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This is to certify that the

thesis entitled

The Effects of Selected Water Pollution
Control Rules on the Simulated Behavior
of Beef Feedlots, 1974—85

presented by

David Lynn Forster

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ABSTRACT
THE EFFECTS OF SELECTED WATER POLLUTION CONTROL

RULES OF THE SIMULATED BEHAVIOR OF
BEEF FEEDLOTS, 1974-85

By

David Lynn Forster

The failure of a free market to maximize the welfare of society
occurs when technical externalities, indivisibilities, or collective
consumption is present. Most instances of market failure in the agri-
cultural sector are due to technical externalities. During the past
two decades, citizens, regulatory agencies and legislative bodies have
recognized the need for nonmarket force intervention into several areas
of agriculture. The externalities associated with pesticides, insecti—
cides, fertilizers, soil erosions, feed additives, and feedlot pollutants
have been addressed often during the past two decades.

The focus of this study concerned beef feedlot pollutants which
have been deemed one of the more important contributors of agricultural
pollution. The analysis was an economic evaluation of selected water
pollution control rules and suggested methods and practices for lessen-
ing water pollution directed at beef feedlots. These rules and methods
and practices have been suggested in order to achieve the environmental

policy of no discharge of pollutants into navigable waters.

&)1V' David Lynn Forster
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46g)
(f The purpose of this study was to investigate some of the costs
involved in applying a selected set of rules and/or suggested methods
and practices. Costs investigated included the costs of the rules in
terms of reducing feedlot production and costs incurred by feedlot
owners in complying with the rules.

A simulation model was developed to allow the observation of the
behavior of feedlots until l985 under a selected set of rules and/or
methods and practices. The feedlots represented by the simulation model
were intended to be those in Michigan and surrounding states.

The simulation model attempted to investigate the paths of
adjustment of feedlots before and after being subjected to selected
rules and/or acceptable methods and practices for water pollution con-
trol. The model simulated the production of several individual farm-
feedlots through the 1960-85 period. Each simulated firm was given
certain initial financial and production characteristics. It was then
allowed to develop expectations concerning exogenous prices and expecta-
tions concerning its production function. A linear programming solution
allowed the firm to produce with the types and amounts of inputs which
it expected to be the most profitable. The model simulated the firm's
annual operation with actual prices received (gx_pQ§t_prices) being
different than the expected prices (gx_antg_prices). Similarly, the
firm's gx_p9§t_production function was different than the gx_afltg_pro-
duction function used in arriving at the input level the firm employed.

Decisions were based on gx_ante functions while success was determined

by ex.post functions.

 

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Upon the imposition of a rule and/or method and practice to
control water pollution, the cost structure of the firm changed. The
firm made a decision concerning resources to employ based on the expec-
tations of how the pollution abatement control would affect the profit-
ability of the feedlot. This decision determined the inputs to be used,
and pollution abatement resources could have changed the firm's output
as well as the resources employed relative to those produced and
employed if no controls had been established.

The selected rules investigated included requirements that all
firms: (1) have the capacity to control runoff from a 10-year, 24-hour
storm by l977 and from a 25-year, 24-hour storm by 1983; (2) have the
capacity to control runoff from a 25-year, 24-hour storm by l977; (3)
have the capacity to control runoff from a 6-month rainfall by l977;
(4) adopt the method and practice of storing animal wastes during the
winter months plus the capacity to control the runoff from a 6-month
rainfall, and (5) a do nothing rule.

The four action rules each reduced production and imposed costs
on producers over the l974-85 period compared to the do nothing rule.
The rule that firms have the capacity to control runoff from a 10-year,
24-hour storm by 1977 and a 25-year, 24-hour storm by l983 resulted in
a mean of 7.0 head production decline per firm over the entire l974-85
period relative to the do nothing rule. This relative decline was
0.167 percent of the total. The mean present value of equity losses
over 1974-85 as a result of this rule was $3,724 per firm. The second

rule, firms have the capacity to control a 25-year, 24-hour storm by

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David Lynn Forster

1977 caused a relative decline in production over the 1974-85 period by
7.2 head per firm (0.17 percent of production) and cost each feedlot
owner a mean present value of $3,911. The third rule, a requirement
that feedlots have the capacity to control a 6-month rainfall, resulted
in a mean present value loss of $4,800 per firm and a relative decline in
production of 37.7 head per firm (0.90 percent of production) over the
period. The last rule, controlling runoff from a 6-month rainfall and
adopting the practice of no winter spreading, resulted in a mean present
value equity loss of $5,990 per firm with a relative decline in produc-
tion of 38.3 head per firm (0.91 percent of production) over the entire
period.

Other findings include:

1. Economies of size exist with any of the four rules analyzed in
this study.

2. Any of the selected rules were regressive in nature. Reducing
the mean net worth of the simulated firms in 1973 by one-half,
resulted in the cost per dollar of 1973 equity nearly doubling
under all four rules.

3. The simulation model was sensitive to several critical param-
eters. Those parameters strongly affecting model results
included the mean net worth of the firm, the determinant of the
amount of debt employed by the feedlot, the determinant of the
user cost of durable assets, and the initial age of the feedlots.

4. The effects of the four selected rules were nearly the same

regardless of feedlot age. The capital outlay required by any

David Lynn Forster

of the four rules had a minor impact on the profitability of the
feedlot enterprise for all ages of feedlots.

The rules had little effect on the asset structure of the firms.
While increased asset fixity resulted from the rules, the

increase was slight.

THE EFFECTS OF SELECTED WATER POLLUTION CONTROL
RULES ON THE SIMULATED BEHAVIOR OF
BEEF FEEDLOTS, 1974-85

By

David Lynn Forster

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Agricultural Economics

1974

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ACKNOWLEDGMENTS

I would first like to thank my major professor, Dr. Larry J.
Connor, for his personal interest and guidance throughout my graduate
program. Also, I want to thank Dr. James B. Johnson who gave valuable
assistance and direction throughout the study. Thanks to Drs. John
Brake, Bill Haley, and Roy Black for serving as members of my thesis
committee.

A special thanks goes to my parents, Mr. and Mrs. Frank Forster,
who have given unwavering support and assistance throughout my education
and my life.

Finally, I am sincerely grateful to my wife Pat and my son Chad
for their sacrifices and understanding throughout the years of graduate

training.

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ii

TABLE OF CONTENTS

Page
LIST OF TABLES .......................... vii
LIST OF FIGURES ......................... ix
CHAPTER
I. INTRODUCTION ....................... 1
Introduction ...................... 1
Categories of Market Failures ........... 2
Market Failure in the Agricultural Sector ..... 4
Methods of Correcting Technical Externalities . . . 5
Feedlot Wastes ................... 8
Determination of "Right" Level of Animal Waste
Pollution .................... 10
Purpose of Study .................... ll
Objectives ....................... 13
Summary ........................ 14
Organization of Thesis ................. 14
II. LITERATURE REVIEW .................... 16
Federal Water Quality Act Amendments of 1972 ...... 16
Environmental Protection Agency Guidelines
for Point Sources .................. 18
Role of States in NPDES ................ 20
Review of EPA Point Source Guideline Development . . . . 22
Review of Methods and Practices for Controlling
Water Pollution from Nonpoint Sources ........ 24
Investigations of Economic Impacts of EPA Point
Source Guidelines .................. 25
III. THEORY OF THE FIRM EMPLOYED IN SIMULATION MODEL ..... 36
General Description of Theory Employed ......... 36
Price Expectations ................... 37
Expected Input-Output Relationship ........... 41
Actual Prices and Input and Output Relationships . . . . 44
Decision Making .................... 44

iii

CHAPTER Page

Behavior of Michigan Feedlots ............. 48
Measurement of the Effect of Water Pollution
Control Rules .................... 50
Realism in Theory ................... 52
IV. SIMULATION MODEL ..................... 53
General Description .................. 53
Farm Feedlot Production Component ........... 61
Modifications in Faun-Feedlot Component ........ 65
Ex Ante Price Expectation and §x_Post Price
Realization Equations ................ 69
§x_Post Price Equations ................ 73
Decision Making Progress ................ 76
Accounting Process ................... 85
Optimization Procedure ................. 86
Distribution of Feedlot Owners' Net Worth ....... 92
The Simulation Approach ................ 94
V. RESULTS ......................... 97
Static Cost Analysis .................. 98
Multiperiod Analysis .................. 110
Results of Optimization .............. 110
Measures of Performance Over a Multi-Period
Horizon ..................... 114
Rule Alternatives ................. 116
Results Under Assumption Set 1 ........... 119
Performance of Feedlots Prior to Policy
Implementation, Assumption Set 1 ......... 120
Performance of Feedlots, 1974-85, Assumption
Set 1 ...................... 122
Results Under Assumption Set 2 ........... 134
Performance of Feedlots Prior to Policy
Implementation, Assumption Set 2 ......... 134
Performance of Feedlots 1974-85, Assumption Set 2 . 136
Sensitivity Analysis .................. 141
Summary of Major Findings ............... 152
VI. SUMMARY AND IMPLICATIONS ................. 156
Summary ........................ 156
Implications ...................... 169
Suggestions for Future Research ............ 174

iv

APPENDIX Page

A-1. §§_Ante Price Indices Produced by Price Equations
and Used in Simulation Model .............. 176

A-2. Ex_Post Price Indices Produced by Price Equations
and Used in Simulation Model .............. 177

A-3. Feeder and Slaughter Cattle Price Per Pound Produced
by Price Equations and Used in Simulation Model . . . . 178

B-l. Performance Variables of Simulated Feedlots, 1974-85,
Assumption Set 3 .................... 179

B-2. Performance Variables of Simulated Feedlots, 1974-85
Assumption Set 4 .................... 180

8-3. Performance Variables of Simulated Feedlots, l974-85,
Assumption Set 5 .................... 181

B-4. Performance Variables of Simulated Feedlots, 1974-85
Assumption Set 6 .................... 182

B-5. Performance Variables of Simulated Feedlots, 1974-85,
Assumption Set 7 .................... 183

B-6. Performance Variables of Simulated Feedlots, 1974-85,
Assumption Set 8 .................... 184

B-7. Performance Variables of Simulated Feedlots, 1974-85,
Assumption Set 9 .................... 185

B-8. Performance Variables of Simulated Feedlots, 1974-85,
Assumption Set 10 ................... 186

B-9. Performance Variables of Simulated Feedlots, 1974-85,
Assumption Set 11 ................... 187

B-10. Performance Variables of Simulated Feedlots, 1974-85,
Assumption Set 12 ................... 188

C-1. Output From the Hughes Simulation Component Under
Specified Conditions .................. 189

C-2. Examples of Initial Investment Costs for Two Housing
Systems Using the Runoff Retention System Used in
Simulation Model with the Capacity to Retain a 6-Month
Rainfall ........................ 192

APPENDIX Page

0-1. Formulas Used in Computing Results ........... 193
0-2. Glossary of Terms ................... 196
BIBLIOGRAPHY ........................... 198

vi

TABLE

10.
11.
12.

13.

14.

LIST OF TABLES

Manure Obtained from Cattle Fed on Paved Floor and

Paved Lot ........................

Per Head Capital Outlays and Production Cost Increases
to Control Runoff from Fed-Beef Operations by Size,

Class and Area
Coordinates for the Initial "Simplex" Vertices

Annual Costs and Cost Per Pound of Beef Sold for Three

Feedlot Technologies, 100 Head Capacity .........

Annual Costs and Cost Per Pound of Beef Sold for Three

Feedlot Technologies, 300 Head Capacity .........

Annual Costs and Cost Per Pound of Beef Sold for Three

Feedlot Technologies, 500 Head Capacity .........

Annual Costs and Cost Per Pound of Beef Sold for Three

Feedlot Technologies, 700 Head Capacity .........

Annual Costs and Cost Per Pound of Beef Sold for Three

Feedlot Technologies, 900 Head Capacity .........

Results of Test of Concavity Assumption: Six Random
Combinations of Unknown Variables and Resulting r2

Water Pollution Control Rules Included in Analysis

Parameter Values Used in Assumption Set 1 ........

Measures of Performance for the 20 Simulated Feedlots,
1960-76 (Assumption Set 1)

Simulated Feedlot Performance l974-85 Under a "Do
Nothing" Policy (Assumption Set 1)

Simulated Feedlot Performance, 1974-85, Under the Rule
of Expanding Current EPA Guidelines to Firms of Less

than 1,000 Head Capacity (Assumption Set 1) .......

vii

Page

29
89

102

103

104

105

106

112
117
120

124

TABLE Page

15. Simulated Feedlot Performance, l974-85, Under the
Policy of Retaining Runoff from a 25-Year, 24-Hour
Storm by 1977 (Assumption Set 1) ............. 125

16. Change in Performance of Simulated Feedlots Under
Rules A and B (Assumption Set 1) ............. 127

17. Performance of 20 Simulated Firms Under Rule C,
1974-85 (Assumption Set 1) ................ 130

18. Performance of Simulated Feedlots Under Rule D,
1974-85 (Assumption Set 1) ................ 131

19. Change in Performance of Simulated Feedlots Under
Rules C and D (Assumption Set 1) ............. 133

20. Measures of Performance for the 20 Simulated Feedlots,
1960-76 (Assumption Set 2) ................ 135

21. Mean Change in Performance of Simulated Feedlots Under
Rules A, B, C, and D Vis a Vis a I'Do Nothing" Policy
(Assumption Set 2) .................... 140

22. Simulated Firms' Mean Change in Output and Equity,
1974-85, as a Result of Four Environmental Policies
and Two Initial Equity Levels ............... 141

23. Assumption Sets Used in Determining the Effects of

Selected Water Pollution Control Rules and in the
Sensitivity Analysis ................... 143

viii

FIGURE

10.
11.

12.

13.

14.

LIST OF FIGURES

System to Investigate Beef Feedlot Performance .....

Index of Annual Salvage Values of Buildings and
Machinery Over a 10 Year Period with U==0.8 and

a=1.06 .........................

Production Function for Newly Acquired Alternatives

as Viewed by the Firm ..................

Production Function for Currently Employed Investment

Alternative as Viewed by the Firm ............
Model of Feedlot Behavior in a Single Year .......

Model of Feedlot Over Multiple Year Horizon .......

Optimization Procedure to Find Values for Unknown

Parameters .......................
Farm-Feedlot Production Component ............
Illustration of "Simplex" Procedure ...........

The Erlang Family of Density Functions .........

Cost Per Pound of Beef Sold, Three Housing Types of

Selected Capacities, 1974 Prices ............

Capacity of Simulated Lots and Cattle and Calves on
Feed, 1960-70, with Blim=1.25, K=2, R=0.06 and

U =0.9 (r2 = 0.935) ...................

Annual Change in Net Worth Per Simulated Firms Under

Assumption Sets 5 and 6, 1971-85 ............

Annual Indices of Capacity of Simulated Firms Under

Assumption Sets 7 and 8, 1960-85 (1960==1.0) ......

ix

Page

39

42

43
57
59

62
68
93
95

FIGURE Page

15. Annual Indices of Capacity of Simulated Firms Under
Assumption Sets 9 and 10, 1960-85 (l960==1.0) ....... 149

16. Annual Indices of Capacity of Simulated Firms Under
Assumption Sets 11 and 12, 1960-85 (1960 =1.0) ...... 151

CHAPTER I

INTRODUCTION

Introduction

 

Society is increasingly demanding the improvement and/or
maintenance of the physical environment. Through federal, state and
local legislation, action in the courts in all parts of the nation, and
appeals in the communications media, the individual citizen witnesses
daily the attempts to improve the environment. The "pollution problem"
seems to be recognized by a segment of society as the most important
parameter in determining the future welfare of our nation. In addition,
the vast majority of society now recognizes environmental quality as at
least one of a host of goals that the nation must direct itself toward.

The ever present problem that arises with deteriorating environ-
mental quality is the inadequacy of the free market solution to correct
the deterioration. Societal costs are often inadequately imputed to the
sources of pollution resulting in more pollution than is desirable from
society's point of view. Society then gains by 1e5Sening the level of
the pollutant. The question involved is to what extent should the
externality be abated, by what method should it be abated, how much does

society gain from the effort and how much does the effort cost society.

Categories of Market Failures

 

The deterioration of the environment is an example of market
failure. Bonnen has categorized market failures into three major
e1ements--technica1 externalities, indivisibilities and collective
consumption. Technical externalities include interdependence of pro-
duction functions, interdependence of consumption functions and inter-
dependence of production and consumption.1

Interdependence of production functions is defined as one firm's
costs being determined in part by another firm's output. The firms are
not independent of each other and the private cost of a firm is not the
same as the costs which society sacrifices in producing the output.

Interdependence of production functions is exemplified by the
well known story of "The Tragedy of the Commons."2 The feudal farmers
grazed their flocks of sheep in a large field that was available for all
to use. It took only a short time for the more entrepreneuring farmers
to realize that it was to their advantage to graze more animals than
their neighbors, producing deteriorating pastures. The result was a
pasture that was soon overstocked and eventually destroyed. Ocean
fishery resources provide a modern day analogy to "The Tragedy of the
Commons" if stocks of fish in the ocean are viewed as a common resource.

No economic incentives are provided to force the individual fisherman

 

1James T. Bonnen, Lectures in Agricultural Economics Department,
Michigan State University, 1974.

2Garret Hardin, "The Tragedy of the Commons," Science, 13
December 1968, p. 1234.

to concern himself with the perpetuation of the stock of ocean fish.
To the contrary, incentives are present which encourage him to catch
as many fish as possible regardless of the effect on stocks. Since
there are no personal property rights associated with the resource, it
is advantageous for the producer to fish intensely before others
recover the limited resource.

Interdependence of consumption functions is defined as one
individual's utility being determined in part by the actions of another
person. Thus, the consumption level of a person may affect the satis-
faction of another individual.

Interdependence of consumption functions is exemplified by the
noise and disturbance created by snowmobiles. While the thrill of the
snowmobile may be gratifying to their owners, most nonparticipants con-
sider them a nuisance in terms of noise level and destructiveness.

Interdependence of production and consumption is defined as the
failure of the individual's satisfaction to be included in the produc-
tion decision of the firm. Price commonly reflects consumer desires,
but some of the firm's products may be forced on the consumer without
any market exchange. As a result all societal costs are not included
in the firm's cost structure.

Interdependency of the consumption function and a production
function is exemplified by noise pollution. Suits filed by individuals
living near airports to force remunerations for personal and/or property
damages incurred through "excessive" noise levels attest to the possible

interdependency of the consumption and production function.

Indivisibilities occur when the lumpiness of assets or economies
of size force one or a few firms to furnish all of the market's supply.
The firms act in an imperfectly competitive environment in which maxi-
mization of individual gains does not maximize society's well being.

An example would be the monopoly position of public utilities and the
public regulation of these firms.

Collective consumption occurs when each member of society gains
satisfaction from the amount of the total output. No individual's sat-
isfaction is diminished as a result of another's consumption. National

defense provides an example of this concept.

Market Failure in the Agricultural Sector

The vast majority of incidents of market failure in the agricul-
tural sector occur in the previously described areas of technical exter-
nalities. During the past two decades, citizens, regulatory agencies
and legislative bodies have voiced concern over the externalities asso-
ciated with pesticides, insecticides, fertilizers, soil erosion and
sedimentation, feedlot pollutants and feed additives. The incidents
of market failure due to indivisibilities and collective consumption
are rare in agriculture.

The concern of this thesis is with pollutants which are a sub-
category of technical externalities. Six types of agricultural wastes
are commonly identified as pollutants. Human wastes from the farm
population, crop residues, food processing wastes, dead animals,

agricultural chemical residues and animal wastes.3 The current focus

 

3J. B. Johnson, "Biological, Chemical and Engineering Factors
Related to Economic Analyses of Dairy and Fed Beef Waste Management
and Pollution Abatement," unpublished paper, 1972.

of local, state and federal legislation and regulation has been directed
at food processing wastes, agricultural chemical residues and animal
wastes.

Methods of Correcting Technical
Externalities

 

 

The primary instrument used to correct the level of pollutants
has been sets of rules governing the use of inputs or the level of
pollutant output. Permit allocation is usually employed with little
reliance on adjustments in resource costs to reflect external costs.
As a result, users are often faced with incentives which encourage
practices which misallocate resources.“

The use of rules governing inputs or outputs is not the only
method of abating pollution. There are three broad classes of methods
of solution to environmental quality problems. The first is the market
solution following the establishment of a liability rule to serve as a
starting point in the negotiation. One liability rule might be that
the affected party offers a bribe to induce the acting party to reduce
output. Or the liability rule might be that the acting party offers
compensation to the affected party to continue to pollute.5 Assuming
that the first liability rule, bribing by the affected party, is

established, transaction costs are often substantial due to the large

 

I'Robert H. Haveman, "Efficiency and Equity in Natural Resource
and Environmental Policy," American Journal of Agricultural Economics,
December 1973.

 

5Alan Randall, "Market Solution to Externality Problems: Theory
and Practice," American Journal of Agricultural Economics, May 1972.

 

numbers of sufferers. A large number of both perpetrators and sufferers
result in high costs of grouping the parties to establish the relevant
bribe. Also, incentives must be present to encourage each of the
sufferers to bribe the perpetrator. If these incentives are not
present, each sufferer tends to rely on others and hopes for a free
ride. Similarly, the second liability rule, compensation by the per-
petrator, may produce high transaction costs in organizing the sufferers
and the "free rider problem" among the perpetrators.

