans were not
even kept in the Farm Credit System. By 1982,
loans in process of liquidation approached 1
percent of outstanding loans, and as of March
1984, Production Credit Association loans in
the process of liquidation were over 2.5 per-
cent of all outstanding loans.


DEFINING STRUCTURAL CHANGE IN AGRICULTURE


Traditionally, American agriculture has been
dominated by farms in which the operators and
their families provided most of the labor, made
the management decisions, owned part of the
resources, accepted most of the production and
price risks, bought and sold in the open mar-
ket, and depended on the farm as their major
source of family income. Such farms have been
revered since the days when Thomas Jefferson
argued for national policies of public land dis-
tribution that favored small, independent land-
holders. In recent years, the dispersed, inde-
pendent farm, open market system has become
less dominant in American agriculture. Major
questions are whether this system can compete
for world markets and whether society should
take steps to halt present trends that are grad-
ually diminishing this system's prominence.
Answering these questions entails viewing the
causes of structural change-that is, how farm
resources are organized and controlled-through
economic and noneconomic perspectives.


Tbe Economic Perspectiv
An economic perspective encompasses con-
centration and vertical integration in agri-
culture.

Comncetrcion
Concentration refers to the proportion of pro-
duction controlled by the largest firms. It is im-
portant to consider because the more highly
concentrated the market, the greater the poten-
tial impact of a firm or group of firms on price.
Concentration of total production in agricul-
ture compared to that in many of the other eco-
nomic sectors is generally low. As shown in
chapter 2, concentration has occurred to the
point where in 1982 about 28,000 very large
commercial farms-1.2 percent of all farms-
produced one-third of the total value of U.S.
farm products and accounted for over 60 per-
cent of U.S. farm net income.





24 A Special Report for the 1985 Farm Bill


However, concentration in land resources is
also occurring.' Trends in the distribution of
harvested cropland according to sales class
show that these productive acres are rapidly
becoming concentrated in the farms in the
large commercial and very large commercial
sales classes. Table 3-4 shows the percentage
of total cropland harvested by the top two sales
classes of farms for the census years 1969 and
1982 and projects them linearly to 1990 and
2000. If present trends continue, almost half
of all cropland will be harvested by farms in
these sales classes by 2000.
The degree of concentration varies from
commodity to commodity. For example, beef
cattle operators with sales over $500,000 per
year in 1982 represented only 0.5 percent of
all beef cattle operations and accounted for 55
percent of the total value of cattle sales. The
69 largest of these feedlots produced 21 per-
cent of the fed cattle in 1980 (USDA, 1981). The
largest cattle feeders were also some of the
largest feed manufacturers and grain com-
panies.
Higher levels of concentration exist for
broilers (chickens). In 1977 the 16 largest
broiler producers and contractors controlled
'Land resources in the agricultural sector can be viewed in
the general category of "land in farms," as defined by the Bu-
reau of the Census, or in the "harvested cropland" category. The
acreage of cropland harvested is a more accurate measure of
productive agricultural resources than is the general category
of land in farms.

Table 3-4.-Historical and Projected Percentages of
Cropland Harvested by Farms With Sales in Excess
of $200,000
Year
Sales class 1969 1982 1990 2000
$200,000-$499,000 ......... 12.0 25.3 27.0 32.0
$500,000 + ............... 6.0 11.2 12.0 14.0
Total .................. 18.0 36.5 39.0 46.0
Projection Assumptions:
growth in total harvested acres is linear, resulting in an increase of 2.4 million
acres per year.
rowth follows the linear trend for the two sales classes and results in an In-
crease of 2.7 million acres per year for the farms in the $200,000-5499,000
class and of 1 million acres per year for the $500,000+ class.
3The linear projections are based on the acres harvested by sales classes, ad-
justed for inflation. Inflation in commodity prices tonds to move acres from
lower to upper sales classes. Since inflation in commodity prices is likely to
continue, nominal growth in acreage harvested by these sales classes may be
greater than projected.
SOURCE: Office of Technology Assessment.


about 50 percent of the production (Brooke,
1980). In vegetable crops, such as lettuce and
celery, concentration is comparably high
(Brooke, 1980).
On the other hand, concentration is still very
low for most crop agriculture. Relative to other
American industries, where the market share
of the four largest manufacturers frequently ex-
ceeds 50 percent, concentration in agricul-
ture-even for cattle feeding, broilers, lettuce,
and celery-is low. However, attention is
drawn to agriculture because of the rapidity
with which certain industries, such as broilers
and fed cattle, have gone from a diffused to a
concentrated and integrated agriculture (Knut-
son, et al., 1983).
Concern exists that if extended over a period
of time, the increasing concentration of agri-
cultural production could lead to higher food
prices (Breimyer and Barr, 1972). This would
result from increased merchandising and mar-
keting costs, the potential unionization of agri-
cultural workers, and lack of effective competi-
tion (Rhodes and Kyle, 1973).


Vetcal IfgratloM
Firms are vertically integrated when they
control two or more levels of the production-
marketing system for a product. Such control
may be exercised by contract or by ownership.
Contract integration exists when a firm
establishes a legal commitment that binds a
producer to certain production or marketing
practices. At a minimum, contract integration
requires that the producer sell the product to
the buyer. Additional commitments may bind
the farmer to specified production practices
and sources of inputs. While all forms of con-
tract integration have created concern, the
greatest controversy exists with contracts that
control both production and marketing deci-
sions of farmers. In addition, from a legal
perspective, the producer may not even own
the product being grown (Knutson, et al., 1983).
The extent of contract integration is not well
documented. Ronald Knutson estimates that all
forms of contract integration represented 32






Ch. 3-The Changing Character of the U.S. Agricultural Sector 25 ,


percent of farm sales in 1981 (Knutson, et al.,
1983). He makes the following observations on
the extent of contracting:
1. Contracting used to be limited to perish-
able products; now it has expanded to vir-
tually all commodities.
2. Production contracting appears to be asso-
ciated with commodities where breeding
and control of genetic factors play an im-
portant role in either productivity deter-
mination or quality control.
Ownership integration is a single ownership
interest extended to two or more levels of the
production-marketing system. It may involve
either cooperatives or proprietary agribusiness
firms. Knutson estimates that proprietary
ownership integration accounts for about 6
percent of farm sales. Some proprietary agri-
business firms such as Cargill (beef), Superior
Oil (fruits, vegetables, and nuts), Coca-Cola
(oranges and grapefruit), Tysons (broilers and
hogs), Tenneco (fruits, vegetables, and nuts),
and Ralston Purina (mushrooms) have made
substantial investments in agricultural produc-
tion. In products such as broilers, eggs, cotton,
vegetables, and citrus fruits, ownership integra-
tion is over 10 percent of total U.S. production
(Knutson, et al., 1983).
Cooperative ownership integration is much
more prevalent than proprietary ownership in-
tegration, accounting overall for 34 percent of
farm sales. However, in only 13 percent of co-
operative integration is there a legal commit-
ment by farmers to market their commodities
or purchase inputs from the cooperative.
The economic implications and concern for
structural change of vertical integration are
debated. A principal problem in agriculture has
been the difficulty of coordinating production
with market needs. Vertical integration can
make a substantial contribution to satisfying
this need. For example, in broilers and turkeys,
vertical integration has contributed to the uni-
form size and quality of poultry sold. It has also
contributed to increased efficiency and re-
duced costs (Schrader and Rogers, 1978).


On the other hand, there are potentially
adverse consequences of vertical integration.
Contract integration with corporations, and
sometimes cooperatives, radically changes the
role of the traditional independent farmer.
More often than not, the farmer loses control
of, if not legal title to, the commodities grown
under a production-integrated arrangement.
Payment to the grower is largely on a per-unit
or piece-wage basis, and not necessarily related
to product value.
It has been argued that in the long run, mar-
ket power in integrated agriculture will become
sufficiently highly concentrated that the con-
sumer will pay higher prices for food. How-
ever, no definitive conclusion can be made.
The above argument fails to take into account
efficiency gains from integration. The extent
to which these gains could be realized without
the development of a vertically integrated sys-
tem is open to question.

The Sociological Perspective
Many concerns relating to structural change
are of a sociological nature. They revolve
around the impact of concentration and in-
tegration on the institution of the family farm,
on rural communities, and on rural institutions.
Concern has been expressed that continu-
ously increasing the concentration and integra-
tion will lead to the demise of the family farm
as an institution. The term family farm has
been associated with the existence of an inde-
pendent business and social entity that shares
responsibilities of ownership, management, la-
bor, and financing. The family farm system
leads to dispersion of economic power and has
been associated with the perpetuation of basic
American values and of the family as an insti-
tution. Increased concentration and integration
tend to destroy the family farm institution.
Very large farms lose many of the characteris-
tics of the traditional family farm because their
business and hired labor aspects clearly pre-
dominate. Most of the management functions
traditionally associated with the family farm


38-857 0 85 5 : QL 3





26 A Special Report for the 1985 Farm Bill


institution are removed by integration. With in-
tegration the farmer takes on more of the char-
acteristics of a businessman.
Another concern is that concentration and
ownership integration reduce the number of
farms and make the integrator less dependent
on the local community. As a consequence,
small rural towns and their social institutions
decline or vanish. Recent research conducted
in California provides some evidence to sub-
stantiate such a relationship. Dean MacCan-
nell (1983) has found that rural communities
where a few large and integrated farms domi-
nate are associated with few services, lower
quality education, and less community spirit.
Concerns are also expressed about the im-
pact of structural change on the nature of the
U.S. political system. Thomas Jefferson vis-
ualized the merits of a decentralized political
system where power was highly diffused and


where every individual had the opportunity for
input to public decisions. His philosophy
placed a high value on independent farmers
and landowners as a means of maintaining a
democratic system of government.
Already there has been a marked departure
from the decentralized power structure ideal
visualized by Jefferson. The question is whether
agriculture is basically unique and different
from other sectors of U.S. society, as has long
been maintained-that is, are there unique
social, cultural, and traditional values in hav-
ing land ownership widely dispersed, or should
agriculture join the mainstream where the
other economic sectors have long been? As
U.S. agriculture continues along the trends laid
out in this report, it will increasingly take on
characteristics of the nonfarm sector. Some
will interpret this trend as progress; others will
interpret it as a step backward.


CAUSES OF STRUCTURAL CHANGE


A number of factors have been identified by
researchers as causes of structural change.
However, there has been no delineation of the
relative importance of each factor. One of the
objectives of this study is such a delineation.
Before moving to that analysis in the follow-
ing chapters, however, it is important to un-
derstand why each of these factors is consid-
ered important to structural change.
Most observers of structural change cite
three main determinants: 1) technology and
associated economies of size, specialization,
and capital requirements; 2) institutional forces;
and 3) economic and political forces (fig. 3-1).
This section briefly defines these forces.

Teschological Forces
Certain farmers have a strong incentive to
adopt new technology rapidly. The early in-
novator achieves lower per-unit costs and in-
creased profits, at least for a short time, before
other farmers follow his lead. For example, in
Washington State a winter wheat farmer with


2,500 acres can reduce average machinery
costs by 9 percent per acre by replacing a con-
ventional crawler tractor with a four-wheel-
drive tractor. If he also expands the size of his
farm to 3,900 acres, he can reduce costs by an
additional 18 percent (Rodewald and Folwell,
1977). This nearly 60-percent increase in farm
size can be made without additional labor.
Once the innovative wheat farmer adopts the
technology, other crop farmers generally have
two options: purchase a four-wheel-drive trac-
tor and expand the size of their farm or accept
a lower net income as market prices for their
crops fall. In short, new technology can play
an important role in determining acreage and
capital requirements. Different farmers have
different costs because they use different com-
binations of inputs, have different management
skills, or have different scales of operation.

hkoomles of Siz
The relationship of scale of operation to cost
is of particular significance to structure. If
costs are relatively the same for all farm sizes,






Ch. 3-The Changing Character of the U.S. Agricultural Sector 27


Figure 3-1.-Factors Influencing the Structure of Agriculture

Economic environment
Rate of inflation
Growth of demand
/ \ Consumer tastes and preferences

Institutional factors (agriculture specific) -
Farm organizations
SCredit institutions (public and private)
Research and development (public and private)
Tax policies

Technical factors affecting farming
Rate of adoption
e Distribution of costs of production
S\ Human capital

Structure of agriculture
Number and size of farms r
SContractual arrangements
Control of management decisions
Off-farm employment
Extent of tenancy
Ownership of farmland


SOURCE: Office of Technology Assessment.


one would expect all farm sizes to have rela-
tively little incentive to increase in size. In ad-
dition, with relatively even costs, consumers
would clearly not benefit from increases in
farm size. If, on the other hand, costs decline
sharply as farm size increases, not only would
there be strong incentives for farms to grow
in size, but consumers would potentially realize
lower prices for food. Of at least equal impor-
tance to policymakers, if costs decline sharply
as farm size increases, efforts to prevent this
change from occurring-for example, to pre-
serve the family farm-would not only be dif-
ficult but could be counterproductive from a
consumer perspective. Smaller farm operators
could exist in a cost-declining environment
only if they were willing to accept lower re-
turns to contributed labor, capital, and man-
agement, and/or had an off-farm job.


Past studies of the relationship between aver-
age production costs and farm size support two
major conclusions. First, most economies of
size are apparently captured by moderate
farms. Second, while the lowest average cost
of production may be attainable on a moder-
ate farm, average cost tends to remain rela-
tively constant over a wide range of farm sizes.
Thus, farmers have a strong incentive to ex-
pand the sizes of their farms in order to in-
crease total profits.

Earlier studies on economies of size have sev-
eral limitations. External economies gained
from buying and selling in large volumes and
from access to credit have usually been ig-
nored. Common ownership of related farm and
nonfarm activities has not been considered.
There is some evidence that inclusion of such


_ ___ _





26 A Special Report for the 1985 Farm Bill


institution are removed by integration. With in-
tegration the farmer takes on more of the char-
acteristics of a businessman.
Another concern is that concentration and
ownership integration reduce the number of
farms and make the integrator less dependent
on the local community. As a consequence,
small rural towns and their social institutions
decline or vanish. Recent research conducted
in California provides some evidence to sub-
stantiate such a relationship. Dean MacCan-
nell (1983) has found that rural communities
where a few large and integrated farms domi-
nate are associated with few services, lower
quality education, and less community spirit.
Concerns are also expressed about the im-
pact of structural change on the nature of the
U.S. political system. Thomas Jefferson vis-
ualized the merits of a decentralized political
system where power was highly diffused and


where every individual had the opportunity for
input to public decisions. His philosophy
placed a high value on independent farmers
and landowners as a means of maintaining a
democratic system of government.
Already there has been a marked departure
from the decentralized power structure ideal
visualized by Jefferson. The question is whether
agriculture is basically unique and different
from other sectors of U.S. society, as has long
been maintained-that is, are there unique
social, cultural, and traditional values in hav-
ing land ownership widely dispersed, or should
agriculture join the mainstream where the
other economic sectors have long been? As
U.S. agriculture continues along the trends laid
out in this report, it will increasingly take on
characteristics of the nonfarm sector. Some
will interpret this trend as progress; others will
interpret it as a step backward.


CAUSES OF STRUCTURAL CHANGE


A number of factors have been identified by
researchers as causes of structural change.
However, there has been no delineation of the
relative importance of each factor. One of the
objectives of this study is such a delineation.
Before moving to that analysis in the follow-
ing chapters, however, it is important to un-
derstand why each of these factors is consid-
ered important to structural change.
Most observers of structural change cite
three main determinants: 1) technology and
associated economies of size, specialization,
and capital requirements; 2) institutional forces;
and 3) economic and political forces (fig. 3-1).
This section briefly defines these forces.

Teschological Forces
Certain farmers have a strong incentive to
adopt new technology rapidly. The early in-
novator achieves lower per-unit costs and in-
creased profits, at least for a short time, before
other farmers follow his lead. For example, in
Washington State a winter wheat farmer with


2,500 acres can reduce average machinery
costs by 9 percent per acre by replacing a con-
ventional crawler tractor with a four-wheel-
drive tractor. If he also expands the size of his
farm to 3,900 acres, he can reduce costs by an
additional 18 percent (Rodewald and Folwell,
1977). This nearly 60-percent increase in farm
size can be made without additional labor.
Once the innovative wheat farmer adopts the
technology, other crop farmers generally have
two options: purchase a four-wheel-drive trac-
tor and expand the size of their farm or accept
a lower net income as market prices for their
crops fall. In short, new technology can play
an important role in determining acreage and
capital requirements. Different farmers have
different costs because they use different com-
binations of inputs, have different management
skills, or have different scales of operation.

hkoomles of Siz
The relationship of scale of operation to cost
is of particular significance to structure. If
costs are relatively the same for all farm sizes,





26 A Special Report for the 1985 Farm Bill


institution are removed by integration. With in-
tegration the farmer takes on more of the char-
acteristics of a businessman.
Another concern is that concentration and
ownership integration reduce the number of
farms and make the integrator less dependent
on the local community. As a consequence,
small rural towns and their social institutions
decline or vanish. Recent research conducted
in California provides some evidence to sub-
stantiate such a relationship. Dean MacCan-
nell (1983) has found that rural communities
where a few large and integrated farms domi-
nate are associated with few services, lower
quality education, and less community spirit.
Concerns are also expressed about the im-
pact of structural change on the nature of the
U.S. political system. Thomas Jefferson vis-
ualized the merits of a decentralized political
system where power was highly diffused and


where every individual had the opportunity for
input to public decisions. His philosophy
placed a high value on independent farmers
and landowners as a means of maintaining a
democratic system of government.
Already there has been a marked departure
from the decentralized power structure ideal
visualized by Jefferson. The question is whether
agriculture is basically unique and different
from other sectors of U.S. society, as has long
been maintained-that is, are there unique
social, cultural, and traditional values in hav-
ing land ownership widely dispersed, or should
agriculture join the mainstream where the
other economic sectors have long been? As
U.S. agriculture continues along the trends laid
out in this report, it will increasingly take on
characteristics of the nonfarm sector. Some
will interpret this trend as progress; others will
interpret it as a step backward.


CAUSES OF STRUCTURAL CHANGE


A number of factors have been identified by
researchers as causes of structural change.
However, there has been no delineation of the
relative importance of each factor. One of the
objectives of this study is such a delineation.
Before moving to that analysis in the follow-
ing chapters, however, it is important to un-
derstand why each of these factors is consid-
ered important to structural change.
Most observers of structural change cite
three main determinants: 1) technology and
associated economies of size, specialization,
and capital requirements; 2) institutional forces;
and 3) economic and political forces (fig. 3-1).
This section briefly defines these forces.

Teschological Forces
Certain farmers have a strong incentive to
adopt new technology rapidly. The early in-
novator achieves lower per-unit costs and in-
creased profits, at least for a short time, before
other farmers follow his lead. For example, in
Washington State a winter wheat farmer with


2,500 acres can reduce average machinery
costs by 9 percent per acre by replacing a con-
ventional crawler tractor with a four-wheel-
drive tractor. If he also expands the size of his
farm to 3,900 acres, he can reduce costs by an
additional 18 percent (Rodewald and Folwell,
1977). This nearly 60-percent increase in farm
size can be made without additional labor.
Once the innovative wheat farmer adopts the
technology, other crop farmers generally have
two options: purchase a four-wheel-drive trac-
tor and expand the size of their farm or accept
a lower net income as market prices for their
crops fall. In short, new technology can play
an important role in determining acreage and
capital requirements. Different farmers have
different costs because they use different com-
binations of inputs, have different management
skills, or have different scales of operation.

hkoomles of Siz
The relationship of scale of operation to cost
is of particular significance to structure. If
costs are relatively the same for all farm sizes,






28 A Special Report for the 1985 Farm Bill


pecuniary economies would lower the average
production costs for large farm units and
would shift the conclusion about the size of the
most competitive farm (Smith, et al., 1984).

Specialization
Technology has also influenced specializa-
tion and regional production patterns. Cotton
production has moved westward, for example,
into areas of broad, flat fields where larger ma-
chinery can be used to optimum advantage.
Specialization in crop production is also due
in part to technology. Farmers who once relied
on crop rotation and diversification to con-
serve soil fertility, prevent soil erosion, and
control pests have replaced these practices by
chemical fertilizers, insecticides, and her-
bicides, with questionable long-run effects.
They can thus grow one crop exclusively year
after year, specializing in commodities that are
the most profitable. Similarly, the development
of new disease control techniques has given
poultry and livestock farmers unprecedented
opportunities to specialize. The vertically in-
tegrated broiler industry of today would have
been impossible without scientific advances in
breeding, feeding, housing, and medicine,
which have reduced the real cost of broilers
by as much as 50 percent over the past 30 years.
These scientific breakthroughs have gener-
ally enabled both small and large farmers to
specialize more. However, improvements in
farm machinery have perhaps been most im-
portant in fostering large-scale, specialized
operations. A decision to invest in a special-
ized piece of equipment means that an opera-
tor will emphasize production of the com-
modity for which the machine is intended,
quite likely at the expense of some other com-
modity. And, insofar as a machine is most
economical on a particular size of operation,
expansion to that size is encouraged. Thus,
specialization and farm growth occur simul-
taneously.

Capital Requiremomfts
Agriculture is one of the most capital-inten-
sive industries in the American economy. The
result is high requirements for credit to finance
new capital investments, production, or storage.


Technology has made barriers to entry more
formidable. The cost of machinery raises cap-
ital requirements for beginning farmers. Tech-
nologies that allow individuals to farm in-
creasingly larger acreages have added to the
competition for land, resulting in high land
prices, the single greatest expense in farming
today. The average investment in 1980 in a
farming operation with gross sales between
$40,000 and $60,000 ranged from $350,000, for
fruit and nut farms, to over $800,000, for live-
stock ranches.

Institutional Forces
Institutional factors have their primary in-
fluence on the costs of inputs used in produc-
tion, the prices of products, and the generation
of new technology for agriculture. These insti-
tutions may be either in the private or the pub-
lic sector.
The costs of inputs are primarily a function
of competition between private sector agri-
business firms. Input costs do not have to be
the same for all farmers. Input suppliers may
offer farmers discounts for larger volume pur-
chases of fertilizer or chemicals. Likewise,
larger scale farmers may receive higher prices
for products marketed through the use of crop
contracts or futures markets.

Rsoarcb and Rxtonsion Service
New technologies are generated in both the
public and private sector. Basic agricultural re-
search is primarily a public sector function per-
formed by the U.S. Department of Agriculture
(USDA) and the land grant universities. Ap-
plied research functions are shared between
the public and private sector, with the private
sector dominating development activities. Ex-
tension activities assist in evaluating and trans-
ferring technological innovations into practice.
An integral part of agricultural research and
extension policies is the generation of higher
levels of training and expertise embodied in
human capital. The result is more skilled
farmers, agribusinessmen, scientists, and agri-
cultural policymakers.
Research and extension have had differen-
tial impacts on farms, farm workers, rural com-





Ch. 3-The Changing Character of the U.S. Agricultural Sector 29


munities, and even entire regions, depending
on their characteristics and the type of tech-
nology developed. Some technological innova-
tions, particularly mechanical innovations,
have favored and hence fostered larger farms.
Other technological innovations that could be
applied on farms of any size are often first
adopted by larger farms (Paarlberg, 1981; Per-
rin and Winkelman, 1976). By being the first
to adopt new technologies, larger farms receive
greater benefits than those not adopting the
technologies (typically, smaller farms).
A major effort of the extension service is to
disseminate timely information through pub-
lic meetings. The topics covered in publica-
tions and public meetings are heavily influ-
enced by current research results. Any bias
toward larger farms that is embodied in re-
search results would most likely be carried over
into meetings and publications.
Even though extension personnel make in-
formation available to all farmers, those
farmers that make the most use of the research
results and extension information can gener-
ally be characterized as more innovative, more
aggressive, and better managers, usually of
larger farms (Paarlberg, 1981). Such farmers
are also generally more vocal, providing feed-
back to research and extension personnel on
the. usefulness of the information received.
Even though no overt effort is made to exclude
particular groups, such as operators of small
farms, the net result is that many research and
extension programs become more oriented
toward those select groups that generally avail
themselves of the information (Paarlberg,
1981).
This lack of structural neutrality was recog-
nized in 1979 by Secretary of Agriculture
Bergland when he questioned the use of Fed-
eral funds for research projects having the ob-
jective of producing large-scale, labor-saving
technology and set up a special task force to
investigate the impact of research and exten-
sion on structure. At the same time, Congress
earmarked research and extension funds for
increased work with small farms and for proj-
ects involving direct marketing from farmers


and consumers. However, no special programs
were developed for moderate farms.
The Bergland initiative on research was
deemphasized with the change in administra-
tion in 1981. It has, however, been rekindled
by the announcement of joint initiatives in bio-
technology research between private sector
companies and universities. Questions have
arisen as to whether the primary beneficiaries
of the initiatives will be the private sector firms
or the initial farmer adopters of the resulting
new technology.

Public Poliey
Many public policies affect the structure of
agriculture by influencing resource use, capi-
tal requirements, technology development and
adoption, freedom of decisionmaking, exchange
arrangements, risks, and costs and profits.
Some policies are oriented specifically to the
farm sector, such as price and income policy
(commodity programs). Others affect agricul-
ture directly but are more broadly oriented,
such as tax policy. Still others are general-
national macroeconomic policy, for example-
and affect agriculture indirectly.
Public policies offer viable ways to maintain
or alter the structure of the agricultural sector.
In this section, areas of public policy involve-
ment that affect the structure of agriculture are
briefly examined.
Commodity Programs.-Beginning with the
Agricultural Adjustment Act of 1933, a series
of commodity programs have evolved to deal
with price and income problems in farming.
These programs have covered such commod-
ities as wheat, feed grains, cotton, wool, sugar,
rice, peanuts, tobacco, and dairy products. To
stabilize and increase farm prices and incomes,
a variety of program tools have been used:
price supports, direct payments, acreage
allotments, set-asides, conservation reserves,
surplus disposal, and stock accumulation.
There is widespread agreement that these
programs, in the short run, held farm incomes
above what they would otherwise have been;
there is much less agreement about their long-





30 A Special Report for the 1985 Farm Bill


term effects on income. Price stability from
these programs has, however, enabled farmers
to adopt new and improved technologies.
Commodity programs along with technologi-
cal advances influence structural change in
agriculture through the following mechanisms.
Since farmers are price takers, no one farmer
can significantly influence the aggregate sup-
ply of a commodity and hence the price that
he receives. However, the individual farmer
can do something about his operating costs. By
adopting a new technology an innovative
farmer increases productivity and lowers his
firm's cost structure. Since price is not affected
at the early stage of technology adoption, he
reaps a profit. As his cost structure falls, the
farmer increases his output at the given price.
It is possible that innovative farmers used some
of their profits to buy up assets of less efficient
neighbors, thus starting the change in the struc-
ture of farming. As more farmers realize the
benefit of new technology and follow this in-
novator, the adoption of the new technology
becomes widespread. As they do this, aggre-
gate supply increases, and the price of the
product declines. After a period of adjustment
a new equilibrium is reached at a lower price,
a situation in which the innovator no longer
receives a profit and in which the laggard adop-
ters of new technology suffer an economic loss.
This dynamic interaction has been referred to
as the "agricultural treadmill" (Cochrane,
1958).
Under a commodity program in which the
price of the commodity is supported, the same
treadmill concept applies. However, under such
a commodity program the price does not fall
when the aggregate supply increases, because
the product price is supported by Government
action. Instead, each early adopter continues
to reap a profit and seeks to expand output by
acquiring the land of his less innovative neigh-
bors. Thus, farm technological advances coupled
with Government-supported product prices re-
sult in structural change in which productive
assets in farming are concentrated in the
hands of aggressive, innovative farmers. How-
ever, since the total amount of arable land is
limited, competition for this land between the


innovative farmers causes the price of land to
rise. The cost of production will thus rise un-
til a new equilibrium is reached in which the
expanded, innovative farmers are back in a no-
profit situation while the laggard adopters end
up with a loss. In this case the equilibrium is
reached by an increase in land values rather
than a fall in product prices.
Tax Policy.-Tax laws and provisions are
widely recognized as being a determinant of
agricultural structure. There is not agreement,
however, about the relative importance of tax
policy because of tax policy's interactions with
other structural determinants. Some tax laws
and provisions can be directly related to struc-
ture (i.e., estate and corporate tax law), while
others (i.e., investment tax credits, deprecia-
tion provisions, capital gains, and cash ac-
counting) are indirectly related and often in-
teract with credit and commodity policies.
In animal agriculture, tax factors such as
cash accounting, current deductibility of costs
of raising livestock, and capital gains treatment
for sales of breeding livestock, together with
investment tax credits and accelerated depre-
ciation, influence livestock investments and
can affect structure. Tax policy issues in ani-
mal agriculture include tax shelter and non-
farm investments, tax provisions as a factor in
economies of size, and the legal structure of
agriculture. The cattle sector provides one
example.
For mechanical technology, current tax laws
favor the substitution of capital for labor and
may speed the adoption of mechanical systems.
Two tax factors are at work: payroll taxes,
which increase the cost of labor, and provi-
sions for investment tax credit and accelerated
depreciation, which decrease the cost of ma-
chinery (Carman, 1983).
The income tax advantages of cattle feeding
were packaged as limited partnership syn-
dicates in the late 1960s and early 1970s and
sold to nonfarm investors. The growth of non-
farm investment in cattle feeding was closely
associated with the movement of cattle feeding
out of the Midwest and with the growth of
large-scale feedlots in the High Plains area.






Ch. 3-The Changing Character of the U.S. Agricultural Sector 31


Other factors also played a role, but limited em-
pirical evidence suggests that tax-induced in-
vestment in cattle feeding through limited part-
nerships was related to structural change
(Carman, 1983).
It is conventional wisdom that tax provisions
are an important consideration in the adoption
of capital-intensive innovations, since invest-
ment tax credit and accelerated depreciation
do have a significant impact on after-tax costs.
Such innovations include the large four-wheel-
drive tractors, circle irrigation systems, mini-
mum tillage systems, and large-scale and im-
proved harvesters.
An important implication can be drawn
about structural change from the above discus-
sion. Small farms and very large farms have
more off-farm interests against which to off-
set farm losses than do moderate farms. This
could be a significant factor in accounting for
the decline of the moderate farm.
Agricultural Credit Policy.-Public policy
directly influences the supply of capital to
farmers through the Farmers Home Adminis-
tration (FmHA) of the USDA and the Farm
Credit System, which includes the Federal
Land Bank, Production Credit Association, and
Bank for Cooperatives. The original capital for
the Farm Credit System was supplied by the
Federal Government, but the system is now


wholly owned by its borrowers. However, the
Farm Credit System is still accorded agency
status, whereby interest costs on its bonds and
discount notes are lowered. The FmHA is a
Government agency that has a mandate from
Congress to make low-interest loans to family
farmers who cannot obtain credit elsewhere.
The FmHA and the Farm Credit System to-
gether account for approximately 40 percent
of the total farm debt outstanding (8 and 33 per-
cent, respectively) (Barry, 1983).
The general intent of farm credit policies has
been to ensure appropriate capital availability
for agriculture. Policies established by these
agencies and their attendant programs are
thought to have influenced the structure of the
farm sector, although the extent of their impact
has not been studied thoroughly.

Economic and Political Forces
Agriculture operates in a broader overall eco-
nomic and political environment. This environ-
ment determines the rate of interest, the rate
of inflation, and the value of the dollar-all of
which influence the costs and prices of farm
products. The increased importance of these
effects has made macroeconomic policies that
influence the overall economic environment
within which agriculture operates more impor-
tant to farmers.


THE DYNAMICS OF STRUCTURAL CHANGE


A study of this type cannot possibly analyze
all of the technical, economic, and institutional
factors that influence the structure of agricul-
ture. This study therefore concentrates on
those factors that appear to be the most criti-
cal in affecting structure and that also relate
to current farm policy decisions. These factors
include:
The technical factors influencing the costs
of production as related to farm size.
The major farm program elements.
The institutions that lead to the develop-
ment and assimilation of new technology.


The factors interact in a dynamic fashion to
influence the structure of farming. New tech-
nology continuously infused into agriculture
is adopted by the most progressive farmers.
While the initial adopters assume increased
risk in applying a new technology, they gen-
erally also gain substantially higher returns.
Farm programs that reduce price risk help
assure higher returns.
As more farmers realize the advantages of
new technology, the adoption process becomes
more general. As this happens, supplies in-
crease, with the tendency to force down mar-






Ch. 3-The Changing Character of the U.S. Agricultural Sector 31


Other factors also played a role, but limited em-
pirical evidence suggests that tax-induced in-
vestment in cattle feeding through limited part-
nerships was related to structural change
(Carman, 1983).
It is conventional wisdom that tax provisions
are an important consideration in the adoption
of capital-intensive innovations, since invest-
ment tax credit and accelerated depreciation
do have a significant impact on after-tax costs.
Such innovations include the large four-wheel-
drive tractors, circle irrigation systems, mini-
mum tillage systems, and large-scale and im-
proved harvesters.
An important implication can be drawn
about structural change from the above discus-
sion. Small farms and very large farms have
more off-farm interests against which to off-
set farm losses than do moderate farms. This
could be a significant factor in accounting for
the decline of the moderate farm.
Agricultural Credit Policy.-Public policy
directly influences the supply of capital to
farmers through the Farmers Home Adminis-
tration (FmHA) of the USDA and the Farm
Credit System, which includes the Federal
Land Bank, Production Credit Association, and
Bank for Cooperatives. The original capital for
the Farm Credit System was supplied by the
Federal Government, but the system is now


wholly owned by its borrowers. However, the
Farm Credit System is still accorded agency
status, whereby interest costs on its bonds and
discount notes are lowered. The FmHA is a
Government agency that has a mandate from
Congress to make low-interest loans to family
farmers who cannot obtain credit elsewhere.
The FmHA and the Farm Credit System to-
gether account for approximately 40 percent
of the total farm debt outstanding (8 and 33 per-
cent, respectively) (Barry, 1983).
The general intent of farm credit policies has
been to ensure appropriate capital availability
for agriculture. Policies established by these
agencies and their attendant programs are
thought to have influenced the structure of the
farm sector, although the extent of their impact
has not been studied thoroughly.

Economic and Political Forces
Agriculture operates in a broader overall eco-
nomic and political environment. This environ-
ment determines the rate of interest, the rate
of inflation, and the value of the dollar-all of
which influence the costs and prices of farm
products. The increased importance of these
effects has made macroeconomic policies that
influence the overall economic environment
within which agriculture operates more impor-
tant to farmers.


THE DYNAMICS OF STRUCTURAL CHANGE


A study of this type cannot possibly analyze
all of the technical, economic, and institutional
factors that influence the structure of agricul-
ture. This study therefore concentrates on
those factors that appear to be the most criti-
cal in affecting structure and that also relate
to current farm policy decisions. These factors
include:
The technical factors influencing the costs
of production as related to farm size.
The major farm program elements.
The institutions that lead to the develop-
ment and assimilation of new technology.


The factors interact in a dynamic fashion to
influence the structure of farming. New tech-
nology continuously infused into agriculture
is adopted by the most progressive farmers.
While the initial adopters assume increased
risk in applying a new technology, they gen-
erally also gain substantially higher returns.
Farm programs that reduce price risk help
assure higher returns.
As more farmers realize the advantages of
new technology, the adoption process becomes
more general. As this happens, supplies in-
crease, with the tendency to force down mar-






32 A Special Report for the 1985 Farm Bill


ket prices. If Government policies prevent mar-
ket prices from falling, surpluses build up, as
they have in the dairy industry or did before
the payment-in-kind (PIK) program. If market
prices fall, Government payments rise.
Wider adoption of technologies also changes
the nature of costs as farm size increases. If
larger farms are the first adopters, their costs
are substantially lower. The laggers in adop-
tion realize much higher costs. By not adopt-
ing, they become, in effect, left behind-even-
tually being either forced off the farm altogether
or forced to take an off-farm job. Moreover, the
higher returns gained by early adopters of tech-
nology encourage them to seek expansion of


output by acquiring more land. Given the fixed
land base, however, innovative farmers can
only grow in size by acquiring the land of their
neighbors. Thus, growth and prosperity of
large, progressive farmers can only take place
by the failure of those who are slow to adopt
technology.
These consequences often lead to sugges-
tions of turning off the technological wheels
of progress. Such a strategy, however, would
have a devastating effect on the competitive-
ness of American farmers in world markets.
Instead of just some people being left behind,
the whole American farm system would be left
behind.






Chapter 4

Economic Impacts of

Emerging Technologies and

Selected Farm Policies for

Various Size Crop Farms


The impacts of emerging technologies will
spur many adjustments at the farm level. Pol-
icymakers must thus consider several questions
as they debate the 1981 farm bill: Who will
adopt these technologies and benefit the most
from them-the moderate farms, large farms,
or very large farms? What set of farm policies
in conjunction with technology advance will
benefit each size of farm the most? What com-
bination of emerging technologies and farm
policies encourages each size of farm to grow
or remain at its present size? How important
is technology compared to farm policy in deter-
mining farm growth? What is the likelihood of
a new entrant in agriculture remaining solvent?
To help answer these questions, this chapter
and the next will present the findings of an
analysis of selected regions in the United States
that represent significant agricultural produc-
tion in the commodities considered in farm pol-
icy: dairy, corn, cotton, soybeans, rice, and
wheat. Within each production region ana-
lyzed, representative commercial farms were
identified for each of the three size categories:
moderate, large, and very large.1 It was as-
sumed that the technology development and


'Small and part-time farms were not included because these
farm operators in general depend on off-farm employment for
their primary source of income.


adoption conditions in existence would be
those of the baseline environment outlined in
chapter 2.
Two techniques were used to analyze the ef-
fects of selected policy provisions and technol-
ogy on farms within each region. Information
was obtained on resource characteristics,
acreages devoted to specific crops, and historic
projected yields of crops eligible for farm pro-
gram provisions. These data were used to de-
velop resource characteristics of the three dif-
ferent farm sizes. Then a simulation model was
used to analyze the economic viability and
growth potential of each representative farm
for selected policy and technology advance
scenarios.
The following sections present the represent-
ative farms and major findings for the produc-
tion areas analyzed. Obviously, more areas
could have been analyzed, but neither time nor
the resources allocated to this study would per-
mit their inclusion. It is expected that the
results will apply in broad principle to the ma-
jor production region of which each area is a
part. It is important to remember that the
results of this analysis are mainly illustrative.
Thus, the relative results for the several farm
sizes and for the several alternative policy and
technology scenarios are probably more impor-
tant than any specific numbers generated by
the analysis.






36 A Special Report for the 1985 Farm Bill


THE CROP FARMS ANALYZED


Corn-Soybean Farms In the Corn Be*lt

The North Central Region of the United
States produces approximately 50 percent of
the total production of corn and soybeans. Rep-
resentative farms for this region are the three
farms from the corn-soybean cash grain area
of east central Illinois and the three farms from
the irrigated row crop area of south central
Nebraska.
The representative farm situations developed
and used in this analysis were constructed
from two basic data sources: 1) national cost-
of-production surveys by the U.S. Department
of Agriculture (USDA) in 1978 and 1983, and
2) farm record data collected and analyzed by
the Universities of Illinois and Nebraska. The
size of representative farms and acreages of
owned and rented cropland were developed
from the size distributions in the USDA cost-
of-production surveys. The very large farms ap-
proximate the largest 10 percent of farms in
the surveys, the large farms the 70th to 90th
percentiles, and the moderate farms the 40th
to 70th percentiles.
Financial status, as measured by net worth,
debt load (both intermediate-term and long-
term), and leverage ratio, differs dramatically
from farmer to farmer. Data from the most re-
cent Agricultural Finance Survey were used to
depict the beginning financial characteristics
for the six representative farms (tables 4-1 and
4-2).
All of the representative farms are well-
mechanized production units ranging from 640
to 2,085 acres of cropland, and all farms in-
clude a combination of owned and rented land.
Of the six representative farms, only the very
large units in each area employ full-time work-
ers. The other farms operate with a combina-
tion of family and part-time workers. The II-

'These representative farms were developed and analyzed in
the paper "Economic Impacts of Selected Farm Policies, Income
Tax Provisions, and Production Technology on the Economic
Viability of Corn-Soybean Farms in East Central Illinois and Ir-
rigated Row Crop Farms in South Central Nebraska," prepared
for the Office of Technology Assessment by W. B. Sundquist.


Table 4-1.-Financial Characteristics of Three
Representative Corn-Soybean Farms
in East Central Illinois'

Farm size
Moderate Large Very large


Cropland acres..........
Acres owned.............
Acres leased.............
Value of owned
real estate ($1,000)b....
Value of machinery ($1,000)
Long-term debt ($1,000) ..
Intermediate-term
debt ($1,000) ..........
Initial net worth ($1,000)c .
Leverage ratio (fraction) ..
Long-term debt/asset
(fraction) .............
Intermediate-term
debt/asset (fraction)....
Equity ratio (fraction) ....
Off-farm income ($1,000)..
Minimum family living
expenses ($1,000)......
Maximum family living
expenses ($1,000)......
Marginal propensity
to consume (fraction) ..


640
260
380
900.5
92.2
126.1
55.3
855.4
0.21
0.14
0.60
0.82
8.2
18.0
36.0
0.20


982
429
553
1,480.6
104.8
557.4
62.9
1,027.6
0.61


0.38
0.60
0.62
7.4
20.0
40.0
0.20


1,630
458
1,172
1,538.4
129.0
579.2
83.8
1,106.4
0.60
0.38
0.65
0.63
7.6
24.0
48.0
0.20


a A family size of four persons was assumed for the purposes of estimating family
labor supply and determining appropriate income tax rates.
b Includes land and buildings.
c May include assets other than land, buildings, and machinery.
SOURCE: Office of Technology Assessment.


linois farms have all of their cropland devoted
to cash crop production of corn and soybeans.
The Nebraska farms are cash crop operations
that combine both gravity and sprinkler tech-
nologies to irrigate corn and a small acreage
of soybeans. In addition, they produce a sub-
stantial acreage of grain sorghum under a
nonirrigated drylandd) regime. Production on
this dryland acreage tends to be somewhat
riskier than for the irrigated component of their
farming operations, but irrigated farming still
has some year-to-year yield variability, owing
to weather. Although a number of these ir-
rigated corn farms also produce some wheat
and/or corn silage, those enterprises have not
been included in the analysis.
The crop mix for the Nebraska farms is iden-
tical for all three farm sizes: irrigated corn (58.3
percent of cropland acres), irrigated soybeans
(6 percent), and dryland sorghum (35.7 per-






36 A Special Report for the 1985 Farm Bill


THE CROP FARMS ANALYZED


Corn-Soybean Farms In the Corn Be*lt

The North Central Region of the United
States produces approximately 50 percent of
the total production of corn and soybeans. Rep-
resentative farms for this region are the three
farms from the corn-soybean cash grain area
of east central Illinois and the three farms from
the irrigated row crop area of south central
Nebraska.
The representative farm situations developed
and used in this analysis were constructed
from two basic data sources: 1) national cost-
of-production surveys by the U.S. Department
of Agriculture (USDA) in 1978 and 1983, and
2) farm record data collected and analyzed by
the Universities of Illinois and Nebraska. The
size of representative farms and acreages of
owned and rented cropland were developed
from the size distributions in the USDA cost-
of-production surveys. The very large farms ap-
proximate the largest 10 percent of farms in
the surveys, the large farms the 70th to 90th
percentiles, and the moderate farms the 40th
to 70th percentiles.
Financial status, as measured by net worth,
debt load (both intermediate-term and long-
term), and leverage ratio, differs dramatically
from farmer to farmer. Data from the most re-
cent Agricultural Finance Survey were used to
depict the beginning financial characteristics
for the six representative farms (tables 4-1 and
4-2).
All of the representative farms are well-
mechanized production units ranging from 640
to 2,085 acres of cropland, and all farms in-
clude a combination of owned and rented land.
Of the six representative farms, only the very
large units in each area employ full-time work-
ers. The other farms operate with a combina-
tion of family and part-time workers. The II-

'These representative farms were developed and analyzed in
the paper "Economic Impacts of Selected Farm Policies, Income
Tax Provisions, and Production Technology on the Economic
Viability of Corn-Soybean Farms in East Central Illinois and Ir-
rigated Row Crop Farms in South Central Nebraska," prepared
for the Office of Technology Assessment by W. B. Sundquist.


Table 4-1.-Financial Characteristics of Three
Representative Corn-Soybean Farms
in East Central Illinois'

Farm size
Moderate Large Very large


Cropland acres..........
Acres owned.............
Acres leased.............
Value of owned
real estate ($1,000)b....
Value of machinery ($1,000)
Long-term debt ($1,000) ..
Intermediate-term
debt ($1,000) ..........
Initial net worth ($1,000)c .
Leverage ratio (fraction) ..
Long-term debt/asset
(fraction) .............
Intermediate-term
debt/asset (fraction)....
Equity ratio (fraction) ....
Off-farm income ($1,000)..
Minimum family living
expenses ($1,000)......
Maximum family living
expenses ($1,000)......
Marginal propensity
to consume (fraction) ..


640
260
380
900.5
92.2
126.1
55.3
855.4
0.21
0.14
0.60
0.82
8.2
18.0
36.0
0.20


982
429
553
1,480.6
104.8
557.4
62.9
1,027.6
0.61


0.38
0.60
0.62
7.4
20.0
40.0
0.20


1,630
458
1,172
1,538.4
129.0
579.2
83.8
1,106.4
0.60
0.38
0.65
0.63
7.6
24.0
48.0
0.20


a A family size of four persons was assumed for the purposes of estimating family
labor supply and determining appropriate income tax rates.
b Includes land and buildings.
c May include assets other than land, buildings, and machinery.
SOURCE: Office of Technology Assessment.


linois farms have all of their cropland devoted
to cash crop production of corn and soybeans.
The Nebraska farms are cash crop operations
that combine both gravity and sprinkler tech-
nologies to irrigate corn and a small acreage
of soybeans. In addition, they produce a sub-
stantial acreage of grain sorghum under a
nonirrigated drylandd) regime. Production on
this dryland acreage tends to be somewhat
riskier than for the irrigated component of their
farming operations, but irrigated farming still
has some year-to-year yield variability, owing
to weather. Although a number of these ir-
rigated corn farms also produce some wheat
and/or corn silage, those enterprises have not
been included in the analysis.
The crop mix for the Nebraska farms is iden-
tical for all three farm sizes: irrigated corn (58.3
percent of cropland acres), irrigated soybeans
(6 percent), and dryland sorghum (35.7 per-





Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 37


Table 4-2.-Financial Characteristics of Three
Representative irrigated Corn Farms
in South Central Nebraska*
Farm size
Moderate Large Very large
Cropland acres.......... 672 920 2,085
Acres owned............ 302 530 1,042
Acres leased............ 370 390 1,043
Value of owned
real estate ($1,000)b.... 477.7 838.4 1,648.3
Value of machinery ($1,000) 102.7 112.1 183.9
Long-term debt ($1,000) .. 123.2 102.0 291.1
Intermediate-term
debt ($1,000) ......... 40.1 53.7 98.0
Initial net worth ($1,000)c 448.3 839.0 1,463.1
Leverage ratio (fraction) .. 0.39 0.20 0.27
Long-term debtlasset
(fraction) ............. 0.26 0.12 0.18
Intermediate-term
debtlasset (fraction).... 0.39 0.48 0.53
Equity ratio (fraction) .... 0.72 0.84 0.79
Off-farm income ($1,000).. 8.2 8.2 9.7
Minimum family living
expenses ($1,000)...... 18.0 18.0 24.0
Maximum family living
expenses ($1,000)..... 36.0 36.0 48.0
Marginal propensity
to consume (fraction) .. 0.20 0.20 0.20
a A family size of four persons was assumed for the purposes of estimating family
labor supply and determining appropriate income tax rates.
b Includes land and buildings.
c May include assets other than land, buildings, and machinery.
SOURCE: Office of Technology Assessment.

cent). On the Illinois farms, the proportion of
corn to soybeans varies only slightly for the
three representative farms, with corn planted
on 52 to 55 percent of the cropland acreage and
soybeans on the balance.
For the Illinois farms, all cropland has the
same per-acre value, while the price of crop-
land on the Nebraska farms reflects the dif-
ferentials for four categories of land: 1) grav-
ity irrigated, 2) sprinkler irrigated, 3) dryland
with irrigation potential, and 4) dryland with-
out irrigation potential. Each of the three
Nebraska farms do, however, have the same
proportions of gravity irrigation, sprinkler ir-
rigation, and dryland acres.


Wheat Farms in the Southern Plains'

Approximately 65 percent of the U.S. wheat
production is produced in the Great Plains. For
the analysis of representative wheat farms,
farms were selected from the Southern Plains
region and are representative of wheat farms
in western Kansas, eastern Colorado, and the
Oklahoma and Texas Panhandle.
The three farms selected for the analysis are
the typical moderate farm in the region (1,280
acres), a large farm (1,900 acres), and a very
large farm (3,200 acres). The initial financial
characteristics for the three representative
farms are summarized in table 4-3. The propor-
tion of cropland owned by each farm was ob-
tained from the most recent Agricultural Fi-
nance Survey summarized for wheat farmers
in western Kansas, eastern Colorado, the Okla-
homa Panhandle, and the Northern High
Plains of Texas who had real estate debt.
Average long- and intermediate-term debt-to-
asset ratios from the Agricultural Finance
Survey were used to estimate initial values for
long- and intermediate-term debts. All three
wheat farms had about the same beginning
equity levels (75 percent) (table 4-3). Minimum
family living expenses were based on values
obtained from a Texas A&M survey that asked
for the minimum annual cash expenditure for
family living. The Agricultural Finance Survey
was used to obtain values of off-farm income
for the three representative farm operators.
A typical cropping pattern in the Southern
Plains is to irrigate 50 percent of all cropland
and to raise wheat on one-half of this irrigated
land. Grain sorghum is typically raised on the

'These representative farms were developed and analyzed in
the paper "Economic Impacts of Selected Policies and Tech-
nology on the Economic Viability of Three Representative Wheat
Farms in the Southern Plains," prepared for the Office of Tech-
nology Assessment by James W. Richardson.






38 A Special Report for the 1985 Farm Bill


Characteristics


Cropland acres owned ...
Cropland acres leased ...
Acres of pastureland owned
Value of owned
cropland ($1,000) ......
Value of owned pastureland
Value of machinery ($1,000)
Value of off-farm
investments ($1,000) ...
Beginning cash reserve
($1,000) ..............
Long-term debt ($1,000) ..
Intermediate-term debt
(1,000) ................
Initial net worth ($1,000) ..
Equity ratio (fraction) ....
Leverage ratio (fraction) ..
Long-term debtlasset
(fraction) ............
Intermediate term
debt/asset (fraction)....
Off-farm income ($1,000)..
Minimum family living
expenses ($1,000)......
Maximum family living
expenses ($1,000)......
Marginal propensity
to consume (fraction) ..