The second class of methods of solutions to environmental
quality problems is a system of per unit taxes, charges, or subsidies.
Generally, this system involves encouraging the production unit to
lessen the pollution by forcing it to internalize the cost of abating
pollutants. A requirement is that the unit to which the tax, charge
or subsidy is levied is easily defined and measurable. For example,

a tax on odoriferous pollutants would be difficult unless some cardinal
measurement of identifying the odor level could be employed.

The last broad classification of methods is a system of rules
enforced by the threat of fines or jail sentences. This system is the
one that has been used primarily for pollution abatement in the United
States. Rather than taking an economic approach to internalization of
costs and attempting to devote the proper amount and combination of
resources to pollution abatement, a system of rules is a legalistic
view of establishing the level of output or inputs.

Having opted for the establishment of rules to abate pollution,

increasing importance is placed on analyzing the economic impacts of

such rules. It is important that the decision makers in the
environmental policy process recognize the effects of the newly created
rules. Damage costs associated with various levels of pollution should
be weighed against abatement costs in arriving at directives or regula-
tions to be used in pollution abatement policy.6 While it may be
politically useful to demand zero effluent discharge, its long run
implications are often contrary to the well-being of society.

The trade off between benefits of an improved environment and
abatement costs are difficult to quantify. Nevertheless, some "feel"
for these benefits and costs must be used in the process of rule estab-
lishment. Unfortunately, the measurement of benefits from lessening
environmental damage is highly imprecise due to imperfect knowledge of
the effects of wastes. The simple fact is that the extent to which
agricultural wastes affect the production and consumption function of
others is unknown. Certainly, there is a growing body of evidence that
agricultural wastes impose costs on others. On an aggregate basis, the
Environmental Protection Agency's Water Quality Office made a study in
1971 of the prevalence and major causes of stream pollution throughout
the country. The results emphasize the need to consider the damage
costs of agricultural pollution. Forty-eight percent of the watersheds

surveyed in the United States were found to be "extensively polluted."

 

6Allen V. Kneese, The Economics of Regional Water Quality
Mana ement,)Resources for the FUture, Inc. (Baltimore: John Hopkins
Press, 1971 .

Agricultural wastes were cited as one of the major contributors to

this pollution.7

Feedlot Wastes

 

Feedlot wastes have been deemed one of the more important con-
tributors of agricultural pollution. With the increasing importance of
confined feeding facilities, the mere volume of animal wastes created
by the facility is staggering. Table 1 illustrates the quantities in-
volved; however, the large volume involved may exaggerate the potential
for polluting ground and surface water. Only a small portion of the
waste, perhaps 5-10 percent, actually enters surface and ground water.6

The degrees of potential damage that manure possesses is often
described in terms of the amounts of biological material, nitrogen,
phosphorus, and dissolved solids. Biological material determines the
degree of oxygen usage due to bacterial digestion of wastes, and a
measurement of this process is biochemical oxygen demand (BOD). Another
indication of the biological material is the amount of oxidizable carbon
in the waste, and the chemical oxygen demand (C00) is used as a measure.
Both COD and 800 are in high concentration in feedlot waste flows.

The most common forms of nitrogen in feedlot wastes are organic,

ammonia, and nitrate. Organic nitrogen breaks down into ammonia nitrogen,

 

7J. L. Buckley, "Agriculture and the Environment," Waste
Management Research--Proceedings of the 1972 Cornell Agricultural Waste
Management Conference, Cornell University, 1972.

°A. H. Schulz, "Basic Requirements for Beef Cattle Housing,
Feeding and Handling," #gricultural Engineering, No. 41, 1960.

 

 

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Table l. Manure Obtained from Cattle Fed on Paved Floor and Paved Lota

 

 

500 Head Lot

 

Lbs./Day/Head Tons/Day
Calves:
Full fed with silage 15.33 3.83
Full fed with ear corn silage 18.67 4.67
Yearling:
Fed over 140 days 30.0 7.50

 

aA. F. Butchbaker gt_al,, Evaluation of Beef Cattle Feedlot
Waste Mana ement Alternatives, U.S. Environmental Protection Agency,
November 1 .

 

 

and ammonia nitrogen has toxic properties and converts into nitrates.
Nitrates which reach streams and/or water bodies promote the growth of
algae and aquatic plants. 'This growth increases the oxygen demand on
streams and water bodies.

Phosphorus has been directly linked to the eutrophication
process of streams and water bodies. Small amounts of phosphorus in-
crease the oxygen demands. While phosphorus readily becomes fixed in
the soil, phosphorus from feedlots may find its way into water bodies
through soil erosion.

Dissolved solids include potassium, calcium, sodium and other
inorganic salts. High levels are found often in animal waste and can

increase the salinity in streams and water bodies.9

 

9Environmental Protection Agency, Development Document for
Effluent Limitations Guidelines and New Source Performance Standards--
Feedlot Point Source Category, August 1973.

 

10

While the potential damage of feedlot wastes is high in terms
of the above four technical components, the actual pollution damage done
is determined by the environment in which the feedlot operates. The
amount of precipitation, intensity of precipitation, degree of soil
compaction, distance from a water body, density of cattle, condition of
lot surface, type of ration fed to the cattle, and size of cattle may
affect the quality and quantity of runoff from the feedlot. The han-
dling of wastes is also an important factor including frequency of
spreading, area to which the manure is applied, and weather conditions
during spreading. Furthermore, the size and assimilative capacity of
the receiving stream or water body affects the damage caused by the
runoff. The damages to society caused by a particular size feedlot may
vary from a negative cost (no pollution damage and positive net value
in the manure as a fertilizer) to a large positive cost similar to the
damages caused by a city pouring untreated effluent into a stream.

Determination of “Right" Level of
Afiimal waste Pollution

 

 

The determination of the "right“ level of pollution from each
of the nation's feedlots is impossible. The output from the feedlot is
multidimensional with some level of each dimension being acceptable from
society's viewpoint. The nation's feedlots number in excess of 150,000
and each feedlot has a near infinite number of input combinations that
affect the quantity and quality of runoff.

Since society has opted for a legalistic approach to environ-

mental improvement through rules and regulations, the decision maker

11

must realize that any established rule is going to be suboptimal. It

is impossible to decree the combination of inputs and the level of each
input to be employed to produce each feedlot's "right" amount of pollu-
tion.10 However, the decision maker should be concerned with obtaininga
"feel" for the trade offs between aggregate benefits in the form of
abatement in levels of pollution and the costs of the rules that are

established.

Purpose of Study

 

The purpose of this study is to provide a mechanism to investi-
gate some of the costs involved in a set of alternative rules to control
beef feedlot pollution. Specifically, the focus of the study is on the
construction of an analytical system that permits one to observe the
behavior of beef feedlots under a variety of alternative rules (Figure l).
The feedlots to which the model is directed are those found in Michigan
and surrounding states.

The analytical system developed can be employed to represent
either specific types of feedlots or the entire distribution of Michigan
feedlots. For example, one might be interested in examining the behavior
of "small" feedlots relative to the behavior of larger lots. Thus, the
feedlot system should be capable of representing lots with specific
financial characteristics and lot structure (feeder capacity, housing

type, etc.).

 

l°"Right" would be that level of pollution where societal welfare
is maximized.

Controllable Inputs
(water pollution
control rules)‘

. rules governing
abatement of
runoff

 

 

 

- rules governing
waste disposal

12

Exogenous Variables

 

- input prices

0 output prices

- enterprise alternatives
0 weather conditions

11, Feedl ot Performance

 

 

- o earnings
Beef .
:::§:, Feedlot ;::é:> ° feedlot capac1ty
System . capital intensity

 

o equity changes

Figure 1. System to Investigate Beef Feedlot Performance.

13

It is also desirable that the feedlot system be able to
represent aggregate performance of Michigan feedlots in terms of feedlot
capacity, rate of return on investment, and degree of capital intensity.
This representation would be accomplished by selecting several lots from
the distribution of Michigan feedlots and observing their performance.
Building the feedlot system to be capable of examining aggregate per-
formance increases the potential usefulness of the model since it
enables one to investigate the effects of alternative rules on the

entire distribution of Michigan feedlots.

Objectives

 

The objectives of the study include:

1. Construct a systems model which will predict Michigan feedlot
performance over time under a variety of alternative environ-
mental rules.

2. Analyze the predicted future performance of Michigan feedlots
under a set of pollution abatement rules and "acceptable
methods and practices" currently being formulated by the
Environmental Protection Agency.

3. Investigate the sensitivity of feedlot performance criteria
to small changes in the values of critical parameters employed

in the systems model.

14

Summary

In summary, market failures due to technical externalities,
indivisibilities, and collective consumption may lead to the failure
of the market to maximize societal welfare. In the agricultural sector,
technical externalities are commonly the cause of market failure. Rules
for environmental maintenance and/or improvement have been directed at
several types of technical externalities in the agricultural sector
including beef feedlot pollution. The purpose of the study is to pro-
vide a mechanism to enable one to observe the effects of a selected set
of rules for water pollution control on the performance of Michigan beef
feedlots. While the focus of the study is on Michigan beef feedlots,
the results of the study also have implications for feedlots operating

in environments similar to those found in Michigan.

Organization of Thesis

 

The remainder of the thesis is organized into four major areas.
First, a review of the literature (Chapter II) briefly summarizes studies
throughout the United States that have investigated the economic impacts
of selected pollution control rules on beef feedlots. Also included in
the literature review is a summary of the recent federal legislation and
Environmental Protection Agency guidelines which are concerned with feed-
lot runoff. The second area of organization is a description of the
model developed to analyze the effects of environmental policies. Two

chapters are devoted to the model's description: Chapter III addresses

15

the economic theory of the firm that is employed in the simulation model
to represent the behavior of feedlot firms, and Chapter IV describes the
simulation model in detail. The economic effects of a selected set of
water pollution control rules on the behavior of Michigan feedlots com-
prise the third topic and are described in Chapter V. Finally, a
summary of the study and some implications from the results are

discussed in Chapter VI.

CHAPTER II

LITERATURE REVIEW

This study concerns a specific problem--the effects of selected
pollution control rules on the performance of beef feedlots. The rele-
vant literature to be reviewed is past studies of beef feedlot perfor-
mance under a variety of pollution abatement rules. First, recent
history of the rules is briefly reviewed. Second, the studies of the
economic effects of these rules are examined. While the background of
the method of investigation--a computerized simulation mode1--may be of
interest to many, the applications of this methodology to agricultural
problems is well documented and will not be reviewed.

Federal Water Quality Act
Amendments of 1972

 

 

On October 18, 1972, the Congress of the United States passed
the Federal Water Pollution Control Act Amendments which became Public
Law 92-500. The primary aim of the act is to "restore and maintain the
chemical, physical, and biological integrity of the Natjon's waters."1
The Act requires that the Environmental Protection Agency (EPA) estab-

lish effluent limitations guidelines to be achieved by "point" sources

 

1Public Law 92-500, 92nd Congress, October 18, 1972. Defini-
tions of several terms used in the act are provided in Appendix D-2.

16

m:

17

of waste discharge into navigable waters and tributaries. In addition,
the Act directs the EPA to issue information identifying and evaluating
the nature and extent of nonpoint source pollution and processes, pro-
cedures and methods to control pollution from these nonpoint sources.
Feedlots are explicitly included in the point source category making
them subject to the National Pollution Discharge Elimination System
(NPDES).

The NPDES is the mechanism used to achieve control of discharges
from all point sources. All point sources subject to the NPDES must
obtain a permit by the EPA or a Federally approved state program. The
permit recipient is issued a compliance schedule which requires a step-
by-step reduction in pollutants over a specific time interval.

The measurement of the maximum allowable rate of discharge from
a point source is referred to as an effluent limitation. Under terms of
the 1972 Water Pollution Control Act Amendments, the chemical, physical,
and biological characteristics of the rate of discharge determines the
level of this effluent limitation. The concept is that industries (in-
cluding feedlots) currently possess the technology necessary to reduce
this effluent limitation to some manageable quantities. Thus, the
emphasis is on identifying specific technologies to be employed by
industries; moreover, various types of industries are able to discharge
various types and amounts of effluents based on ability of current
technology to abate the effluent discharge.

The legislation adopts a two-level program of effluent limita-

tion for existing point sources. The first level is identified as a

18

technology referred to as the "best practicable technology currently
available." This level is to be achieved by not later than July 1, 1977.
The second level is some technology identified as the "best available
technology economically achievable." By not later than July 1, 1983,
this technology must be utilized by point source categories of indus-
tries. Needless to say, the identification of these two levels is
extremely difficult and is subject to wide debate; however, the EPA

was given the task by the 1972 Act of establishing these technologies
within one year of the Act's enactment.

The EPA was also given the task of providing information
concerning nonpoint sources of pollution. This information was to
include (1) guidelines for identifying the nature and extent of nonpoint
sources of pollutants and (2) processes, procedures and methods to
control nonpoint source pollution.

Environmental Protection Agency Guidelines
for Point Sources

 

 

On September 7, 1973 notice was published in the Federal Register
that the EPA was proposing effluent limitation guidelines for existing
feedlot point sources. On February 14, 1974 the EPA published in the

Federal Register final effluent limitation guidelines for existing point

 

sources in the feedlot category and standards of performance for new
point sources in the feedlot category. The final regulation was set
forth in this document to take effect April 15, 1974.

The beef feedlots subject to the provisions of the regulations

include those with one time capacity in excess of 1,000 head. With

19

respect to Operations smaller than these, the Agency is in the process
of studying the economic impacts on smaller sized lots with the possi-
bility of issuing further regulations for beef feedlots of less than
1,000 head.

The regulation specifies that "there shall be no discharge of
process waste water pollutants to navigable waters."2 The technology
level employed in terms of the "best practicable technology currently
available" is the control of all process generated waste waters plus
the runoff from a lO-year, 24-hour storm. In short, the EPA recognizes
that overflow of a particular retention facility may occur. This over-
flow is legitimate from July l, 1977 to July l, 1983 if the retention
facility is constructed to retain runoff from a lO-year, 24-hour storm
plus water used in the operation of the feedlot ("process generated
waste water" which is zero for most Michigan beef feedlots).

The technology level employed in terms of the "best available
technology economically achievable" is the control of all runoff from
a 25-year, 24-hour storm plus all process generated waste water. Thus,
after July l, 1983 the greater than 1,000 head capacity feedlot may
discharge pollutants into navigable waters only if the discharge is
associated with an overflow of the appropriate retention facilities.
These retention facilities must be designed to retain a 25-year, 24-hour
storm plus process generated waste water. Again, process generated

waste water is essentially nonexistent for the beef feedlot.3

 

2Anonymous, Federal Register, 39, No. 2, 5705.

 

3Ibid.

20

For new sources, the standard of performance is that there is
to be no discharge of process waste water pollutants to navigable
waters unless it overflows the technology type designated for the new
source category. This technology level is the capacity to control a
25-year, 24-hour rainfall eventpflus all process generated wastes. Thus,
the abatement technology required for new feedlots in excess of 1,000
head is essentially the same as the "best available technology econom-
ically feasible" required for existing feedlots after July l, 1983.

In addition to control of runoff and process waste waters
specified in the two technologies for existing point sources and the
one technology for new point sources, storm runoff which has been iden-
tified by either the Regional Administrator of the EPA or the state

water pollution control agency is also subject to effluent guidelines.“

Role of States in NPDES

 

The authority to administer the National Pollution Discharge
Elimination System (NPDES) rests in the hands of the EPA or the appro-
priate state agency. The EPA will delegate its authority to issue
permits for the NPDES if the state meets certain federal requirements.
The state agency must have the authority to:

1. issue permits complying with the requirements of the Act

2. modify or revoke permits if there is a violation of the law

 

l'J. B. Johnson and G. A. Davis, "The Economic Impacts of Impos-
ing EPA Effluent Guidelines on the U.S. Fed-Beef Industry," Cornell
University Waste Management Conference, March 1974.

21

3. inspect, monitor, and enter the premises of all dischargers
4. require reports from permit holders

5. insure that interested parties have the opportunity to comment
on a permit application

6. punish permit violations through civil and criminal penalties
7. establish a continuing planning process and an enforcable law
prohibiting discharge of pollutants not authorized by the
permit.5
In Michigan the authority for pollution control rests with the
Water Resources Commission and the Air Pollution Control Commission.
Responsibility for establishing pollution standards for the various
surface and ground waters of the State rests with the Water Resources
Commission.6 Michigan has accepted responsibility for the NPDES permit
system, and the Water Resources Commission will be the issuing and
monitoring body of the Federal program.7 While it is possible for a
state to have a more rigorous pollution abatement program than the EPA
system, Michigan's present stance is to proceed under the Environmental
Protection Agency's guidelines.
While the state permit issuing agency may supervise the NPDES
permits and monitoring of polluting municipalities and industries, the

state agency is not an autonomous unit. Each state agency must transmit

to the EPA regional administrator a copy of each permit application and

 

5Public Law 92-500, 92nd Congress, S. 2770, October 18, 1972,
p. 66.

6J. B. Johnson, L. J. Connor, and C. R. Hoglund, "Summary of
State Air and Water Quality Statutes Applicable to the Management of
Livestock Wastes," Agricultural Economics Report No. 231, Michigan State
University, August 1972.

7L. J. Connor, personal communication, April 1974.

:‘

nib

D‘. V;

[I

LIV

.u~\~us unlll.

22

any action relating to each permit application. Within 90 days of such
transmittal the EPA may stop issuance of a permit if it deems such a
permit to be outside the "guidelines and requirements" or the Water
Pollution Control Act Amendments of 1972.8 The implication of the EPA
supervisory role is that modification of the "best practicable technol-
ogies currently available" and the "best available technologies econom-
ically achievable" may occur for problem point sources. Thus, it is con-
ceivable that abatement technology requirements could be more rigorous

than the guidelines established in the February 14, 1974 Federal Register.

 

Review of EPA Point Source Guideline Development

 

In setting the "best practicable technology currently available"
and the "best available technology economically achievable," a wide
diversity of possible control technologies were available. Some 20
different technology types were identified as being applicable to manure
from feedlots with another 10 technology types available to treat runoff.g
With respect to manure, the EPA identified land spreading as a "techni-
cally sound means for animal waste utilization." The agency reported
that fertilization rate application of animal wastes generally does not
have secondary pollution characteristics in excess of inorganic ferti-

lizers. Potential for pollutional runoff occurs only when these crop

 

°Public Law 92-500, 92nd Congress, S. 2770, October 18, 1972,
p. 67.

’Environmental Protection Agency, Development Document for
Effluent Limitations Guidelines and New Source Performance Standards,
EffluentFGuidETTnes DivisTon, Environmental Protection Agency, August
1973.

 

23

fertilization rates are exceeded and manure spreading is used primarily
as a disposal activity without regard to crop fertilization.10
The problem of controlling feedlot runoff was complicated by the
enormous diversity of individual feedlots. EPA's dilemma with respect
to finding the technology levels to apply can be seen in the following
statement:
To better understand the runoff control problem, a look
at the nature and extent of runoff from animal feedlots is
required. First, the runoff from feedlots is not readily
amenable to classification methods of treating water borne
wastes. . . . Second, the waste flow is almost completely
dependent upon rainfall or snowmelt for conveyance from
the lot and is therefore unpredictable in duration and
quality. Third, the wastes are extremely variable in
quality while remaining consistently strong in organic
constituents. Fourth, the raw wastes vary widely in
characteristics depending upon many factors, among which
are the type of feed, the ambient temperature, the species
and age of the animal, the type of housing and many other
factors.11
After briefly reviewing the various control technologies for
manure and runoff, the recommendation was that no discharge of feedlot
process waste waters to navigable water bodies be allowed by July 1,
1977 except for precipitation events in excess of the 10-year, 24-hour
storm. Also by 1983, recommended was that the no discharge limitation
would apply except for precipitation in excess of the 25-year, 24-hour
storm; moreover, this technology also applied to the new point source
category. In addition, the elimination of discharge to navigable waters
should be achieved by the recycling of wastes to land for efficient

utilization as moisture and nutrients by growing crops.

 

1°Ibid., p. 149.

nIbid., pp. 150-151.

24

The recommendations were made while admitting that "a completely
reliable estimate of total investment costs required of the industry in
achieving the specified effluent limitation is beyond the scope of known
information." Investment costs required to comply with these recommenda-
tions were estimated at $0.5 to $1 billion for the nation's feedlots.12

Review of Methods and Practices for Controlling
Water Pollution from Nonpoint Sources

 

 

In October 1973 the EPA published "Methods and Practices for
Controlling Water Pollution from Agricultural Nonpoint Sources" which
was intended to provide information and practices to control or reduce
water pollution from nonpoint agricultural sources.13 Animal wastes
applied to land were identified as a source of nonpoint source pollution.
Waste removal from feeding facilities was recognized as one of the major
contributors to animal waste nonpoint source pollution.

The report stressed that the application of animal wastes to
land can be a highly effective and acceptable means of disposal. The
nutrient content of the waste can improve the quality of the soil and
may reduce soil erosion into streams and water bodies. Pollution
results only when "good waste management practices" are not followed.

The report listed some "good management practices" which should

be followed; however, no specific recommendations concerning waste

 

12Ibid., p. 259.

13Environmental Protection Agency, "Methods and Practices for
Controlling Water Pollution from Agricultural Nonpoint Sources," Water
Quality and Nonpoint Source Control Division, October 1973.

25

disposal were made. These practices were suggestions concerning waste
application rather than enforceable guidelines such as those established
for feedlot runoff.