Farm size (acres)
Moderate Large Very large
640 840 1,400
640 1,080 1,800
120 220 360

296.0 388.5 647.5
29.4 53.9 88.2
241.9 352.2 477.2
37.3 49.0 53.5
10.0 12.0 20.0
60.2 86.3 143.5
83.2 126.5 171.3
470.3 642.3 970.7
0.77 0.75 0.75
0.31 0.33 0.33

0.19 0.20 0.20


0.34
12.4
18.0
40.0


0.36
9.8
20.0
50.0


0.36
9.0
23.0
50.0


0.25 0.25 0.25


SOURCE: Office of Technology Assessment.


other half of the irrigated cropland. Wheat is
generally also raised on the portion of the
cropland that is not irrigated. This cropping
pattern was assumed for all three farms.
Numerous crop share arrangements prevail
in the region for leased land. However, these
arrangements generally involve the producer
paying the landlord about 25 percent of the
crop and the landlord paying none of the
production and harvesting costs. This crop
share arrangement was assumed for all leased
cropland.

General Crop Farms in tbe
Delta Region of Mississippi4

The Mississippi Delta is an excellent region
for analysis of general crop farms. Farms in

4These representative farms were developed and analyzed in
the paper "Economic Effects of Selected Policies and Technol-
ogy on the Economic Viability of General Crops Farms in the
Delta Region of Mississippi," prepared for the Office of Tech-
nology Assessment by B. R. Eddleman.


Table 4-3.-Financial Characteristics of Three
Representative Wheat Farms by Size
in the Southern Plains


this area can produce a variety of crops not
possible in other parts of the United States. The
representative farms in this region produce cot-
ton, rice, soybeans, and wheat (or other small
grains).
The three representative farms developed for
this study are a moderate farm (1,443 acres),
a large farm (3,119 acres), and a very large farm
(6,184 acres). Table 4-4 provides a summary of
the financial and resource characteristics for
the three representative farms. The long- and
intermediate-term debt-to-asset ratios for the
1,443-acre farm and the 3,119-acre farm were
obtained from USDA's Agricultural Finance
Survey and adjusted to reflect the equity levels
as reported from a 1983 mail survey of farms

Table 4-4.-Financial and Resource Characteristics
for Three Representative General Crops Farms
in the Delta of Mississippi, 1983

Farm size
Characteristics Moderate Large Very large
Age of farm operator* .... 44 44 44
Family sizea ............ 4 4 4
Cropland acres owned ... 533 1,419 3,064
Cropland acres leased ... 910 1,700 3,120
Acreage of principal crops
in 1983:
Cotton ............... 395 1,088 2,250
Rice ................. 305 574 871
Soybeans............. 640 1,190 2,539
Wheat (or other
small grains)........ 82 247 180
Value of owned cropland
($1,000)............... 799.5 2,128.5 4,596.0
Value of farm machinery
($1,000)............... 378.9 786.7 1,209.8
Value of off-farm
investments ($1,000) ... 129.1 210.3 358.7
Beginning cash reserve
($1,000) .............. 31.9 71.1 141.6
Long-term debt ($1,000) .. 331.4 840.8 1,640.8
Intermediate-term debt
($1,000) ............... 243.8 413.0 574.7
Net worth ($1,000) ....... 748.6 1,921.5 4,047.5
Total equity to assets
(fraction) ............. 0.56 0.60 0.64
Long-term debt/asset
(fraction) ............. 0.41 0.40 0.36
Intermediate-term
debt/asset (fraction).... 0.64 0.52 0.48
Off-farm income ($1,000).. 18.3 18.2 36.0
Minimum family living
expenses ($1,000)...... 18.0 24.0 30.0
Maximum family living
expenses ($1,000)...... 27.0 36.0 45.0
Marginal propensity
to consume (fraction) .. 0.25 0.25 0.25
a Values for the age and family size variables assumed for simulating the effects
of alternative farm program provisions for the representative farms.
SOURCE: Office of Technology Assessment.






Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 39


in the Delta. These debt ratios are the average
for part-owner general crops farms in the
Mississippi Delta region that had debt on real
estate in 1979. Financial ratios for the largest
farm were developed by extending the ratios
on a per-acre basis for a 3,457-acre farm, as re-
ported in the most recent Agricultural Finance
Survey, and were adjusted by the equity levels
reported for the largest farm size group.
The mix of acreages planted in each crop
changes by farm size. In general, the acreage
planted in cotton and soybeans increased rela-
tive to the acreage planted in rice and wheat
as farm size increased. The moderate farm
planted 73 percent of tillable cropland in cot-
ton and soybeans, while the large and the very
large farm planted 89 and 82 percent, respec-
tively, of tillable cropland in cotton and soy-
beans. In the analysis, as the farm was allowed
to grow in size to the next largest farm size,
the proportion of cropland planted to each crop
was changed to reflect these relative differ-
ences in crop mix.

Cotton Farms In the Texas
Southern High Plains'
Cotton is an important commodity in the
United States, and over one-half of the cotton
produced can be found in the Southern High
Plains of Texas. The three farms selected for
analysis are a typical moderate farm in the re-
gion (1,088 acres), a large farm (3,383 acres),
and a very large farm (5,570 acres). These size
farms account for 31 percent of the farms and
'These representative farms were developed and analyzed in
the paper "Economic Impacts of Selected Policies and Tech-
nology on the Economic Viability of Three Representative Cot-
ton Farms in the Texas Southern High Plains," prepared for the
Office of Technology Assessment by James W. Richardson.


62 percent of the cotton lint produced in the
Texas Southern High Plains.
Table 4-5 provides a summary of the demo-
graphic and financial characteristics for the
three representative cotton farms used in the
present study. The long- and intermediate-term
debt-to-asset ratios for the moderate farm were
obtained from USDA's Agricultural Finance
Survey. These debt ratios are the average for
part-owner cotton farmers in the Texas High
Plains who had debt on real estate in 1979.

Table 4.5.-Financial Characteristics of Three
Representative Cotton Farms by Size In the
Texas Southern High Plains
Farm size
Characteristics Moderate Large Very large
Age of operator ......... 42 45 51
Acres owned............ 381 1,048 3,453
Acres leased............ 707 2,335 2,117
Value of owned
cropland ($1,000) ..... 222.4 611.7 2,015.4
Value of machinery
($1,000)............... 144.5 420.8 713.9
Value of off-farm
investments ($1,000) ... 59.0 110.0 213.7
Beginning cash reserve
($1,000) ............... 16.7 52.0 85.5
Long-term debt ($1,000) .. 61.1 120.9 488.7
Intermediate-term
debt ($1,000) ......... 98.3 203.6 475.4
Initial net worth ($1,000) 275.0 854.8 2,032.3
Equity ratio (fraction) .... 0.62 0.72 0.67
Leverage ratio (fraction) .. 0.61 0.40 0.49
Long-term debt/asset
(fraction) ............. 0.27 0.20 0.24
Intermediate-term
debt/asset (fraction).... 0.68 0.48 0.67
Off-farm income ($1,000).. 16.0 0.0 0.0
Minimum family living
expenses ($1,000)...... 15.2 29.1 38.0
Maximum family living
expenses ($1,000)...... 50.0 50.0 60.0
Marginal propensity
to consume (fraction) .. 0.25 0.25 0.25
SOURCE: Office of Technology Assessment.


POLICY AND TECHNOLOGY SCENARIOS


The three representative farms for each pro-
duction region were analyzed for the period
1983-92 under alternative policy scenarios." Six

'The current version of the Firm Level Income Tax and Farm
Policy Simulator (FLIPSIM V), developed by James W. Richard-
son and Clair j. Nixon, was used to simulate the three repre-
sentative farms in each region.


farm policy scenarios (including a continuation
of the 1981 farm bill), an income tax provision
scenario, two financial stress scenarios, a tech-
nology option, and a new-entrant scenario
were analyzed for each farm. All assumptions
and policy values associated with each sce-
nario were held constant across farm sizes to






Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 39


in the Delta. These debt ratios are the average
for part-owner general crops farms in the
Mississippi Delta region that had debt on real
estate in 1979. Financial ratios for the largest
farm were developed by extending the ratios
on a per-acre basis for a 3,457-acre farm, as re-
ported in the most recent Agricultural Finance
Survey, and were adjusted by the equity levels
reported for the largest farm size group.
The mix of acreages planted in each crop
changes by farm size. In general, the acreage
planted in cotton and soybeans increased rela-
tive to the acreage planted in rice and wheat
as farm size increased. The moderate farm
planted 73 percent of tillable cropland in cot-
ton and soybeans, while the large and the very
large farm planted 89 and 82 percent, respec-
tively, of tillable cropland in cotton and soy-
beans. In the analysis, as the farm was allowed
to grow in size to the next largest farm size,
the proportion of cropland planted to each crop
was changed to reflect these relative differ-
ences in crop mix.

Cotton Farms In the Texas
Southern High Plains'
Cotton is an important commodity in the
United States, and over one-half of the cotton
produced can be found in the Southern High
Plains of Texas. The three farms selected for
analysis are a typical moderate farm in the re-
gion (1,088 acres), a large farm (3,383 acres),
and a very large farm (5,570 acres). These size
farms account for 31 percent of the farms and
'These representative farms were developed and analyzed in
the paper "Economic Impacts of Selected Policies and Tech-
nology on the Economic Viability of Three Representative Cot-
ton Farms in the Texas Southern High Plains," prepared for the
Office of Technology Assessment by James W. Richardson.


62 percent of the cotton lint produced in the
Texas Southern High Plains.
Table 4-5 provides a summary of the demo-
graphic and financial characteristics for the
three representative cotton farms used in the
present study. The long- and intermediate-term
debt-to-asset ratios for the moderate farm were
obtained from USDA's Agricultural Finance
Survey. These debt ratios are the average for
part-owner cotton farmers in the Texas High
Plains who had debt on real estate in 1979.

Table 4.5.-Financial Characteristics of Three
Representative Cotton Farms by Size In the
Texas Southern High Plains
Farm size
Characteristics Moderate Large Very large
Age of operator ......... 42 45 51
Acres owned............ 381 1,048 3,453
Acres leased............ 707 2,335 2,117
Value of owned
cropland ($1,000) ..... 222.4 611.7 2,015.4
Value of machinery
($1,000)............... 144.5 420.8 713.9
Value of off-farm
investments ($1,000) ... 59.0 110.0 213.7
Beginning cash reserve
($1,000) ............... 16.7 52.0 85.5
Long-term debt ($1,000) .. 61.1 120.9 488.7
Intermediate-term
debt ($1,000) ......... 98.3 203.6 475.4
Initial net worth ($1,000) 275.0 854.8 2,032.3
Equity ratio (fraction) .... 0.62 0.72 0.67
Leverage ratio (fraction) .. 0.61 0.40 0.49
Long-term debt/asset
(fraction) ............. 0.27 0.20 0.24
Intermediate-term
debt/asset (fraction).... 0.68 0.48 0.67
Off-farm income ($1,000).. 16.0 0.0 0.0
Minimum family living
expenses ($1,000)...... 15.2 29.1 38.0
Maximum family living
expenses ($1,000)...... 50.0 50.0 60.0
Marginal propensity
to consume (fraction) .. 0.25 0.25 0.25
SOURCE: Office of Technology Assessment.


POLICY AND TECHNOLOGY SCENARIOS


The three representative farms for each pro-
duction region were analyzed for the period
1983-92 under alternative policy scenarios." Six

'The current version of the Firm Level Income Tax and Farm
Policy Simulator (FLIPSIM V), developed by James W. Richard-
son and Clair j. Nixon, was used to simulate the three repre-
sentative farms in each region.


farm policy scenarios (including a continuation
of the 1981 farm bill), an income tax provision
scenario, two financial stress scenarios, a tech-
nology option, and a new-entrant scenario
were analyzed for each farm. All assumptions
and policy values associated with each sce-
nario were held constant across farm sizes to





40 A Special Report for the 1985 Farm Bill


allow direct comparison of their impacts on
different size farms. Appendix A contains sum-
mary tables of the analysis for each farm size
by region.

Farm Policy Scenarios
Current Policy
The current policy scenario involves con-
tinuation through 1992 of current income tax
provisions and of the price supports, income
support, and supply control programs of the
1981 farm bill. In addition, it is assumed that
annual mean crop yields for the three repre-
sentative farms will increase as new technol-
ogies are introduced and adopted by farmers
in the baseline technology environment. For
this policy scenario it is assumed that the fol-
lowing farm policies are in effect:
The Commodity Credit Corporation (CCC)
loan program is available to producers for
corn, cotton, rice, sorghum, soybeans, and
wheat.
A 3-year, indirect, farmer-owned reserve
(FOR) is available for feed grains and
wheat.'
An acreage diversion/set-aside program is
in effect for 1983-85, using the actual acre-
age reduction levels and diversion pay-
ment rates specified for these years.
A target price-deficiency payment pro-
gram is available for corn, cotton, rice,
sorghum, and wheat in all years.
The $50,000-payment limitation for defi-
ciency and diversion payments is in effect
and is effective on the farm as specified.
Farms of all sizes are eligible to participate
in these farm program provisions.
Values for loan rates, target prices, diversion
rates, and diversion payment rates for 1983 and
1984 are set at their actual values, expressed
in 1982 dollars. Values for these variables for
1985 are set at their respective levels announced
on or before September 14, 1984, by Secretary

'The 1977 farm bill established FOR as a 3-year extension of
the CCC loan after grain had been in the regular loan for 9
months. Stocks remain in the farm operator's control until the
Secretary of Agriculture authorizes release.


of Agriculture Block. Loan rates and target
prices for 1985 are held constant through 1992.
No acreage reduction program was assumed
to be in effect after 1985.
It was assumed that the following options for
depreciating machinery and calculating in-
come taxes are used for the current policy
scenario:
Machinery, livestock, and buildings placed
in use prior to 1981 are depreciated using
the double declining balance method.
Machinery, livestock, and buildings placed
in use after 1980 are depreciated using an
accelerated cost recovery method.
The operator elects to claim first-year ex-
pensing for all depreciable items placed
into use after 1980.
The operator elects to take maximum in-
vestment tax credit (ITC) and thus reduce
the basis for all depreciable assets placed
into service after 1980.
The operator adjusts crop sales across tax
years to reduce current-year taxes.
The operator may use either the regular
income tax computation or income aver-
aging to calculate Federal income tax
liabilities.
There is no maximum interest deduction
for calculating taxable income.
The actual self-employment tax rates and
maximum income levels subject to this tax
for 1983 and 1984 are used. Announced
values for these variables in 1985-86 were
used, and the 1986 values were held con-
stant through 1992.
The operator elects to trade in old machin-
ery on new replacements at the end of
each item's economic life.
Results Expected.-Since this policy in-
cludes price supports, income supports, and
supply control programs to maintain and sta-
bilize prices and farm income at a reasonable
level and reduce the price and income risks,
it is anticipated that all farms under this pro-
gram will have a higher probability of remain-
ing solvent over the 10-year planning horizon,
have higher net farm incomes, and have stronger
financial positions.






Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 41


Results Obtained:
Except for Texas cotton farms, all farms
in the other four regions had a 100-percent
probability of remaining solvent over the
10-year period. For Texas cotton farms, the
probability of survival ranged from 92 per-
cent for the moderate farms to 94 percent
for very large farms.
All farms in four of the five regions in-
creased their absolute net worth by the end
of the period with very large farms increas-
ing more than the moderate farms. The
two smaller farms in Illinois experienced
a loss in net worth over the period, while
the largest farm experienced a 14.5 percent
increase in real net worth.
On the average, all three farms were able
to grow by purchasing and leasing crop-
land. Moderate farms grew in size at a
faster rate than the very large farms. The
moderate and large grain farms grew at ap-
proximately the same rate of growth.
Average annual net farm incomes for all
farms substantially benefited by the pres-
ence of price and income supports in the
current policy. Removal of these program
provisions resulted in negative average an-
nual net farm incomes for farms in all re-
gions except Illinois. (Illinois net farm in-
comes did not fall below zero because a
large portion of cropland is devoted to soy-
beans, and this crop does not receive a
deficiency payment.)
Ratios of net farm income to total Govern-
ment payments reveal that, across all re-
gions, the moderate farms are more depen-
dent on Government payments to maintain
their incomes than are the very large
farms.

Prike Suppots
The price supports program is designed to
prevent prices from falling below a certain
level and to stabilize prices through the CCC
nonrecourse loans at established loan rates to
farmers. Such loans, plus interest and storage
cost, can be repaid within 9 to 12 months when
the commodity is sold on the cash market. If
the market is not favorable for a farmer to sell


the commodity and repay his loan, CCC ac-
cepts the commodity in full payment of the
loan.
CCC releases its stock to the market when
prices are high and withdraws stocks from the
market when prices are low. Thus, the program
also stabilizes prices.
Results Expected:
Since price supports stabilize prices and
prevent prices from falling below the loan
rate, this program should increase farm
income and reduce the price risk for
farmers.
All farms should have a higher probabil-
ity of survival, greater net present value,"
and higher net farm incomes than they
would have had without the program.
Results Obtained:
Price supports increased the probability of
survival for all three representative farms
in all regions.
Net farm incomes for these farms also in-
creased with the price supports program.
In all regions, the larger the farms, the
greater the increase in net farm incomes.
With increased farm incomes and reduced
price risk, all three farms in all regions ex-
perienced increases in real net worth with
the price supports program.
Average ending farm sizes were not sig-
nificantly different as a result of the price
support program.

come S rpports
Income supports are accomplished through
deficiency payments and the target price. Defi-
ciency payments are paid to farmers to make
up the difference between a price determined

The concept of present value is used to help measure the profit
potential of an investment decision. Simply put. a dollar today
is worth more than a dollar in the future because today's dollar
can be invested and can accrue interest. Thus, the present value
of a specified amount of money payable at a specified future
date is the amount of money that one would have to invest now
in order to have that future amount by that future date. In analyz-
ing an investment over several periods, a positive present value
would indicate an economically attractive decision; a negative
present value would not.


38-857 0 85 7 : QL 3





42 A Special Report for the 1985 Farm Bill


to achieve a politically acceptable income level
(target price) and the average market price.
Deficiency payments are made on each farm's
base acres and farm program yield. The farm
program yield is based on each farm's yield his-
tory. Target prices were set initially to reflect
an average cost of production.
Deficiency payments were initiated to raise
and stabilize farmer incomes to the level of the
nonfarm population while allowing farm prices
to be competitive in the export market. Total
annual Government payments (deficiency and
diversion) were limited to $50,000.
Results Expected:
The major impact of deficiency payments
should be to increase the income level of
producers who participate in the farm pro-
gram. Since the payments are based on the
quantity of eligible production, large-scale
producers benefit more than small-scale
producers, up to the $50,000-payment
limitation.
Deficiency payments also reduce income
risk for producers, increase their ability to
obtain financing, and thus increase the
probability of all farms remaining solvent.
Results Obtained:
The deficiency payment program increased
the probability of survival more for mod-
erate Texas cotton farms than for the very
large farm. For farms of other regions, the
probability of survival was 100 percent,
with or without income support.
Income supports increased net farm in-
comes substantially for all farms, often
moving net farm incomes from negative
to positive.
Income supports enhanced net farm in-
comes of all farms more than the price sup-
port program.
The presence of the $50,000-payment
limitation causes the income support pro-
gram to benefit moderate farms relatively
more than very large farms. In contrast,
the price support program results in a
greater relative advantage for large and
very large farms.


With reduced income risk and greater
farm incomes under the income support
program, all farms improved real wealth,
and average after-tax net present value in-
creased for all farms.
Income supports increased the average
ending farm size for all farms. Average
ending farm size increased at a faster rate
for moderate farms than for very large
farms.
Removal of the $50,000 limitation on defi-
ciency payments benefited larger farms
more than smaller farms. Big winners of
this program were big farms in Texas and
Mississippi. In Texas, for example, when
the $50,000-payment limitation was re-
moved, average annual net farm income
increased $3,600, $50,000, and $104,000
for moderate, large, and very large farms,
respectively.
Increased farm income strengthened the
financial positions of larger farms, increas-
ing their ability to obtain more financing.
All three representative farms, especially
the very large farms, had increased net
worth at the end of the 10-year period. For
example, removal of the $50,000 limitation
increased the ending net worth of the mod-
erate Texas cotton farm by $37,000, of the
large Texas farm by $441,000, and of the
very large Texas farm by $1,019,000.

Supply Ceotrol Polky
(Acrege Reduction Program)
The objective of acreage reduction programs
is to reduce the quantity produced and thus the
supply of a given commodity. Acreage reduc-
tion consists of an acreage set-aside and/or
acreage diversion that is generally voluntary.
Acreage set-aside programs require that par-
ticipating farmers idle a percentage of their
crop base acres so that they are eligible for
other program benefits. Acreage diversion pro-
grams pay producers a given amount per acre
to idle a percentage of their base acres. A
farmer's base acres are determined by the pro-
duction history of the crop.
For this analysis the provisions of the cur-
rent policy were modified by adding a 15-






Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 43


percent set-aside with a 5-percent diversion for
corn, cotton, rice, sorghum, and wheat in 1986-
92. Normal slippage* (30 percent for corn and
70 percent for all other crops) and program par-
ticipation rates were used to estimate the re-
sulting real increase in mean prices for these
crops in 1986-92. All other provisions of the
current policy were used without change.
Results Expected:
To the extent that acreage reduction pro-
grams reduce production, they reduce
supply and stocks and increase prices do-
mestically for those commodities. Higher
prices will result in higher total and net
incomes for all farm sizes. Farms that par-
ticipate in diversion payments also bene-
fit from the program through increased
cash receipts, up to the $50,000 limit.
Slippage in the programs reduces the pro-
grams' effectiveness, increases the farms'
net present value, and increases farm size.
Higher incomes lead to more disposable
income for debt repayment and retained
earnings for accelerating farm growth.
Farm operators' average net present value
should increase.
Faster rates of growth should be experi-
enced by the farms because of increased
cash accumulation, repayment capacity,
and equity in existing land assets.
Results Obtained:
Imposing a 20-percent acreage reduction
program increased the average net present
value and ending net worth for all three
farms in all regions except for the large
farm in Illinois.
Imposing a 20-percent acreage reduction
to existing farm programs resulted in a 20-
to 300-percent increase in net farm income
for almost all farms.
Average ending farm size for all three farm
sizes increased relative to the initial farm
size.

*Slippage is the difference between the percent of production
decrease and the percent of acreage reduced. These two per-
centages are different because farmers tend to set aside mar-
ginal lands in Government programs or intensify the cultiva-
tion of remaining land.


Imposing additional supply controls to ex-
isting farm programs does not substan-
tially change the rate of growth or ending
farm size of all farms. Moderate farms con-
tinued to grow at a faster rate than larger
farms.
Eliminating slippage reduced the rate of
growth relative to that in the current pol-
icy for all three farm sizes.
The less slippage in an acreage reduction
program, the smaller the increase in aver-
age net present value for all three farm
sizes.

ne Farm Pregram
In the no-farm-program scenario, all farm
programs outlined for the current policy were
eliminated for all 10 years of the planning
horizon. In this essentially free market envi-
ronment, farm prices and income are very
unstable because: 1) production varies, owing
to weather and biological factors; and 2) de-
mand for farm products changes. The inelastic
nature of supply and demand for farm prod-
ucts makes farm prices particularly unstable.
The variability in prices and incomes has both
favorable and unfavorable aspects. From a
favorable perspective, the movement in prices
reflects changes in supply and demand condi-
tions and is a signal for production regarding
market needs. However, when prices become
highly unstable, the signals may be misinter-
preted and mistakes may be made in produc-
tion and marketing decisions. The result fre-
quently is misallocation of resources. In
addition, variability in price and income in-
creases the risk and uncertainty to the farm
business.
Results Expected:
Average farm incomes will be less with no
loans or price supports because the floor
on prices received for these commodities
has been removed, allowing prices to fluc-
tuate freely.
Net present value will be lower and more
unstable than with price and income
supports.
Net worth of farms will decline because
the market value of cropland will be less,


-





44 A Special Report for the 1985 Farm Bill


since there are no benefits from the pro-
grams to be capitalized into the land.
* Farms will have less probability of survival
because of increased instability in prices
for crops. The impact will be more pro-
nounced for highly leveraged farms that
cannot survive without price and/or in-
come support and for smaller farms that
cannot survive with high price risk.
Results Obtained:
* Removing all farm programs reduced the
probability of survival for all three farm
sizes in cotton and wheat regions, relative
to the base policy. The probability of sur-
vival fell more for the moderate farms in
these regions than for the very large farms.
For example, in cotton the moderate
farm's chance of remaining solvent for 10
years decreased from 92 to 42 percent; the
chance for the solvency of very large farms
decreased from 94 to 78 percent.
* The probability of having a positive after-
tax net present value declined significantly
for all farm sizes in each of the four re-
gions except the Mississippi Delta. For ex-
ample, in the Southern Plains the probabil-
ity of a positive net present value for the
moderate farm declined to about 10 per-
cent. In most cases the very large farms
had a higher probability of positive net
present value than the moderate farms.
The probability of a positive net present
value was 100 percent in the Mississippi
Delta without the farm program, owing
primarily to diversification of crop produc-
tion and the reduced relative yield vari-
ability in the Delta compared with that of
the other regions.
* Ending net worth declined for all three
farm sizes in all regions. In most regions
the absolute decline in net worth was
greater for the large and very large farms
than for the moderate farms. For example,
the large and very large Texas cotton farms
experienced a $743,000 and $1,100,800 de-
cline in net worth, respectively, from that
of the current policy, while the moderate
farms' net worth declined $396,800. The
ending net worth of the Mississippi Delta


farms declined the least of all regions be-
cause a significant portion of crop acre-
age was devoted to soybeans.
*In the absence of farm programs, all three
farm sizes continued to grow in all regions,
but at a much slower rate than under the
current policy. For example, farms in the
Southern Plains declined from the current
policy on average about 20 percent in end-
ing farm size.