Investigations of Economic Impacts
of EPA Poiht Source GuideTines

 

The Environmental Protection Agency contracted Development
Planning and Research Associates, Inc. to investigate the broad economic
effects which might result from the application of the required technol-
ogies.1“ An effort was made to analyze the economic effects of point
source guidelines on the cattle, hog, dairy, sheep, broiler, turkey and
duck industries. An impact analysis was made for the beef, swine and
dairy feedlots. The impacts of controls for each type of feedlot were
considered for the price effects, the financial effects, the production
effects and effects on employment and community.

Briefly reviewing the price, financial, production, employment,
and community effects resulting from the proposed beef feedlot regula-
tions, Development Planning and Research Associates, Inc. used a micro
level analysis as a basis. After quantifying the effects of the pro-
posed guidelines on the cost structure of various sized feedlots, the
analysis of aggregate price, financial, production, employment and
community effects were primarily qualitative in nature.

First, incremental costs of pollution control as recommended by

the EPA were estimated for various representative firms. Feedlots were

 

1"M. L. David, R. E. Seltzer and W. D. Eickhoff, Economic
Analysis of Proposed Effluent Guidelines--Feedlot Industry, Environ-
mental ProtectionAgency, August 1973.

 

26

categorized as 100, 500, 1,000, 5,000, 10,000, and 20,000 capacity
units. Under all types of farms, an open lot system (200 sq. ft. of
space per animal with little if any shelter) was assumed to be the
housing technology employed. It was assumed that 60-70 percent of all
lots exceeding 1,000 head capacity met the effluent guidelines while
only 20-30 percent of the less than 1,000 head capacity met the
guidelines.

Incremental costs of runoff abatement expenditures were esti-
mated in terms of initial investment expenditUres and annual operating
and depreciation costs for each of the representative lots. Economies
of size were found in the 25-year, 24-hour storm technology with total
annual costs equalling $3.04 per head for the 100 head lot, $2.11 for
the 500 head lot, $2.01 for the 1,000 head lot, $1.57 for the 5,000
capacity lot, $1.10 per head for the 10,000 head lot and $0.69 per head
for the 20,000 headlot.ls

The price effects resulting from this change in cost structure
were qualitative assessments of the price changes required to maintain
existing profit levels, the probable short run price effects, and the
expected long run price movements. Existing profit levels could be
maintained with price increases of 30¢/cwt for lots of 100 head, 21¢/cwt
for 500 head lots, 9¢/cwt for 1,000 head lots, 7¢/cwt for 5,000 head lots,
5¢/cwt for 10,000 head lots and 3¢/cwt for 20,000 head lots.16 The
probable short run price effects of imposing pollution control technology

was concluded to be quite minor as were the long run price effects.

 

15Ibid., p. XII-11.
16Ibid., p. XIII-5.

27

The financial effects of imposing EPA runoff controls were
estimated to be substantial for the small lot while being minimal for
the large lot. The after tax rate of return on investment declined from
22.5 percent to 15.3 percent for the 100 head lot while declining by
approximately 1-2 percent for the greater than 1,000 head lots.17

From the price and financial effects, the study concluded that
production effects would be most severe in the less than 1,000 head lots.
The imposition of runoff control measures would simply speed up the
trend of the exit of less than 1,000 head lots from production. The
number of 1,000-1,999 head feedlots was predicted to increase with
effluent controls accelerating the expansion of some smaller feedlots.
The study concluded that large feedlots would be affected by a very
small amount with the overall supply relationship not being changed
materially.18

Since most of the effects are felt by small feedlots, the study
concluded that employment and community effects would be negligible.
"Capital and hired labor will most likely be utilized in an alternative
enterprise" with resources being directed from the feedlot enterprise to
other agricultural enterprises within the local community.19

A 1974 study by Johnson and Davis developed estimates of the
economic impacts of runoff control with emphasis on capital outlays

and changes in production costs necessary to conform to effluent

 

Ibid., p. XIII-8.

17
18Ibid., p. XIII-19.

1’1 id., p. XIII-26.

28

guidelines.2° The analysis considered only the application of the best
practicable control technology currently available (zero runoff except
from facilities designed to contain the runoff from a lO-year, 24-hour
rainfall event). Furthermore, the analysis considered only one avail-
able system for retaining the runoff. The system considered is one of
diversion terraces to divert extraneous flows away from feedlot sur-
faces, settling basins to prevent solids from entering retention ponds,
retention ponds for containment of runoff until it can be applied to
farmland, and pump-irrigation equipment for emptying ponds and distrib-
uting the runoff to the field. This system is probably the maximum
technology required under under the best practicable control technology
currently available.

Results of the study are categorized by location and housing
type. Table 2 provides some of the results from the study and illus-
trates the economies of size inherent in pollution control technology.

Aggregate estimates of total capital outlays necessary to adopt
the 4-component system were made by Johnson and Davis. An estimate of
$133 million was considered the requirement of capital necessary to
construct the diversion terraces, settling basins, retention ponds and
pump-irrigation equipment. Approximately 95 percent of the investment
would be imposed on fed-beef operations of less than 1,000 head

capacity.

 

2°J. B. Johnson and G. A. Davis, "The Economic Impacts of
Imposing EPA Effluent Guidelines on the U.S. Fed-Beef Industry,"
Cornell University Waste Management Conference, March 1974.

29

Table 2. Per Head Capital Outlays and Production Cost Increases to
Control Runoff from Fed—Beef Operations, by Size Class and

 

 

 

 

Areaa
Production Cost
Size or Capital Outlays Increases per
Capacity Class per Head Head Marketed
(I) (i)
Eastern States:
100 145.20 21.17
100-199 21.00 3.19
200-499 11.60 1.84
500-999 8.18 1.28
1,000 + 3.13 0.69
Western States:
1,000 21.65 5.79
1,000-7,999 2.92 0.57
8,000-15,999 1.61 0.40
16,000 + 1.38 0.36

 

aJ. B. Johnson and G. A. Davis, "The Economic Impacts of
Imposing EPA Effluent Guidelines on the U.S. Fed-Beef Industry,"
Cornell University Waste Management Conference, March 1974.

30

This analysis is limited by the fact that all fed-beef
operations were assumed to construct the four component system and
retain historic production levels. As Johnson and Davis state,

reactions of individual fed-beef operations . . . cannot
be fully determined. Some may discontinue producing beef
. . others may make adjustments and continue to operate
at historic production levels. Other‘paths of adjustment
are also possible. Additional knowledge of production
system--cost relationships, operator equity position,
access to capital sources . . . and operators' expec-
tations of beef and input prices would need to be
specified.21

A study by G. R. CroSs investigated the economic effects on
confined animal feeding Operations by imposition of the Oklahoma Feed
Yards Acts of 1969.22 The Act applied to feedlots feeding 250 or more
head of livestock at one time during the year. While the Act was not
as specific as current EPA guidelines, technologies employed to comply
with the Act were quite similar to current EPA guidelines. The abate-
ment technologies employed were made definitive by the actions of the
Agricultural Stabilization and Conservation Service (ASCS) in Oklahoma.
Waste control technologies were identified by the ASCS as being accept-
able in order to provide cost sharing funds to feedlots. The practices
include a retention pond or storage tank to avoid runoff into any stream,

lake, river or creek and a diversion terrace to direct runoff flows from

 

21Ibid., p. 16.

22George R. Cross, "Economic Impact of Environmental Quality
Legislation on Confined Animal Feeding Operations in Oklahoma"
(unpublished M.S. thesis, Oklahoma State University, 1971).

31

feedlots, and runoff flows from adjacent areas. Thus, the implementa-
tion of the Act resulted in technologies similar to current EPA
guidelines.

The examination of the costs of handling wastes under the Act
revealed that the Act had little effect on the larger feedlots in the
state. The larger feedlots, which handle the majority of feeder cattle
in Oklahoma, are in the western part of the state. This area has low
rainfall, high evapotranspiration rates, and most of the feedlots had
runoff retention structures at the time of the Act's passage. The
effect of the Act largely fell on small producers who were not equipped
with waste control technology at the time of the Act's passage.23

Average total costs of beef waste handling was found to decline
until a lot of approximately 10,000 head was reached. Average total
costs for the small lot (500 head) was $0.0032 per pound gain, a 5,000
head lot was $0.0015 with average total cost rising slightly above this
figure at a 10,000 head capacity lot.2“ (These figures include a nomi-
nal license fee.) Converting these figures into a per head basis, the
study indicates that annual operating and amortized fixed costs would
be $1.28 per head for the 500 head lot used the entire year and $0.60
per head for the 5,000 head feedlot.

A 1971 Nebraska study by Daiss attempted to assess the total

costs of attaining the level of control of feedlot runoff as set forth

 

23Ibid., p. 85.

2"Ib'ld., p. 52.

ti

32

by the Nebraska Water Pollution Control Council?5 A 1967 Nebraska Act
adopted a set of measures to comply with the Federal Water Quality Act
of 1965. Included in the measures was the passing of administrative
responsibilities of feedlot runoff control to the Nebraska Water
Pollution Control Council. The policy of the Council at the time of
the Study by Daiss was the following: "If wastes run off the feeder's
property or into a water course, he should develop a waste control
facility plan and have it approved by the Water Pollution Control
Council."26

As in the case with the Oklahoma runoff technology, the waste
control facility plans adopted by the Nebraska Water Pollution Control
Council were similar to the current EPA guidelines. Generally involved
was a system of diversion terraces to divert outside runoff away from
feedlot, a pond to collect the runoff from the feedlot and an acceptable
disposal method.

Again, decreasing runoff control investment costs per head and
decreasing annual runoff control operating costs per head were identi-
fied. As lot sizes progressed from 72 head to 7,500 head, investment
cost declined from $31.84 per head to $4.61 per head while annual
operating costs declined from $5.06 per head to $1.10 per head. It
appears from the Daiss study that most runoff control economies of size

were gained at the 500-750 head capacity lot size. While per head costs

 

25Bill J. Daiss, "Economics of Water Pollution Abatement from
Beef Cattle Feedlots" (unpublished M.S. thesis, University of Nebraska,
1971).

26Ibid., p. 6.

33

declined gradually past 750 head, substantial reductions in average
investment and operating costs occurred when capacity was expanded
to 750 head.27

The study estimated total costs by summing the investment costs
and operating costs over the existing feedlots. No attempt was made to
estimate the effect of the runoff control systems on the exit or entry
of firms or how these controls might affect the capacity of firms over
time.

Like the studies by Development Planning and Research Associates,
Inc., Johnson and Davis, and Cross, the Daiss study does not consider
the dynamic elements associated with rules for runoff control. The ques-
tions remain as to how these water pollution control rules may affect
(a) the outputs produced and the production systems utilized and (b) how
they might affect feedlots of different age and salvage values compared
to a "do nothing" rule that was followed prior to the late 1960's.

Pherson explicitly recognized the possibility of water pollution
control rules encouraging a shift in the input mix and output level in
a 1974 study of Minnesota feedlots.28 The study calculated investment
and operating costs for imposing runoff and waste handling controls on
representative farms in Southwestern Minnesota with feedlots of 100, 500,
1,000 and 1,500 head capacity. To determine how profit maximizing oper-

ators would operate after the imposition of runoff control and waste

 

27Ibid.. pp. 43-47.

28Carl L. Pherson, "Beef Waste Management Economics for Minnesota
Farmer-Feeders," Cornell University Waste Management Conference, March
1974.

34

handling controls, a linear programming model was used. The linear
program was developed around a 500 acre corn-soybean farm having a
feedlot with a one time capacity of 500 head.

A whole farm approach was then used to determine the profit
maximizing combination of enterprises given the farm's resource con-
straints. For the farmer with an open lot system, the imposition of
EPA type runoff controls and suggested waste management practices led
to a slight reduction in earnings ($377), and a less than optimal plant-
ing schedule. For the farmer with a dry lot system, runoff controls and
suggested waste management practices also resulted in decreased earning,
decreased numbers of cattle fed and a less than optimal harvesting
system. Results also indicated that the profit maximizing feedlot
system would tend to favor a more confined system under the imposition
of these controls. Totally confined and drylot systems were more
profitable systems under an environmental control policy.

This static (before and after the imposition of controls)
analysis added some depth to the information as to how water pollution
control rules affect feedlots. First, the study recognized that the
imposition of controls may have some immediate effect on feedlot per-
formance, and it attempted to quantify these effects in terms of output
and earnings. Second, the study recognized that controls may have some
longer run impacts on feedlot performance through changes in housing-

production systems.29

 

29Ibid.. PP. 27-32.

35

Each of the above studies is a useful contribution to the
understanding of the impacts of water pollution control rules on beef
feedlots. Furthermore, the static type of analysis continues to be
employed with regard to this problem. Don Gailey's forthcoming Ph.D.
thesis analyzes the effects of runoff and solid waste controls on
Michigan feedlots similar to the Oklahoma and Nebraska methodology.3°
Also, a study by Don Byrkett of Ohio State University is underway to
analyze the effects of EPA guidelines on the location of feedlots in
the United States.31 Certainly, the structural implications of these
guidelines may be important due to difference in waste control economies
between feedlot size groups and differences in cost structures between
feedlots in various areas of the country.

The attempt in this study is to more clearly define the effects
of selected water pollution control rules by looking at paths of
adjustment of beef feedlot firms over time. The paths of adjustment
are traced by viewing the performance of simulated feedlots in terms
of earnings, lot capacity, feedlot-production system structure, and

equity positions.

 

3°Donald Gailey, forthcoming Ph.D. thesis, Michigan State
University.

31Donald Byrkett, Ohio State University, personal communication,
March 1974.

CHAPTER III

THEORY OF THE FIRM EMPLOYED IN SIMULATION MODEL

General Description of Theory Employed

 

The simulation model constructed for this study has the firm as
its basis. The distribution of Michigan beef feedlots is assumed to be
known and firms are randomly selected from this distribution. These
individual firms are simulated over the selected time horizon (1960
through 1985) to draw implications concerning the effects of various
water pollution control rules. Thus, the behavioral theory employed
by each simulated firm is of primary importance in the construction of
the model.

Generally, a static neo-classical theory of the firm with asset
fixity modifications is used as the underlying behavioral theory. Each
firm simulated is assumed to behave as a profit maximizer subject to
constraints imposed by financial and resource constraints. Expected
future returns from various enterprises are based on returns from pre-
sumably known production relationships and price expectation relation-
ships based on past price movements.

The basis for the firm's decision concerning its current level
of production and kinds and quantities of inputs utilized can be broken

down into three general areas--the price expectation process, the

36

37

input-output relationships expected by the firm, and the decision making
mechanism used to determine the type of investment and the level of

input usage.

Price Expectations

 

The price expectation models used by the simulated firms are
generally "naive" models that base future price expectations on past
price behavior. Expected input prices for investments in new building,
machinery, and other durable investments are some trend of past prices

such as

P d.°P (1)

a,t+l = a,t
Expected salvage values for durable assets in current use are a

function of length of life of the durable asset, expected investment

costs of a new and identical durable asset, and the annual rate of user

costs or economic depreciation.

Ps,t = k 'Pa,t (2)

k = f(age, U) (3)

where Ps,t is the expected salvage value of a currently owned resource
in time period t and Pa,t is the acquisition price in time period t.
The current salvage value is some proportion, k, of the price
of an identical new durable asset. This proportion, k, is a function
of the age of the currently owned asset and the annual user cost, U, or

the rate of economic depreoiation of the asset. This rate, U, is assumed

to be a constant where

38

U = Ps,t+1/Ps,t (4)

It should be recognized that U refers to the user cost problem
identified by Johnson.1 Identifying U as a constant is a gross simpli-
fication since its value is decided by the rate at which services are
extracted by durables, and the value of the services flowing from the
durable resource. Unfortunately, the economic theory underlying the
determination of a value for the user cost has not been identified.
Thus, the alternative approaches to the treatment of user cost are to
neglect it or to recognize it and make some gross and theoretically
unsupported estimation of the annual user cost. The latter method is
chosen in order to explicitly recognize the concept in formulating the
simulation model.

All durable assets such as machinery and buildings are assumed
to have the same value of U. Assuming the assets' new value increases
of 6 percent per year with a user cost of 0.1 (l -U =0.1), the index
of the salvage value of machinery and buildings would decline as shown
in Figure 2.

Land acquisition and salvage values are expected to be equal
in any one year. Values in t-+l are expected to be equal to a constant

times the value of the land in t.

Pland,t+l = “'Pland,t (5)

 

1G. L. Johnson, "Alternatives to the Neo-Classical Theory of the
Firm," American Journal of Agricultural Economics, May 1972.

100

90

80

7O

60

50

40

Index of Asset Value

30
20

10

Figure 2.

39

 

 

 

1 1 J 1 1 J g g _l l
l 2 3 4 5 6 7 8 9 10
Years

Index of Annual Salvage Values of Buildings and Machinery
Over a 10 Year Period with 0 =0.8 and o=l.06.

99!

:53

501

lb?

40

Other inputs besides durable assets and land include flow
variables such as feed, labor services, fuel, and so forth. These
variables are used up during the production cycle. The price expecta-
tion model for these variables is the same form as (1). It is assumed
that feedlot operators estimate prices of these inputs in the next
period by inflating current input prices by some constant reflecting
past inflation rates of the particular input.

Beef feeder and slaughter price expectations are assumed to be
somewhat different than the simplistic trend model for flow variables.
While both feeder and slaughter expected prices are for an input and
output flow, they are assumed to be recognized by firms as not being
a simple linear trend of past prices of the form in equation (1).
Expected slaughter prices are a function of the current feeder price,
the current difference between feeder and slaughter prices, and the

recent change in the slaughter price.

P f(P

,t. AP ) (6)

slaughter,t+1== feeder,t’ Pslaughter,t ' Pfeeder slaughter

Thus, the firm expects the future slaughter price to be reflected by
current feeder prices, current price "margins," and recent changes in
slaughter prices. As feeder prices rise, the firm's expectations of
future slaughter prices changes. Similarly, the "margin" (difference
between slaughter and feeder prices) gives some information concerning

future slaughter prices as does the trend in slaughter price changes.

41

Expected feeder prices are simply equal to the expected

slaughter prices minus the current margin or

P P

feeder.t+l = slaughter,t ' (Pslaughter,t"Pfeeder,t) (7)

Expected Input-Output Relationship

The input and output prices described above are used by the
entrepreneur in evaluating the profitability of each investment alterna-
tive along with the expected input-output relationships. The firm is
assumed to face n-+2 mutually exclusive investment alternatives where n
is equal to the number of mutually exclusive investment alternatives
which are purchased at acquisition value. The firm may also invest in
off-feedlot investments or retain the investment alternative currently
being employed.

Each feedlot investment alternative has a production function of

the form

v = fa(X],X2,...X1.|X

a ..Xm)a=l,...,n+2 (8)

i+l°
where Ya stands for the quantity of beef produced and X],...Xm stand for
the inputs employed. Variable inputs are X],...,Xi and fixed inputs are
Xi+1’ooo,xmo

The firm views each mutually exclusive investment alternative as
possible uses for its borrowed and owned resources. Thus, the feedlot
firm considers investments in alternative feedlot technologies, but it

employs only one feedlot technology. Examples of feedlot technologies

42

are completely open lot construction (no shelter for cattle) or
completely confined housing facilities (cattle under shelter at all
times). After evaluating each mutually exclusive investment alternative,
the farm selects one alternative for each time period.

In the evaluation of new investment alternatives, the firm views
the variable inputs in each alternative production function as perfect
complements. The resulting shape of the production function for the

newly acquired alternatives is shown in Figure 3.

 

 

 

 

 

 

 

 

 

 

X1 Values of Isoquants:
l. Y3>Y2>Y1>Y0
2. Y3 - Y2 =
Y2 -Y1=

Y3 Y1 'Y0

Y2

Y1

Y0

x2|x3...xm

Figure 3. Production Function for Newly Acquired Alternatives as
Viewed by the Firm.

43

The only constraints on the amount of inputs that the firm
desires to employ in each investment alternative are the financial
constraints placed on it from outside sources and the labor constraints
placed on it by the availability of labor.

The production function in Figure 3 is viewed by the firm as the
general shape of each newly acquired investment alternative or for off-
feedlot investments. For the investment alternative currently being
employed, the production function is somewhat different. While variable
inputs are assumed to be perfect complements, the relationship between
the variable inputs and the fixed inputs is also assumed to be perfectly

complementary. Figure 4 illustrates the relationship.

X] Values of Isoquants:
1. Y3=Y2
2. Y2>Y1>Y0

 

 

 

 

 

 

 

 

 

 

x2|x3...xm

Figure 4. Production Function for Currently Employed Investment
Alternative as Viewed by the Firm.

44

Once an investment is in place on the feedlot, production cannot
exceed some maximum. The marginal physical product of the addition of
perfectly complementary inputs is constant until capacity is reached.