Target Farm Program Benefit
For the target farm program benefits sce-
nario, all farm program and income tax provi-
sions of the current policy were used except
that large farms were not eligible to participate
in farm program provisions. Farms producing
more than 300,000 dollars' worth of program
commodities (corn, cotton, rice, sorghum, soy-
beans, and rice) valued at their localized loan
rate were not permitted to participate directly
in the program provisions (CCC loan, FOR, tar-
get price/deficiency payments, and set-aside
diversions). Mean prices and relative variabil-
ity in prices were not adjusted because a suf-
ficient number of "small" farms were assumed
to participate in the farm program for the price
support actions of the CCC loan and FOR to
function normally.

Results Expected:
Findings for moderate farms will be the
same as the findings for the current policy.
Large and very large farms exempted from
the programs will receive indirect benefits
from other farms participating in the
programs.
Compared with the no-farm-program sce-
nario, the following should be observed for
large and very large farms:
-Net present value will be higher and
more stable.
-Net worth of these farms will be greater.
-Farms will have a greater probability of
survival because of the increased sta-
bility in prices.
-Farms will be larger because of increased
income and large repayment capacity.





Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 45


Results Obtained:
Moderate farms consistently producing less
than $300,000 in program crops exhibit the
same growth rates, net farm incomes, and
ending financial positions as they do under
the current policy.
Farms that grow beyond or are initially
larger than the $300,000 threshold level of
sales experience lower average Government
payments, net farm incomes, average net
present values, and net worths than under
the current policy, owing to targeting pro-
gram benefits.
The larger the farm, the greater the reduc-
tion in average ending acres from the cur-
rent policy for farms in the Southern Plains,
Nebraska, and Illinois. Moderate grain farms
in these regions experienced no real change
in average ending farm size because of their
level of total sales being less than $300,000.
Growth rates for the very large farms in
Texas and the Delta were similar to those
experienced under the no-farm-program op-
tion. The moderate and large farms in the
Delta experienced reduced rates of growth
relative to the very large farms. A similar
relationship was observed between the large
and very large cotton farms in Texas. The
reason for these different rates of growth is
that the very large farms in these regions are
less dependent on farm programs than are
smaller size farms.

Tax Policy Scenarios
The Federal income tax provisions in place
for the current policy were made more restric-
tive in the reduced income tax benefits and
base farm program scenario. All farm policy
provisions of the current policy were left un-
changed. The more restrictive Federal income
tax provisions included the following:
Machinery, livestock, and buildings were
depreciated using the straight-line cost
recovery method.
First-year expensing provisions were elim-
inated for all depreciable items.
Maximum ITC provisions were eliminated.


* The maximum annual interest expense
that could be used to reduce taxable in-
come was $15,600.
* The operator was required to sell obsolete
machinery upon disposition rather than
trading it in on new replacements, thus
forcing recapture of excess depreciation
deductions.
Results Expected:
* Making Federal income tax policies less
favorable tends to increase income tax
payments by reducing tax deductions. Net
cash farm income is not affected directly
in the first 4 to 6 years. After that, inter-
est income usually becomes a factor, and
higher tax payments the first 4 years re-
duce cash available for interest income in
later years.
* The farm operator will have lower tax
deductions and tax credits when machin-
ery is replaced. The length of time machin-
ery is kept will not likely be shortened from
the current policy because machinery was
replaced based on its normal economic
life, not its depreciation life.
* Reducing tax deductions and tax credits
will mean greater annual income tax
payments, resulting in greater cash flow
requirements and reduced ending cash re-
serves. Net present value will likely be re-
duced because of lower retained earnings
and the slower accumulation of wealth.
Results Obtained:
* Adoption of a more restrictive set of Fed-
eral income tax provisions had little im-
pact on farm survival.
* Increasing the Federal tax burden on
farmers reduced the average annual rate
of growth in farm size about the same for
all sizes of farms in each region. Average
ending farm size was about. 8 percent less
than that for the current policy for large
and very large farms and about 4 percent
less for moderate farms.
* The more restrictive income tax provisions
reduced the propensity to grow through
purchasing cropland and increased the





46 A Special Report for the 1985 Farm Bill


propensity to lease cropland for growth.
For example, in the Mississippi Delta the
growth rate in owned cropland for the
moderate farm was reduced to 4 percent,
and its rate of growth in leased cropland
increased by 49 percent.
The changes in the tax provisions resulted
in reduced annual net farm incomes on all
sizes of farms in all regions. The reduction
in net farm income was greater for the
very large farm relative to the moderate
farm because the very large farm had more
depreciable items affected by changes in
depreciation rules, investment tax credit,
and capital gains treatment of sales of used
machinery.

Technology coenarios
To determine the impact of technology on
structure, selected farm policy scenarios were
simulated, assuming increases in mean yields
of crops only from the use of existing technol-
ogies. A comparison of these simulated results
with the previous farm policy scenarios, which
included increases in mean yields from emerg-
ing technologies, indicates the impact of new
technology on structure. Three policy alterna-
tives were analyzed under these conditions.
They were the base farm policy, which con-
tinues all provisions of the 1981 farm bill, the
elimination of income support provisions, and
the elimination of all farm program provisions.
Results Expected:
Technology advance would have the great-
est impacts on wealth accumulation, net
farm income, and rate of growth in acres
controlled for very large farms that adopted
the technology first and had it in use over
a longer period of time.
The greater the increase in productivity
through technology advance the greater
should be the rate of increase in wealth,
net farm income, and rate of growth in
acres controlled.
Technology advance in the presence of
price and income support programs would
have greater impacts on growth in real
wealth, farm acres controlled, and net


farm income than it would in the absence
of these programs.
Results Obtained:
Farm commodity policies had more effect
on the final amount of acres controlled
than did technology advance, across all
sizes of farms in all regions.
Technology advance had little impact on
the final amount of acres controlled in all
regions. Yield-enhancing benefits from
emerging technologies increased average
final farm size from 0 to 2 percent in the
Delta, Illinois, and Texas and from 6 to 10
percent in the Southern Plains. The great-
est increase in farm size occurred on very
large farms in the Southern Plains under
the current policy scenario because these
farms are principally wheat producers,
and the greatest increases in yields were
predicted by OTA to occur for wheat.
Small increases in final farm size for the
other regions can be explained by the rela-
tively smaller increases in yields (based on
the results of OTA workshops for corn,
soybeans, cotton, and rice).
Farms did not exhibit any appreciably
larger rates of growth in real wealth and
farm size under price and income support
programs than under open market condi-
tions. But in the presence of technology ad-
vance, annual net farm income increased
relatively more under the price and in-
come support program than under open
market conditions.
Flows of new technology for all commod-
ities in all regions were found to increase
annual net farm incomes relatively more
than real wealth and ending farm acreage
across all sizes of farms. Net farm income
was increased relatively more for the very
large farms than for the moderate and
large farms, across all farm policies
evaluated.

Implications for the 1985 Farm Bill
* Farm programs have major impacts on rates
of growth in farm size, wealth, and incomes
of commercial farmers.





46 A Special Report for the 1985 Farm Bill


propensity to lease cropland for growth.
For example, in the Mississippi Delta the
growth rate in owned cropland for the
moderate farm was reduced to 4 percent,
and its rate of growth in leased cropland
increased by 49 percent.
The changes in the tax provisions resulted
in reduced annual net farm incomes on all
sizes of farms in all regions. The reduction
in net farm income was greater for the
very large farm relative to the moderate
farm because the very large farm had more
depreciable items affected by changes in
depreciation rules, investment tax credit,
and capital gains treatment of sales of used
machinery.

Technology coenarios
To determine the impact of technology on
structure, selected farm policy scenarios were
simulated, assuming increases in mean yields
of crops only from the use of existing technol-
ogies. A comparison of these simulated results
with the previous farm policy scenarios, which
included increases in mean yields from emerg-
ing technologies, indicates the impact of new
technology on structure. Three policy alterna-
tives were analyzed under these conditions.
They were the base farm policy, which con-
tinues all provisions of the 1981 farm bill, the
elimination of income support provisions, and
the elimination of all farm program provisions.
Results Expected:
Technology advance would have the great-
est impacts on wealth accumulation, net
farm income, and rate of growth in acres
controlled for very large farms that adopted
the technology first and had it in use over
a longer period of time.
The greater the increase in productivity
through technology advance the greater
should be the rate of increase in wealth,
net farm income, and rate of growth in
acres controlled.
Technology advance in the presence of
price and income support programs would
have greater impacts on growth in real
wealth, farm acres controlled, and net


farm income than it would in the absence
of these programs.
Results Obtained:
Farm commodity policies had more effect
on the final amount of acres controlled
than did technology advance, across all
sizes of farms in all regions.
Technology advance had little impact on
the final amount of acres controlled in all
regions. Yield-enhancing benefits from
emerging technologies increased average
final farm size from 0 to 2 percent in the
Delta, Illinois, and Texas and from 6 to 10
percent in the Southern Plains. The great-
est increase in farm size occurred on very
large farms in the Southern Plains under
the current policy scenario because these
farms are principally wheat producers,
and the greatest increases in yields were
predicted by OTA to occur for wheat.
Small increases in final farm size for the
other regions can be explained by the rela-
tively smaller increases in yields (based on
the results of OTA workshops for corn,
soybeans, cotton, and rice).
Farms did not exhibit any appreciably
larger rates of growth in real wealth and
farm size under price and income support
programs than under open market condi-
tions. But in the presence of technology ad-
vance, annual net farm income increased
relatively more under the price and in-
come support program than under open
market conditions.
Flows of new technology for all commod-
ities in all regions were found to increase
annual net farm incomes relatively more
than real wealth and ending farm acreage
across all sizes of farms. Net farm income
was increased relatively more for the very
large farms than for the moderate and
large farms, across all farm policies
evaluated.

Implications for the 1985 Farm Bill
* Farm programs have major impacts on rates
of growth in farm size, wealth, and incomes
of commercial farmers.





Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 47


* Most farm program benefits are capitalized
into land values and net worth. Very large
farms increase their net worth significantly
more than moderate farms under current
farm programs.
* Moderate farms are much more dependent
on farm programs to maintain their incomes
than are very large farms.
* Income supports provide significantly greater
benefits to moderate farms than to very


large farms. (In contrast price supports pro-
vide more wealth and growth benefits to
very large farms than to moderate farms.)
Targeting of income supports to moderate
farms is an effective policy to prolong their
survival.
SVery large farms can survive without income
supports. A loan safety net may be needed
to deal with instability and world competi-
tive environment.


FINANCIAL STRESS AND NEW ENTRANTS SCENARIOS


FInaclal Stress Scenrios
The financial position of many farmers is
under severe stress. As discussed in chapter
3, the situation is serious and may not improve
for some time. Policymakers are considering
various solutions to this problem. Two of the
most discussed alternatives are interest subsidy
and debt restructuring. To analyze the effects
of these two financial bail-out policies, the fi-
nancial position of the three representative
farms in each of the four regions was modified
to depict highly leveraged farms. The long-term
debt-to-asset ratio for each farm was increased
to 55 percent, the intermediate-term debt-to-
asset ratios were set equal to 60 percent, and
annual interest rates on old loans were in-
creased to their average values for 1980-83.

leerest SbIIdy
An interest subsidy is a loan at below-market
interest rates. For example, if the Government's
cost of money is 11 percent and the Farmer's
Home Administration makes loans at 5 per-
cent, there is a 6-percent direct interest rate
subsidy. The object of an interest rate subsidy
is to reduce the cash expenses for interest costs,
thus increasing total net cash farm income. The
total cash requirements are reduced, thereby
benefiting all farms. The total saving is greater
for larger farms because of the total debt be-
ing larger on these farms. An interest subsidy
for the first 2 years of the 10-year simulation
was provided. Interest charges on both long-


and intermediate-term debt were set at 8 per-
cent annually for the two years.
The results expected are:
Higher probability of survival.
Higher land values, net worth, and aver-
age net present value.
An increase in the equity ratio because
current debts are paid and longer term
debts are reduced, allowing greater oppor-
tunity for the farm to grow in size because
of the increased ability to leverage existing
equity.

Debt RIstructurlig
Debt restructuring refers to the rescheduling
of loan commitments. Debt may be restruc-
tured by rewriting short- or intermediate-term
debt to a long-term basis if the collateral jus-
tifies such change. The amount paid per year
is then reduced. Without sufficient additional
long-term collateral, debt restructuring is
limited to rescheduling each class of loans-
short-, intermediate-, and long-term-over a
longer repayment period. Also, if the debt is
on a fixed interest rate basis and interest rates
have declined, the debt might be rescheduled
in part to take advantage of lower interest rates
to obtain a longer repayment period. For the
highly leveraged farms, debt restructuring was
provided through increasing the length of
intermediate-term loans by 1 year and by con-
verting a portion of the intermediate-term debt


I





Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 47


* Most farm program benefits are capitalized
into land values and net worth. Very large
farms increase their net worth significantly
more than moderate farms under current
farm programs.
* Moderate farms are much more dependent
on farm programs to maintain their incomes
than are very large farms.
* Income supports provide significantly greater
benefits to moderate farms than to very


large farms. (In contrast price supports pro-
vide more wealth and growth benefits to
very large farms than to moderate farms.)
Targeting of income supports to moderate
farms is an effective policy to prolong their
survival.
SVery large farms can survive without income
supports. A loan safety net may be needed
to deal with instability and world competi-
tive environment.


FINANCIAL STRESS AND NEW ENTRANTS SCENARIOS


FInaclal Stress Scenrios
The financial position of many farmers is
under severe stress. As discussed in chapter
3, the situation is serious and may not improve
for some time. Policymakers are considering
various solutions to this problem. Two of the
most discussed alternatives are interest subsidy
and debt restructuring. To analyze the effects
of these two financial bail-out policies, the fi-
nancial position of the three representative
farms in each of the four regions was modified
to depict highly leveraged farms. The long-term
debt-to-asset ratio for each farm was increased
to 55 percent, the intermediate-term debt-to-
asset ratios were set equal to 60 percent, and
annual interest rates on old loans were in-
creased to their average values for 1980-83.

leerest SbIIdy
An interest subsidy is a loan at below-market
interest rates. For example, if the Government's
cost of money is 11 percent and the Farmer's
Home Administration makes loans at 5 per-
cent, there is a 6-percent direct interest rate
subsidy. The object of an interest rate subsidy
is to reduce the cash expenses for interest costs,
thus increasing total net cash farm income. The
total cash requirements are reduced, thereby
benefiting all farms. The total saving is greater
for larger farms because of the total debt be-
ing larger on these farms. An interest subsidy
for the first 2 years of the 10-year simulation
was provided. Interest charges on both long-


and intermediate-term debt were set at 8 per-
cent annually for the two years.
The results expected are:
Higher probability of survival.
Higher land values, net worth, and aver-
age net present value.
An increase in the equity ratio because
current debts are paid and longer term
debts are reduced, allowing greater oppor-
tunity for the farm to grow in size because
of the increased ability to leverage existing
equity.

Debt RIstructurlig
Debt restructuring refers to the rescheduling
of loan commitments. Debt may be restruc-
tured by rewriting short- or intermediate-term
debt to a long-term basis if the collateral jus-
tifies such change. The amount paid per year
is then reduced. Without sufficient additional
long-term collateral, debt restructuring is
limited to rescheduling each class of loans-
short-, intermediate-, and long-term-over a
longer repayment period. Also, if the debt is
on a fixed interest rate basis and interest rates
have declined, the debt might be rescheduled
in part to take advantage of lower interest rates
to obtain a longer repayment period. For the
highly leveraged farms, debt restructuring was
provided through increasing the length of
intermediate-term loans by 1 year and by con-
verting a portion of the intermediate-term debt


I





Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 47


* Most farm program benefits are capitalized
into land values and net worth. Very large
farms increase their net worth significantly
more than moderate farms under current
farm programs.
* Moderate farms are much more dependent
on farm programs to maintain their incomes
than are very large farms.
* Income supports provide significantly greater
benefits to moderate farms than to very


large farms. (In contrast price supports pro-
vide more wealth and growth benefits to
very large farms than to moderate farms.)
Targeting of income supports to moderate
farms is an effective policy to prolong their
survival.
SVery large farms can survive without income
supports. A loan safety net may be needed
to deal with instability and world competi-
tive environment.


FINANCIAL STRESS AND NEW ENTRANTS SCENARIOS


FInaclal Stress Scenrios
The financial position of many farmers is
under severe stress. As discussed in chapter
3, the situation is serious and may not improve
for some time. Policymakers are considering
various solutions to this problem. Two of the
most discussed alternatives are interest subsidy
and debt restructuring. To analyze the effects
of these two financial bail-out policies, the fi-
nancial position of the three representative
farms in each of the four regions was modified
to depict highly leveraged farms. The long-term
debt-to-asset ratio for each farm was increased
to 55 percent, the intermediate-term debt-to-
asset ratios were set equal to 60 percent, and
annual interest rates on old loans were in-
creased to their average values for 1980-83.

leerest SbIIdy
An interest subsidy is a loan at below-market
interest rates. For example, if the Government's
cost of money is 11 percent and the Farmer's
Home Administration makes loans at 5 per-
cent, there is a 6-percent direct interest rate
subsidy. The object of an interest rate subsidy
is to reduce the cash expenses for interest costs,
thus increasing total net cash farm income. The
total cash requirements are reduced, thereby
benefiting all farms. The total saving is greater
for larger farms because of the total debt be-
ing larger on these farms. An interest subsidy
for the first 2 years of the 10-year simulation
was provided. Interest charges on both long-


and intermediate-term debt were set at 8 per-
cent annually for the two years.
The results expected are:
Higher probability of survival.
Higher land values, net worth, and aver-
age net present value.
An increase in the equity ratio because
current debts are paid and longer term
debts are reduced, allowing greater oppor-
tunity for the farm to grow in size because
of the increased ability to leverage existing
equity.

Debt RIstructurlig
Debt restructuring refers to the rescheduling
of loan commitments. Debt may be restruc-
tured by rewriting short- or intermediate-term
debt to a long-term basis if the collateral jus-
tifies such change. The amount paid per year
is then reduced. Without sufficient additional
long-term collateral, debt restructuring is
limited to rescheduling each class of loans-
short-, intermediate-, and long-term-over a
longer repayment period. Also, if the debt is
on a fixed interest rate basis and interest rates
have declined, the debt might be rescheduled
in part to take advantage of lower interest rates
to obtain a longer repayment period. For the
highly leveraged farms, debt restructuring was
provided through increasing the length of
intermediate-term loans by 1 year and by con-
verting a portion of the intermediate-term debt


I





Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 47


* Most farm program benefits are capitalized
into land values and net worth. Very large
farms increase their net worth significantly
more than moderate farms under current
farm programs.
* Moderate farms are much more dependent
on farm programs to maintain their incomes
than are very large farms.
* Income supports provide significantly greater
benefits to moderate farms than to very


large farms. (In contrast price supports pro-
vide more wealth and growth benefits to
very large farms than to moderate farms.)
Targeting of income supports to moderate
farms is an effective policy to prolong their
survival.
SVery large farms can survive without income
supports. A loan safety net may be needed
to deal with instability and world competi-
tive environment.


FINANCIAL STRESS AND NEW ENTRANTS SCENARIOS


FInaclal Stress Scenrios
The financial position of many farmers is
under severe stress. As discussed in chapter
3, the situation is serious and may not improve
for some time. Policymakers are considering
various solutions to this problem. Two of the
most discussed alternatives are interest subsidy
and debt restructuring. To analyze the effects
of these two financial bail-out policies, the fi-
nancial position of the three representative
farms in each of the four regions was modified
to depict highly leveraged farms. The long-term
debt-to-asset ratio for each farm was increased
to 55 percent, the intermediate-term debt-to-
asset ratios were set equal to 60 percent, and
annual interest rates on old loans were in-
creased to their average values for 1980-83.

leerest SbIIdy
An interest subsidy is a loan at below-market
interest rates. For example, if the Government's
cost of money is 11 percent and the Farmer's
Home Administration makes loans at 5 per-
cent, there is a 6-percent direct interest rate
subsidy. The object of an interest rate subsidy
is to reduce the cash expenses for interest costs,
thus increasing total net cash farm income. The
total cash requirements are reduced, thereby
benefiting all farms. The total saving is greater
for larger farms because of the total debt be-
ing larger on these farms. An interest subsidy
for the first 2 years of the 10-year simulation
was provided. Interest charges on both long-


and intermediate-term debt were set at 8 per-
cent annually for the two years.
The results expected are:
Higher probability of survival.
Higher land values, net worth, and aver-
age net present value.
An increase in the equity ratio because
current debts are paid and longer term
debts are reduced, allowing greater oppor-
tunity for the farm to grow in size because
of the increased ability to leverage existing
equity.

Debt RIstructurlig
Debt restructuring refers to the rescheduling
of loan commitments. Debt may be restruc-
tured by rewriting short- or intermediate-term
debt to a long-term basis if the collateral jus-
tifies such change. The amount paid per year
is then reduced. Without sufficient additional
long-term collateral, debt restructuring is
limited to rescheduling each class of loans-
short-, intermediate-, and long-term-over a
longer repayment period. Also, if the debt is
on a fixed interest rate basis and interest rates
have declined, the debt might be rescheduled
in part to take advantage of lower interest rates
to obtain a longer repayment period. For the
highly leveraged farms, debt restructuring was
provided through increasing the length of
intermediate-term loans by 1 year and by con-
verting a portion of the intermediate-term debt


I





48 A Special Report for the 1985 Farm Bill


to long-term debt as long as the long-term debt
to asset ratio did not exceed 65 percent.
Restructuring debt has the same type of ex-
pected effects as interest rate subsidy; however,
they differ in their methods. Debt restructur-
ing does not reduce the annual interest pay-
ments in the initial period unless long-term in-
terest rates are less than intermediate-term
interest rates. Annual principal payments are
reduced, thus reducing cash flow needs of the
farm operator.

results Experienced From Financial
Stress Sek aries
Restructuring initial debt for highly lever-
aged farms failed to increase appreciably the
probability of survival for each size of farm
in any region except for moderate and large
wheat farms in the Southern Plains.
In all regions, the interest rate subsidy strat-
egy substantially increased the survival rate
and average net farm income more than did
the restructuring of farms' debts.
Both debt restructuring and interest subsidy
policies resulted in increased growth in real
wealth (i.e., ending net worth) on the very
large farms in all regions.
Except for Texas cotton farms, the very large
farms with high debts in each region are not
as dependent upon financial bail out strate-
gies for survival as the moderate and large
farms.
Debt restructuring resulted in less rapid rates
of growth in real wealth than interest rate
subsidies on moderate and large farms in
the Corn Belt and High Plains regions.


New Entrants Into Farming Scenario
All previous simulations of the effects from
the farm commodity policy alternatives were
based on representative farms operated by
established farm producers. These simulations
provide indications of the short-run effects of
the alternative farm commodity policy provi-
sions on economic survival and growth char-
acteristics of established farm operations. They


do not provide information on the survivability
and economic viability of potentially new en-
trants into farming. To obtain some general no-
tions of the effects of selected farm commodity
policies on newly established farming opera-
tions, the smallest farm in each region was
simulated under the condition that the farm
operator was a new entrant.
In this scenario the entering farm operator
was allowed to have only minimum equity in
owned farmland (30 percent) and farm ma-
chinery (35 percent). All farm machinery was
considered to have a new machinery cost, and
annual interest rates on long- and intermediate-
term loans were equal to the 1980-83 averages.
The operator was not allowed to have any off-
farm investments. Because the farm operator
was paying the full cost of all inputs (land, cap-
ital, machinery, and labor), these simulations
provide an indication of long-run survivability
and profitability of the representative farms.
Three policy alternatives were analyzed under
these conditions for the new entrant. They
were the base farm policy, which continues all
provisions of the 1981 farm bill, the elimina-
tion of the target price/deficiency payments
provision of the program (no income support
provisions), and the elimination of all farm pro-
gram provisions.
Results Expected:
New entrants would be expected to face
lower probabilities of survival, slower rates
of real wealth accumulation, and slower
rates of growth in farm size than would
current operators on the representative
farms in each region under existing farm
legislation. Because both depreciation ad-
justments on machinery and annual cash
requirements for debt repayment on real
estate and machinery loans are based on
new 1982 costs and current (1980-83) in-
terest rates, annual net farm incomes will
be lower for new entrants than for current
operators, under existing policy.
Elimination of income support provisions
of the 1981 farm bill will be expected to
reduce the probability of survival, rate of
growth in real net worth and farm size,
and annual net farm incomes of new en-






Ch. 4-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Crop Farms 49


I































I


trants in each region. The greatest impacts
would be expected for specialized crop
farms producing commodities eligible for
target prices and deficiency payments.
Elimination of all farm program provisions
would be expected to reduce further the
rate of growth in real wealth and farm size.
Annual net farm incomes for new entrants
would be expected to be even lower, par-
ticularly on representative farms produc-
ing commodities eligible for set-aside and
paid diversion provision.
Results Obtained:
* New entrants exhibited considerably lower
probabilities of survival under the base
farm policy than did current operators for
all specialized crop farms. Only the diver-
sified crop farms in Nebraska and the
Mississippi Delta exhibited relatively high
probabilities of survival for new entrants
under current farm commodity policy.
* New entrants experienced much lower
rates of real wealth accumulation than did
current operators under current policy. In
three of the regions-High Plains wheat
farm and Nebraska and Illinois crop farms
-real net worth after 10 years was lower
than initial net worth on the farms, in-
dicating that the new entrant operator had
to sell owned cropland to remain solvent.
Net farm incomes were negative for all
farms, with the High Plains wheat farm ex-
periencing the largest relative decline in
annual net income.
* New entrant farm operators in the High
Plains wheat and Nebraska and Illinois
crop regions were unable to increase farm
size over the 10-year period under current
farm policy. The Texas cotton farm and
Mississippi Delta crop farms experienced
considerable growth, 20 and 27 percent,
respectively.
* Eliminating the target price/deficiency
payments provision of current legislation
substantially decreased the probability of
survival and ending net worth on all farms.
Only the Texas cotton farms exhibited any
appreciable growth in farm acreage (about
6 percent).