At capacity the marginal physical product of the complementary group of
inputs becomes zero and marginal costs become infinite. Thus, the firm
has two constraints on its production under an old technology regime--
(a) the financial constraint by the lender, (b) labor constraints, and

(c) the capacity constraint.
Actual Prices and Input and Output Relationships

Once an investment alternative is chosen and this alternative is
put into use, the production function does not assume those simplistic
properties described above. Rather the production relationship is curvi-
linear with diminishing returns occurring with increasing levels of
input usage. Furthermore, prices do not behave as expected and follow
paths that are not predictable on an gx_gnt§_basis. Thus, the imperfect
knowledge of each firm concerning its production relationship and future

prices produce suboptimal performance by the firm.
Decision Making

The decision making process of choosing the type of investment
and the level of complementary inputs to employ is a problem of entre-
preneural decisions over a multi-period time horizon. With the pre-
viously formulated price expectation models and expected production

functions in mind, it can be seen that the model's economic agent

45

assumes that he possesses complete information when decisions are made.
Thus, under Knight's classification, the decision maker faces g_prig£i
certainty.2 While risk and uncertainty are undoubtedly present in the
firm's environment, they have been ignored in model formulation.

Under Hick's definition, a model is dynamic if every quantity
in the decision process is dated.3 Thus, the model is essentially a
dynamic model employing certainty in the decision making process.

Hick's formulation of a dynamic model of entrepreneural decision
making under certainty is a generalization of the static model. The
firm chooses that course of action which maximizes the payoff function.
The payoff function relies on the current and future actions of the firm,
and the value of payoff is the present value of cash flows over the time
horizon. At any point in time, the firm is assumed to solve a con-
strained maximization problem for the planning horizon and determine
the optimal investments over the entire planning horizon.

This dynamic decision making model is modified for the purpose
at hand. Instead of basing a present decision on all possible invest-
ment paths over the foreseeable future, the decision is reduced to
making the most profitable first move. The firm is assumed to consider
as relevant the profitability of possible investment alternatives in the
current time period. It does not weigh the results from all investment

paths over an expansive planning horizon. The firm makes its investment

 

2Frank H. Knight, Risk, Uncertaintygand Profit (Boston:
Houghton Mifflin Company, 1921).

 

3J. R. Hicks, Value and Capital, 2nd ed. (London: Oxford
University Press, 1946).

 

46

decision from choices available during the current period. The firm
considers the future but only as it affects the choices currently
available.“

A capital budgeting approach is used to assess the choices and
find the current "best" investment. Using the net present value method,
all future cash flows are discounted to the net present value using the
required rate of return. The net present value of an investment would

be

 

T At
NPV = z [ t] (9)
t=0 (1+R)

where At represents the cash flow in period t, T represents the time
horizon of the investment, and R represents the required rate of return.
The required rate of return is equal to the opportunity costs of capital
in an off-feedlot investment of equal risk. Thus, the NPV of $1
invested in off-farm activities is $0. NPV's greater than $0 indicate
that feedlot investment is "better" than off-feedlot investment.
Investments in each of n mutually exclusive new feedlot facil-

ities would have a net present value

—'

A sv
van=z tt+ TT...
t=0 (1+R) (1+R)

 

 

I0 (10)

 

I'Cohen and Cyert, Theory of the Firm: Resource Allocation in a
Market Economy (Englewood Cliffs, N.J.: Prentice-Hall, Inc., 1965).

47

where At represents the operating cash flow in period t, SVT is the
salvage value at the end of T years, I0 is the current value of assets
committed in the investment and R is the Opportunity costs of capital.
The investment in facilities currently in place is evaluated by
the same general technique with adjustments made for a different length
planning horizon. The amount of investment committed to an old
facility is equal to the cyrrent salvage value of that facility.

T-i At SV

NPV = Z + - SV. (11)
C t=o (142)" (1+R)"' 1

 

where i is the present age of the feedlot investment currently being
used.
The current value of investment in the current feedlot or the
salvage values of machinery, buildings, and land is assumed to be a
function of the current replacement value and the length of life of the
asset.
i

5V1 = U '1 I Pland,i ('2)

where i is the age of the asset, U is a constant, I is the replacement

 

 

value of the buildings and machinery being used, and Pland i is the
market price of land.
Reformulating equations (11) and (12)
T-i A uTI -+P
_ t T land,T i
NPVC ‘ X t T T-i ' u '1 ’ Pland i ('3)
t=o (1+R) (1+R) ’

48

The present value of each investment alternative is evaluated

using equations (10) and (13) with the firm selecting that investment

with the greatest net present value.5

Behavior of Michigan Feedlots

 

Using the above theoretical construction, dynamic behavior of

a firm can be predicted with the following known elements:

1.
2.
3.

01

PVC»

firm's initial net worth

initial debt structure

the debt limit placed on the firm in terms of the debt/equity
ratio

Off-feedlot opportunity cost of capital

beginning age and type of feedlot facility

input and output prices (expected and actual)

annual user cost

production function (expected and actual).

In each time period, the firm evaluates its investment oppor-

tunities using the expected input-output relationships and the expected

prices.

The result of this evaluation is a decision concerning the type

and level of input utilization. The annual profits of the firm are

determined by decision and the actual prices paid for inputs and prices

 

5The decision making model is similar to the one presented by

R. H. Day, S. Morley and K. R. Smith, "Myopic Optimizing and Rules of
Thumb in a Micro Model of Industrial Growth," The American Economic
Review, March 1974.

 

49

received for outputs. Moreover, the resulting profits in combination
with the annual user costs determines the financial situation of the
firm in the next time horizon.

Aggregate production in a specified geographic area is also
predictable under a few simplifying yet not entirely unrealistic
assumptions. Assuming that the totality of production of the firms
under investigation has no effect on output or input prices and that
there was no interactive effects between firms, the firms' production
could be summed to trace total production in the area of interest.

Michigan feedlot production may well fit these simplifying
assumptions. Michigan feedlot producers marketed only 1 percent of the
total United States fed beef marketings in 1969.6 The type of feedlot
found in Michigan is generally one of less than 1,000 head capacity with
only 19 feedlots out of a total of 1,696 feedlots having feedlot capac-
ity of over 1,000 head. The total value of Michigan feedlot production
is also a small proportion of the value of Michigan's agricultural
production. Thus, these feedlots are relatively small atomistic opera-
tions with little individual or collective effect on output and input
prices.

Michigan feedlots are not the only feedlots to which water
pollution control rules are directed. One might argue that while
Michigan feedlot production may not affect the output and input prices,

the application of water pollution control rules will have an aggregate

 

6J. B. Johnson, Gary A. David, J. Rod Martin, and C. Kerry Gee,
"Economic Impacts of Controlling Runoff Arising from Fed Beef Production
Facilities" (unpublished research, 1973).

50

effect on output and input prices. Therefore, it might be argued

that one cannot simply compare aggregate performance in Michigan under
various sets of water pollution control rules. Rather, using the above
theory, the argument would stress that these rules affect all feedlots
throughout the country, and output and input prices may differ under
alternative rules.

Thus, an additional assumption is necessary to evaluate
aggregate feedlot performance in Michigan under various water pollution
control rules under the above theoretical construct. The assumption is
that water pollution control rules have no effect on output prices and
input prices. Preliminary evidence indicates that this assumption may
approximate reality. J. B. Johnson and associates report that beef
production costs increase by only 36-57 cents per head for feedlots over
1,000 head in the western states and 60 cents per head for feedlots over
1,000 head in the eastern states.7 Since these feedlots now produce
over one-half of fed beef marketing, the input and output price effects
may be minimal.

Measurement of the Effect of Water
Pollution Control Rules

 

Upon the imposition of water pollution control rules, the cost
structure of the firm may be affected. The firm's gx_ggtg_production
function changes for those feedlot technologies that include an exposed
lot surface. The decision making process may transmit this change into

a lessening of output and/or a decision to acquire a new feedlot.

 

7I id.

51

Whether the firm is affected by increased costs, reduced output, or
changed feedlot technology, its equity position suffers relative to
the situation where no rules are imposed.

Furthermore, the firm's ability to make change might be impaired
by the installation of technology to conform to the water pollution
control rules. If the salvage price of durable assets which can be
obtained in off-feedlot activities is severely affected, the operator
may be rigidly locked into his production pattern. Equity losses may
occur as future prices drop below the prices expected when the facil-
ities were constructed.

A method of viewing the impact of water pollution control rules
would be to view the following four measures for each firm under alter-

native rules:

—I
0

output of beef cattle for each firm
2 rate of return on equity

3. annual change in equity

4

proportion variable costs are of total assets.

The first measure would demonstrate the output change under
alternative rules. By comparing the second measure, the impact of the
rules on the rates of return could be observed. The annual cost to a
feedlot operator could be determined by comparisons of the annual change
in equity under various rules. Finally, the effect of the rule on asset
fixity could be determined by the fourth measure. If this measure shifts
sharply downward, the operator would tend to be locked into the present

production pattern.

52

Realism in Theory

 

The economic environment faced by the feedlot operator is
different than the theoretical environment postulated. Firms do face
a great deal of risk and uncertainty in future prices and input-output
relationships. One only would have to point to the unpredictable events
of 1972-73, grain and beef price gyrations and government intervention
in the beef market to illustrate the departure in the real world from
the theoretical environment postulated.
Fortunately, complete realism is not required in model formula-
tion as persuasively expressed by Friedman:
. . the relevant question to ask about the "assumptions"
of a theory is not whether they are descriptively "realis-
tic," for they never are, but whether they are sufficiently
good approximations for the purpose in hand. And this
question can be answered only by seeing whether the theory

works, which is whether it yields sufficiently accurate
predictions.8

 

8Milton Friedman, "The Methodology Of Positive Economics,"
Essays in Positive Economics (Chicago: The University of Chicago
Press, 1973), p. 15.

 

CHAPTER IV

SIMULATION MODEL

Simulation models are difficult to describe since the
construction of each model tends to be unique. In an effort to improve
clarity, the description of the model proceeds in two stages. First, a
brief overview of the model's components is presented. Next, a detailed

description is made of each model component.
General Description

The model is a simulation model representing the production
behavior of individual firms over a multi-period time horizon. The
purpose of this multi-period construction is to observe how a firm's
(or firms') behavior differs under a variety of water pollution control
rules directed at the firm.

The basic components of the simulation model include:

1. a farm-feedlot production component

2. ex_gntg_price expectation equations and gx_pg§t_price
realization equations

3. a decision making component

4. An accounting process

5. an Optimizing component to find values of unknown parameters.

53

54

The farm-feedlot production component is a modified product of
a joint effort by personnel in System Science, Agricultural Economics,
Crops and Soils, and Agricultural Engineering Departments at Michigan
State University.1 The model was designed as a part of a larger re-
search project financed by the National Science Foundation in coopera—
tion with Michigan State University for the purpose of designing a
framework to better understand and manage the environment in which
man lives.2

The farm-feedlot production simulator is designed to simulate
Michigan feedlots of various size levels and technology types. Output
of the model includes (a) annual energy requirements (fossil and elec-
trical), (b) labor requirements, (c) annual production costs for
variable inputs such as fuel, labor; seed,fertilizer, taxes, interest,
repair, insurance, and so forth, and (d) capital requirements in the
form of tractors, wagons, harvesting equipment, planting equipment,
silos, barns, feedlot lot structures, feeding equipment, waste removal
equipment and land.

Inputs required for this component arelfeedlot capacity,
beginning and ending cattle weights, days that the cattle are on feed,
the kind of feedlot technology employed, and feed requirements per head
per day. Given these inputs, the component establishes the necessary

resources to produce the specified amount of beef.

 

1L. J. Connor §t_gl,, "Beef Feedlot Design and Management"
(unpublished working paper, Michigan State University, 1972).

2Michigan State University, "Research Proposal for the Ecosystem
Design and Management," December 8, 1971.

55

The component assumes a whole farm approach to feedlot production
by simulating feedlot design and beef production, the production of crops
necessary to feed the cattle, transportation of the crops from field to
storage facilities, the design of feed storage facilities, and the
removal of wastes to the fields. The machinery and land employed is
sufficient to accommodate the crops necessary to produce the required
amount of feed. The amount of feed is detennined by the following
inputs: feedlot capacity, beginning and ending cattle weights, turnover
rates, and feed requirements for cattle under various housing conditions.

The implicit assumptions in the farm-feedlot production compo-
nent should be stressed. First, the component assumes that inputs are
perfect complements in the production of beef. Given the amount of beef
to be produced, the kinds and amounts of feed required, and the type of
feedlot technology to be employed on the farm-feedlot, the component is
able to determine the set of inputs required. Second, the amount of
labor is assumed to be fixed and have zero opportunity cost in alterna-
tive uses. The procedure used to calculate the size and number of
equipment components necessary to accomplish a field activity is a
systematic search for the equipment set that fully utilizes the days
that are available for field activity when a particular field operation
is performed.

The value of the farm-feedlot production component is that it
provides a production function for the remainder of the simulation model.
The farm-feedlot component (component 1) is employed to provide the sim-

ulated decision process (component 3) some notion of the profitability

56

of various feedlot types at a given capacity. After the decision
making process determines the number of cattle to produce and the
type of farm-feedlot technology to employ, the farm feedlot component
provides the production function that determines the costs and returns
to the operation.

Production decisions are based on some gx_gnt§_prediction of
the future behavior of input and output prices and expected input-output
relationships. While the previously described production component (com-
ponent 1) provides the expected input-output relationships, the gx_§ntg_
price expectation equations (component 2) provide the expected price
relationships.

The simulated production behavior of the farm-feedlot in a
single year is seen in Figure 5. Production behavior is constrained
by some factors peculiar to each firm. The total investment employed
is constrained by the level of the owner's equity plus the level of
funds that may be borrowed in any year. The feedlot is also constrained
by the available labor force.

One of the critical components of the model is the decision
making component (component 3). The theory of the firm as described
in Chapter III underlies this component's development. This component
postulates that in selecting an investment each firm maximizes the
present value of future flows from its investment alternatives.

The gx_pg§t_price equations (component 2) produce prices of
factor inputs and product outputs that are independent of the quantity

used and produced on the farm. These price relationships are attempts

57

 

Ex Ante
”Price
Equations

 

 

 

 

 

 

Borrowing, [___,.

Equity and
Labor ’

Constraints

. . . Ex Post Beef Produced
Dec1g;g:e::king PrOauction and Inputs
Function Employed

 

 

 

 

 

 

 

 

 

 

 

Ex_Ante
Production
Function

 

 

Figure 5. Model of Feedlot Behavior in a Single Year.

to provide prices for the model that reflect actual prices. The price
equations needed are those that closely represent gx_pg§t_price
relationships in future years.

The accounting process(component 4) has the function of being
a bookkeeper of the levels of resource flows and resource stocks. The
annual net fund flow for a producer would be the difference between the
accrued value of livestock raised during the year and the accrued costs
of production (less depreciation). This part of the accounting process
includes the calculation of depreciation, income and property taxes, and
the summation of the level of flow resources.

Also included in the accounting process is the calculation of

the level of the stock resources. While traditional accounting methods

58

(as used in the tax calculation sections of the accounting component)
develop a depreciation schedule for capital assets, this schedule does
not Offer the true economic depreciation of the asset. Instead, the
amount of economic depreciation of an asset is a function of the value
of the product produced by the asset and the reduction in value due to
its use in the production process. The term often applied to this
concept is user cost or the "sacrifice of value in the production of
the output."3 The accounting process makes use of an estimated user
cost for capital assets, the changing salvage value of land resources,
and the value of liquid assets in order to approxiximate the asset
position of the individual firm.

Figure 6 illustrates the procedure in an annual simulation of
a firm's activities over a multi-year time horizon. As shown in the
illustration, the accounting process computes the equity position
resulting from a year's operation, records the age of buildings,
machinery, and other capital assets, and records the amount of liquid
assets, capital assets and land resources in the asset structure. At
this point, the model is ready to simulate another year's activities.

Through the use of (a) some rather simplistic ex_gntg_and gx_
pg§t_price equations, (b) the recently constructed feedlot production
component, (c) development of the fund flow accounting process, and
(d) the development of a capital budgeting decision making model, the
simulation model is close to being operational. Preventing the opera-

tion of the model are unknown estimates for five parameters:

 

3John Maynard Keynes, The General Theory of Employment, Interest
and Money (New York: Harcourt, Brace and HOrld, Inc., 1964), p. 55.

59

 

 

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60

1. the user cost of capital assets used in the production process

2. the opportunity cost of funds used in off-feedlot investments
of equal risk

3. the borrowing limit that feedlot firms face

4. the equity distribution of Michigan feedlots

5. the age of capital assets at the beginning of the simulation

period.

The Optimization component (component 5) is used to estimate
values for these unknown parameters. Basically, the optimization
component is a systematic search for values of unknown parameters which
enables the simulated output to closely reflect historic data. The term
optimization is used to describe the process of minimizing some Quad-
ratic loss function; moreover, the quadratic loss function is the sum
of squared differences between the models predicted output and historic
data.

Four of the five unknown parameter values are estimated through
the optimization procedure. The fifth parameter, age of capital assets
at the beginning of the simulation period, is estimated for each simu-
lated firm by randomly selecting an age from a uniform distribution with
a range of one to fifteen years. There exists no §_prjgrj_information
indicating that the age of feedlots would have any particular distri-
bution. The uniform distribution is selected since any one age in the
1-15 year range is as likely to be selected as any other age in the
range. Although an arbitrary time period, 15 years is assumed to be

the maximum length of life of feedlot structures and field equipment

61

found on Michigan farms. While this time span is rather arbitrary it
approximates the life of machinery and buildings on midwest farms.

Figure 7 illustrates the optimizing procedure to find value for
the four unknown parameters. Initial values are selected for the un-
known variables. Net worths are randomly selected for twenty firms
from a net worth distribution where this distribution is determined
by one of the unknown parameters. The behavior of the firms, illus-
trated in Figure 6, is simulated over the 1960-72 time period.

One of the output variables of the simulation model is the
capacity Of the feedlots during each time period. The annual percentage
changes in the total capacity of the simulated lots are compared to the
annual percentage changes in January 1, Michigan Cattle and Calves on
Feed data published by the United States Department of Agriculture. A
systematic procedure is then employed to find values of these unknown
parameters in order to accurately "postdict" 1960-70 cattle on feed

changes.

Farm Feedlot Production Component

 

The basic structure of this component is explained in detail by
Hughes.“ While modifications were made in the model developed by Hughes
in order to produce a usable component for the purpose at hand, the

structure of the component remains the same as that designed by Hughes.

 

“H. A. Hughes, "Energy Consumption in Beef Production Systems as
Influenced by Technolo y and Size" (unpublished Ph.D. thesis, Michigan
State University, 19731

62

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63

The objective of the component is to provide the ability to
simulate a wide range of feedlot capacities over several technology
types. The simulation approach is essentially that of a computerized
representation of the activities of the firm under a variety of condi-
tions. The alternative approach would be to investigate actual operat-
ing systems over the desired range of capacities and technology types.
The research costs associated with the latter approach, the inability to
assess conditions that do not already exist on these operating units,
and the potential difficulty in obtaining cooperation from operating
units make the simulation approach rather attractive.

The Farm Feedlot Production component includes two basic sub-
systems: material transformation and transportation. The material
transformation subsystem transforms input materials into output mate-
rials.5 The mix of inputs used in producing a given level of output
is determined by technical relationships between inputs and outputs.
All inputs are assumed to be perfect complements with respect to the
amount of energy produced; moreover, each type and level of output is
assumed to have one level of total energy required for its production.
Once the output has been specified the subsystem proceeds to calculate
the energy requirements needed to produce this output, the types of
inputs needed to produce the output, the energy levels needed for each
type of input, and the number and size of inputs needed to produce the
output. As an example of the logic used, assume that corn requires Y

units of energy for the production of 15,000 bushel of corn.

 

5Ibid., p. 9.

64

X. = KiY i = 1,2,...,m

There are m input materials needed in the production Y, and each

input material Xi requires Ki units of energy per unit output of Y.

Total energy required is a 5-dimensional concept. For each unit

of output, five types of energy flows are required:
1. capital ($)
2. labor (man hours)
3 fossil energy (horsepower hours)
4. electrical energy (kilowatt hours)
5. land (acres).

Total cost of flow variables in the system can be computed as
a scalar function of the five energy costs. Total costs of stock var-
iables (or the capital costs) can be calculated as a scalar function
of labor, fossil energy, electrical energy and land.

The second of the two basic subsystems of the farm feedlot
production component, the transportation subsystem, is similar to the
material transformation subsystem in the calculation of input require-
ments. Given the output (i.e., bushels of corn, tons of silage), the
subsystem calculates the energy requirements for each input and deter-
mines the inputs required to transport the feed.

After the ration has been produced and transported to storage,
it is moved to the animals in the feedlot. The cost of flow variables
and the cost of stock variables associated with the feedlot structure

is determined after a specification is made of the type of feedlot

65

technology and feedlot capacity. Inputs determined by this process
include building and lot structure, labor, fuel, and machinery.

From the feedlot flows wastes which are accounted for by a
four dimensional flow variable. The four dimensions of the waste
are quantities of nitrogen, phosphorus, potassium, and waste water
(non-nutrient portion).

The nutrient and non-nutrient portion of the waste are
transported to the field for application on the soil. Prior to
transportation of the material, some losses occur in storage. The
waste is assumed to be applicable to crop lands as a substitute for
N, P, and K in commercial fertilizer. Waste transportation inputs
needed to transport and spread the waste during specified periods of
the year are calculated by a method similar to that used in other
transportation activities.

The total nutrient requirement is determined by the acres
of land planted to crOps and the amount of nutrients needed per acre
of cropland to maintain a steady state nutrient balance. Commercial
fertilizer quantities needed are computed as a difference between the
total nutrients (N, P, and K) required and the nutrients supplied by

the waste.

Modifications in Farm-Feedlot Component

 

The simulation model as described by Hughes was modified to
accommodate this economic analysis. First, the model is modified to

be able to manipulate it as desired. Since the model is used in each

66

year for all of the firms simulated, it is necessary that the model
be modified to be as computationally efficient as possible.

Besides the technical modifications, the model is adjusted to
improve its representation of reality. In its initial construction the
model did not accommodate scraping activities that occur in a feedlot.
Waste must be scraped from the surface of the lot on a regular basis
to prevent excessive waste buildup, and corrections are made to reflect
this real world condition.

In addition, runoff abatement facilities and equipment are not
employed on the feedlot in the model developed by Hughes. In order to
accommodate the imposition of runoff control, one runoff abatement
system is added to the model. The system consists of a set of a diver-
sion terrace, settling basin, holding pond and pump and irrigation
equipment to empty the pond.6 The runoff abatement system's capital
outlay is determined by the rainfall occurring and the amount of feedlot
surface exposed to the rainfall. While this runoff abatement system is
certainly not the only system capable of accommodating zero runoff
requirements, the system is felt to be representative of the investments
and annual costs needed. The controlled runoff collected by this system
is accounted for by only the total quantity of waste returned to the
land by irrigation, and it is not dimensioned by its nutrient value.
Thus, the runoff abatement system is assumed to produce only costs and

does not produce a product that is of economic value to the producer.

 

6Cost equations in the runoff abatement system are from G. A.
Davis and J. B. Johnson, ERS, USDA, Michigan State University.

67

The zero value placed on the waste removed from the runoff
abatement system is a close approximation of its nutrient content at
the time of application to the land. While the quantity of runoff
varies by rainfall intensity, lot structure, animal density, and the
type of feedlot operation approximately 5 percent of the total waste
generated leaves the feedlot in the form of surface runoff.7 The result
is that runoff contains a large amount of rain water and a low nutrient
content. When the contained runoff is applied to the field only a small
percentage of the total quantity applied is available for usage by
crops.8

The Farm-Feedlot Production component with the appropriate
modifications presents an adequate production function of the farm-
feedlot firm (Figure 8). Although perfect complementarity of inputs
is assumed, the combination of inputs needed to produce a certain output
under a given technology type offers a seemingly accurate representation

of the input and output combinations seen on Michigan farm-feedlots.9

 

7John M. Madden and James N. Dornbush, "Measurements Of Runoff
and Runoff Carried Waste from Commercial Lot," in Proceedings Inter-
national Symposium on Livestock Wastes, Ohio State University, 1971.

 

 

0C. F. Hensler, "Cattle Manure: I. Effect on CrOps and Soils.
II. Retention Properties of Cu, Mn, and An" (unpublished Ph.D. thesis,
University of Wisconsin, 1970).

9J. R. Black, personal communication, Agricultural Economics
Department, Michigan State University, April 1974.

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69

Ex Ante Price Expectation and Ex Post
Price RealizationTEquations

 

 

The second component, the price expectation and realization
equations, determines the expected returns for various size and type
of investments and the actual returns accruing to the investment type
and size level chosen.

Price expectation has long been realized as the relevant price
variable in decision making. During the last two decades attempts have
been made to formulate price expectation models that produce useable
empirical results. The distributed lag model presented by Cagon Offers
a great amount of simplicity and clarity in formulating empirical expec-

tations. This adaptive expectations model is of the form

*
Pt Pt-l

+ WM 44-1)

where Pt-l is the actual price in period t-l and P; is the expected
price in period t. B can vary between 0 and l.10

The criticism of this approach is that it lacks the ability to
include future oriented information. The Interstate Managerial Survey
points out that farmers use more than one simple model to develop
expectations of future prices.11 Decision making models and future
price expectation models tend to be quite sophisticated and employ

current information about future events in their formulation.

 

1°Marc Nerlove, The Dynamics of Supply: Estimation of Farmers'
Response to Price (Baltimore, Md.: John Hopkins Press, 1958.

 

11G. L. Johnson et al., Managerial Processes of Midwestern
Farmers (Ames, Iowa: The Iowa State University Press, 1961).

70

Lerohl explicitly recognized current information about future
events in the develOpment of a price expectation model for product
prices.‘2 The method of including current information consisted of

1. an expectation model using past prices to derive estimated
current prices; and
2. modification of these expectations based on current information

at the point in time when the estimates were made.

While Lerohl's method may be useful in "postdicting" past price
expectations, its use relies on knowledge of current information about
future events. In the simulation model constructed for this study,
feedlot adjustment is viewed through 1985. Of course, one is incapable
of including current information when simulating expectations in the
distant future. Thus, while recognizing that expectation models tend
to be complex and incorporate more than past price information, one is
forced to rely on rather simplistic models in order to accommodate price
expectations made in future periods.

The price expectation equation developed for future slaughter

prices is the following:
LPR = ao+a1FDPRt+a2MARGt+a3DSLPRt (l)

where: SLPR is the expected future price of slaughter cattle,
FDPRt is the slaughter and feeder price difference during the

time period t,

 

12Milburn L. Lerohl, "Expected Prices of U.S. Agricultural
Commodities, 1917-62" (unpublished Ph.D. thesis, Michigan State
University, 1965).

71

MARG is the slaughter and feeder price difference during the

t
time period,

DSLPRt is the change in slaughter price over the past six months.

Equation (1) is fitted substituting the average slaughter price
over the next twelve months for the value of SLPR. Fed cattle prices of
choice steers at Omaha, 900-l,000 lbs., is the data series employed.13

FDPR is the current months price of choice feeder steer cattle at

t
Kansas City, 400-500 lbs.'“ MARGt is the difference between these two
prices at each month while DSLPRt is the current slaughter price minus
the slaughter price lagged six months.

The equation fitted is the following with the t statistics of

the regression coefficients in parentheses below the equation.

SLPR = 7.0218 +0.7275 FDPRt-O.1547 MARGt-+0.03602 DSLPRt (1)*
R2==.92 (12.8672) (1.7591) (0.5248)

The price expectation equation for future feeder cattle prices
is simply an identity with feeder cattle prices being equal to the
expected future slaughter prices and the current margin (equation 2).

The feedlot operator is

FDPR = SLPR - (SLPR -FDPRt) (2)

t
assumed to expect no change in the margin between fat and feeder cattle

prices.

 

13United States Department of Agriculture, Livestock and Meat
Situation, 1959-73 issues.

1"Ibid.

72

Observing 1973 events, equation (l)* seems plausible. Rising
feeder cattle prices in fall of 1973 indicated rising expectations of
high future slaughter prices. As slaughter prices leveled off and
finally turned downward, feeder prices retreated quickly. One could
argue that feedlot operators' reflections on the changes in slaughter
prices and the expectation of lower future cattle prices led to a
reduction in the current price that operators were willing to pay for
feeder cattle. Thus, indicators of these future expectations are (l)
the price the producers are willing to pay for feeder, (2) the current
difference between buying and selling prices, and (3) the recent
direction of cattle movements.

Current feeder cattle and slaughter cattle differences shape
operators expectation of future feeder prices according to equation (2).
Feeder prices expectations are presumably determined by slaughter price
expectations in future time periods plus an adjustment for expected
margins. Equation (2) says that expected margins and future margins
are equal. As with equation (1) the equation is used as a result of
its plausibility rather than its proven representation of producers
price expectations.

Price expectation equations are also incorporated into the
simulation model for farm machinery, building and fencing material,
fertilizer, land, labor and other inputs. These input price expec-
tations assume the form
machinery
buildings (3)

fertilizer
all other inputs

Pi = ("*ai) Pt,i

#wN-J
II II II II

73

where P} is the expected future price of input i,
ai is a constant, and

Pt i is the actual price of input in time period t.

The coefficients a], a2, a3, a4 are set equal to .05 for the
period 1960-73. As the simulation model progresses beyond 1973, these
coefficients are allowed to change to reflect actual price movements

during the t-l period.

Ex Post Price Equgtions

 

The movement of actual prices of farm machinery, buildings and
fences, fertilizer, land, labor and other inputs is similar to gx_
gntg_movement of these prices. Changes in the prices of commodities
other than cattle during the 1960-73 period move according to equation

(4) where Pt+l,i is the actual price

P = (1+bi) Pt,i i=1,...,4 (4)

t+]’i

of commodity group i in time period t+l and bi is tha annual rate of
change of the price of commodity group i.15

As with ex_gntg_price movements, the 1960-73 commodity group
inflation rates used in the model reflect actual price movements.
However, after 1973 the annual price changes are allowed to assume a
constant path. This path reflects an assumption of a 4 percent rate

of inflation over the next few years.

 

15United States Department of Agriculture, "Index of Prices Paid
by Farmers," _gricultural Prices, 1960-73 issues.

 

74

Prices of feeder cattle and slaughter cattle are extremely
variable as witnessed by the often referred to beef cattle cycle.

A Cobweb model is often used as the explanation of this phenomena.
Due to faulty price expectations producers are in a cyclical pattern
of production with a resulting cyclical fluctuation in prices.

Harmonic regressions have been used to provide a relatively low
cost method of price prediction for markets displaying cyclic tendencies.
Talpaz was able to explain a relatively high proportion of the variation
in the hog cycle using a harmonic model.16 Franzmann and Walker used a
harmonic model to predict slaughter, wholesale and feeder calf market
prices. Their conclusion drawn from the statistical properties of the
slaughter cattle and feeder calf models is that these models have the
ability "to detect turning points within acceptable tolerances for
decision with rather long run planning horizons."17

The model used by Talpaz and Franzmann and Walker is a Fourier

series of the form

m
Yt = a0 + 2 (an cosnwot+bn Sin n Wot) + e
n+1
where m = the maximum number of terms in the series
Wo = 2H/T

 

16Hovav Talpaz, "Simulation, Decomposition and Control of a Multi-
Frequency Dynamic System: The United States Headquarters Production
Cycle" (unpublished Ph.D. thesis, Michigan State University, 1973).

17John R. Franzmann and Rodney L. Walker, "Trend Models of Feeder,
Slaughter, and Wholesale Beef Cattle Prices," American Journal of Agri-
cultural Economics, August 1972, p. 507.

 

75

T = period of cycle which is determined by trial and error,
t = time period of simulation, and
e = error term.

The model is of orthogonal design and is able to represent a periodic
waveform which demonstrates reasonable smoothness and continuity.18
The beef slaughter and feeder cattle models estimate by Franz-
mann and Walker are used as price predictors in the simulation model.
Equation (5) is the slaughter cattle model, and equation (6) is the
feeder model. The t-statistics for each regression coefficient are

in parentheses below the coefficients.

Slaughter Cattle

 

PS = 5.25636 + 0.00720t - 00.49010 sin 31: +1 .00516 cos 31'. + 0.36839Sin 30t

(50.42) (-14.43) (29.42) (10.88)
(5)
- 0.26806 cos 30t R2 =0.87
(-7.92)

 

18Thomas J. Manetsch and Gerald L. Park, System Analysis and
Simulation with Applications to Economic and Social Systems, Michigan
State University, 1973, pp. 3-13.

 

 

 

76

Feeder Cattle

 

f = 5.43936 + .008125 - 0.62209 sin 3t + 1.5536 cos 3t+ 0.44348 sin 30t

(40.87) (-l4.01) (26.05) (10.06)
(6)
+ 0.04107 cos 30t R2 =0.83
(0.93)

Data used to estimate the equations (5) and (6) is the monthly
weighted cost per cwt for all grades and weights of feeder steers
shipped from Kansas City from January 1921 to December 1969. The series
were divided by the Index of Prices Received by Farmers for All Farm
Products, 1910 - 14 = 100. The trend models' t is the time trend vari-
able with t==0 in January 1921. The t-statistics for each regression

coefficient are in parentheses below the coefficients.

Decision MakingProgress

 

The alternatives available for the individual firm in each time
period are to invest in new feedlot facilities at any capacity level, to
retain the current feedlot and raise animals at any level less than or
equal to the capacity of the feedlot, or to sell the enterprise and
invest in Off-feedlot investments.

The alternative to invest in new feedlot facilities at any
capacity level is constrained by several factors. The first constraint
is the total amount of capital available to the individual firm.

Availability of capital is determined by the firm's financial structure

77

(present asset and liability structure) and the amount of borrowed funds
available. This borrowing limit may be imposed by the firm itself or by
lenders. Thus, the second constraint is the borrowing limit and may be
expressed as the inverse of the maximum debt/equity ratio allowable.
Another constraint is the labor availability faced by the feedlot.
Michigan feedlots are generally family owned with the labor force
provided by the family and a small amount of hired labor.

The alternative to retain the present facility and to produce
at a level equal to or less than capacity faces another constraint.

This alternative faces the same capital, borrowing limit and labor force
constraints that face new investment alternatives; moreover, its size is
constrained by the limiting resources available at the time of the
facility's construction.

The amount of funds available to invest in off-feedlot invest-
ments is limited to the equity of the feedlot owner operator. An
opportunity cost concept is used since only a rate of return is
identified and not the type of investment available to the farm feedlot.
It is feasible that this investment could be other on-farm enterprises,
or it could be investment ventures off the farm.

Capital rationing or the problem of determining the profit
maximizing allocation of investment funds has been addressed by a
number of authors." The basic model used in a mathematical program-

ming solution is:

 

19Richard H. Bernhard, "Mathematical Programming Models for
Capital Budgeting--A Survey, Generalization and Critique," Journal of
Financial and Quantitative Analysis, June 1969.

78

11

max 2 b.x.
j=1 J J

n
Subject to 2 c
i=1

X C

tjj-<— t

where bj is the net present value of investment proposal j,

c is the net cash outlay required for proposal j in period t,

ti
and

Ct is the budget constraint in period t.2°

The problem at hand, selecting investments among farm-feedlot
alternatives, can be solved through modifying the above model. The
investment alternative array consists of the following twelve types
of investments:

A. New Farm-Feedlot Investment Alternatives
1. Drylot paved feedlot with tower silo storage. The feedlot
structure consists of a shelter with an open front allowing
access to a paved outside lot. There is 25 square feet of
sheltered area per animal and 35 square feet of paved lot
per animal.

2. Drylot paved feedlot with bunker silo storage. The feedlot

is designed as in alternative 1 with bunker silo storage for

corn silage.

 

2°J. C. Van Horne, Financial Management and Policy_(Englewood
Cliffs, N.J.: Prentice Hall, Inc., 1971).

 

6.

79

Drylot unpaved feedlot with tower silo storage. Shelter
area is 25 square feet per animal with lot area of 150
square feet per animal.

Drylot unpaved feedlot (as in alternative 3) with bunker
silo storage.

Open lot with tower silo storage. No shelter is provided
for the animals. Facility consists of a dirt lot with
200 square feet per animal.

Open lot with bunker silo storage.

Each of the above six facility types would require runoff abatement

control to contain runoff from exposed surfaces.

7.

Cold confinement with solid floor construction and tower
silo storage. Feeders are completely confined in a
sheltered structure with the floor being solid concrete.
Each animal is allotted 30 square feet per animal. Manure
is scraped from the structure regularly and either stored
to spread later or spread immediately.

Cold confinement with solid floor construction and bunker
silo storage.

Cold confinement with slotted floor construction and tower
silo storage. The structure confines the animals to a 30
square foot per head sheltered area, and the floor is
slotted with a pit below the floor providing storage for
waste. The wastes are distributed to fields several times
per year by pumping the waste into wagons which spread the

waste on fields.

80

10. Cold confinement with slotted floors and bunker silo
storage. Feedlot technologies 7-10 need no runoff
containment devices since none of the surface of these
confinement structures are exposed to rainfall.

Each of the above 10 feedlot types also is equipped with moist corn
storage. The feed ration employed in each housing type is "1% concen-
trates ration" typical of Michigan feedlots. This ration consists of
feeding a quantity of concentrates equal to 1 percent of the current
body weight plus a free feeding of silage. The ration consists of corn,
silage and supplement with the corn stored in moist corn storage
facilities.

The size of the bunker or tower silo and the size of the moist
corn storage is a function of the type of feedlot technology employed.
Turnover rates (animals fed per year/capacity and feed requirements per
day) vary among the alternative housing structures.21 A detailed expla-
nation of the silo size selection and the equipment complement selection
is found in Hughes.22

The investment array also includes:

11. Retain present feedlot facilities. These facilities would

be of one of the 10 technology types described above which

was constructed in a previous year.

 

21Ration data from J. R. Black and H. D. Ritchie, "Average Daily
Gain and Daily Dry Matter Intake of Various Kinds of Cattle Fed Three
Different Rations Under Several Environmental Situations," Staff Paper
1973-l, Agricultural Economics Department, Michigan State University,
9 .

22H. A. Hughes, op. cit.

81

12. Off-feedlot investment.

In addition the firm may borrow money to help supply the needed

capital in each of these investments. It is assumed that the cost of

outside funds is equal to the off-feedlot opportunity costs.

The mathematical programming formulation of the annual invest-

ment de-ision is the following:

10
Max nil (NPVn)-+NPVc-NPVB
Subject to

10

nit] Int +1ct - Bt _<_Net wortht
lO

2 L +l. < Labor

"=1 n C—

(Blim)Bt §_Net Wortht

where new feedlot investment alternatives are n==1,.

current feedlot is c; and the borrowing activity is B.

(7)

(8)

(9)

(10)

..,10; retention of

In equation (7) the NPVn (net present value of a new investment)

would have a value similar to that shown in Chapter 3 equation (10) or

T At SVT
NPV= z t+——-IO.
n t=0 (1+R) (1+R)

 

82

Also in equation (7) the NPVc (net present value of the current
investment) would have a value similar to that found in Chapter 3,
equation (13) or

. T
t-i A U I -+P
NPVC = Z t + T 1 and,T

t=0 (1+R) (1+R)]:1

 

 

1‘
' U Ii+Pland,i ()1)

(Note: i is the current age of the asset.)

Returns and investment costs in new facilities are found by
using the farm-feedlot production component. Setting capacity at 400
head, the farm-feedlot component is used to identify operating and
investment costs for each of the 10 technology types. Annual fund flows
and investment costs are found for each time period by adjusting flow
and stock levels by the appropriate ex ggtg_price expectation indices.

Also in equation (7) is the term NPVB which stands for the cost
attributable to borrowed funds. Assuming that the rate of interest on
the unpaid balance of the loan is the same as the opportunity cost of
funds, the following would hold NPVB==O.

The constraints on the annual investment decision specify that
the sum of liabilities and owner's equity does not exceed the total
feedlot investment in any one year. Labor is constrained to some
reasonable level for Michigan feedlots (Labor 5_3 fulltime workers).
The term (Blim) in equation (10) is established by the optimization
routine briefly referred to at the beginning of this chapter and serves
as a constraint on the amount of loans outstanding.

An additional constraint is placed on the decision making

process to insure that the feedlot investments are mutually exclusive

83

activities. The constraint is that the annual decision making
mechanism only considers capacity levels less than equal to the
capacity level currently employed. Once it is discovered that a new
feedlot technology is more profitable at the present size level than
the current technology, then this constraint is removed during the
next time horizon. The result of this additional constraint is two
fold. First, the investments are forced to be mutually exclusive
with only one alternative being selected in any one year. Second,
any expansion program takes place over a two year horizon. During
the first year the maximum capacity level attained is the capacity
level that existed prior to the decision to expand. During the second
year the feedlot is allowed to expand to a capacity level constrained
only by the financial and labor position of the firm.

The four variables R, U, Blim, and Net Worth, seen in equations
(8), (10), and (11) are the four unknown variables that are found
through the optimization procedure previously discussed. The oppor-
tunity costs of capital (R), the annual user cost (U), the borrowing
limit of firms (Blim) and the simulated firms' initial equity positions
are unknown empirically but are identified through the optimization
component.

In order to use the above decision making model the user must
assume constant returns to scale in the ex_ggte_production function as
all inputs are expanded in fixed proportions. (Constant returns to
scale are not a property of the gx_pg§t_production function.) In short

the various types of investment alternatives are assumed to have

84

constant returns to fixed factors of production, and all variable
inputs are assumed to be combined in fixed proportions.

One basic reason for this rather heroic assumption of constant
returns to scale in the gx_gntg_function can be offered. Constant
returns and perfect complements may be reasonably accurate assessments
of the economics of feedlots over the relevant size level. Michigan
feedlot size has traditionally been confined to a rather narrow range
of size levels. In Michigan only 19 feedlots out of a total 1,696
feedlots have greater than 1,000 head capacity.23 Since model described
by Hughesz“ shows nearly constant returns to scale for Michigan feedlots
in the 350-l,000 head range, the linearity assumption used in the
decision making model seems realistic. Nearly perfect complementarity
among the individual types of feedlot technology also seems to conform
to reality. While the input mix of feedlots varies greatly, organizing
feedlots around 10 technology types accounts for much of the variability
in input mix seen on Michigan farms.

The results of the decision making model determines the number
of animals to be fed and the feedlot technology to be employed. Estab-
lishing levels for these variables allows the farm-feedlot production
component to determine the actual inputs needed to produce the

established level of output (see Figure 2).

 

23U.S., Department of Commerce, Bureau of the Census, Census of
Agriculture,,l969.

2"Hughes, op. cit.

85

Accounting Process

 

The functions of the accounting process are to compute and have
available for recall the financial position of the individual firms
during the simulated time horizon. The accounting process used a market
value concept in the calculation of a firm's financial statement. Thus,
the firm's current equity is equal to the salvage value of owned assets
less the amount of debt outstanding.