Under the policy alternative of no farm
programs, none of the farms exhibited rea-
sonable potentials for remaining solvent
over the 10 years. Farms in the Texas High
Plains, Southern Plains, and Corn Belt had
less than a 10-percent probability of sur-
vival. Mississippi Delta farms had only a
60-percent chance for remaining solvent
over the 10 years.
Under the current farm program only the
Nebraska and Mississippi Delta crop farms
had sufficient returns for new farmers to
enter agriculture with a reasonable chance
of remaining solvent and making a reason-
able return on their investment.
Elimination of income support, price sup-
port, and supply control provisions of cur-
rent farm policy resulted in new entrant
farmers in all four regions facing little
chance of surviving and becoming eco-
nomically viable farming operations.
Other sources of income, economic assist-
ance, or wealth accumulation will be re-
quired for these new entrants to survive
economically in an open market farm pol-
icy environment.

Implications for the 1985 Farm Bill
Restructuring of debt for highly leveraged
farms does not appreciably increase their
probability of survival.
Interest rate subsidy substantially increases
average net farm income more than debt
restructuring. It is, therefore, a more effec-
tive strategy to ease financial stress.
* Very large farms with high debts are not as
dependent on these programs for survival as
moderate farms. Under either of these pro-
grams, very large farms grow significantly
in farm size and real wealth.
* New entrants into agriculture will not likely
survive even with current farm programs.
Other sources of income, economic assist-
ance, or wealth accumulation will be re-
quired.






Chapter 5

Economic Impacts of

Emerging Technologies and

Selected Farm Policies for

Various Size Dairy Farms


One of the most controversial policy areas
in the 1985 farm bill debate is expected to be
in dairy policy-in 1983 a large amount of
surplus milk production cost taxpayers approx-
imately $2.6 billion. For that reason, there will
be many alternatives proposed to the current
dairy program. This chapter examines the cur-
rent state of the dairy industry, identifies the
technologies most likely to affect the industry
from 1983 to 1992, identifies policy options


most likely to be considered in the 1985 farm
bill, and analyzes the effects of these options
on moderate, large, and very large dairy farms
in major U.S. dairy production regions.1

'The representative farms were developed and analyzed in the
paper "Economic, Policy, and Technology Factors Affecting
Herd Size and Regional Location of U.S. Milk Production,"
prepared for the Office of Technology Assessment by Boyd M.
Buxton.


BACKGROUND


During the 1970s, milk production increased
41 percent in the Southwest region of the
United States and 33 percent in the Northwest,
while total milk production increased only 11
percent (fig. 1). Much of the increased produc-
tion came from dairies with more than 500
cows, with herds of 1,500 to 2,000 cows being
common. Although 303,710 farms in the
United States reported having milk cows in
1983, less than 5,000 well-managed dairies with
1,500 cows each could have produced all the
milk sold commercially that year.
Herd size, technologies employed, and prac-
tices used in milk production vary considerably
throughout the United States. In May 1983 the
average herd size for 120,655 producers sell-
ing milk to plants regulated by Federal milk
marketing orders was 63 cows per farm (table
5-1). However, the average herd size in each
State varied from 49 cows in Pennsylvania to
532 cows in Florida.


The variation in herd size within each State
was even more dramatic. Although the aver-
age herd size in Florida was 532 cows, the aver-
age herd size for the largest 10 percent of the
herds in that State was 1,861 cows (table 5-1).
Similarly, the average herd size for the largest
10 percent of herds regionally was about 1,700
cows in the Southwest, but only 125 cows in
the Lake States region. Generally, dairy herds
are much larger in the Southwest, Southeast,
and Northwest regions than in the Lake States
and Northeast regions.
From the herd size information in table 5-1,
22 dairies were selected to represent existing
herd sizes in five major dairy areas (table 5-2).
The 200-cow Pennsylvania and 600-cow New
York dairies exceed the average size of the
largest 10 percent of dairies in those States.
However, such larger sized dairies exist in
these States and will become more prevalent
in the near future.






Chapter 5

Economic Impacts of

Emerging Technologies and

Selected Farm Policies for

Various Size Dairy Farms


One of the most controversial policy areas
in the 1985 farm bill debate is expected to be
in dairy policy-in 1983 a large amount of
surplus milk production cost taxpayers approx-
imately $2.6 billion. For that reason, there will
be many alternatives proposed to the current
dairy program. This chapter examines the cur-
rent state of the dairy industry, identifies the
technologies most likely to affect the industry
from 1983 to 1992, identifies policy options


most likely to be considered in the 1985 farm
bill, and analyzes the effects of these options
on moderate, large, and very large dairy farms
in major U.S. dairy production regions.1

'The representative farms were developed and analyzed in the
paper "Economic, Policy, and Technology Factors Affecting
Herd Size and Regional Location of U.S. Milk Production,"
prepared for the Office of Technology Assessment by Boyd M.
Buxton.


BACKGROUND


During the 1970s, milk production increased
41 percent in the Southwest region of the
United States and 33 percent in the Northwest,
while total milk production increased only 11
percent (fig. 1). Much of the increased produc-
tion came from dairies with more than 500
cows, with herds of 1,500 to 2,000 cows being
common. Although 303,710 farms in the
United States reported having milk cows in
1983, less than 5,000 well-managed dairies with
1,500 cows each could have produced all the
milk sold commercially that year.
Herd size, technologies employed, and prac-
tices used in milk production vary considerably
throughout the United States. In May 1983 the
average herd size for 120,655 producers sell-
ing milk to plants regulated by Federal milk
marketing orders was 63 cows per farm (table
5-1). However, the average herd size in each
State varied from 49 cows in Pennsylvania to
532 cows in Florida.


The variation in herd size within each State
was even more dramatic. Although the aver-
age herd size in Florida was 532 cows, the aver-
age herd size for the largest 10 percent of the
herds in that State was 1,861 cows (table 5-1).
Similarly, the average herd size for the largest
10 percent of herds regionally was about 1,700
cows in the Southwest, but only 125 cows in
the Lake States region. Generally, dairy herds
are much larger in the Southwest, Southeast,
and Northwest regions than in the Lake States
and Northeast regions.
From the herd size information in table 5-1,
22 dairies were selected to represent existing
herd sizes in five major dairy areas (table 5-2).
The 200-cow Pennsylvania and 600-cow New
York dairies exceed the average size of the
largest 10 percent of dairies in those States.
However, such larger sized dairies exist in
these States and will become more prevalent
in the near future.








54 A Special Report for the 1985 Farm Bill


Figure 5-1.-How the Dairying Picture Has Changed
(percent change in milk production in various regions from 1970-71 to 1980-81)


SOURCE: U.S. Department of Agriculture.


Table 5-1.-Total Producers and Size Distribution of Herds Selling Milk to Plants Regulated by
Federal Milk Marketing Orders, May 19838

Average herd size (milk cows) for:


Total producers Larges_ __maiies
Region (State) (number) All farms 10 percent 70-89 percent 40-69 percent 40 percent
Lake States:
Minnesota ........... 9,968 53 116 74 49 30
Wisconsin ........... 24,400 54 133 68 52 28
Northeast:
Pennsylvania ......... 12,928 49 127 66 44 25
New York............ 13,374 59 162 81 53 27
Southeast:
Georgia.............. 962 127 343 181 117 54
Florida .............. 352 532 1,861 931 355 133
Southwest:
New Mexico.......... 176 333 1,832 433 169 32
Arizona.............. 160 510 1,733 714 433 160
California ............ 13 400 1,640 580 253 110
Northwest:
Idaho................ 574 135 607 169 90 34
Washington .......... 1,647 127 418 171 108 46
United States .......... 120,655 63 202 82 54 26
SThe 120,655 farms accounted for about 69 percent of all milk produced In May 1983, but excluded most farms in Calfornia and other States where there is no Federal
milk order.
SOURCE: Boyd M. Buxton and John P. Rourke, "Size Distribution of Dairy Farms Marketing Milk Under Federal Milk Orders," unpublished report, Economic Research
Service, U.S. Department of Agriculture, April 1984.






Ch. 5-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Dairy Farms 55


Table 5-2.--Representative Dairies by Region and Herd Size

Herd size Cropland Housing facilities" Silage storage Total labor
RegionlState (cows) (acres) (type) Sun shades Feed produced (type) (W/e)b
Lake States:
Minnesota .... 52 188 Stanchion No Most Upright 2.03
Minnesota .... 125 449 Free stall No Most Upright 3.30
Northeast:
Pennsylvania.. 52 156 Stanchion No Forage Trench 2.2
Pennsylvania .. 125 375 Free stall No Forage Trench 3.8
Pennsylvania .. 200 600 Free stall No Forage Trench 5.54
New York ..... 52 156 Stanchion No Forage Trench 2.21
New York ..... 200 600 Free stall No Forage Trench 5.54
New York ..... 600 1,800 Free stall No Forage Trench 14.36
Southeast:
Georgia....... 200 400 Free stall Yes Forage Trench 4.5
Georgia....... 350 700 Free stall Yes Forage Trench 7.84
Florida ....... 350 0 Open field Yes None NA 7
Florida ....... 600 0 Open field Yes None NA 11
Florida ....... 1,436 0 Open field Yes None NA 18
Southwest:
New Mexico... 900 0 Corral Yes None NA 13
Arizona ....... 359 0 Corral Yes None NA 7
Arizona ....... 834 0 Corral Yes None NA 12
Arizona ....... 1,436 0 Corral Yes None NA 16
California ..... 550 0 Corral Yes None NA 9
California ..... 1,436 0 Corral Yes None NA .16
Northwest:
Washington ... 140 51 Free stall No Silage Trench 2.96
Idaho......... 200 400 Corral No Most Trench 5.0
Idaho ......... 550 0 Corral No None NA 10.5
a Housing types are:
* Stanchion: A conventional barn with locking stanchions in which cows are milked and fed.
. Free stall: A covered barn with individual stalls in which cows freely enter and exit.
* Open field: A field where cows are kept that is large enough to maintain plant cover.
* Corral: A drvlot open pen where cows are kept and fed at a fenceline feeder.
b Labor in worker equivalents of 2.500 hours annually.
NA-not applicable.
SOURCE: Office of Technology Assessment.


TECHNOLOGIES AND PRACTICES


The technologies and practices assumed for
each of the 22 dairy operations were based on
discussions with dairy producers, university
and Government employees, and equipment
representatives. The objective of these discus-
sions was to describe efficiently organized
dairy operations that use proven technologies
and practices for each specified herd size.
Therefore, the dairy operations in this analy-
sis are not the average of what exists, but rather
approximate modern sizes and types of oper-
ations.

The 52-cow dairies in Minnesota, Pennsyl-
vania, and New York use the conventional
stanchion barns for housing and milking cows
(table 5-2). For larger herds in the Lakes States,


the Northeast, Washington, and Georgia, free-
stall housing and milking parlors are assumed.

Cows are kept in open corrals throughout the
Southwest and on larger Idaho dairies. Sun
shades in the corrals are assumed in New Mex-
ico, Arizona, and California (Southwest), but
not in Idaho. Cows are milked twice a day in
milking parlors and fed at fenceline bunks from
a feed wagon or truck.

Open fields with sun shades are assumed in
Florida. One-half acre per cow is provided,
allowing fields to remain grass-covered to min-
imize mud problems. Cows are milked twice
a day in a milking parlor. After leaving the
milking parlor, they are fed concentrates in a





56 A Special Report for the 1985 Farm Bill


feed barn. before being released back to the
field. Roughage is fed loose in the open fields.
The source of feed follows the common prac-
tice existing in the various States. For New
Mexico, Arizona, California, and Florida, most
feed is purchased from off the dairy operation.
The same is assumed for the 550-cow Idaho


dairy. Dairy operations in Pennsylvania, New
York, and Georgia purchase most of the con-
centrates but produce most of the forage used
by their dairy herds. All feed is assumed to be
produced on-farm for the Minnesota and the
200-cow Idaho dairies.


POLICY AND TECHNOLOGY SCENARIOS


Eight representative dairy operations of the
22 presented in table 5-2 were selected to simu-
late selected policy and technology scenarios.2
The likelihood of a particular dairy remaining
solvent under alternative policies is directly af-
fected by its financial characteristics. A pol-
icy change can have quite different implica-
tions for the operator of a dairy with a high
level of debt than one with a low level of debt.
The average financial situation that exists on
the eight dairies of the size and location se-
lected are shown in table 5-3. The averages
were approximated from the U.S. Department
of Agriculture (USDA) farm financial survey.

PThe current version of the Firm Level Income Tax and Farm
Policy Simulator (FLIPSIM V), developed by James W. Richard-
son and Clair J. Nixon, was used to simulate the representative
farms in each region.


The eight dairy operations in three regions
were simulated for 10 years under the alterna-
tive scenarios described below. Seven policy
scenarios (including the 1983 base described
in a previous section) and two technology
scenarios were simulated for each dairy. The
assumptions and policy values associated with
each scenario were held constant across all
dairies to allow direct comparison of their im-
pacts on different size dairies in different
regions.
Two financial stress scenarios (interest sub-
sidy and debt restructuring) were evaluated for
the Minnesota 52-cow and 125-cow, Arizona
359-cow, and Florida 350-cow dairies, assum-
ing an initial high debt position and assuming
a new entrant with high debt position. Each
scenario is described below, along with the ex-


Table 5-3.-Financial Characteristics Assumed for Eight Dairy Operations in Four States
Herd size in:
Minnesota Arizona California Florida
Financial characteristics 52 125 359 550 1,436 350 600 1,436
Value of:
Cropland and farmstead ($1,000)...... 293.4 679.1 39.4 160.0 312.0 262.5 450.0 1,074.0
Buildings ($1,000) .................. 92.7 176.7 192.8 284.4 512.6 87.9 108.9 211.7
Farm machinery ($1,000) ........... 104.1 159.0 120.3 183.1 303.0 114.6 180.0 260.7
All livestock ($1,000) ................ 77.9 181.4 599.6 960.7 2,505.0 525.5 981.4 2,344.3
Off-farm investments ($1,000) ........ 5.5 13.1 0 0 0 0 0 0
Beginning cash reserves ($1,000) ....... 12.0 62.5 89.8 137.5 35.9 70.0 212.0 505.5
Debt:
Long-term ($1,000) .................. 111.2 213.9 67.3 155.5 288.6 143.7 218.0 475.7
Intermediate-term ($1,000) ........... 57.1 88.5 230.4 308.8 842.4 160.0 243.9 468.9
Initial net worth ($1,000) ............... 417.1 969.4 744.2 1,261.3 2,537.5 756.9 1,464.7 3,343.0
Equity ratio (fraction) ................. 0.71 0.76 0.71 0.73 0.69 0.71 0.76 0.76
Family living:
Minimum ($1,000)................... 20.0 25.0 25 27 30 25 27 30
Maximum ($1,000) .................. 32.0 35.0 30 38 40 30 38 40
Marginal propensity (fraction) ........ 0.3 0.4 0.3 0.4 0.4 0.35 0.4 0.4
Off-farm income ($1,000) .............. 0 0 0 0 0 0 0 0
SOURCE: Office of Technology Assessment.





Ch. 5-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Dairy Farms 57


pected results and the observed results from
the analysis. Appendix B contains summary
tables of the analysis for each farm size by
region.

Farm Policy Scenarios
Curret Poliky
The current policy assumes the continuation
of the Dairy and Tobacco Production Stabiliza-
tion Act of 1983 through September 30, 1985.
The Government stocks of dairy products are
assumed to be high enough through 1985 and
1986 to trigger a 50-cent drop in support price
on April 1, 1985, and again on July 1, 1985, as
specified in the 1983 act.
All features of the 1983 act are scheduled to
expire on September 30, 1985. It is assumed
that the support price will remain at the 1985
level through 1986, then rise to $13.11 for man-
ufacturing milk through the end of the 10-year
simulation period.
Results Expected.-Under current policy, it
is expected that a well-managed dairy of aver-
age size would about break even after paying
expenses and farm overhead and making with-
drawals for family living. It is also expected
that well-managed dairies in all regions should
be able to survive under a continuation of the
current program. Farms that are not in a posi-
tion to realize most of the economies of size
in dairying would be gradually forced out of
business. In other words, an extension of cur-
rent policy would force dairies to compete on
the basis of cost and efficiency.
Results Obtained:
All dairies except the 52-cow Minnesota
operation were able to increase their real
net worth over the 10-year planning hori-
zon. The 52-cow dairy experienced a 54-
percent reduction in net worth.
The larger the dairy, the greater its finan-
cial success. Dairies in Florida and the
Southwest were more profitable than
dairies in Minnesota. The Florida dairy
benefited greatly from higher milk prices.
The 52-cow dairy had the lowest probabil-
ity of survival (70 percent) due to having


the highest unit cost of production. It lost
an average of $27,000 annually in net farm
income.

A Crop Acreage Reductlon Program
The present feed grain program was as-
sumed through 1985. From 1986 to 1992 a 15-
percent set-aside with a 5-percent diversion for
corn, cotton, rice, sorghum, and wheat was
assumed. This program results in dairy feed
prices being 9 percent higher than those under
current policy.
Results Expected.-Feed cost represents
about 50 to 60 percent of total costs per cow.
A crop program that results in a 9 percent
higher feed cost is roughly equal to a 5-percent
reduction in the price of milk. This would have
an adverse impact on a dairy's ability to in-
crease net worth, reduce debts, and achieve as
high an internal rate of return as under cur-
rent policy. In the short run, dairies that raise
most of their feed would be less directly af-
fected. The probability of survival would most
likely be reduced for dairies operating at or
below the break-even point under the current
policy because they would be unable to absorb
the higher feed costs.
Results Obtained:
The associated higher feed prices had the
greatest adverse financial impact on dairies
that purchased most of the feed from off
the farm. For example, compared to that
of the current policy, the average annual
net farm income of the 1,436-cow Califor-
nia dairy declined 64 percent from $375,000
to $136,000.
The probability of survival was reduced
for all dairies except the 1,436-cow Florida
dairy and the 125-cow Minnesota dairy.
There was relatively little impact on Min-
nesota dairies, where most feed is raised
on the dairies.
o Crop Programs
There is much discussion of a desire to move
to more market-oriented crop programs. Re-
moving all price supports and income supports
would increase the variability of feed prices,






58 A Special Report for the 1985 Farm Bill


subjecting the dairyman who purchases feed
to greater risk. For this scenario the Commod-
ity Credit Corporation (CCC) loan, farmer-
owned reserve (FOR), and target price provi-
sions were eliminated for all years in the plan-
ning horizon (1983-92). This increased the vari-
ability in feed costs facing dairy operations.
The impact of this variability was evaluated.
Results Expected.-Feed prices paid by
dairies would be higher in some years but
lower in other years. Over time, high and low
price years would be expected to balance out,
leaving a surviving dairy about as prosperous
as under the current policy. However, the cost
associated with possible borrowing to tide a
dairy over periods of high feed costs might be
expected to affect somewhat adversely its
ability to retire debt and increase net worth.
Dairies under tight financial conditions under
current policy would be expected to have a
lower probability of survival without crop pro-
grams because they would be less able to ab-
sorb the effects of periods of relatively high
feed prices. This would be less a problem for
dairies in a relatively strong financial position
under current policy because they would be
better able to absorb these shocks.
Results Obtained:
The increased variability in feed prices,
associated with eliminating all crop pro-
grams, had little financial impact on all
dairies compared with the results under
the current policy. Average net present
value declined less than 2 percent for all
dairies.
Increased price risk did not reduce the
probability of survival for any of the farms.

Fifty Cots Lower Prie
All the assumptions of the current policy
were retained except that the mean milk prices
were reduced 50 cents per hundredweight
(cwt) and the variability of milk price is in-
creased. This scenario was included in the
analysis because of the current high level of
Government stocks and program costs.


Results Expected.-Lower support prices
would be expected to affect adversely the
dairies' net incomes as well as their survival
and growth. The dairies most adversely af-
fected would be those that are already in finan-
cial difficulties under the base policy.
Results Obtained:
All farms were more negatively affected
by this policy than by current policy. All
farms experienced more losses under this
policy in net farm income, net present val-
ue, and net worth.
The largest dairies in each region experi-
enced little reduction in the probability of
survival.
The greatest adverse impact was on the
smallest Minnesota dairy, where the prob-
ability of survival declined from 70 to 38
percent and the probability of a positive
net present value declined from 24 to 14
percent. Other dairies that were adversely
affected included the smaller Florida and
California farms. Therefore, reduced price
supports would force many small dairies
out of business.

eN Dairy Program
With no dairy program, the price of milk
would drop about 8 percent across the regions
(about $1/cwt) to the variable cost of produc-
tion in Minnesota and California as excess
stocks and production are eliminated. It was
assumed that this would take 4 years. After
that, prices were expected to increase 6.6 per-
cent ($0.80/cwt), equal to the average total cost
of production for large-scale dairies in Min-
nesota and California.3 Historical price rela-
tionships were maintained.



'The variation of milk prices without a dairy price support
program was developed from the following study: Cameron S.
Thraen and Jerome W. Hammond, Price Supports, Risk Aver-
sion and U.S. Dairy: An Alternative Perspective of the Long-
Term Impacts, Economic Report ER83-9, Department of Agri-
cultural and Applied Economics, University of Minnesota, June
1983.





Ch. 5-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Dairy Farms 59


Results Expected.-Without a dairy price
support program there would be no guaranteed
price floor. In some years milk prices would
be higher, while in other years they would be
lower than under current policy. However,
they would still fluctuate about the long-term
equilibrium price. Over time, favorable and un-
favorable prices should balance out, meaning
that the ability of a dairy to increase net worth,
repay debt, and achieve a favorable internal
rate of return would not be seriously affected.
However, the probability of survival for dairies
in tight financial situations would be adversely
affected.
Results Obtained:
The probability of survival fell for all
farms, with the greatest reduction experi-
enced by the moderate and large farms
analyzed. The lowest probability of sur-
vival was 34 percent for the 52-cow Min-
nesota dairy.
Net present value declined significantly
for all farms. For example, the very large
California dairy experienced a 43-percent
decline in net present value and a 27-
percent decrease in net worth.
However, the very large farms were still
able to survive in all regions.

Supply Cotrol
All assumptions of the base current policy
were retained, except that mandatory quotas
were imposed on dairies. Quotas equal to 96.5
percent of a producer's normal production
would, over time, be expected to maintain milk
prices $1 above those under current policy.
Herd size would be reduced about 4 percent
in order to reduce milk production 3.5 percent,
assuming that poorer-than-average cows would
be culled in complying with the quota.
Results Expected.-The financial perform-
ance of all dairies would likely be improved as
a result of permanently higher milk prices, de-
spite those dairies having to reduce total milk
produced within the designated quota. The
probability of survival would increase along
with a greater ability to reduce debt and in-
crease net worth for dairies existing at the time


the program is implemented. However, this
economic advantage could be capitalized into
the quota value, thereby eroding the advantage
for new entrants or producers who would have
to purchase quotas to expand milk production.
Results Obtained:
Probability of survival was increased for
all farms of all regions. The 52-cow Min-
nesota dairy experienced the largest in-
crease in the probability of survival from
70 percent under the base scenario to 92
percent.
Average net present value increased for all
dairy farms. The 52-cow Minnesota dairy
increased from negative $77,000 to $22,000.
Ending net worth was increased for all
dairies due to retained earnings and repay-
ment of debt.
Net farm income for Minnesota dairies
was increased by $15,000. These dairies
previously had the lowest income.

Tax Policy Scenarios
All assumptions of the current policy were
retained except for more restrictive Federal in-
come tax provisions, including the following:
Machinery, livestock, and buildings were
depreciated using the straight-line cost
recovery method.
First-year expensing provisions were elim-
inated for all depreciable items.
Maximum investment tax credit provi-
sions were eliminated.
The maximum annual interest expense
that could be used to reduce taxable in-
come was $15,600.
The operator must sell obsolete machin-
ery upon disposition rather than trading
it in on new replacements, thus forcing
recapture of excess depreciation deductions.
Results Expected.-These tax policy changes
would have an adverse impact on the ability
of a dairy to reduce debt, increase net worth,
and, if in a tight financial situation, reduce the
probability of survival. All tax changes increase
the tax liability, reducing the net income of the
operation and leaving less for debt retirement
and increases in net worth.