The calculation of the firm's equity is the following:
EQt+l = EQt+Yt'("U) ItTGPI and,t

where EQt is the equity in year t,
Yt is the net fund flow,
(l-u) is the user cost coefficient,
It is the replacement value of building and equipment
in year t, and

cxP is the appreciation in land value over the period t.

1 and,t

The net fund flow Yt is computed annually by the accrued income
received by the firm for cattle raised and subtracting the costs of
the flow variables associated with raising the animals. Flow variables
include fertilizer, herbicides, feed supplement, labor, fuel, insurance,
property taxes, equipment and building repair costs, the interest pay-
ment made on debt and income taxes. Labor is priced at $5.00 per hour
for the 1973 time period and includes all labor (family and nonfamily)

used in the farm feedlot operation. The price of labor is adjusted by

86

the appropriate gx_pg§t_price index to arrive at its price for periods
other than 1973. Other flow variable prices are those used by Hughes25
for 1973 with prices in other years found by adjusting the 1973 prices
by the appropriate price-indices.26 Calculation of the annual income
tax for each firm assumes that all buildings and equipment are
depreciated by the straight line method over 15 years. A marginal

tax rate of 30 percent is used in computing the annual income tax.

Optimization Procedure

 

The Optimization procedure is used to find values of unknown
parameters which result in the model's output performing consistently
with the real world. While the simulation model may produce a number
of measures of the system's performance, the output used to compare the
model's performance to the real world phenomena is the sum of the feed-
lots' capacities. Under the assumptions that the simulated feedlots
are representative of Michigan feedlots and that the performance of each
is independent of the performance of the group as a whole, changes in
Michigan feedlots' production can be witnessed through the changes in
the capacities of simulated feedlots.

Data is readily available to indicate the output of the Michigan

feedlots. Quarterly cattle on feed data is available to identify the

 

25Ibid.

26U.S., Department of Agriculture, "Index of Prices Paid by
Farmers," Agricultural Prices, 1960-73.

 

87

number of cattle being fed at regular time intervals.‘27 This data
(Michigan Cattle and Calves on Feed, January 1) is used to represent
the capacity changes of Michigan feedlots. The data reports the
animals being fattened for slaughter on grain or other concentrates
as of January 1 each year. The number of cattle fed on this date is
consistently higher than any other period throughout.

By systematically searching the values of unknown parameters,
a set of values are found which make changes in the stimulated firms'
total capacity correspond to changes in the historic cattle on feed
data. The time period selected for this "fine tuning" exercise is
the 1960-71 time period. The measure of the ability of the model to

explain real world changes is

1971
2 (CATTLE -——ECATTL ) (COF -'C'(TF‘)
t=1961 t t

 

r:

 

1971 I 1971 .___
z (CATTLEt-CATTLE)2 z (COFt-COF)2
t=1961 t=l961

where CATTLEt is the sum of the simulated feedlots' capacities
in year t,
COFt is the cattle on feed, January 1 in year t,
CATTEE is the mean value for the simulated capacities, and
COP is the mean value for actual cattle on feed during the

1961-71 time period.

 

27U.S., Department of Agriculture, Livestock and Meat Situation,
1960-73.

88

The optimization procedure assumes that r is to be maximized
where r is some function of the four unknown variables-~one variable
determining user cost, another determining the net worth distribution
of farm-feedlot operators, the third being the opportunity cost of off-
feedlot investment and the fourth being a coefficient determining the
maximum debt position of the firm. The first step of the optimization
procedure is based on the assumption that r is a strictly concave func-
tion of the four unknowns. This concave function is then systematically
searched until the maximum value of r is found. The second step is a
check to assure that the systematic search routine has found a global
maximum rather than a local maximum. This step is accomplished by
setting up a matrix of several possible combinations of the four unknown
variables. A check is made of the resulting r values from several com-
binations of unknown variables. If this "coarse grid" approach enables
the model to achieve a higher degree of correlation between simulated
results and actual data, unknown variables are selected by this latter
technique.28

Given the assumption of a strictly concave function, several
optimization techniques are available.29 The "direct search method"
(sometimes this is called the "simplex" method, but it is not to be

confused with the linear programming algorithm) is used to locate the

 

28G. L. Newhauser, Dynamic Programming(New York: John Wiley
and Sons, Inc., 1977).

 

29V. W. Eveleigh, Adaptive Control and Optimization Techniques
(New York: McGraw Hill, 1970).

89
optimum.3° The approach is to start out with a set of points defined

by the coordinates in Table 3. The number of points would equal n-+1

where n is the number of unknown variables.

Table 3. Coordinates for the Initial "Simplex" Vertices

 

 

n Coordinates of Each Point

 

Point j Y Y

 

 

l,i 2.j 3.j ' ' ' 0.3
.I Y] ,0 Y2,o Y3,0 o o o Yn,o
2 Y], +P Y2’0+q Y3’o+q . . . Yn,o+q
3 Y1’0+q Y2’0+p Y3,o+q . . . Yn,o+q
n+1 Y1’0+q Y2’0+q Y3,o+q . . . Yn,o+p
where p = —L (Jn+.l + n-l).
n/ 2
q = —a— (/n+l - l),
n /2
a = constant, and
n = number of unknown parameters.

 

“'G. S. Beveridge and R. S. Schecter, Optimization Theory and
Practice (New York: McGraw Hill, 1970).

90

Once the above n-+l points are identified, the criteria value
is calculated for each vertex with the simulation model being run n-+l
times. The following three rules would be followed until the optimum
(or criteria value that is satisfactory) is reached:
1. The lowest criteria value is rejected and a new vertex of points
is calculated where ’
n+1

Z

2
v. =[—(
1,11 n31

Yigj-Y1,R)]-Y1,R j=1,...,n (12)

The new set of vertices is composed of the nonrejected old

vertices and YiN

where Yi N = ith component of the New index,
Yi j = ith component of the jth vertex,
Yi R = ith component of the rejected vertex.

2. The procedure never returns to a vertex that it has just left.
To prevent the procedure from hanging up on a ridge, the second
worse vertex is rejected in this case.

3. If the best criteria value remains unchanged for several

iterations, the distance between vertices is reduced.31

In order to clarify the procedure a simple example is demon-
strated. Assume the function Z = Y2-+X2-lOY-8X is to be minimized.
By simple calculus, one can find the minimum value of Z to be -41 where

y==5 and X =4. The simplex procedure would find the optimum by first

 

3'Ibid.

91

establishing the n-+1 initial vertices, three vertices would be found
in the example. Referring to Table 3 one can see that each of three
initial points or vertices would be composed of two coordinates. If
the initial point is assumed to be where x =3.5 and y =3.5, Table 3

can be reconstructed to obtain the initial set of points.

Initial Coordinates for Example

 

a==.25

Point j .x y. (assumed value)
1 3.5 3.5 [>=.241
3.565 3.741 q= .065

mm

3.741 3.565

The criteria value is calculated for each of these three points
and the least desirable of the three values is rejected according to the
first rule. Point 1 yields the worse criteria value on the three points
and it is rejected with a new point being computed. Using equation (12),

x and y values for point 4 are calculated.

£0.11: a x .2.
l (rejected) 3.5 3.5 -38.5
2 3.5+p=3.565 3.5+q=3.741 -39.227
3 3.5+q=3.741 3.5+p=3.565 -38.873
4 3.806 3.806 -38.537

The procedure continues with the worse criteria value of
points 2, 3, and 4 being the criteria value at point 2. Again using

equation (12), x and y values for point 5 are calculated.

92

 

Point 5 y 5

2 (rejected) 3.565 3.741 -39.227
3 3.741 3.565 -38.873
4 3.806 3.806 -38.873
5 3.983 3.629 -39.828

Figure 9 illustrates the values of the dependent and independent
variables as the procedure is continued. After point 14 is found the
procedure is in the vicinity of the optimum. By invoking rule 1 and
equation (12), the points begin to cycle around the point with the
optimum criteria value. The distance between the vertices is reduced
(Rule 3) and the procedure of rejecting the lowest criteria value and
calculating the coordinates of a new point continues. (Rule 2 is not

needed in this example due to the shape of the function.)

Distribution of Feedlot Owners' Net Worth

 

The first of the four variables found through optimization
is a parameter of a family of density functions. By varying this one
parameter, the density function assumes a variety of distributions from
the exponential distribution to the normal distribution. After assuming
a mean for feedlot net worth, the parameter K is set and the new worth

distribution is calculated by equation (13).32

K K-1 -abK
f(b) _._ L319 “(3521)!(5 ) (13)

 

32Manetsch and Park, op. cit.

 

93

Point 14

0 Z = -40.98
Point 13
‘ Z = -40.99

Point 12

Point 11 . Z='40'94

' Z = -40.88

Point 10
Point 9 ‘ =-40.8
o Z=040.7

Point 8
Point 7 ' Z='40'5

' Z=-40.3

Point 6

. .-
P911112 5 Z--40.1

Z=-39.8

Point 4

C -
Point 2 2'. '39°5

' Z =-39.2

Point 3

. —
Point 1 Z--38'9

‘ Z=-38.5

l 1

3.5 3.7 3.9 4.1 43 4.5 4.7

Figure 9. Illustration of the "Simplex" Procedure.

94

where f(b) = probability of b net worth,
a = l/mean net worth,
K = parameter to be determined, and
b = net worth.

Figure 10 illustrates the set of net worth distributions
obtained by changing the value of K.

Initial net worth values are selected for each simulated firm
by a random selection from the appropriate net worth distribution. The
mean net worth for the feedlot firms being simulated at the initial time
period (1960) is assumed to be $80,000. Thus, the parameter K is chosen
by the optimization process, and this parameter alone determines the net
worth distribution of Michigan firms in the initial period.

The variable Blim is the second variable found through optimi-
zation, and serves as the constaint on borrowing as seen in equation
(10) of this chapter. This variable is assumed to remain constant over
all firms being simulated throughout the time horizon. The third vari-
able U is a determinant of salvage values of machinery and buildings
and is identified in equation (10) in this chapter. Finally, the vari-
able R is the off-feedlot opportunity cost and is identified in
equations (10) and (11) of this chapter.

The Simulation Approach

 

The simulation model used in this study is a computerized
representation of the activities of the firm through time. The modeling

effort has incorporated a wide range of techniques and data sources.

95

.mcop
.uuczd xuwmcoo mo xpwsom mcmpgm Och

F166

.2 6.52.:

 

 

 

3:

96

Estimates of input and output prices received by the feedlot operator
are based on regression equations which approximate future prices by
extending the trends and cycles of historic prices. The decision making
process is based on a mathematical programming model which assumes the
firm profit maximizes. The simulation of the production process is
based on engineering concepts of basing resource requirements on the
energy flows necessary to accomplish a given activity. Data sources
are time series in government documents, opinions of equipment dealers,
engineers, extension personnel and researchers, and past research
results from universities and government agencies.

It is felt that this approach enables the researcher to incor-
porate a wide range of information and expertise. The simulation model
allows the judgment of engineers, system scientists, agronomists,
animal scientists, and economists to be utilized in an effort to
approximate the Michigan feedlot system.

Problems of validating the accuracy of the simulation remain
as one of the serious shortcomings of the approach. Any computerized
model is only as good as its internal logic and consistency with real
world occurrences. The tests of internal and external consistency and
workability of the model should be constantly applied in an effort to

validate model results.

CHAPTER V

RESULTS

In an attempt to maintain clarity, the empirical results of the
simulation are presented in three sections. The sections are (l) tradi-
tional static analysis, (2) a dynamic analysis of the imposition of
selected water pollution control rules, and (3) a sensitivity analysis
of the model for parameter values selected through the optimizing
routine.

In the static analysis cost and return data are presented for
feedlots of various sizes with similar feedlot technology types. These
cost and return data are examined before and after the imposition of
runoff control requirements.

In the dynamic analysis performance of Michigan feedlots is
compared under a selected set of water pollution controls which are or
could be imposed on beef feedlot firms. Performance is measured by the
total capacity of the feedlots simulated, the asset structure of the
firms, the firm's rate of return, and equity positions.

A sensitivity analysis is conducted on some of the critical
parameters in the model. Those variables which depend heavily on un-
confirmable assumptions and those which were derived through the
optimizing routine are the focus of the analysis. Changes in simulated
feedlots' performance are observed under a variety of values for these

parameters.

97

98

Static Cost Analysis

 

Traditional static analysis, as presented in several of the
studies reviewed in Chapter II, compares costs over a variety of feedlot
sizes. In comparing the cost before and after the imposition of runoff
control, inferences are made concerning the effects of these measures.
As previously discussed, these costs are only a snapshot of the firm at
one moment in time. They do not answer many of the relevant questions
concerning the effect of these policies on future feedlot performance.

Viewing the firm through snapshots of its cost structure or
static cost curves limits the analyst's inferences; however, the impor-
tance of the firms' cost structure should not be minimized. When view-
ing feedlot firms' behavior over a multi-period horizon using the
methodology employed in this study, the firms' cost structure is rele-
vant in the decision making process in the determination of the quantity
of inputs to employ and the type of feedlot technology to use. It is
also relevant in determining the profitability of the chosen enterprise.

The simulation model constructed for the analysis is capable of
calculating nearly an infinite number of cost estimates for various
feedlots. Internal logic employed in the model and consistency with the
real world limit the most reliable simulated cost estimates to those
associated with feedlot capacities of greater than 50 and less than
1,000 head. The model is equipped to compute costs for various com-
binations of (1) five housing technologies (drylot unpaved, drylot paved,

open lot, cold confinement with slotted floors, and cold confinement with

99

solid floors); (2) two silage storage systems (bunker and tower);

(3) four runoff abatement technologies ("do nothing," lO-year, 24-hour
rainfall event storage, 25-year, 24-hour rainfall event storage, 6-month
rainfall storage); and (4) minimum time intervals between waste spread-
ings. In addition, the model is equipped to present the cost estimates
for any year during the 1960-85 interval using the price estimates of
that year.

Needless to say, the presentation of static cost estimates paint
only a small portion of the total picture. Analyzing the changes in
environmental policies involves assumptions concerning the behavior of
firms under changing cost structures. While changing cost structures
are important in estimating the impacts of environmental policies, their
primary importance lies in their effect on the firms' behavior.

Costs associated with three feedlot technologies are presented
as an example of the kind of cost calculations which are made in the
simulation model. The three technologies include drylot unpaved housing
with no runoff retention facilities, drylot unpaved housing with reten-
tion facilities to retain a 25-year, 24-hour rainfall event, and cold
confinement housing with slotted floors (no runoff control required).
The input prices used for the cost estimates are the gx_ggtg_prices for
1974. Costs for nine capacity levels (100, 200, 300, ..., and 900 head)
are calculated for each of the three feedlot technologies and detailed
costs are presented for the 100, 300, 500, 700, and 900 head capacity
lots.

100

The assumptions made in the construction of these static cost
estimates are the following:

1. All cattle are fed a "1 percent concentrates ration."l
Each steer or heifer is assumed to consume an average of 6.4 pounds
of corn per day and 31.6 pounds of silage per day. The number of days
the cattle are on feed varies with the type of housing. The drylot,
unpaved facility allows the cattle to go from 450 pounds to 1,050 pounds
in 300 days. The confined facility allows the cattle to gain the 600
pounds in 293 days.

2. The number of cattle in the feedlot is maintained at
capacity throughout the year.

3. The cost of using durable assets is determined by a fixed
percentage of the replacement cost of the asset. Cattle housing, silos,
moist corn storage and runoff retention facility costs are 6.7 percent
of replacement costs. User costs of machinery and equipment are 10
percent of replacement costs.

4. All non-durable input costs are financed with funds having
an 8 percent opportunity cost. It is assumed that the purchase price
of feeder calves is financed over the entire production cycle while the
other nondurable inputs are financed over an average of one-half of the
production cycle. Finance charges are paid at the end of the production

cycle.

 

1J. Roy Black and Harlan 0. Ritchie, "Average Daily Gain and
Daily Dry Matter Intake of Various Kinds of Cattle Fed Three Different
Rations Under Several Environmental Situations,“ Staff Paper-l973-l,
Agricultural Economics Department, Michigan State University, January
1973.

101

5. Machinery, buildings, and land have an opportunity cost
equal to 8 percent of their market value. All durable assets are
assumed to be recently purchased.

6. The opportunity costs of durable assets would decline as
the assets remain in place. Since the salvage value of durable assets
are assumed to decline exponentially, the opportunity cost of these
assets would decline exponentially. The static cost estimates are for
assets recently purchased; however, these costs would decline slightly

as the durable assets became older.

Tables 4-8 demonstrate the annual costs of each of five capacity
levels under the three feedlot technologies. Also shown is the total
cost per pound gained.

Figure 11 indicates the total cost per pound of beef sold for
various levels. Three points are plotted at each capacity level; one
point indicates the cost per pound sold under drylot, unpaved housing
with no runoff control; another indicates the cost per pound sold under
drylot, unpaved housing with storage to control the runoff of a 25-year,
24-hour storm. The third point is the cost per pound under the cold
confinement, slotted floor housing alternative. This cost would rep-
resent the cost per pound before and after the imposition of runoff
control since the confined housing does not have exposed feedlot

surfaces.

Table 4.

102

Technologies, 100 Head Capacity

Annual Costs and Cost Per Pound of Beef Sold for Three Feedlot

 

 

Drylot, Unpaved

 

Drylot, Unpaved Runoff Abatement Cold
No Runoff for 25-Year, Confinement
Abatement 24-Hour Storm Solid Floor
(2) (i) (L) (i) (5;) (5;)
Feeder Calves 25,732 25,732 26,347
Nondurable Inputs:
Fertilizer and
Herbicides 2,425 2,425 2,425
Supplement 1,979 1,979 1,979
Seed 684 684 684
Fuel 186 186 146
Labor 9,271 9,271 9,329
Repair 1,971 1,952 2,068
Insurance 93 99 102
Property Tax 1,155 1,187 1,182
Interest on Short
Term Loan 3,750 3,752 3,851
Runoff Abatement 0 335 0
Total 21,512 21,890 21,768
Durable Inputs:
Silo 1,122 1,122 1,122
Moist Corn Storage 495 495 495
Lot and Buildings 525 525 701
Transport 1,280 1,251 1,436
Runoff Abatement 0 212 0
CrOp Machinery 2,408 2,408 2,408
Total 5,829 6,012 6,162
Opportunity Costs of
Land and Durables 7,039 7,054 7,066
Total Annual Costs 60,114 60,688 61,343
Cost Per Pound Sold 0.470 0.475 0.469

 

103

Annual Costs and Costs Per Pound of Beef Sold for Three Feedlot
Technologies, 300 Head Capacity

Table 5.

 

 

Drylot, Unpaved

 

Drylot, Unpaved Runoff Abatement Cold
No Runoff for 25-Year Confinement
Abatement 24-Hour Storm Solid Floor
(.2) (i) (i) (i) (L) (i)
Feeder Calves 77,197 77,197 79,042
Nondurable Inputs:
Fertilizer and
Herbicides 7,275 7,275 7,275
Supplement 5,938 5,938 5,938
Seed 2,053 2,053 2,053
Fuel 574 574 462
Labor 9,980 9,980 10,201
Repair 2,614 2,614 2,730
Insurance 182 191 202
Property Tax 3,239 3,295 3,331
Interest on Short
Term Loan 10,456 10,458 10,691
Runoff Abatement 0 354 0
Total 42,320 42,731 42,883
Durable Inputs:
Silo 2,179 2,179 2,179
Moist Corn Storage 1,225 1,225 1,225
Lot and Buildings 1,567 1,567 2,100
Transport 1,299 1,299 1,485
Runoff Abatement O 308 0
Total 9,733 10,141 10,452
Opportunity Costs of
Land and Durables 20,580 20,613 20,812
Total Annual Costs 149,831 150,683 153,014
Cost Per Pound Sold 0.391 0.393 0.390

 

 

 

104

Table 6. Annual Costs and Costs Per Pound of Beef Sold for Three Feedlot

Technologies, 500 Head Capacity

 

 

Drylot, Unpaved

 

Drylot, Unpaved Runoff Abatement Cold
No Runoff for 25-Year, Confinement
Abatement 24-Hour Storm Solid Floor
(3) ($) (is) ($) ($) ($)
Feeder Calves 128,662 128,662 131,736
Nondurable Inputs:
Fertilizer and
Herbicides 12,126 12,126 12,126
Supplement 9,896 9,896 9,896
Seed 3,421 3,421 3,421
Fuel 1,005 1,005 829
Labor 10,855 10,855 11,239
Repair 3,079 3,079 3,194
Insurance 277 289 309
Property Tax 5,370 5,431 5,512
Interest on Short
Term Loan 17,144 17,147 17,533
Runoff Abatement 0 452 0
Total 63,173 63,701 64,059
Durable Inputs:
Silo 3,528 3,528 3,528
Moist Corn Storage 1,895 1,895 1,895
Lot and Buildings 2,556 2,556 3,469
Transport 1,363 1,363 1,549
Runoff Abatement 0 407 0
Crop Machinery 4,369 4,369 4,369
Total 13,713 14,119 14,813
Opportunity Costs of
Land and Durables 34,128 34,160 34,215
Total Annual Cost 239,676 240,643 244,821
Cost Per Pound Sold 0.375 0.377 0.374

 

 

Table 7.