60 A Special Report for the 1985 Farm Bill


Results Obtained:
* Eliminating the tax benefits increased tax
liabilities and reduced the net present
value and net worth for all farms. These
reductions, however, were relatively small
-in the range of 1 to 10 percent.
* The increased tax liabilities were not large
enough to reduce significantly the prob-
ability of survival.

Technology Scenarios


computer-confrolled


Feeding


A technology now available but not widely
adopted is individual cow feeding by using
computer-controlled feed stalls. With this tech-
nology concentrates fed to individual cows can
be controlled in total and over time. One ex-
periment suggests that average daily milk pro-
duction per cow can be increased 2 pounds
with a 0.1 percent higher butterfat content
without increasing total feed fed to the herd
(Wildhaber, et al., 1984). The estimated added
investment costs for computer feeding for the
three largest dairies were:
Minnesota 125-cow herd............. $18,750
Florida 1,436-cow herd .............. $157,960
California 1,436-cow herd............ $157,900
Investment included a neck responder for
each cow, a feeder stall with storage and auger
feeder, and a computer. It was assumed that
this technology would be adopted only by the
largest dairies in each region; thus, only three
dairies were analyzed.
All other assumptions of the current policy
were retained except that allowances were
made for added investment and operating costs
and for higher average milk production per
cow. The gain in milk production was expected
to exceed the added cost, giving dairy pro-
ducers a more favorable financial position.


Growth Mormone
A technology not yet in commercial use but
demonstrated in experimental work is bovine
growth hormone. Injecting milk cows with this
hormone every other day would result in in-
creased milk production. Preliminary results
are that with this technology, milk production
per cow during the last two-thirds of the lac-
tation period is increased 30 to 40 percent with-
out additional feed (about 23 percent annually).
The cost for the hormone can be expected to
decline since it can probably be produced
cheaply.
Injections given every other day and costing
$1 each are assumed in this analysis. Combin-
ing this cost with increased hauling and other
costs of added milk results in about a $185-
increase in cost per cow per year. Once again,
it was assumed that only the largest farms
would adopt, and allowances were made for
added cost and yields.

Results Expected
The expected impact of adopting these tech-
nologies is to improve greatly the financial per-
formance of the larger adopting dairies. The
probability of survival and all measures of fi-
nancial performance would be improved for
the adopting dairies. The disparity in costs and
returns for moderate and very large dairies
could be significantly increased.

Results Obtained:
* Large increases in net farm income, net pres-
ent value, and net worth were experienced
by the adopting dairies. These increases
were significantly larger for the bovine
growth hormones.
* Any lag in the adoption of new cost-reduc-
ing technologies seriously adversely affected
the ability of dairies to compete.






Ch. 5-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Dairy Farms 61


FINANCIAL STRESS SCENARIOS


The assumed beginning financial conditions
for four of the eight dairies were changed to
reflect high-debt operators and new entrants.
Debt load was doubled to reflect high-debt sit-
uations. For new entrants all equipment was
assumed to be new, which increased both the
initial value of the machinery and the total debt
load.
Two policies were considered for high-debt
dairies. One was to subsidize interest rates on
all debt so that the effective rate for all loans
paid would be 8 percent rather than the higher
rates used in the current policy. The second
was to restructure the debt by converting a por-
tion of intermediate debt into long-term loans
and/or to extend the length of intermediate-
term loans. In the second case, interest rates,
total debt loads, and other assumptions of the
high-debt dairies remained the same as under
current policy.


The impact of higher feed costs and elimi-
nating the dairy price support program was
evaluated for new entrants with a high-debt
position. The results obtained included the fol-
lowing:
The probability of survival for any dairy
depends greatly on its initial financial posi-
tion. Dairies and new entrants with high
debt had significantly lower probabilities
of surviving than dairies with initial finan-
cial situations assumed in current policy.
Neither interest subsidies nor opportuni-
ties for debt restructuring greatly im-
proved the chances of high-debt dairy
farms remaining solvent.
The probability of survival for both Min-
nesota dairies was zero for all policy
scenarios. The implication is that high-
debt producers in this region cannot sur-
vive under even the current dairy policy.


IMPLICATIONS FOR THE 1985 FARM BILL


* Policies and technologies that are favorable
for the dairy industry provide greater finan-
cial opportunities for large rather than small
dairies.
* Policies that adversely affect the dairy indus-
try such as higher feed costs, fewer income
tax benefits, and no dairy price support pro-
gram will negatively affect small dairies
more than larger dairies.
* The major advantage enjoyed by larger
dairies is more related to the efficiency of
operation than to specific dairy policies.
* There will be a continued trend to fewer and
larger dairies in all regions. Milk production
can be expected to continue to increase in
the lower cost regions of the Southeast and
Southwest.
* Traditional dairy regions will continue to ex-
perience increased competitive pressure


from larger scale, more efficient producers
in other parts of the United States. Substan-
tial restructuring of dairies in the Lake States
and Northeast will be required for them to
compete.
* Dairy price supports must be sufficiently
flexible to adjust to the increased production
and lower costs spurred by technological
change. This could be accomplished either
by adjusting the price support level to
changes in production costs per unit of out-
put or by adjusting the level of CCC pur-
chases.
* Current geographic price alignment systems
in Federal milk marketing orders are becom-
ing increasingly outdated. A comprehensive
study is needed of changes required to mod-
ernize the Federal order system in light of
technological changes.






Ch. 5-Economic Impacts of Emerging Technologies and Selected Farm Policies for Various Size Dairy Farms 61


FINANCIAL STRESS SCENARIOS


The assumed beginning financial conditions
for four of the eight dairies were changed to
reflect high-debt operators and new entrants.
Debt load was doubled to reflect high-debt sit-
uations. For new entrants all equipment was
assumed to be new, which increased both the
initial value of the machinery and the total debt
load.
Two policies were considered for high-debt
dairies. One was to subsidize interest rates on
all debt so that the effective rate for all loans
paid would be 8 percent rather than the higher
rates used in the current policy. The second
was to restructure the debt by converting a por-
tion of intermediate debt into long-term loans
and/or to extend the length of intermediate-
term loans. In the second case, interest rates,
total debt loads, and other assumptions of the
high-debt dairies remained the same as under
current policy.


The impact of higher feed costs and elimi-
nating the dairy price support program was
evaluated for new entrants with a high-debt
position. The results obtained included the fol-
lowing:
The probability of survival for any dairy
depends greatly on its initial financial posi-
tion. Dairies and new entrants with high
debt had significantly lower probabilities
of surviving than dairies with initial finan-
cial situations assumed in current policy.
Neither interest subsidies nor opportuni-
ties for debt restructuring greatly im-
proved the chances of high-debt dairy
farms remaining solvent.
The probability of survival for both Min-
nesota dairies was zero for all policy
scenarios. The implication is that high-
debt producers in this region cannot sur-
vive under even the current dairy policy.


IMPLICATIONS FOR THE 1985 FARM BILL


* Policies and technologies that are favorable
for the dairy industry provide greater finan-
cial opportunities for large rather than small
dairies.
* Policies that adversely affect the dairy indus-
try such as higher feed costs, fewer income
tax benefits, and no dairy price support pro-
gram will negatively affect small dairies
more than larger dairies.
* The major advantage enjoyed by larger
dairies is more related to the efficiency of
operation than to specific dairy policies.
* There will be a continued trend to fewer and
larger dairies in all regions. Milk production
can be expected to continue to increase in
the lower cost regions of the Southeast and
Southwest.
* Traditional dairy regions will continue to ex-
perience increased competitive pressure


from larger scale, more efficient producers
in other parts of the United States. Substan-
tial restructuring of dairies in the Lake States
and Northeast will be required for them to
compete.
* Dairy price supports must be sufficiently
flexible to adjust to the increased production
and lower costs spurred by technological
change. This could be accomplished either
by adjusting the price support level to
changes in production costs per unit of out-
put or by adjusting the level of CCC pur-
chases.
* Current geographic price alignment systems
in Federal milk marketing orders are becom-
ing increasingly outdated. A comprehensive
study is needed of changes required to mod-
ernize the Federal order system in light of
technological changes.







Chapter 6

Agricultural Research

and Extension Policy'


Much of the success of American agriculture
is attributable to the creation of its agricultural
research and extension system (Ruttan, 1982;
Cochrane, 1958). For well over a century, the
public has invested substantial sums of money
(currently about $3 billion annually) in agricul-
tural research and extension at Federal and
State levels. This investment has been no ac-
cident. Several important events have helped
make the agricultural research and extension
system an integral and longstanding part of
U.S. agricultural policy-the first Federal ap-
propriations to agricultural research in 1856,
the establishment of the land grant university
system in 1862, and the creation of the Federal-
State-local extension partnership in 1914 (Knut-
son, et al., 1983).
The agricultural research and extension sys-
tem continues to be an important contributor
to a plentiful and low-cost food and fiber
supply, as well as to the positive U.S. balance
of agricultural trade. For the period 1945-79,
technological innovations brought about by the
system increased agricultural output 85 per-
cent, with no change in the level of agricultural
inputs (USDA, 1980).
Agriculture's entrance into the era of biotech-
nology and information technology raises sev-



'Agricultural research and extension policy issues were iden-
tified and analyzed in papers prepared by the OTA research and
extension policy workgroup. Authors of the papers were Ronald
Knutson, Roy Loworn, George Hyatt. and Fred White. This
chapter is based on an integration prepared by Ronald Knut-
son, of the workgroup's findings.


eral questions about the impact of technical ad-
vances on the performance of the research and
extension system and about how that perform-
ance will ultimately affect the structure of agri-
culture. For example:
Who gains and who loses from the proc-
ess of technological change in agriculture?
Is agricultural research and extension
structurally neutral or does it favor the
growth of large industrialized farms?
What are the roles of the various compo-
nents of the agricultural research and
extension system as they relate to techno-
logical change in the biotechnology and in-
formation technology era?
What are the implications of increased pri-
vate sector involvement in agricultural re-
search?
What are the implications of patents be-
ing conferred on biotechnology and infor-
mation technology discoveries for the
social contract under which the agricul-
tural research system was created?
How is a proper balance to be struck be-
tween public and private sector compo-
nents of the agricultural research and ex-
tension system?
These are the major issues that will be ad-
dressed in this chapter. The answers are based
on previous OTA studies, on an extensive body
of literature regarding the impact of technol-
ogy on agriculture, and on papers commis-
sioned by OTA regarding the status of the agri-
cultural research and extension system as it
relates to developments in biotechnology and
information technology.





WHO PROFITS FROM TECHNOLOGY CHANCE


The point that technology is one of the driv-
ing forces behind structural change in agricul-
ture has perhaps been most clearly argued by
Willard Cochrane (1983), who notes that the
first adopters of new technology are also the
immediate beneficiaries in that their costs per
unit of production are lowered and their pro-
fits are thus increased. The profits of those
firms supplying the products of new technol-
ogy also increase. In addition, higher profits
for the farmers encourage the adopting farmers
to expand output--even to the extent of increas-
ing the scale of their farm operation. However,
as output expands, prices decline; later tech-
nology adopters thus realize less profit. Those
farmers who are the last to adopt new technol-
ogies may actually be forced either to adopt or
to get out of agriculture.
Three important lessons arise from this
description of the process of technological
change:
Those farmers who are most aggressive in
effectively adopting and applying new
technologies are the most likely to survive.
Their size or scale of operation thereby in-
fluences the structure of agriculture. Like-
wise, structure is affected to the extent that
research discoveries or extension pro-
grams favor farm operations of a certain
scale. The significance of technology's role
in fostering structural change makes it an
important factor to consider when design-
ing research and extension programs.
Research and extension are vital to main-
taining the competitiveness and compara-


tive advantage of U.S. agriculture in inter-
national trade. Competition in export
markets is becoming increasingly keen as
countries strive to expand output and ex-
port to earn foreign exchange. Through-
out the 1970s, exports were the driving
force behind farm prices and incomes. A
return to agricultural prosperity awaits a
resurgence of exports. Growth in export
markets cannot be maintained without the
benefits of continuous adoption of cost-
reducing technologies.
The ultimate beneficiary of agricultural re-
search and extension is the consumer-
domestic and foreign. Larger supplies,
lower food prices, and better quality have
almost invariably been the main results of
agricultural research. This does not mean
that research operates contrary to the in-
terest of all farmers; rather, research
directly benefits the more progressive
farmers. Research is also critical for ex-
panding markets for farm products and for
overcoming the constant threat of disease
and other vagaries of nature.
The result of these gains and losses has been
a handsome rate of return from public invest-
ment in agriculture. Rates of return on public
investment in agricultural research typically
fall in the 30 to 60 percent range (Ruttan, 1982).
Rates of return for extension have been esti-
mated to run even higher-particularly in the
case of specific extension activities (White,
1984). The high rate of return indicates that
agricultural research and extension services
have been highly productive.


THE EFFECT OF AGRICULTURAL RESEARCH
AND EXTENSION ON FARM STRUCTURE


The impacts of research and extension on
farms, farm workers, agribusiness, and rural
communities depend on the type of technology
developed and the rate of adoption. Some tech-
nological innovations, particularly mechanical


innovations, favor and hence foster larger
farms. Other innovations could be applied on
farms of any size, but are often first adopted
by larger farms (Paarlberg, 1981; Perrin and
Winkelman, 1976; White, 1984).


66 A Special Report for the 1985 Farm Bill





WHO PROFITS FROM TECHNOLOGY CHANCE


The point that technology is one of the driv-
ing forces behind structural change in agricul-
ture has perhaps been most clearly argued by
Willard Cochrane (1983), who notes that the
first adopters of new technology are also the
immediate beneficiaries in that their costs per
unit of production are lowered and their pro-
fits are thus increased. The profits of those
firms supplying the products of new technol-
ogy also increase. In addition, higher profits
for the farmers encourage the adopting farmers
to expand output--even to the extent of increas-
ing the scale of their farm operation. However,
as output expands, prices decline; later tech-
nology adopters thus realize less profit. Those
farmers who are the last to adopt new technol-
ogies may actually be forced either to adopt or
to get out of agriculture.
Three important lessons arise from this
description of the process of technological
change:
Those farmers who are most aggressive in
effectively adopting and applying new
technologies are the most likely to survive.
Their size or scale of operation thereby in-
fluences the structure of agriculture. Like-
wise, structure is affected to the extent that
research discoveries or extension pro-
grams favor farm operations of a certain
scale. The significance of technology's role
in fostering structural change makes it an
important factor to consider when design-
ing research and extension programs.
Research and extension are vital to main-
taining the competitiveness and compara-


tive advantage of U.S. agriculture in inter-
national trade. Competition in export
markets is becoming increasingly keen as
countries strive to expand output and ex-
port to earn foreign exchange. Through-
out the 1970s, exports were the driving
force behind farm prices and incomes. A
return to agricultural prosperity awaits a
resurgence of exports. Growth in export
markets cannot be maintained without the
benefits of continuous adoption of cost-
reducing technologies.
The ultimate beneficiary of agricultural re-
search and extension is the consumer-
domestic and foreign. Larger supplies,
lower food prices, and better quality have
almost invariably been the main results of
agricultural research. This does not mean
that research operates contrary to the in-
terest of all farmers; rather, research
directly benefits the more progressive
farmers. Research is also critical for ex-
panding markets for farm products and for
overcoming the constant threat of disease
and other vagaries of nature.
The result of these gains and losses has been
a handsome rate of return from public invest-
ment in agriculture. Rates of return on public
investment in agricultural research typically
fall in the 30 to 60 percent range (Ruttan, 1982).
Rates of return for extension have been esti-
mated to run even higher-particularly in the
case of specific extension activities (White,
1984). The high rate of return indicates that
agricultural research and extension services
have been highly productive.


THE EFFECT OF AGRICULTURAL RESEARCH
AND EXTENSION ON FARM STRUCTURE


The impacts of research and extension on
farms, farm workers, agribusiness, and rural
communities depend on the type of technology
developed and the rate of adoption. Some tech-
nological innovations, particularly mechanical


innovations, favor and hence foster larger
farms. Other innovations could be applied on
farms of any size, but are often first adopted
by larger farms (Paarlberg, 1981; Perrin and
Winkelman, 1976; White, 1984).


66 A Special Report for the 1985 Farm Bill






Ch. 6-Agricultural Research and Extension Policy 67


The extent to which agricultural research
and extension affect farm structure has become
an item of increasing debate and concern. Jim
Hightower (1973) focused and fueled the con-
troversy by concluding that "Agriculture's pre-
occupation with scientific and business effi-
ciency has produced a radical restructuring of
rural America and consequently urban Amer-
ica .... America's land grant college complex
has wedded itself to an agribusiness vision of
automated, vertically integrated and corpora-
tized agriculture." Hightower's perspective ap-
pears to be that agricultural research and ex-
tension should be structurally neutral (i.e., not
favor one farm size over another), but if it
favors anything, it should favor moderate and
smaller farms.
The impact of agricultural research and ex-
tension on farm structure can best be under-
stood by considering the separate impacts of
research, extension, and technological adop-
tion on farm structure.
A research program that is structurally neu-
tral would develop technologies that can be
used by any size farm. There is limited evi-
dence about whether the type of agricultural
research being conducted by public institutions
is structurally neutral (White, 1984). Biological-
chemical technologies, the focus of most land
grant research, are more likely to be structur-
ally neutral than is mechanical research, which
is primarily done in the private sector. Mechan-
ical innovations such as the cotton picker, com-
bine, and mechanical tomato harvester have fa-
vored large farms by reducing labor require-
ments and lowering costs on large farms (Schmitz
and Seckler, 1970). The biological-chemical
technologies over the past 50 years have ac-
counted for about a doubling of output in most
farm commodities-i.e., wheat, corn, rice, and
cotton. However, mechanization and econo-
mies of size have accounted for a tenfold to
twentyfold increase in output, and this has not
been structurally neutral. In general, there has
been no widespread public recognition of the
consequences of such technological develop-
ments before their release and widespread
adoption (White, 1984).


Dissemination that is structurally neutral en-
tails dissemination of research results by re-
search and extension staff to all farmers. Al-
though the extension service disseminates
research results through a wide range of pub-
lications, public meetings, and result demon-
strations, these means are more readily ac-
cessed by the more knowledgeable and better
educated farmers, who more often are the oper-
ators of larger, more progressive farms. Since
the topics covered in publications and public
meetings are heavily influenced by current re-
search results, any bias toward larger farms in
these results would be carried over into those
publications and meetings. On the other hand,
one of the criticisms of extension has also been
that operators of the larger, more progressive
farms are more knowledgeable about the state
of the art than are extension staff. This claim
is more likely true of county-level staff than of
the State specialist staff.

Adoption that is structurally neutral involves
the equal willingness and ability of operators
of all farm sizes to adopt new technology.
Adoption neutrality would be hampered if re-
search andlor dissemination were not struc-
turally neutral. But even when research and ex-
tension activities are structurally neutral,
adoption may not be neutral because adoption
of new technology is dependent on many fac-
tors, including the potential profitability of
technology, the capital investment required,
the natural resources controlled by farmers, the
economic environment within which farmers
operate, and the technical skills of the farmer.

The structural trend in agriculture is quite
clearly toward a bimodal distribution-small
and large farms surviving, with moderate
farms struggling to exist. Small farms are sur-
viving and even increasing in number because
they have off-farm income against which to off-
set farm losses. Large farms are increasing in
number because their operators are more effi-
cient and can purchase inputs at lower prices,
sell their products at higher prices, obtain more
farm program benefits, and therefore have
higher incomes (Smith, et al., 1984).





68 A Special Report for the 1985 Farm Bill


Considering the number and complexity of
these factors, it would be difficult to achieve
a farm structure that maintains the moderate
farm simply by focusing more research and ex-
tension resources on producing and dissemi-
nating technologies specifically oriented toward
the moderate farm segment. Instead, research
and extension activities would have to be in-
tegrated into other targeted policy tools to
achieve the desired structural goals.
Since dissemination and adoption would ap-
pear to be more important than research to
structural change, the emphasis in a program
to achieve greater neutrality would logically fall
on highly applied research and extension func-
tions targeted toward the competitiveness and
survival of moderate farms. Such a program
would have to:
Increase public research efforts aimed at
developing farming and management sys-
tems that allow moderate farms to achieve
the same technical or production efficien-
cies as their larger scale counterparts.
Provide higher levels of support for farmer
cooperative research and educational
activities aimed at serving family farm
agriculture. With proper orientation,
farmer cooperatives should be able to
allow moderate farms the same input
economies as larger farms.


Increase emphasis on the use of modern
marketing and management tools by oper-
ators of moderate farms. An understand-
ing of contracting, futures markets, op-
tions markets, and committed cooperatives
will be critical to the future survival of the
moderate farm system. In addition, mod-
erate farms will have to use state-of-the-art
computer information and financial sys-
tems. Public research and extension will
play the major role in seeing that this
knowledge base is developed and reaches
farmers.
Reorienting the research and extension sys-
tem in this manner carries some risk. The com-
petitive position of American agriculture in an
open world economy could be jeopardized if,
while concentrating on improving the competi-
tive position of moderate farms, technological
advances for larger farms stagnated. Therefore,
while directing more efforts toward moderate
farms, research and extension must continue
to foster improvements in production, market-
ing, and management systems for all farm
sizes. Accomplishing such changes would re-
quire additional staff, retraining of existing
staff, more resources, and a reorientation of ex-
isting resources.


RESEARCH, PRIVATE SECTOR, AND EXTENSION ROLES


One of the most important contemporary
issues that the agricultural research and exten-
sion system has had to deal with is that of estab-
lishing both the broad priorities for research
and extension and the roles of the components
of the research and extension system. Since the
passage of the 1977 farm bill, considerable pro-
gress has been made in establishing roles and
priorities in the various components of the agri-
cultural research system. The Joint Council and
the Users Advisory Board, given sufficient time
and encouragement to perform, have the po-
tential for dealing effectively with the priorities
issue. Positive progress is indicated by the re-


cently released Joint Council Needs Assess-
ment for Food and Agricultural Sciences.

The primary question regarding the roles
issue involves the line of demarcation between
the U.S. Department of Agriculture (USDA)
and the land grant programs. This issue has
been treated quite differently by research and
extension. OTA's agricultural research system
study concluded that USDA research should
concentrate on those agricultural problems that
are important to the Nation and for which no
one State or private group has the resources,
facilities, or incentive to solve (OTA, 1981).









Such a role can logically be assigned to the
USDA Agricultural Research Service and the
USDA Economic Research Service. Concen-
trating only on national and regional problems
would represent a marked shift by the Agricul-
tural Research Service from its past decentral-
ization policies involving increasing emphasis
on research having a State or local focus.

Private Sector ImvolvemMnt
The land grant university system was estab-
lished largely because it was concluded that in
a decentralized competitive structure, the pri-
vate sector would not have the economic in-
centive to provide the level of funding needed
to maintain an efficient, viable agriculture. De-
spite many changes in the structure of agricul-
ture since the founding of the land grant sys-
tem, this premise went largely unchallenged
until the 1970s.
As a result, private sector grants for agricul-
tural research have historically come primar-
ily from foundations such as Ford or Rocke-
feller and from a small number of grants for
university developmental research associated
with the introduction of new products. With
the advent of biotechnology, the interest of pri-
vate firms in agricultural research increased
sharply. While much of this interest appears
to be a spinoff of biomedical human research,
substantially expanded resources have also
been committed to plant and animal reproduc-
tion designed to produce new varieties or to
expand the rate of genetic improvement. In ad-
dition, increased interest is being shown in
developing disease- and insect-resistant plants
as well as in more organic methods of pest
control.
One of the major reasons for this expanded,
private sector interest in agricultural research
has been the extension of patent rights to plant
varieties and other biological discoveries.
These rights, in turn, gave rise to increased pri-
vate sector interest in supporting university re-
search that could result in profitable, patented
discoveries.


Ch. 6-Agricultural Research and Extension Policy 69

The current magnitude of private sector com-
mitment to agricultural research is largely un-
known. Studies suggest that it may approach
$3 billion (National Agricultural Research and
Extension Users Advisory Board, 1983). Ap-
proximately half of the amount is spent on
production agriculture and half on food pro-
duction or postharvest technology research.
Private sector research resources are obviously
devoted to those areas having the highest short-
run profit potential. Also, despite recent large
increases in private sector agricultural re-
search, questions remain about the long-term
willingness of private sector firms to invest
large sums of money in agricultural research
and about the breadth of such research. As
noted previously, private firms have tended to
cut back on research first in times of adversity.
The private sector also plays a role in edu-
cation. For most agribusiness firms, this role
is pursued in conjunction with their efforts to
promote the products and services that they
market. The educational value of these promo-
tional activities relates more to alerting farmers
to the availability of new products than to
evaluating objectively the performance of those
products.
The burden of new product evaluation then
falls either on the farmer (through trial and er-
ror) or on the extension service (through result
demonstration); extension involvement is more
efficient. However, the biotechnology era holds
potential for increased antagonism between
private sector firms and extension because the
extension service evaluates the comparative
performance of new biotechnological products,
a role not always appreciated by firms produc-
ing products that have relatively lower levels
of performance.
With a few important exceptions, such as in-
tegrated pest management (IPM) checkoff pro-
grams, the private sector's direct financial sup-
port for agricultural extension programs has
been limited, but appears to be growing. It
might be argued that limited private sector
funding is essential for keeping extension edu-


I





70 A Special Report for the 1985 Farm Bill


cation programs objective. Greater dangers
may lie more in increased private sector fund-
ing of extension than of research. In the fund-
ing of both, it is critical to maintain the objec-
tivity and availability of information flows.

Research Involvement
Land grant universities were created to serve
the public. The agricultural component of the
land grant universities has unique respon-
sibilities to conduct and extend the results of
research for the public benefit. Traditionally,
those research results have been readily and
freely available to the public, since they have
no private property or exclusivity rights at-
tached to them. Research results that were to
be held in confidence or had proprietary rights
attached to them were frowned upon. Policy
changes that have occurred over the past 15
years hold the potential for substantially chang-
ing this traditional concept of ready and free
access to land grant university research. Some
changes have already occurred; others may oc-
cur very rapidly. In other words, changes in
property rights and exclusivity rules may have
also changed the very concept of the land grant
system.
Questions of how the land grant universities
might adjust to the new concept of research
property rights and the related opportunities
for increased private sector funding have been
the subject of extensive study. However, the
impact of these factors on the unique nature
or "social contract" of the land grant system
has received little attention.
Policy changes regarding property rights in
agricultural research had their origin in the
enactment of the Plant Variety Protection Act
of 1970. Previously, patent protection in plants
was limited to asexually reproduced material-
mainly orchard fruits and ornamental flowers.
The Plant Variety Protection Act provided that
a breeder of a new, stable, and uniform vari-
ety of sexually reproduced plants could prevent
other seedsmen from reproducing and selling
that variety for 17 years.


Of possibly greater significance was the 1980
landmark U.S. Supreme Court decision, Dia-
mond v. Chakrabarty, which held that the in-
ventor of a new micro-organism, whose inven-
tion otherwise met the legal requirements for
obtaining a patent, could not be denied a pat-
ent solely because the innovation was alive.
This decision opened the door for patenting po-
tentially all new products of the biotechnology
era.
Since the passage of the Plant Variety Pro-
tection Act and the Chakrabarty decision, pri-
vate sector interest in agricultural research has
mushroomed. OTA, for example, found that in
1983 there were 61 companies pursuing ap-
plications of biotechnology in animal agricul-
ture and 52 companies applying biotechnology
to plants. Most of these firms have developed
their own in-house research capability, employ-
ing molecular biologists, biochemists, genet-
icists, plant breeders, and veterinarians.
Relationships are also developing between
universities and many of these firms. For ex-
ample, Monsanto has a 5-year, $23.5 million
contract with Washington University under
which individual research projects are con-
ducted. At Stanford University, five corporate
sponsors (General Foods; Koopers Co., Inc.;
Bendix Corp.; Mead Corp.; and McLoren Power
and Paper Co.) contributed $2.5 million to form
the for-profit Engenics and the not-for-profit
Center for Biotechnology Research.
Such relationships are not limited to private
universities. Michigan State University (a land
grant college) created the entity Neogen to seek
venture capital for limited partnerships to de-
velop and market innovations arising out of re-
search. The formation of Neogen points up a
significant problem being encountered by
universities in the biotechnology era. Neogen
was formed, in part, for the purpose of retain-
ing faculty members who are getting offers
from biotechnology companies. In Neogen,
faculty members are allowed to develop their
entrepreneurial talent and gain financial re-
wards while remaining at the university.








The formation of Neogen reflects the reality
that biotechnology development is resulting in
or might result in a substantial drain on univer-
sity basic and applied research talent. If leading
faculty members are not overtly hired away
from universities, they may form their own
companies or become consultants. The estab-
lishment of biotechnology property rights has
substantially heightened scientists' interest in
private sector employment opportunities. In
the process, questions have arisen over who
should maintain the property right-the univer-
sity, the private firm, or the scientist.
In the Washington University-Monsanto
case, the university retains the patent rights
while Monsanto has exclusive licensing rights.
In Engenics, Stanford likewise gets the patent
rights while Engenics and its five corporate
sponsors receive the royalty-bearing licenses.
Neogen will buy patent rights from Michigan
State University, while the inventor will get a
15-percent royalty or a stock option in Neogen.
It does not take much imagination to recog-
nize the potentially profound implications of
such developments on the land grant univer-
sity system. While public sector-private sector
arrangements were kept previously at arms
length, private sector arrangements now in-
tegrate business into the university fabric.
Questions develop over who controls the
university research agenda, the allegiance of
scientists to their university employer, the will-
ingness of scientists to discuss research discov-
eries related to potentially patentable products,
and potential favoritism shown particular com-
panies by the university because of its research
ties.
The advent of patent rights, exclusive licen-
sing, and private sector investment in public
sector research may change the distribution of
benefits from land grant research discoveries.
These changes warrant direct public discus-
sion and consideration by policymakers. They
occur for at least five reasons:
By exclusive licensing or transferring of
patent rights to private firms, the right to
use discoveries is no longer freely avail-


Ch. 6-Agricultural Research and Extension Policy 71


able-even if information on the discovery
itself is freely available.
Certain individuals and firms are con-
ferred the benefits of specific land grant
research, to the potential detriment of
others. Prior to the transfer of discovery
rights, the benefits were available to any-
one who adapted a land grant discovery
to commercial usage.
The costs of the resulting discoveries are
internalized in the price of the resulting
product. The price the public pays for the
product also includes any monopoly rents
associated with the conferral of the rights.
Society thus pays twice: once for the cost
of the research and again for its benefits.
Without the conferral of property rights,
rents are minimized by competition.
Private sector-public sector inequities are
virtually assured in any granting of re-
search property rights to an individual
firm. This occurs because a relatively
small private sector investment brings ac-
cess to a much broader range of current
and prior research.
The existence of patent rights, trade secrets,
and confidential information has many po-
tentially adverse implications for exten-
sion in terms of the increased burden for
product testing, the potential lags in infor-
mation, and the absence of research infor-
mation that previously would have been
readily available.

The argument does not, however, flow ex-
clusively against the conferral of private sec-
tor property rights by the land grants. There
are three main counterbalancing arguments:

With the conferral of private property
rights and the associated private sector in-
vestment, the quantity of research discov-
eries may increase. Robert Evenson (1983),
for example, found a sharp acceleration in
private plant breeding programs after the
1970 Plant Variety Protection Act was
enacted into law. Over 1,088 patent-like
certificates were granted by February 1,
1983.


I





72 A Special Report for the 1985 Farm Bill


Without land grant university involvement
in private sector-funded research, the
universities may not be able to retain the
top-quality scientists needed to conduct
agricultural research on the frontiers of
knowledge. In the process, the agricultural
research, extension, and teaching pro-
grams would all suffer.
Patent monopoly rights may be necessary
to attract the capital investment needed to
translate the scientific advances of land
grant universities into commercial reality.
Without such proprietary protection, new
discoveries may not be able to compete for
resources to develop marketable products
or technologies. The public availability of
such products could thereby be affected.
If policymakers want land grant universities
to refrain from conferring property rights, it
will be necessary for policymakers to provide
the level of funding whereby land grant univer-
sities can compete with non-land grant univer-
sities that confer such rights. This basic deci-
sion may be the most important related public
policy decision since the land grant system was
created. Once the land grant system starts ac-
tively competing for private sector grants and
conferring licensing rights, there will be no
turning back.


Extensloe Roles
Available evidence suggests that the progress
of the agricultural research community in
establishing priorities is more advanced than
that of the extension community. The agricul-
tural research community has been widely
studied and critically evaluated within and
without the system in a series of projects ex-
tending back to the mid-1960s. In light of these
analyses, the agricultural research system has
adjusted the distribution of its resources in rec-
ognition of potential advances evolving from
biotechnology and information technology.
Similar progress is not apparent in extension.
Extension administrators suggest that this is
the case because most of the extension plan-
ning occurs at the local level through advisory
committees. Yet such a system does not obviate


the need for setting national plans and prior-
ities. One major congressionally mandated ex-
tension evaluation project culminated in a
series of reports that concentrated more on
past benefits than on future needs, priorities,
and required adjustments (Extension Service,
1983). There is also relatively little reference
to the functions or programs of extension in
the reports of either the Joint Council or the
Users Advisory Board.
Federal extension has also dramatically de-
emphasized its direct education role in the past
20 years (Hyatt, 1984). Although Federal exten-
sion specialists were generally viewed as hav-
ing a vast subject matter base in their own right
and were frequently called upon to engage in
staff training and to conduct educational pro-
grams, these specialists are viewed today more
as program leaders, coordinators, and facili-
tators. The education function is thus left to
State specialists and agents. These changes
were at least partially forced by reductions in
personnel ceilings and limited appropriations.
Regardless of the cause, this change in strat-
egy has not been beneficial to the overall na-
tional extension education program, which is
left to cope with a lack of progress in national
planning and needs assessment and a deterior-
ation in the quality of educational service to
the States.
As in research, there are issues of national
significance that the USDA Extension Service
is better able to deal with educationally than
are the States. While ultimately the States must
still take the lead in extending educational pro-
grams to farmers, the USDA Extension Serv-
ice can play an important role in making the
information and related educational materials
available on a timely basis. (For another per-
spective see Hyatt, 1984.) Currently, this role
is being played on, at best, a spotty basis. A key
mission of the Federal Extension Service
should be to facilitate technology transfer be-
tween USDA research agencies and the State
extension services as well as between States.
If this function is not adequately performed,
research agencies become motivated to develop
their own outreach programs. The need then
is for increased integration of the research and
extension function-not greater fragmentation.




Ch. 6-Agricultural Research and Extension Policy 73


To add Federal extension national program
leaders who are knowledgeable about the state
of the art of technology would be substantially
more expensive. Such staff would have to be
recognized as national extension coordinators
and be provided compensation consistent with
that role. Finally, they would have to have ac-
cess to resources whereby State specialists and
researchers coordinated to develop state-of-the-
art educational materials that could be used in
all States.
The biotechnology era presents some very
important challenges to the extension com-
munity-challenges that could determine ex-
tension's future usefulness as an educational
aid to farmers. With renewed emphasis on
basic agricultural research, substantial concern
arises about whether a gap in applied research
will develop. This could occur as applied scien-
tists are attracted into basic research that of-
fers higher rewards, leaving open the jobs in
applied research. The potential for such a gap
is reduced by increased private sector interest
and involvement in biotechnology research
and development (R&D). However, as the pri-
vate sector performs a larger share of the ap-
plied research, extension may become even
more involved in the evaluation of technologies
and products flowing out of the private sector.
Without such evaluation individual farmers
and ranchers will incur the costs of experimen-
ting to determine which combinations are op-
timum for use in production. These costs will
be converted into a decline in the number of
farms (for those who used the wrong input
combinations), higher food costs, and reduced
competitiveness in international commodity
markets.
Substantial challenge is involved in exten-
sion's adjusting to this new role. While in some
States technology and extension are already
deeply involved in the evaluation of new prod-
I ucts, in other States product evaluation has
been primarily a function of experiment sta-
tions. In the future, experiment stations will
likely be doing less of this work, and exten-
sion's responsibilities will correspondingly in-
crease. Meeting this increased responsibility
will entail a larger specialist staff with mod-


ern scientific training. Some States may be in-
clined to forego the responsibility of getting in-
volved in conflict-oriented product evaluation
programs. To the extent that this occurs, the
usefulness of extension to the farmer will
decline.
Many of the technologies on the horizon are
exceedingly complex and foreign to many ex-
tension staff. In the foreseeable future embryo
transplant technology may be as important to
the dairy industry as artificial insemination has
been over the past three decades. Growth reg-
ulators will increasingly be applied in minute
quantities to plants to increase productivity.
New strains of genetically engineered plants
and animals will be entering commercial pro-
duction channels. Extensive staff training and
development will be required at both the spe-
cialist and county levels for extension to play
an effective role in technology transfer during
the biotechnology era. Without such training,
extension will play an increasingly less impor-
tant role in production agriculture. Technol-
ogy transfer will occur less efficiently with
more structural impacts-larger farms will ben-
efit at the expense of smaller farms.
At current funding levels, the most difficult
issue facing extension is whether to limit its
role and coverage to those functions for which
it has the greatest expertise. Without criteria
for limiting the role of extension, extension
activities might become so dispersed and out
of focus that their effectiveness would be im-
paired. Regardless of whether the problem is
related to agriculture or not, extension may be
called upon to solve it. It is not possible for ex-
tension to be everything to everybody, particu-
larly in times of limited resources.
The Joint Council has not given sufficient at-
tention to the role of extension. As a starting
point for defining that role, it must be remem-
bered that the root of extension is research.
Similarly, extension is a primary outlet for re-
search, after an appropriate level of product
development. Extension is, therefore, delimited
by the scientific endeavors of the research com-
ponents of the agricultural research system, in-
cluding both the public and private sector com-
ponents.





74 A Special Report for the 1985 Farm Bill


The core mission of extension is, therefore,
one of developing, extending, and bringing
about the use of research-based knowledge.
The core source of that knowledge is the agri-
cultural experiment station. Viewing extension
in a broader context than this runs the serious
risk of reducing its overall effectiveness. This
is particularly the case when it is recognized
that extension is likely to play an increasing
role in filling a portion of the gap between basic
research and extension, i.e., applied research.
Another dimension of this role problem in-
volves the tendency for the experiment station
to become more involved in extension-type
educational programs as a way of gaining pub-


lic recognition and support. Considerable care
must be taken not to foster such duplication
of efforts.
The 1890 land grant universities have evolved
into institutions that have a comparative advan-
tage in studying problems that are unique to
small farmers-particularly those that depend
on agriculture for a majority of their income.
Satisfactory performance of this function re-
quires a recognition of this role and a closer
working relationship with the 1862 land grant
university in both research and extension pro-
grams (Lovvorn, 1984).


IMPLICATIONS FOR THE 1985 FARM BILL


* Granting of property rights and exclusive
licensing of technological discoveries have
brought the unique nature or "social con-
tract" of land grant universities into ques-
tion. These new rules may change the dis-
tribution of benefits from land grant research
discoveries. These changes warrant direct
public discussion and consideration by pol-
icymakers.
* Progress of the agricultural research com-
munity in establishing priorities is more ad-
vanced than that of extension.
* The agricultural research system has ad-
justed the allocation of resources in recog-
nition of potential advances evolving from
biotechnology and information technology.
Similar progress is not apparent in ex-
tension.


* There is a need to address the following ex-
tension issues:
-clientele and mission of extension,
-organizational structure of the extension
system,
-role of Federal extension service, and
-need for extension to conduct applied re-
search.
* Research and extension policy is a critical
component of agricultural structure policy.
For moderate farms to be able to compete,
for example, ways must be developed for
making new technologies more available to
moderate farms and for providing training
in the use of these technologies.









Appendix A.-Summary Analysis Tables

for Crop Farms



Table A-i.-Comparlson of Selected Farm Commodity and Income Tax Policy Scenarios on Representative
Corn-Soybean Farms in East Central Illinois

Alternative Scenariosa
Criteria I II III IV V VI VII VIII
Moderate size (640 acres):
Probability of survival........................ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth ($1,000) ..... 703.0 743.0 703.0 568.0 593.0 669.0 563.0 719.0
Ending farm size (acres) ..................... 902.0 904.0 902.0 824.0 837.0 907.0 834.0 893.0
Annual net farm income ($1,000) .............. 23.2 29.9 23.2 10.2 11.8 19.1 11.1 19.0
Annual government payment ($1,000) .......... 11.6 9.8 11.6 0.7 0.7 8.6 0.0 11.7
Large size (982 acres):
Probability of survival ........................ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth ($1,000) ..... 975.0 970.0 991.0 645.0 693.0 801.0 622.0 852.0
Ending farm size (acres) ..................... 1,374.0 1,364.0 1,388.0 1,139.0 1,180.0 1,355.0 1,134.0 1,217.0
Annual net farm income ($1,000) .............. 24.3 22.9 26.4 14.3 5.2 8.0 1.1 24.9
Annual government payment ($1,000) .......... 22.6 16.6 24.3 1.0 1.0 7.8 0.0 21.9
Very large size (1,630 acres):
Probability of survival ........................ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth ($1,000) ..... 1,267.0 1,348.0 1,266.0 991.0 1,033.0 1,056.0 1,036.0 1,044.0
Ending farm size (acres) ..................... 1,945.0 1,932.0 1,942.0 1,856.0 1,859.0 1,908.0 1,876.0 1,784.0
Annual net farm income ($1,000) .............. 51.8 62.2 52.4 31.1 35.1 34.7 34.8 54.4
Annual government payment ($1,000) .......... 23.6 19.3 25.3 1.7 1.7 0.0 0.0 23.3



Table A-2.-Comparison of Selected Farm Commodity and Income Tax Policy Scenarios on
Representative Irrigated Row Crop Farms in South Central Nebraska

Alternative Scenarios a
Criteria I II III IV V VI VII VIII
Moderate size (672 acres):
Probability of survival...................... 100.0 100.0 100.0 92.0 100.0 100.0 90.0 100.0
Present value of ending net worth ($1,000) ..... 670.0 736.0 670.0 260.0 476.0 670.0 264.0 628.0
Ending farm size (acres) ..................... 921.0 909.0 921.0 882.0 870.0 921.0 808.0 917.0
Annual net farm income ($1,000) .............. 26.8 31.0 26.8 -9.8 10.6 26.8 -11.4 26.8
Annual government payment ($1,000) 17.3 14.5 17.3 1.0 1.0 17.3 0.0 17.9
Large size (920 acres):
Probability of survival ........................ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth ($1,000) ..... 1,349.0 1,377.0 1,369.0 739.0 1,084.0 1,180.0 750.0 1,269.0
Ending farm size (acres) ..................... 1,257.0 1,253.0 1,257.0 1,242.0 1,240.0 1,257.0 1,243.0 1,234.0
Annual net farm income ($1,000) .............. 58.4 60.9 57.4 0.1 35.7 37.4 -0.5 58.9
Annual government payment ($1,000) .......... 24.1 19.3 23.9 1.3 1.3 15.3 0.0 24.4
Very large size (2,085 acres):
Probability of survival...................... 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth ($1,000) ..... 2,259.0 2,374.0 2,407.0 1,013.0 1,863.0 1,270.0 1,007.0 2,072.0
Ending farm size (acres) .................... 2,375.0 2,383.0 2,384.0 2,167.0 2,280.0 2,197.0 2,128.0 2,330.0
Annual net farm income ($1,000) .............. 118.6 127.3 134.6 1.3 88.0 10.8 -0.1 112.8

aThe Scenarios are:
I-Continuation of the 1981 Farm Bill and 1983 Federal Income tax provisions.
II-A 20% Acreage Reduction in 1986-1992.
Ill-No Farm Program Payment Limitation in 1983-1992.
IV-No Price Support and No Deficiency Payment in 1983-1992.
V-No Target PricelDeficiency Payment in 1983-1992.
VI-Target Farm Program Benefits to farms that produce less than $300,000 In program crops.
VII-No Farm Program in 1983-1992.
VIII-Reduced Income Tax Benefits and the Base Farm Program.
The impact of Price Supports can be derived by subtracting Scenario 5 from Scenario 6.
The impact of Income Supports can be derived by subtracting Scenario 6 from Scenario 1.
The impact of Income Supports with a $50,000 Payment Limitation can be found by subtracting Scenario 6 from Scenario 4.






78 A Special Report for the 1985 Farm Bill



.Table A.3.-Comparison of Selected Farm Commodity and Income Tax Policy Scenarios on
Representative Southern Plains Wheat Farms

Alternative Scenarios
Criteria I II III IV V VI VII VII
Moderate size (1,280 acres):
Probability of survival....................... 100.0 100.0 100.0 76.0 100.0 100.0 48.0 100.0
Present value of ending net worth ($1,000) ..... 803.0 1,032.0 811.0 283.0 426.0 761.0 189.0 710.0
Ending farm size (acres) .................... 1,901.0 1,955.0 1,901.0 1,565.0 1,648.0 1,910.0 1,478.0 1,757.0
Annual net farm income ($1,000) .............. 2.6 18.3 3.1 -33.6 -21.4 -0.9 -41.6 -8.3
Annual government payment ($1,000) .......... 30.9 31.5 31.6 2.5 2.5 27.7 0.0 29.4
Large size (1,920 acres):
Probability of survival ........................ 100.0 100.0 100.0 50.0 90.0 96.0 32.0 100.0
Present value of ending net worth ($1,000) ..... 1,028.0 1,359.0 1,117.0 294.0 475.0 696.0 179.0 833.0
Ending farm size (acres) .................... 2,765.0 2,890.0 2,755.0 2,234.0 2,339.0 2,618.0 2,093.0 2,499.0
Annual net farm income ($1,000) .............. 9.0 28.5 17.3 -52.5 -34.9 -17.6 -67.9 -21.8
Annual government payment ($1,000) .......... 39.0 39.1 44.7 4.2 3.7 16.2 0.0 37.3
Very large size (3,200 acres):
Probability of survival....................... 100.0 100.0 100.0 100.0 100.0 100.0 92.0 100.0
Present value of ending net worth ($1,000) ..... 1,936.0 2,204.0 2,231.0 1,096.0 1,412.0 1,087.0 925.0 1,657.0
Ending farm size (acres) .................... 4,218.0 4,365.0 4,483.0 3,552.0 3,834.0 3,494.0 3,472.0 3,805.0
Annual net farm income ($1,000) .............. 48.9 59.5 78.4 -7.8 15.6 -13.6 -25.1 28.1
Annual government payment ($1,000) .......... 44.2 45.0 76.9 5.8 5.9 0.0 0.0 44.1




Table A-4.-Comparison of Selected Farm Commodity and Income Tax Policy Scenarios on
Representative General Crop Farms in the Delta of Mississippi

Alternative Scenarios a
Criteria I II III IV V VI VII VIII
Moderate size (1,443 acres):
Probability of survival ........................ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth ($1,000) ..... 1,651.0 1,757.0 1,881.0 1,106.0 1,134.0 1,059.0 1,070.0 1,533.0
Ending farm size (acres) ..................... 2,009.0 2,057.0 2,093.0 1,625.0 1,645.0 1,581.0 1,590.0 1,913.0
Annual net farm income ($1,000) .............. 38.9 92.6 64.6 -14.2 -6.9 -16.3 -17.6 29.9
Annual government payment ($1,000) .......... 48.2 45.2 75.4 1.9 1.9 0.0 0.0 47.9
Large size (3,119 acres):
Probability of survival....................... 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth ($1,000) ..... 2,940.0 3,280.0 4,418.0 2,482.0 2,537.0 2,433.0 2,454.0 3,139.0
Ending farm size (acres) ..................... 3,327.0 3,340.0 3,877.0 3,119.0 3,135.0 3,119.0 3,119.0 3,135.0
Annual net farm income ($1,000) .............. 38.3 65.1 147.9 -20.6 -8.2 -28.9 -25.1 21.8
Annual government payment ($1,000) .......... 49.9 49.1 160.6 4.7 4.8 0.0 0.0 49.9
Very large size (6,184 acres):
Probability of survival ........................ 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth ($1,000) ..... 5,450.0 6,117.0 7,728.0 5,135.0 5,175.0 4,964.0 5,079.0 5,902.0
Ending farm size (acres) ................... 6,248.0 6,254.0 6,530.0 6,270.0 6,245.0 6,242.0 6,267.0 6,203.0
Annual net farm Income ($1,000) .............. 41.8 118.2 277.1 -19.7 -0.6 -42.9 -32.4 5.9
Annual government payment ($1,000) .......... 49.9 49.8 277.9 7.9 7.9 0.0 0.0 49.9
The Scenarios are:
I-Continuation of the 1981 Farm Bill and 1983 Federal Income tax provisions.
II-A 20% Acreage Reduction In 1986-1992.
Ill-No Farm Program Payment Limitation In 1983-1992.
IV-No Price Support and No Deficiency Payment In 1983-1992.
V-No Target Price/Deficiency Payment In 1983-1992.
VI-Target Farm Program Benefits to farms that produce less than $300,000 In program crops.
VII-No Farm Program in 1983.1992.
VIII-Reduced Income Tax Benefits and the Base Farm Program.
The Impact of Price Supports can be derived by subtracting Scenario 5 from Scenario 6.
The Impact of Income Supports can be derived by subtracting Scenario 6 from Scenario 1.
The Impact of Income Supports with a $50,000 Payment Limitation can be found by subtracting Scenario 6 from Scenario 4.