105

Technologies, 700 Head Capacity

Annual Costs and Cost Per Pound of Beef Sold for Three Feedlot

 

 

Drylot, Unpaved

 

 

Drylot, Unpaved Runoff Abatement Cold
No Runoff for 25-Year, Confinement
Abatement 24-Hour Stonm Solid Floor
($) ($) ($) ($) ($) ($)
Feeder Calves 180,127 180,127 184,431
Nondurable Inputs:
Fertilizer and
Herbicides 16,976 16,976 16,976
Supplement 13,855 13,855 13,855
Seed 4,790 4,790 4,790
Fuel 1,450 1,450 1,216
Labor 11,860 11,860 12,407
Repair 3,592 3,592 3,708
Insurance 374 389 418
Property Tax 7,501 7,576 7,702
Interest on Short
Term Loan 23,840 23,843 24,383
Runoff Abatement O 471 0
Total 84,238 84,802 85,454
Durable Inputs:
Silo 4,807 4,807 4,807
Moist Corn Silage 2,677 2,677 2,677
Lot and Buildings 3,566 3,566 4,859
Transport 1,439 1,439 1,625
Runoff Abatement O 500 0
Crop Machinery 5,115 5,115 5,115
Total 17,604 18,104 19,083
Opportunity Costs of
Land and Durables 47,668 47,708 47,785
Total Annual Cost 329,637 330,742 336,160
Cost Per Pound Sold 0.369 0.371 0.367

 

 

 

Table 8.

106

Technologies, 900 Head Capacity

Annual Costs and Cost Per Pound of Beef Sold for Three Feedlot

 

 

Drylot, Unpaved

 

 

Drylot, Unpaved Runoff Abatement Cold
No Runoff for 25-Year, Confinement
Abatement 24-Hour Storm Solid Floor
($) ($) (i) (3) ($) ($)
Feeder Calves 231,592 231,592 237,125
Nondurable Inputs:
Fertilizer and
Herbicides 21,826 21,826 21,826
Supplement 17,813 17,813 17,813
Seed 6,158 6,158 6,158
Fuel 1,956 1,956 1,670
Labor 12,972 12,972 13,682
Repair 4,233 4,233 7,219
Insurance 476 493 627
Property Tax 9,667 9,755 9,923
Interest on Short
Term Loan 30,547 30,553 31,365
Runoff Abatement 0 490 0
Total 105,650 106,250 110,283
Durable Inputs:
Silo 6,179 6,179 6,179
Moist Corn Storage 3,487 3,487 3,487
Lot and Buildings 4,608 4,608 6,257
Transport 1,526 1,526 6,311
Runoff Abatement 0 592 0
CrOp Machinery 6,335 6,335 6,335
Total 22,135 22,727 28,569
Opportunity Costs of
Land and Durables 61,342 61,390 61,857
Total Annual Cost 420,720 421,960 437,836
Cost Per Pound Sold 0.366 0.367 0.372

 

107

Housing Types:

 

Drylot, Unpaved, Runoff Abatement
for 25-Year, 24-Hour Storm

-—-—- Cold Confinement, Slotted Floor

¢/1b. ----- Drylot, Unpaved, No Runoff Control
48 -
46 L
44 -

42 -

 

 

36

T

 

 

100 200 300 400 500 600 700. 800 900
(Capacity)

Figure 11. Cost Per Pound of Beef Sold, Three Housing Types of Selected
Capacities, 1974 Prices. (These curves are ngt_long run
average cost curves for any of the three technologies. Each
curve is a connection of the points where the average long
run variable cost for each capacity level is at a minimum.)

108

The data in Tables 4—8 and Figure 11 indicate that the
construction of runoff control facilities to retain a 25-year, 24-hour
rainfall event has a minor impact on total costs for the drylot, unpaved
lot. For the small feedlot of 100 head capacity, costs increase approx-
imately one-half cent per pound of beef produced. Additional cost per
head sold for the 100 capacity drylot totals $4.72 with the addition of
the 25-year, 24-hour storm runoff control. Additional costs for the 200
head capacity lot are $3.33 per head; additional costs for the 300, 400,
500, 600, 700, 800, and 900 head capacity drylot, unpaved feedlots are
$2.33, $1.89, $1.59, $1.39, $1.29, $1.20, and $1.13, respectively.

The drylot, unpaved technology used in the above example assumes
an exposed surface area in the feedlot of 150 square feet per animal.
Another feedlot technology typical of Michigan farm-feedlots is the
drylot, paved facility. Under this housing, less feedlot surface per
animal is exposed than with the drylot, unpaved technology resulting in
less additional costs involved in runoff abatement. While a detailed
analysis is not presented, annual runoff abatement costs (1974 prices
for the drylot, paved lot) are about one-half the costs associated with
the drylot, unpaved lot.

Other housing types used in the simulation model include open
lot construction and confined solid floor housing. As with the confined
slotted floor housing used in the above example, confined solid floor
housing costs would not change as a result of runoff control policy.
Open lot runoff abatement costs would be slightly greater than the dry-

lot, unpaved lot due to the larger exposed surface area. The simulation

109

model assumes an exposed lot surface of 200 square feet per animal
resulting in abatement costs being approximately one-fourth greater
than the drylot, unpaved construction.

The previous example viewed a static cost analysis of the firms
under the "best available technology economically achievable" under EPA
guidelines for point sources. An acceptable method or practice for
animal waste application might be that of limiting the time in which
wastes may be returned to the fields. Such a policy might include a
requirement that no spreading of solid wastes occur during periods when
the ground is frozen. The simulation model assumes that the total days
available to spread the waste is constant; therefore, an increase in the
amount of waste to spread necessitates additional waste Spreaders. Feed-
lot capacities of less than 500 head require an additional spreader
($1,240 capital outlay per spreader) and the feedlots of greater than
500 head capacity require two additional Spreaders when the no winter
spreading requirement is added.

While the additional investment requirements is rather minor,
the abolishment of winter spreading increases the labor requirements in
the spring. The model assumes that this labor can be acquired at a con-
stant hourly rate throughout the year. Total annual labor hour require-
ments and labor costs are affected very little by the abolishment of
winter spreading; however, the model's constant hourly wage underesti-
mates the value of spring labor. The demands on spring labor from
cropping activities make the marginal value product of spring labor

higher than during other seasons of the year.2 Thus, it should be

 

2Pherson, op. cit.

110

recognized that the model's analysis of the abolishment of winter

spreading may underestimate the costs involved.

Multiperiod Analysis

 

Results of Optimization

 

The "simplex" procedure described in Chapter IV is used to find
the best fit between actual feedlot performance and simulated perfor-
mance during the 1960-71 period. Twenty firms are picked from a net
worth distribution which has a mean of $80,000 and a shape determined
by the unknown variable K. Each firm is simulated over the 1960-71 time
horizon using one value for each of the four unknown variables--the
borrowing limit (Blim), the opportunity cost of funds (R), user cost
determinant (U), the net worth distribution determinant (K). The total
feedlot capacity of the simulated firms is compared with the cattle on
feed data for the 1960-71 time period in order to test the ability of
the model to duplicate actual performance. Then new values are selected
for the four unknown variables and the results are again tested for
their ability to duplicate past performance. The simplex procedure
continues until the "best" fit is obtained, systematically selecting
new values for the unknown variables, simulating the 20 firms perfor-
mance using the new values, and comparing the performance with corre-
sponding real world performance levels.

Using the "simplex" method (assuming a strictly concave function
for r==f (Blim, R, U, K)), the model's performance best duplicates

actual 1960-71 feedlot performance using the following values for the

111

unknown variables: the opportunity cost of funds (R) = .0697; the
borrowing limit (Blim) = 1.51; the user cost determinant (U) = .9022;
the net worth distribution determinant (K) = 2. The resulting r2 under
this combination of values is 0.784.

The coarse grid approach is then used to check the validity of
the concavity assumption. The four unknowns make the coarse grid
approach a costly procedure; therefore, the values that the four
unknowns could assume are constrained to a rather narrow range. ,A
prjgrj_knowledge of the structure of midwestern farms indicates that
the net worth distribution is skewed to right; therefore K is limited
to values less than 3. The "simplex" Optimizing procedure consistently
results in simulated firms expanding less rapidly than cattle on feed
data for the 1960-71 period.' As a result, the opportunity cost of funds
(R), the borrowing limit (Blim), the user cost determinant (U), and the
determinant of the shape of the net worth distribution are constrained
to values which result in the simulated firms being more expansion
oriented. The values assumed for each parameter are: K= 2, 3;
Blim=1.0, 1.25.1.5; R= 0.04, 0.06, 0.08; U= 0.8, 0.9.

From this set of possible values, there exist 36 combinations
of values for the four unknown variables. Six combinations of variable
values are randomly selected from the 36 possible combinations in order
to test the concavity assumption. The six combinations selected are
shown in Table 9. Also shown in Table 9 is the r2 value obtained for

each of the six combinations of variables.

Table 9. Results of Test of Concavity Assumption:

112

Six Random

Combinations of Unknown Variables and Resulting r2

 

 

 

Combination K Blim U R r
1 2 1.0 0.9 0.04 0.897
2 2 1.0 0.8 0.06 0.670
3 2 1.25 0.9 0.06 0.935
4 2 1.5 0.9 0.04 0.829
5 3 1.0 0.8 0.06 0.756
6 3 1.5 0.9 0.08 0.623

Optimum fr°m 2 1.51 0.9022 0.0697 0.784

simplex method

 

The function r==f (K, Blim, R, U) is not strictly concave as

seen by the results of the coarse grid test.

Two combinations of the

four unknown variables enable the simulation model to reflect historic

data better than the combination found by the "simplex" optimization

procedure.

In finding the optimum value for the criteria function, trade-

offs are present between the degree of accuracy and research costs.

While optimization techniques could be further utilized in increasing

the accuracy of the model's "postdiction" ability, the marginal returns

in terms of increased accuracy would decline rapidly with each addi-

tional optimization effort.

Therefore, it is arbitrarily decided that

an r2 equaling 0.935 is sufficient for the purposes at hand, and the

unknown variable values corresponding with this r2 are used in finding

the effects of alternative water pollution control rules. Figure 12

1

210.
205 ~
200 A
195 ~
190 -
185 *-
180 L
175 L
170 _
165 ~

160 P

155 ~

150 '

Cattle and Calves on Feed (000 Head)

145 ’
140 ‘
135 '
130

I

125

4‘:

 

1"

U6

Figure 12.

113

' 70

v 69

. 68
'67

O64 065
'66

o63

' 62
060

061

I I J _l

200 210 220 230 240 250 260 270
Mean Capacity Per Firm

Capacity of Simulated Lots and Cattle and Calves on Feed,
1960-70, with Blim=1.25, K=2, R=0.06 and U=0.9 (r2=0.935).
(The following regression equation fits this relationship with
the F statistic significant at <.0005 level. Cattle and
Calves on Feed = -696943.-+6034. (Mean Capacity Per Firm)

- 9.74 (Mean Capacity Per Firm)2 r2==0.95.

114

illustrates the ability of the model to track historic data when K =2,

Blim=l.

25, U=0.9 and R=0.06 (the "best" values for these unknowns).

The regression equation below Figure 12 illustrates the accuracy of the

model in tracking historic data.

Measures of Performance Over a Multi-

 

Period Horizon

 

1960-85
ize the

are:

The behavior of the simulated feedlots is viewed over the
period. Four measures of performance are selected to character-

behavior of Michigan feedlots. These four performance measures

Total feedlot capacity of the simulated firms.

The proportion that annual production costs are of the salvage
value of total assets. Annual production costs include supple-
ment, seed, herbicides, fertilizer, fuel, repairs, labor and
property taxes. Total assets include the value of machinery,
equipment and land. This performance measure is found by
weighing each firm's ratio of production costs to total assets
by its capacity.

Weighted averaged return to equity. This measure is computed
by weighing a simulated firm's ratio of return on equity by the
capacity of the feedlot. The annual return is after tax earn-
ings and does not include equity changes.

Equity change during the year. The mean value of the equity
change enjoyed by the simulated firms during the time period is

used as an indication of the equity change of the group.

115

It is important to recognize that the model is a partial
equilibrium model. As a result, the absolute values of each of these
performance measures may be misleading. For example, the capacities
of the simulated firms are forced to expand during the decade of the
1960's by the optimization procedure. This accurate "post diction" is
accomplished by model parameters assuming values that are conducive to
expansion. However, it is quite possible that forces outside of those
considered in this study will force contraction of feedlots during the
1970's and 1980's.

Rather than viewing the value of each performance variable by
itself, the performance measures are better considered as relative
measures. The relative effects of alternative water pollution control
rules on these performance measures is the relevant performance criteria.
Thus, the comparison of equity changes in one year over a variety of
alternative rules is a pertinent measure rather than the absolute value
of equity of the simulated firms.

The performance measures were selected prior to the construction
of the model in an attempt to reduce the vast quantity of available data
to a few meaningful test statistics. Feedlot capacity is selected as a
performance measure in order to observe changes in feedlot output as a
result of selected water pollution control rules. The second measure,
annual production cost as a proportion of durable assets, is used to
compare the asset structure under various policies. While changing
salvage values and market prices make this ratio somewhat difficult

to interpret, it is an attempt to measure asset fixity. Environmental

116

policies which reduce this ratio relative to its value under other
environmental policies would encourage the use of more durable inputs
in the input mix. The third performance measure, weighted average
return to equity, is used to compare industry (the group of farm feed-
lots represented by the simulated firms) returns under various policies.
The fourth performance measure, mean annual equity change, is used to
evaluate the relative costs of each environmental policy to Michigan

feedlot owners.

Rule Alternatives

 

The water pollution control rules investigated are comprised of
rules and accepted methods and practices that might be employed by state
or federal agencies to regulate environmental externalities associated\
with feedlots. These policies are outlined in Table 10.

The first four rules are regulations specifying the technology
to be employed in controlling feedlot pollution. The technology employed
is the system of terraces, settling basin, retention pond, and fencing
developed by Johnson and Davis.3 The fourth rule also contains a speci-
fication of an "acceptable method and practice" of dealing with animal
wastes.

Rules A through D are implemented by assuming that the lO-year,
24-hour rainfall event runoff storage requirement is equal to 5 inches
of rainfall over the exposed feedlot surface; the 25-year, 24-hour

rainfall event is equal to 6 inches over the exposed lot surface; and

 

3Davis and Johnson, op. cit.

117

Table 10. Water Pollution Control Rules Included in Analysis

 

 

Rule Provisions

 

A Current EPA guidelines would be expanded to all feedlots.
Facilities must be constructed to control the runoff from
a 10-year, 24-hour rainfall event by 1977 and the runoff
from a 25-year, 24-hour rainfall event by 1983.

B All feedlots must construct facilities by 1977 to control
runoff from a 25-year, 24-hour rainfall event.

C All feedlots must construct facilities by 1977 to control
all runoff from rainfall occurring in any 6-month interval.

0 All feedlots must construct facilities by 1977 to control
all runoff from the rainfall occurring in any 6-month
interval. Also, the feedlot may not spread solid waste
during winter months.

E "Do nothing" policy. The feedlot is not required to
retain runoff nor is it prevented from spreading solid
waste.

 

the 6-month storage requirement is equal to 16 inches over the exposed
feedlot surface. In addition, rule D's suggested method or practice of
no winter spreading is implemented by assuming that solid waste storage,
loading and spreading activities must be equipped to handle waste
accumulation over a 180 day interval. It is assumed under the other
rules that waste accumulates for a 90-day interval before being spread.
The contern of this analysis is with investigating the behavior
of feedlots under the above alternative rules. It is assumed in the
simulation model that the feedlot owners comply with the provisions of

the policies.

118

In addition to analyzing the behavior of feedlots under the
assumption of compliance, decision makers must give additional thought
into the details of assuring rule compliance.“ Do the operators have
sufficient incentives to comply with the rules? Also, the costs of
administration under various institutions cannot be ignored. Is it
feasible to enforce the provision of no winter spreading without pro-
hibitive administrative costs? Can the retention facility capacity
requirements be enforced without substantial policing costs?

Lastly, the type of administrative agency may be important
in determining policy performance. Might there be better compliance
under county or state agency located nearby than under a federal agency
far removed from the feedlot?

The omission of these considerations from the analysis is not
to disparage their importance. The assumption of automatic compliance
is made in order to simplify the analysis. It may be wrong if the
rules are not backed with incentives urging compliance and willingness
on the part of system participants to accept the institutions. Policy
analysis requires the identification of institutional alternatives, the
conduct of the firms and government agencies, and the performance of

the system.5

 

I'A. Allan Schmid, "Analytical Institutional Economics:
Challenging Problems in the Economics of Resources for a New Environ-
ment," American Journal of Agricultural Economics, December 1972.

 

5Ibid.

119

Results Under Assumption Set 1

 

The effects of the alternative rules on the simulation model
results over the 1960-85 horizon are viewed under a variety of assump-
tions regarding the unknown parameters. The first set of assumptions
are the following:

1. The values of the unknown parameters are those found through
the optimization procedure: the opportunity cost of funds
(R) = .06, the borrowing limit (Blim) =1.25, the user cost
determinant (U)==0.9, and the determinant of the net worth
distribution (K) =2.

2. Initial equity values of the 20 simulated firms are chosen from
the appropriate Erlang distribution with the mean net worth
equal to $80,000.

3. Inflation is equal to 4 percent per year as all input prices
and output prices are assumed to rise by 4 percent annually.

4. The age of feedlots in the period (1960) is determined by random
selection from a uniform distribution of ages with a range of

1 to 15 years.

The assumption of the initial net worth distribution having a
mean value of $80,000 and the assumptions regarding the inflation rate
and the initial age distribution are the same as those used in the

optimization procedure.

120

Table 11. Parameter Values Used in Assumption

Set 1
Parameter Value
K ................ 2
Blim ............... 1.25
U ................ 0.9
R ................ 0.06
Mean equity ............ $80,000
Inflation ............ 0.04/year
Age of feedlots (1960) ...... 1-15 years

Performance of Feedlots Prior to Policy
Implementation, Assumption Set 1

 

 

Since the water pollution control rules are assumed to take
effect in 1977, the simulated behavior of feedlots would be the same
until 1976 regardless of the type of environmental policy imposed.
Table 12 shows the 20 simulated firms' mean performance variables over
the 1960-76 period. The mean net worth of the simulated firms in the
initial time period is $78, 541 per firm. Feedlot capacity is the
performance measure used in the optimization and conforms reasonably
well with the real world. Michigan State University's Telfarm Report
indicates that cooperating feedlots bought an average of 189 feeder
calves in 1967, 209 head in 1969, 206 head in 1970, and 262 head in
1972.“ The capacity level, rate of return, and increase in equity of

the simulated firms correspond well with §_priori expectations and

 

“Leonard R. Kyle, "Business Analysis Summary for Cattle Feeding
Farms," Agricultural Economics Report, Michigan State University,
selected"annual issues.

121

Table 12. Measures of Performance for the 20 Simulated Feedlots,
1960-76 (Assumption Set 1)

 

 

 

Weighted Mean

Mean Feedlot Production Average Return Equity

Year Capacity Costs/Assets to Equity Change
(14:29.) (31619.) (M) (i)

1960 207.2 0.0713 0.0847 --
1961 207.2 0.0748 0.0766 4,359
1962 206.4 0.0779 0.0702 _ 4,454
1963 214.4 0.0803 0.0680 5,446
1964 215.0 0.0838 0.0550 4,612
1965 224.7 0.0863 0.0643 6,831
1966 225.4 0.0900 0.0656 7,499
1967 232.7 0.0936 0.0564 7,397
1968 239.1 0.0968 0.0533 8,295
1969 246.7 0.1008 0.0597 10,357
1970 256.6 0.1048 0.0570 11,548
1971 266.8 0.1091 0.0609 13,930
1972 278.2 0.1130 0.0692 17.187
1973 287.6 0.1176 0.0690 19,337
1974 283.6 0.1261 0.0669 20,064
1975 319.4 0.1264 0.0724 26,015
1976 330.4 0.1295 0.0754 29,860

 

122

Telfarm data for the time span. Thus, the performance measures produced
by simulating farm-feedlots since 1960 approximate real world measures.
The model is tentatively accepted as meeting the validity tests of
internal consistency, external consistency, and accuracy in tracking
historic data.

Performance of Feedlots, 1974-85,
Assumption Setgl

 

 

The behavior of the simulated feedlots during the 1974-85 period
under a "do nothing" rule or rule E is shown in Table 13. Production
expands approximately 29 percent during this time horizon. Most of this
increase occurs in the 1974-79 period reflecting the effects of the
cyclical gx_99§t_price relationships. The asset structure remains
rather stable over the 1974-85 period (see Table 12 for the performance
variables in earlier years). Most of this asset structure stability is
due to the assumption of all input prices increasing in the same propor—
tion. The average return to equity increases in the early part of the
1974-85 period and then declines slightly during the later stages.
Returns in the weighted return on equity computation do not include
annual land value increases. The average equity position of the sim-
ulated firms expands from $220,000 in 1974 to nearly $750,000 in 1985
reflecting an 11 percent annual increase in equity of the simulated
firms.

Tables 14 and 15 demonstrate the effects of the first two rules.
The first rule would be to expand the current Environmental Protection

Agency guidelines to cover all firms under 1,000 head capacity.

123

Table 13. Simulated Feedlot Performance 1974-85 Under a "Do Nothing"
Rule (Assumption Set 1)

 

‘7?