App. A-Summary Analysis Tables for Crop Farms 79


Table A-5.-Comparison of Selected Farm Commodity and Income Tax Policy Scenarios on
Representative Texas Southern High Plains Cotton Farms
Alternative Scenarios a
Criteria I II III IV V VI VII VIII
Moderate size (1,088 acres):
Probability of survival......................... 92.0 94.0 94.0 56.0 68.0 92.0 42.0 88.0
Present value of ending net worth ($1,000) ..... 564.0 648.0 601.0 242.0 301.0 564.0 167.0 516.0
Ending farm size (acres) ..................... 1,558.0 1,635.0 1,648.0 1,216.0 1,274.0 1,558.0 1,213.0 1,565.0
Annual net farm income ($1,000) .............. 8.3 13.3 11.9 -28.9 -21.7 8.2 -40.6 -6.0
Annual government payment ($1,000) .......... 26.0 22.2 29.5 1.3 1.1 25.9 0.0 25.8
Large size (3,383 acres):
Probability of survival........................ 90.0 94.0 94.0 72.0 82.0 86.0 62.0 88.0
Present value of ending net worth ($1,000) ..... 1,412.0 1,697.0 1,853.0 931.0 1,055.0 1,191.0 801.0 1,226.0
Ending farm size (acres) ..................... 4,289.0 4,455.0 4,577.0 3,748.0 3,857,0 3,985.0 3,649.0 3,965.0
Annual net farm income ($1,000) .............. 33.4 53.6 83.3 -14.8 3.6 12.9 -39.7 -7.2
Annual government payment ($1,000) .......... 38.0 35.1 83.3 3.2 3.0 16.8 0.0 37.9
Very large size (5,570 acres):
Probability of survival 94.0 96.0 98.0 92.0 96.0 88.0 78.0 94.0
Present value of ending net worth ($1,000) ..... 3,027.0 3,489.0 4,047.0 2,367.0 2,645.0 2,287.0 2,066.0 2,583.0
Ending farm size (acres) ..................... 6,002.0 6,047.0 6,514.0 5,781.0 5,848.0 5,727.0 5,736.0 5,746.0
Annual net farm income ($1,000) .............. 66.6 100.6 170.6 -3.2 31.0 -13.9 -40.5 -15.6
Annual government payment ($1,000) .......... 40.2 39.1 135.8 4.8 4.6 0.0 0.0 40.4
OThe Scenarios are:
I-Continuation of the 1981 Farm Bill and 1983 Federal income tax provisions.
II-A 20% Acreage Reduction In 1986-1992.
Ill-No Farm Program Payment Limitation in 19831992.
IV-No Price Support and No Deficiency Payment in 1963-1992.
V-No Target Price/Deficiency Payment In 1983-1992.
VI-Target Farm Program Benefits to farms that produce less than S300,000 In program crops.
VII-No Farm Program In 1963-1992.
VIII-Reduced Income Tax Benefits and the Base Farm Program.
The impact of Price Supports can be derived by subtracting Scenario 5 from Scenario 6.
The impact of income Supports can be derived by subtracting Scenario 6 from Scenario 1.
The impact of Income Supports with a W50,000 Payment Limitation can be found by subtracting Scenario 6 from Scenario 4.


I






80 A Special Report for the 1985 Farm Bill



Table A-6.-Comparison of Selected Financial Bailout Scenarios for Three Representative
Corn-Soybean Farms in East Central Illinois*

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
640-acre Farm 982-acre Farm 1,630-acre Farm
Criteria IX X XI IX X XI IX X XI
Probability of survival ............... 80.0 72.0 84.0 88.0 80.0 90.0 100.0 100.0 100.0
Present value of ending net worth
($1,000) .......................... 271.0 291.0 299.0 579.0 588.0 654.0 822.0 872.0 831.0
Ending farm size (acres) ............. 653.0 689.0 662.0 1,046.0 1,062.0 1,073.0 1,795.0 1,740.0 1,712.0
Annual net farm income ($1,000) ...... -0.9 -3.3 3.8 2.0 -3.5 7.8 30.6 27.9 36.9
Annual government payment ($1,000) .. 8.9 8.9 9.1 19.2 18.9 19.0 23.0 22.8 22.8



Table A-7.-Comparison of Selected Financial Bailout Scenarios for Three Representative
Irrigated Row Crop Farms in South Central Nebraska"

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
672-acre Farm 920-acre Farm 2,083-acre Farm
Criteria IX X XI IX X XI IX X XI
Probability of survival .............. 96.0 86.0 98.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth
($1,000) .......................... 353.0 334.0 387.0 871.0 876.0 893.0 1685.0 1820.0 1714.0
Ending farm size (acres) ............. 822.0 822.0 854.0 1,195.0 1,146.0 1,205.0 2,399.0 2,392.0 2,421.0
Annual net farm income ($1,000) ...... 5.9 2.9 11.3 22.6 16.7 28.2 58.9 77.2 72.1
Annual government payment ($1,000) .. 16.7 16.8 17.0 23.0 22.6 22.9 36.0 36.0 36.1



Table A-8.-Comparison of Selected Financial Bailout Scenarios for Three Representative
Southern Plains Wheat Farms*

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
1,280-acre Farm 1,920-acre Farm 3,200-acre Farm
Criteria IX X XI IX X XI IX X XI
Probability of survival ............... 86.0 98.0 100.0 40.0 70.0 80.0 100.0 100.0 100.0
Present value of ending net worth
($1,000) .......................... 289.0 408.0 383.0 258.0 399.0 406.0 1,248.0 1,373.0 1,348.0
Ending farm size (acres) ............. 1,434.0 1,549.0 1,552.0 1,994.0 2,058.0 2,118.0 3,779.0 3,978.0 3,891.0
Annual net farm income ($1,000) ...... -22.5 -21.2 -14.3 -37.9 -35.1 -24.1 17.1 12.4 27.5
Annual government payment ($1,000) .. 25.2 26.4 26.8 34.8 35.2 35.6 43.9 44.1 44.0




Table A-9.-Comparison of Selected Financial Bailout Scenarios for Three Representative
General Crop Farms in the Delta of Mississippil

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
1,443-acre Farm 3,119-acre Farm 6,184-acre Farm
Criteria IX X XI IX X XI IX X XI
Probability of survival ............... 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth
($1,000) .......................... 1,563.0 1,656.0 1,545.0 3,237.0 3,431.0 2,968.0 5,259.0 5,840.0 4,990.0
Ending farm size (acres) ............. 2109.0 2,115.0 2,025.0 3,845.0 4,719.0 3,685.0 6,606.0 7,656.0 6,453.0
Annual net farm income ($1,000) ...... 35.5 29.4 37.7 30.1 20.4 33.8 3.7 -14.8 5.4
Annual government payment ($1,000) .. 48.4 48.4 48.3 49.9 49.9 49.9 49.9 49.9 49.9
aThe Scenarios are:
IX-Continuation of the 1981 Farm Bill and the 1983 Federal tax provisions for a highly leveraged farm.
X-Restructure of debt for a highly leveraged farm.
XI-interest rate subsidy (buy-down) in the first two years for a highly leveraged farm.







App. A-Summary Analysis Tables for Crop Farms 81



Table A-10-Comparison of Selected Financial Bailout Scenarios for Three Representative
Texas Southern High Plains Cotton Farms*


Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
1,088-acre Farm 3,383-acre Farm 5,570-acre Farm


Criteria IX X XI IX X XI IX X XI
Probability of survival ............... 64.0 66.0 72.0 56.0 50.0 60.0 66.0 64.0 66.0
Present value of ending net worth
($1,000) .......................... 304.0 314.0 343.0 604.0 600.0 733.0 1,310.0 1,356.0 1,619.0
Ending farm size (acres) ............. 1,414.0 1,434.0 1,443.0 3,770.0 3,841.0 3,821.0 5,733.0 5,976.0 5,772.0
Annual net farm income ($1,000) ...... -5.4 -6.4 1.3 -9.1 -21.2 6.9 -41.8 -57.3 -6.3
Annual government payment ($1,000) .. 24.4 24.8 24.7 36.8 36.4 37.2 41.1 41.3 41.6
aThe scenarios are:
IX-Continuation of the 1981 Farm Bill and the 1983 Federal tax provisions for a highly leveraged farm.
X-Restructure of debt for a highly leveraged farm.
XI-n-terest rate subsidy (buy-down) in the first two years for a highly leveraged farm.

Table A-11.-Comparison of Selected Policy Scenarios Assuming No New Technology for
Three Representative Corn-Soybean Farms in East Central Illinois'

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
640-acre Farm 982-acre Farm 1,630-acre Farm
Criteria XII XIII XIV XII XIII XIV XII XIII XIV
Probability of survival ............... 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 98.
Present value of ending net worth
($1,000) ................: ......... 699.0 589.0 561.0 862.0 604.0 540.0 915.0 694.0 672.0
Ending farm size (acres) ............. 902.0 837.0 850.0 1,392.0 1,190.0 1,116.0 1,899.0 1,801.0 1,796.0
Annual net farm income ($1,000) ...... 23.0 11.7 10.8 23.9 3.3 -0.8 25.3 9.8 6.1
Annual government payment ($1,000) .. 11.6 0.7 0.0 22.9 1.0 0.0 22.9 1.7 0.0



Table A-12.-Comparison of Selected Policy Scenarios Assuming No New Technology for
Three Representative Irrigated Row Crop Farms in South Central Nebraska'

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
672-acre Farm 920-acre Farm 2,085-acre Farm
Criteria XII XIII XIV XII XIII XIV XII XIII XIV
Probability of survival ............... 100.0 100.0 90.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth
($1,000) ........................ 670.0 475.0 263.0 1,230.0 985.0 671.0 1,812.0 1,388.0 680.0
Ending farm size (acres .............. 921.0 870.0 808.0 1,257.0 1,221.0 1,226.0 2,402.0 2,240.0 2,107.0
Annual net farm income ($1,000) ...... 26.7 10.6 -11.4 53.9 30.3 -2.6 77.5 51.0 -10.9
Annual government payment ($1,000) .. 17.3 0.9 0.0 23.9 1.3 0.0 35.7 3.0 0.0


Table A-13.-Comparison of Selected Policy Scenarios Assuming No New Technology for
Three Representative Southern Plains Wheat Farms'

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
1,280-acre Farm 1,920-acre Farm 3,200-acre Farm
Criteria XII XIII XIV XII XIII XIV XII XIII XIV
Probability of survival ............... 100.0 90.0 32.0 100.0 44.0 10.0 100.0 82.0 28.0
Present value of ending net worth
($1,000) ......................... 726.0 325.0 134.0 780.0 229.0 81.0 1,131.0 562.0 220.0
Ending farm size (acres) ........... 1,859.0 1,632.0 1,430.0 2,605.0 2,304.0 2,048.0 3,699.0 3,542.0 3,322.0
Annual net farm income ($1,000) ...... -1.3 -28.9 -46.8 -10.9 -52.9 -77.1 -2.1 -45.4 -85.8
Annual government payment ($1,000) .. 30.7 2.5 0.0 38.1 3.9 0.0 43.7 5.9 0.0
'The Scenarios are:
XII-Continuation of the 1981 Farm Bill and the 1983 Federal tax provisions, assuming no new technology scenario.
XIlI-No Target Price/Deficiency Payment Program, assuming no new technology scenario.
XIV-Deficiency plus diversion payments and any other government payments received for government loans and storage costs.






82 A Special Report for the 1985 Farm Bill


Table A-14.-Comparison of Selected Policy Scenarios Assuming No New Technology for
Three Representative General Crop Farms in the Delta of Mississippi*

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
1,443-acre Farm 3,119-acre Farm 6,184-acre Farm
Criteria XII XIII XIV XII XIII XIV XII XllI XIV
Probability of survival .............. 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth
($1,000) ........................... 1,613.0 1,104.0 1,043.0 2,786.0 2,451.0 2,354.0 5,286.0 4,915.0 4,714.0
Ending farm size (acres) ............. 2,006.0 1,638.0 1,587.0 3,343.0 3,148.0 3,119.0 6,322.0 6,277.0 6,261.0
Annual net farm income ($1,000) ...... 38.6 -7.3 -18.3 34.0 -11.9 -29.9 15.1 -27.5 -57.7
Annual government payment ($1,000) .. 48.2 1.9 0.0 49.9 4.8 0.0 49.9 7.9 0.0



Table A-15.-Comparison of Selected Policy Scenarios Assuming No New Technology for
Three Representative Texas Southern High Plains Cotton Farms*

Alternative Scenarios for Alternative Scenarios for Alternative Scenarios for
1,088-acre Farm 3,383-acre Farm 5,570-acre Farm
Criteria XII Xlli XIV XII XIII XIV XII XIII XIV
Probability of survival ............... 92.0 68.0 42.0 88.0 78.0 60.0 94.0 90.0 76.0
Present value of ending net worth
($1,000) ......................... 552.0 290.0 161.0 1,325.0 966.0 738.0 2,807.0 2,322.0 1,843.0
Ending farm size (acres) ............. 1,590.0 1,280.0 1,206.0 4,273.0 3,818.0 3,633.0 5,960.0 5,816.0 5,724.0
Annual net farm income ($1,000) ...... 7.0 -22.2 -41.0 25.4 -3.6 -45.5 47.0 0.2 -65.9
Annual government payment ($1,000) .. 26.3 1.1 0.0 37.9 3.0 0.0 40.5 4.8 0.0
aThe Scenarios are:
XII-Continuation of the 1981 Farm Bill and the 1983 Federal tax provisions, assuming no new technology scenario.
XIII-No Target Price/Deficiency Payment Program, assuming no new technology scenario.
XIV-Deficiency plus diversion payments and any other government payments received for government loans and storage costs.






App. A-Summary Analysis Tables for Crop Farms 83


Table A-16.-Comparison of Selected Policy
Scenarios for a New Entrant on a Representative
640 Acre Corn-Soybean Farm In
East Central Illnois*

Alternative Scenarios for
640-acre Farm
Criteria XV XVI XVII
Probability of survival ....... 2.0 0.0 4.0
Present value of ending net
worth ($1,000)............ 221.0 202.0 197.0
Ending farm size (acres) ..... 640.0 640.0 640.0
Annual net farm income
($1,000) .................. -56.9 -61.1 -62.8
Annual government payment
($1,000) .................. 9.6 6.1 0.0



Table A-17.--Comparison of Selected Policy
Scenarios for a New Entrant on a Representative
672 Acre Irrigated Row Crop Farm in
South Central Nebraska*

Alternative Scenarios for
672-acre Farm
Criteria XV XVI XVII
Probability of survival ....... 84.0 42.0 6.0
Present value of ending net
worth ($1,000)............ 187.0 106.0 356.0
Ending farm size (acres) ..... 674.0 666.0 672.0
Annual net farm income
($1,000) .................. -19.2 -35.8 -56.6
Annual government payment
($1,000) .................. 14.5 1.2 0.0


Table A-18.-Comparison of Selected Policy
Scenarios for a New Entrant on a Representative
Southern Plains Wheat Farm,

Alternative Scenarios for
1,280-acre Farm
Criteria XV XVI XVII
Probability of survival ....... 2.0 0.0 0.0
Present value of ending net
worth ($1,000)............ 39.0 26.0 45.0
Ending farm size (acres) ..... 1,280.0 1,280.0 1,280.0
Annual net farm income
($1,000) ................ -94.2 -103.2 -121.9
Annual government payment
($1,000) .................. 18.1 7.4 0.0


Table A-19.-Comparlson of Selected Policy
Scenarios for a New Entrant on a Representative
1443 Acre General Crop Farm in
the Delta of Mississippi8

Alternative Scenarios for
1,443-acre Farm
Criteria XV XVI XVII
Probability of survival ....... 100.0 76.0 62.0
Present value of ending net
worth ($1,000)............. 985.0 395.0 319.0
Ending farm size (acres) ..... 1,830.0 1,459.0 1,443.0
Annual net farm income
($1,000) ................. -18.8 -76.8 -91.3
Annual government payment
($1,000) .................. 47.3 2.3 0.0


Table A-20.-Comparison of Selected Policy
Scenarios for a New Entrant on a Representative
Texas Southern High Plains Cotton Farms

Alternative Scenarios for
1,088-acre Farm
Criteria XV XVI XVII
Probability of survival ....... 50.0 16.0 10.0
Present value of ending net
worth ($1,000)............ 235.0 53.0 41.0
Ending farm size (acres) ..... 1,306.0 1,155.0 1,126.0
Annual net farm income
($1,000) ................ -35.7 -66.5 -84.9
Annual government payment
($1,000) .................. 21.7 2.0 0.0
aThe Scenarios are:
XV-Continuation of the 1981 Farm Bill and the 1983 Federal tax pro-
visions.
XVI-No Target PricelDeficiency Payment Program In 1981-1992.
XVII-No Farm Program In 1983-1992.







Appendix B.-Summary Analysis Tables

for Dairy Farms





Table B-1.-Comparison of Selected Commodity Policy, Tax and Technology Scenarios on
Representative Dairy Farms in Minnesota'

Alternative Scenarios
Initial
Criteria situation Base I II III IV V VI VII VIII
52 cow Minnesota dairy:
Probability of survival ............. NA 70.0 68.0 68.0 38 34.0 70.0 92.0 -
Present value of ending net worth
($1,000) .................. .. 417.0 224.0 222.0 223.0 157.0 149.0 221.0 314.0 -
Ending equity ratio (fraction) ...... 0.71 0.41 0.41 0.41 0.30 0.29 0.41 0.57 -
Annual net farm income ($1,000)... NA -27.0 -27 -27.0 -35.0 -36.0 -27.0 -15.0 -
125 cow Minnesota dairy:
Probability of survival ............ NA 100.0 100.0 100.0 100.0 98.0 100.0 100.0 100.0 100.0
Present value of ending net worth
($1,000) ..................... 969.0 1,012.0 1,019.0 1,012.0 888.0 872.0 965.0 1,111.0 116.0 1,140.0
Ending equity ratio (fraction) ...... 0.76 0.83 0.83 0.82 0.72 0.71 0.79 0.89 0.92 0.91
Annual net farm income ($1,000)... NA 0.0 0.0 0.0 -18.0 -19.0 -9.0 15.0 21.0 44.0


Table B-2.-Comparison of Selected Commodity Policy, Tax and Technology Scenarios on
Representative Dairy Farms in the Southwest'

Alternative Scenarios
Initial
Criteria situation Base I 11 III IV V VI VII VIII
359 cow Arizona dairy:
Probability of survival ............ NA 96.0 86.0 96.0 96.0 92.0 96.0 100.0 -
Present value of ending net worth
($1,000) .................... 744.0 1,404.0 1,018.0 1,399.0 1,334.0 1,098.0 1,325.0 1,719.0 -
Ending equity ratio (fraction) ...... 0.71 0.94 0.84 0.94 0.94 0.88 0.94 0.95 -
Annual net farm income ($1,000)... NA 28.0 -32.0 27.0 13.0 -22.0 31.0 93.0 -
550 cow California dairy:
Probability of survival ............ NA 96.0 76.0 96.0 84.0 76.0 96.0 98.0 -
Present value of ending net worth
($1,000). .................. 1,261.0 1,824.0 1,107.0 1,813.0 1,368.0 1,074.0 1,716.0 2,312.0 -
Ending equity ratio (fraction) ...... 0.71 0.90 0.68 0.90 0.79 0.67 0.90 0.94 -
Annual net farm income ($1,000)... NA -29.0 -142.0 -30.0 -101.0 -147.0 -30.0 65.0 -
1,436 cow California dairy:
Probability of survival ............ NA 96.0 92.0 96.0 94.0 92.0 96.0 100.0 100.0 100.0
Present value of ending net worth
($1,000) ................. 2,538.0 6,507.0 4,968.0 6,496.0 5,448.0 4,774.0 6,278.0 9.553.0 8,750.0 11,084.0
Ending equity ratio (fraction) ...... 0.69 0.92 0.89 0.92 0.89 0.88 0.92 0.95 .96 0.94
Annual net farm income ($1,000).. NA 375.0 136.0 373.0 211.0 99.0 371.0 798.0 614.0 1,154.0
aThe Scenarios are:
Base-Continuation of present policy
I-A 20 percent acreage reduction in 1986-1992-9 percent higher teed costs.
II-No crop program
Ill-Fifty cent per cwt. lower milk pnce.
IV-No dairy price support program
V-Reduce income tax benefit program
VI-Milk supply control program
Vi--Computer feeding technology.
VIII-Bovine growth hormone technology







App. -Summary Analysis Tables for Dairy Farms 85



Table 8-3.-Comparison of Selected Commodity Policy, Tax and Technology Scenarios on
Representative Dairy Farms in Florida'

Alternative Scenarios
Initial
Criteria situation Base I II III IV V VI VII VIII
350 cow Flords dairy:
Probability of survival ............ NA 98.0 70.0 96.0 82 68.0 92.0 100.0 -
Present value of ending net worth
($1,000) .................... 757.0 1,009.0 578.0 1,005.0 933.0 648.0 911.0 1,327.0 -
Ending equity ratio (fraction) ...... 0.71 0.85 0.57 0.85 0.74 0.59 0.80 0.93 -
Annual net farm income ($1,000)... NA -8.0 -71.0 -8.0 -17.0 -66.0 -3.0 28.0 -
600 cow Florida dairy:
Probability of survival ............ NA 100.0 88.0 100.0 98.0 84.0 100.0 100.0 -
Present value of ending net worth
($1,000) .................... 1,465.0 2,170.0 1,547.0 2,169.0 2,130.0 1,630.0 1,996.0 2,326.0 -
Ending equity ratio (fraction) ...... 0.76 0.94 0.81 0.94 0.91 0.78 0.92 0.94 -
Annual net farm income ($1,000)... NA 33.0 -62.0 32.0 30.0 -46.0 33.0 63.0 -
1,436 cow Florid dairy:
Probability of survival ............ NA 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Present value of ending net worth
($1,000).................... 3,343.0 8,691.0 7,338.0 8,670.0 7,942.0 7,766.0 8,396.0 9,954.0 10,576.0 12,358.0
Ending equity ratio (fraction) ...... 0.76 0.95 0.95 0.95 0.95 0.95 0.95 0.95 0.95 0.95
Annual net farm income ($1,000)... NA 586.0 411.0 585.0 504.0 463.0 582.0 749.0 782.0 1,286.0
The Scenarios are:
Base-Continuation of present policy.
I-A 20 percent acreage reduction in 1986-1992-9 percent higher feed costs.
II-No crop program.
Ill-Fifty cent per cwt lower milk price.
IV-No dairy price support program.
V-Reduce income tax benefit program.
VI-Milk supply control program
VII-Computer feeding technology
VIII-Bovine growth hormone technology






86 A Special Report for the 1985 Farm Bill



Table B.4.-Comparison of Selected Policy Scenarios on Representative Minnesota Dairy Farms That Have
High Debt or Are New Entrants With High Debt

Financial Stress Scenarios* New Entrant Scenariosb
Initial Initial
Criteria situation IX X XI situation XII XIII XIV
52 cow Minnesota dairy:
Probability of survival ..................... NA 0.0 0.0 0.0 NA 0.0 0.0 0.0
Present value of ending net worth ($1,000)... 246.0 97.0 93.0 101.0 264.0 138.0 122.0 138.0
Ending equity ratio (fraction)............... 0.42 0.19 0.19 0.20 0.36 0.21 0.19 0.22
Annual net farm income ($1,000) ........... NA -57.0 -46 -57.0 NA -98.0 -105.0 -98.0
125 cow Minnesota dairy:
Probability of survival ..................... NA 0.0 0.0 0.0 NA 0.0 0.0 0.0
Present value of ending net worth ($1,000)... 554.0 238.0 235.0 235.0 575.0 304.0 298.0 303.0
Ending equity ratio (fraction)............... 0.44 0.23 0.22 0.22 0.37 0.23 0.22 0.23
Annual net farm income ($1,000)............ NA -92.0 -73.0 -94.0 NA -147.0 -163.0 -147.0



Table B.5.-Comparison of Selected Policy Scenarios on Representative Florida and Arizona Dairy Farms
That Have High Debt or Are New Entrants With High Debt

Financial Stress Scenarios" New Entrant Scenariosb
Initial Initial
Criteria situation IX X XI situation XII XIII XIV
350 cow Florida dairy:
Probability of survival ..................... NA 26.0 42.0 26.0 NA 22.0 12.0 2.0
Present value of ending net worth ($1,000)... 466.0 334.0 391.0 337.0 527.0 345.0 165.0 180.0
Ending equity ratio (fraction) ............... 0.44 0.35 0.40 0.35 0.41 0.32 0.15 0.17
Annual net farm income ($1,000) ............ NA -101.0 -78.00 -101.0 NA -174.0 -245.0 -230.0
359 cow Arizona dairy:
Probability of survivalS NA 66.0 70.0 66.0 NA 60.0 38.0 24.0
Present value of ending net worth ($1,000)... 471.0 760.0 840.0 763.0 528.0 717.0 372.0 262.0
Ending equity ratio (fraction) ............... 0.45 0.64 0.68 0.63 0.42 0.58 0.33 0.27
Annual net farm income ($1,000)............ NA -59.0 -35.0 -60.0 NA -102.0 -182.0 -194.0
aThe financial scenarios are:
IX-Continuation of present dairy policy and assuming high debt.
X-Subsidize interest rate so effective rate on all loans is 8 percent.
XI-Restructure debt.
bThe new entrant scenarios are:
XII-Base Policy and new entrant.
XIII-New entrant and no price support for dairy products.
XIV-New entrant and a 9-percent increase in feed costs.




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Office of Technology Assessment


The Office of Technology Assessment (OTA) was created in 1972 as
an analytical arm of Congress. OTA's basic function is to help legisla-
tive policymakers anticipate and plan for the consequences of techno-
logical changes and to examine the many ways, expected and
unexpected, in which technology affects people's lives. The assessment
of technology calls for exploration of the physical, biological, economic.
social, and political impacts that can result from applications of scien-
tific knowledge. OTA provides Congress with independent and timely
information about the potential effects-both beneficial and harmful-of
technological applications.
Requests for studies are made by chairmen of standing committees
of the House of Representatives or Senate; by the Technology Assess-
ment Board, the governing body of OTA; or by the Director of OTA
in consultation with the Board.
The Technology Assessment Board is composed of six members of
the House, six members of the Senate, and the OTA Director, who is
a nonvoting member.
OTA has studies under way in nine program areas: energy and ma-
terials; industry, technology, and employment; international security
and commerce; biological applications; food and renewable resources:
health; communication and information technologies; oceans and
environment; and science, transportation, and innovation.
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