 

Mean Weighted Mean Equity

Feedlot Production Return on Change From

Year Capacity Costs/Assets Equity Past Yeara
(flew (8.9312) (3a_t1_o) (i)

(1) (2) (3) (4) (5)
1974 283.6 0.1261 0.0669 20,064
1975 319.4 0.1264 0.0724 26,015
1976 330.4 0.1307 0.0753 30,133
1977 344.2 0.1331 0.0730 33,753
1978 351.8 0.1365 0.0764 38,815
1979 362.0 0.1373 0.0730 42,619
1980 361.3 0.1379 0.0747 48,056
1981 367.5 0.1371 0.0728 53,052
1982 366.1 0.1364 0.0726 58,497
1983 367.4 0.1346 0.0713 64,294
1984 366.6 0.1355 0.0690 68,842
1985 367.6 0.1366 0.0679 74,752

 

aInitial mean feedlot equity in 1974 is $199,795.

124

Table 14. Simulated Feedlot Performance, 1974-85 Under the Rule of
Expanding Current EPA Guidelines to Firms of Less than 1,000
Head Capacity (Assumption Set 1)

 

 

 

Mean Weighted Mean Equity
Feedlot Production Return on Change From
Year Capacity Costs/Assets Equity Past Year3
(L692) (Laue) (M) (;$_)
(1) (2) (3) (4) (5)
1974 283.6 0.1261 0.0669 20,064
1975 319.4 0.1264 0.0724 26,015
1976 330.4 0.1296 0.0754 29,869
1977 343.0 0.1328 0.0724 33,205
1978 350.6 0.1363 0.0759 38,258
1979 360.7 0.1373 0.0721 41,868
1980 361.7 0.1380 0.0740 47,488
1981 372.8 0.1373 0.0723 52,280
1982 367.4 0.1368 0.0726 58,027
1983 365.6 0.1346 0.0711 63,408
1984 367.3 0.1355 0.0693 68,664
1985 366.0 0.1357 0.0680 73,960

 

aInitial mean feedlot equity in 1974 is $199,795.

125

Table 15. Simulated Feedlot Performance 1974-85 Under the Rule of
Retaining Runoff from a 25-Year, 24-Hour Storm by 1977
(Using Assumption Set 1)

 

 

 

Mean Weighted Mean Equity
Feedlot Production Return on Change From
Year Capacity Costs/Assets Equity Past Yeara
(5999.) (3.9119) <5a_t1_o> (i)
(1) (2) (3) (4) (5)
1974 283.6 0.1261 0.0669 20,064
1975 319.4 0.1264 0.0724 26,015
1976 330.4 0.1295 0.0754 29,860
1977 342.9 0.1328 0.0724 33.183
1978 350.6 0.1363 0.0758 38,233
1979 360.6 0.1374 0.0721 41,843
1980 361.7 0.1380 0.0740 47,455
1981 367.3 0.1374 0.0724 52.253
1982 367.3 0.1368 0.0726 57,997
1983 365.7 0.1346 0.0711 63,401
1984 367.3 0.1355 0.0693 68,655
1985 366.0 0.1358 0.0680 73,952

 

aInitiai mean feedlot equity in 1974 is $199,795.

126

Retention facilities would be constructed by firms in 1976 to control
runoff from a lO-year, 24-hour rainfall event, and in 1982 retention
facilities would be constructed to control runoff from 25-year, 24-hour
rainfall event. The behavior of firms under this policy is shown in
Table 14. The second rule is one of requiring all firms to retain
runoff from a 25-year, 24-hour rainfall event by 1977. In this rule
firms would construct retention facilities in 1976 to conform to the
rule. Behavior of the feedlots under this rule is shown in Table 15.

The first two rules are nearly identical in their effects over
the 1974-85 time horizon. Production is nearly identical over the time
period under either rule, and the asset structure and return on equity
remain nearly the same. The cost of a rule to feedlots can be found by
looking at the effect that each of these rules has on the mean equity
change (Table 16).

Over the 12-year period capacity declines relative to the "do
nothing" rule under both the rule to extend current EPA guidelines to
less than 1,000 head capacity feedlots and the rule to require firms to
control the runoff from a 25-year, 24-hour storm by 1977. It is assumed
that the simulated lots are at full capacity throughout the period;
therefore, the relative decline in production over the period would
be the change in capacity due to environmental policy times the turnover
rate. In the case of rule A, production declines by a mean of 7.0 head
compared to the "do nothing" rule for the simulated firms during the
1974-85 time horizon. This decline represents only a 0.167 percent

decline in production.

127

 

 

d

 

Table 16. Change in Performance of Simulated Feedlots Under Rules A

and B (Assumption Set 1)

Mean Change Mean Equity Mean Change Mean Equity

Year in Capacitya Change Per Firm in Capacityc Change Per Firm

(5219) (3;) (£939) (5;)
1974 0 0 0 0
1975 0 0 0 0
1976 0 264 0 273
1977 1.25 548 1.30 570
1978 1.20 557 1.20 582
1979 1.30 751 1.35 776
1980 0.45 570 -0.40 603
1981 0.20 772 0.20 799
1982 -1.30 470 -1.30 500
1983 1.25 886 1.30 993
1984 1.75 178 1.70 187
1985 0.30 792 0.30 800

 

aColumn (2), Table 13--Column (2), Table 14 or capacity in each
year under "do nothing" rule minus the capacity under rule A.

b

Column (5), Table 13--Column (5), Table 14 or equity change in

each year under "do nothing" rule minus the change under rule A.

"do nothing" rule minus the capacity under rule B.

cColumn (2), Table 13--Column (2), Table 15, or capacity under

d

Column (5), Table l3--Column (5), Table 15, or equity change

under "do nothing" rule minus the equity change under rule 8.

128

In the case of the rule 8, controls of a 25-year, 24-hour storm by
1977, production declines by a mean of 7.2 head for the simulated

firms relative to the "do nothing" rule. Thus, neither rule has a
great amount of impact on the production of the simulated firms with
the relative decline being only 0.17 percent of production. If the
simulated firms are representative of all Michigan feedlots of less
than 1,000 head, and the number of these lots remains constant, the
relative decline in production would be approximately 11,200 head in
the 1974-85 period under the rule A (approximately 1,000 head per year).
Under rule B, the relative decline in production would be approximately
11,800 during the period.

The cost to the simulated firms in a rule can be approximated
by discounting the annual equity changes over the 12-year period.7 As
a result of the rule A, extension of current EPA guidelines to lots of
less than 1,000 head capacity, the present value of the equity losses
during the 1974-85 period is less than the "do nothing" rule by $3,724
per firm. As a result of rule 8, control of runoff from a 25-year,
24—hour storm by 1977, the present value of the relative loss in equity
over the period is $3,911 per firm. Again, assuming the simulated firms
accurately represent Michigan feedlots, the present value of the cost of
rule A compared to the "do nothing" rule to Michigan feedlots over the

next twelves years is $6.26 million, and rule 8 is $6.57 million.

 

7Future equity losses are discounted by a rate of 6 percent,
the opportunity cost of funds, to arrive at a present value for equity
losses.

129

The performance of the simulated feedlots under rule C is shown
in Table 17. Rule C would require feedlots under 1,000 head capacity to
control runoff from any 6-month rainfall or in the case of Michigan feed-
lots, runoff from 16 inches of rainfall. Feedlots would implement this
policy by constructing runoff retention facilities in 1976.

The production cost to total asset ratio under rule C remains
nearly the same as in the "do nothing" policy. Thus, the asset struc-
ture of the firm remains the same under both policies. Similarly, the
return on equity is affected only slightly by the six-month runoff
retention requirement.

The final policy under consideration, rule 0, would have the
same strict runoff control requirement as rule C, and it would also
require that no winter spreading of solid wastes occur. This rule has
the most severe effect on the performance of the simulated feedlots of
the water pollution control rules under consideration (as seen in
Table 18). The ratio of production costs to total assets generally
increases above the other four rules (A, B, C, and "do nothing") re-
flecting the higher production costs associated with the use of more
machinery in order to complete the spreading of solid wastes in the
allotted time interval. The annual return to equity is also smaller
under this rule than under the other rules; however, this difference
is quite small. For example, in 1981 the return to equity averages
7.28 percent with the "do nothing" rule, 7.23 percent under the first

three rules, and 7.20 percent under the most severe rule, rule 0.

130

Table 17. Performance of 20 Simulated Firms Under Rule C, 1974-85
(Assumption Set 1)

AA

 

Mean Equity

 

Mean Weighted

Feedlot Production Return on Change From
Year Capacity Cost/Asset Equity Previous Year

(M) (.Retje) (5215.19) 8)
(1) (2) (3) (4) (5)
1974 283.6 0.1261 0.0669 20,064
1975 319.4 0.1264 0.0724 26,015
1976 330.4 0.1292 0.0755 29,770
1977 340.6 0.1330 0.0715 32,499
1978 351.6 0.1368 0.0761 38,430
1979 359.9 0.1375 0.0718 41,362
1980 359.4 0.1387 0.0744 47,412
1981 362.5 0.1377 0.0724 52,035
1982 362.5 0.1372 0.0725 57,685
1983 362.7 0.1350 0.0714 63,653
1984 362.3 0.1360 0.0693 68,490
1985 363.1 0.1361 0.0684 74,304

 

131

Table 18. Performance of Simulated Feedlots under Rule D, 1974-85
(Assumption Set 1)

 

 

 

Mean Weighted Mean Equity

Feedlot Production Return on Change From
Year Capacity Cost/Asset Equity Previous Year

(9299) (8.92.9) (m) (9)
(1) (2) (3) (4) (5)
1974 283.6 0.1261 0.0669 20,064
1975 319.4 0.1264 0.0724 26,015
1976 330.4 0.1297 0.0751 29,665
1977 340.6 0.1335 0.0721 32,356
1978 351.6 0.1374 0.0758 38,279
1979 359.8 0.1381 0.0715 41,191
1980 359.3 0.1394 0.0741 47,220
1981 362.5 0.1384 0.0720 51,835
1982 367.5 0.1380 0.0722 57,463
1983 362.7 0.1358 0.0712 63,432
1984 362.1 0.1368 0.0690 68,213
1985 363.0 0.1370 0.0683 74,068

 

132

The two performance variables feedlot capacity and equity change
reflect the impact of rule C, control of runoff from a 6-month storm,
and rule 0, control of runoff from a 6-month storm plus storing solid
waste for 180 days on production and cost to producers. Table 19 illus-
trates the effect of rules C and D on these two performance variables vis
a vis a "do nothing" rule.

Rule C, the requirement that feedlots of less than 1,000 head
control runoff from a 6 month rainfall, has the effect of lowering pro-
duction by 37.7 head per finn for the simulated lots over the 12 year
period relative to the "do nothing“ rule. The decline is only 0.9 per-
cent in total production. Assuming these lots are representative,
Michigan feedlots would produce 63,000 head less than a "do nothing"
rule over this period if rule C is in force. Under rule 0 relative
production would be lowered by 38.3 head per firm over this twelve year
period or production on Michigan feedlots would be approximately 64,000
head less under rule 0 than the "do nothing" rule. This change repre-
sents 0.91 percent of total production.

The present value of the costs incurred by the simulated firms
if rule C is invoked is approximately $4,800 per firm. The present
value of the cost of rule 0 over the next twelve years is $5,990 per
simulated firm. Assuming these firms are representative, the present
value of the 12 year cost to Michigan producers under the requirement
of controlling a 6 month rainfall is $8.06 million. The present value
of the 12 year cost to Michigan producers under the requirement of 6
month runoff retention and prohibiting winter spreading is $10.06

million.

133

Table 19. Change in Performance of Simulated Feedlots Under Rules C and
0 (Using Assumption Set 1)

 

 

 

 

 

Rule C Rule 0
Mean Change Mean Equity Mean Change Mean Equity

Year in Capacitya Change Per Firmb in Capacityc Change Per Firmd

(Leas) (i) (M) (i)
1974 0 0 0 0
1975 0 0 0 0
1976 0 363 0 468
1977 72 1,274 73 1,397
1978 3 385 5 536
1979 42 1,257 44 1,428
1980 38 644 39 836
1981 100 1,017 100 1,217
1982 72 812 72 1,034
1983 93 641 93 860
1984 85 352 89 629
1985 89 448 91 684

 

aColumn (2), Table 13--Column (2), Table 16 or annual capacity
under the "do nothing" rule minus the annual capacity under rule C.

bColumn (5), Table 13--Column (5), Table 16 or the annual
equity change under the "do nothing" rule less the annual equity change
under rule C.

CColumn (2), Table 13--Column (2), Table 17 or the annual
capacity under the "do nothing" rule minus the annual capacity under
Rule D.

dColumn (5), Table 13--Column (5), Table 17 or the annual equity
change under the "do nothing" rule less the annual equity change under
ru e D.

134

Results Under Assumption Set 2

 

The second set of assumptions is basically the same as the first
set with the exception that alower initial net worth is assumed. The
purpose of this set is twofold: the first is to test the differential
impact that selected water pollution control rules have on firms of
lower net worths; the second is to test the sensitivity of the results
to the initial net worth assumption.

Given that economies of size exist in abiding by the water
pollution control rules, these rules raise income distribution questions
as well as efficiency questions. How do these rules affect firms with a
small resource base? This question is addressed through changing the
initial mean net worth of the simulated firms while leaving all other
assumptions unchanged. The influence of the selected rules on the
annual net worth changes of small firms is compared to the net worth
changes of larger firms.

Performance of Feedlots Prior to Policy
Implementation, Assumption Set 2

 

 

Under assumption set 2 the mean net worth in 1960 is reduced to
$60,000. The distribution is skewed to the right as in the first assump-
tion set by setting K==2 in the Erlang function. Letting the computer
select 20 initial firm net worths from this distribution, results in a
mean net worth of $58,567 for the 20 simulated firms in 1960. Table 20
demonstrates the annual capacity of the 20 simulated firms, mean equity
change of each of the firms, and the other two performance variables

over the 1960-76 horizon.

135

Table 20. Measures of Performance for the 20 Simulated Feedlots,
1960-1976 (Assumption Set 2)

 

 

 

Weighted Mean
Mean Feedlot Production Average Return Equity
Year Capacity Costs/Assets to Equity Change

("13.9) (52519.) (M) (i)

1960 146.1 0.0743 0.0728 --
1961 146.1 0.0805 0.0518 663
1962 143.9 0.0835 0.0482 815
1963 144.6 0.0863 0.0487 1,429
1964 143.5 0.0899 0.0395 1,012
1965 139.6 0.0944 0.0434 1,790
1966 146.2 0.0967 0.0467 2,819
1967 145.2 0.1014 0.0373 2,690
1968 149.5 0.1043 0.0368 3,425
1969 149.8 0.1095 0.0403 4,208
1970 155.3 0.1130 0.0398 5,036
1971 156.5 0.1187 0.0406 5,875
1972 161.3 0.1227 0.0479 7,510
1973 168.8 0.1274 0.0515 8,962
1974 175.9 0.1319 0.0544 10,472
1975 183.7 0.1376 0.0551 11,915
1976 190.6 0.1414 0.0598 13,946

 

136

Capacity expands at a much slower rate under the lower net
worth assumption reflecting the diseconomices associated with the small
capacity units. The firms' simulated capacity is quite sensitive to
changes in net worth. Lowering the initial net worth by 25 percent
results in capacity expanding by only 6 percent during the 1960-70
period. This expansion is compared to an approximate 25 percent capac-
ity expansion during the period under the higher net worth assumption.
Likewise, the weighted average return and the equity changes are lower
vis a vis the simulated firms starting from a larger resource base.
Initial equity is doubled by year 1971 under the higher net worth
assumption (assumption set 1), but under the assumption of lower initial
equity (assumption set 2), doubling of initial equity does not occur
until 1975. Return to equity is also much less under the lower net
worth assumption (assumption set 2) reflecting the economies of size
associated with feedlot technology. The production cost to total asset
ratio is higher under this assumption set; moreover, this result would
add validity to the gx_99§t_production function. As the feedlot firm
becomes smaller, labor is substituted for capital and the annual pro-
duction costs (including labor expenses) become larger relative to
capital requirements.

Performance of Feedlots 1974-85,
Assumption Set 2

 

 

Upon the imposition of the selected rules used in this study,
the simulated firms with the smaller equity positions are affected more

than the firms with the larger resource base. This expected result must

137

be quantified in a way that yields meaningfulness, and the relative
effect on equity positions is selected as the method of quantification.
Under assumption set 1, the mean discounted cost incurred by the firms

as a result of these rules compared to the mean net worth of the firms

 

 

 

 

in 1974 is:
Rule A: mean "peraense1n9t7gagquuefio; costs = % ___ 0.0169
Rule 8: mean "pg‘aense1ngt7gaelguefio; costs = é%3_9_10(1)_0 = 0.0178
T = .9933. =
Rule 0: mean £gaenseln9t74laelqltfi€yf costs = 3%fi%)fi = 0.0272

Thus, rule A, extend current EPA guidelines, is expected to cost 1.69
cents over the next twelve years per dollar of 1974 equity. Rule 8,
control runoff from a 25-year, 24-hour storm by 1977, is expected to
cost 1.78 cents per dollar of 1974 equity. Rule C, control runoff from
a 6 month rainfall, costs 2.18 cents per dollar of 1974 equity. Rule 0,
control 6 month rainfall runoff plus store solid wastes for 180 days
costs 2.72 cents per dollar of 1974 equity.

Under assumption set 2, the ratio of the discounted costs to the
1974 equity position is larger than under the first set of assumptions.

The ratios of discounted cost to net worth for the various policies are:

, mean present value of costs = $3,281 =
RUIE A' mean 1974 equity $105,140 0’0313

mean present‘value of costs _ $3,479

Rule 8‘ mean 1974 equity ' $105,140 = 0'033]

 

138

 

 

, mean present value of costs = $4,983 =

RUIE C' mean 1974 eqUity $105,140 0°0474
, mean present value of costs _ $5,746 _

Rule D- mean 1974 eqmy " 5105717411 " 0-0545

By reducing the mean net worth assumption, the cost to the
simulated firms increases relative to the initial net worth. The policy
of extending current Environmental Protection Agency guidelines, rule A,
is the least expensive to these firms. The present value of 1974-85
costs is 3.13 cents for every dollar net worth. Rules 8, C, and 0 cost
the firms 3.31 cents, 4.74 cents, and 5.46 cents per dollar of 1974
net worth, respectively.

Due to the economies associated with runoff and solid waste
control, the smaller firm suffers substantially more than the larger
firm. Under the assumption of a 25 percent reduction in net worth in
1960 at the beginning of the simulated time horizon, the cost to equity
ratio is nearly twice that under the larger net worth assumption. The
economies associated with controlling feedlot runoff and solid wastes
result in a regressive tax to feedlot operators.

Not only is the imposition of controls regressive in nature, but
these controls cost the firms with a 1974 mean equity of $105,140 nearly
as much as the firms with a mean 1974 net worth of $220,000. Due to
economies in runoff and solid waste control, the small firms' (those
simulated under assumption 2) expansion ability suffers relative to that
of the large finns' (those simulated under assumption 1). Rule A (expan-
sion of current EPA guidelines to include small feedlots) results in

production of 9.15 head per firm less than the "do nothing" policy over

139

the entire 1974-85 interval for the firms under assumption set 2

(Table 21, capacity change over the twelve years times the annual turn-
over rate). 0n the other hand, larger firms under assumption set 1
decrease production only 7.0 head per firm over 1974-85 as a result of
rule A. Likewise, rule 8 (retention of 25-year, 24-hour runoff by 1977)
affects production by 9.75 head per firm over the twelve year period
under assumption set 2; however, it affects production under the higher
net worth of assumption set 1 by 7.2 head per firm over the twelve years.
Rule C (the requirement that firms retain runoff from a six month rain-
fall) changes production by 11.25 head per firm under assumption set 2
and 37.95 head under assumption set 1. Rule 0 (six month rainfall run-
off retention plus abolishment of winter spreading) changes production
by 13.4 head per firm under assumption set 2 while changing production
by 38.3 head under assumption set 1. Table 22 summarizes these changes
under the first two assumption sets.

Equity accumulation has suffered for the simulated firms with
less resources. Not only has the cost per dollar of 1974 equity in-
creased, but the cost of compliance is nearly as great for the smaller
firms simulated under assumption set 2 as those simulated under assump-
tion set 1. The present value of rule A's cost to feedlot owners is
$3,281 per firm under assumption set 2. Comparing this cost to the
discounted costs of $3,740 per firm under assumption set 1, it can be
seen that the absolute value of the losses suffered by the large and
small firms are nearly the same. Likewise, rules 8, C, and 0 result
in approximately the same losses under the two assumption sets as seen

in Table 22.

140

Table 21. Mean Change in Performance of Simulated Feedlots Under Rules
A, B, C, and D, Vis a Vis a "Do Nothing" Policy (Assumption

 

 

 

 

 

 

 

 

 

Set 2)
Rule A Rule 8
Mean Change Mean Equity Mean Change Mean Equity

Year in Capacity Change Per Firm in Capacity Change Per Firm

(bad) (i) (Head) (15.)
1974 0 0 0 0
1975 0 0 0 0
1976 0 68 0 173
1977 0.60 337 0.60 351
1978 1.40 338 1.45 357
1979 2.25 549 2.30 567
1980 4.25 422 4.15 448
1981 1.70 717 1.75 744
1982 -0.60 354 -0.55 380
1983 2.90 1,022 2.95 1,034
1984 0.35 460 0.40 471
1985 3.20 1,137 3.25 1,157

Rule C Rule 0
Mean Change Mean Equity Mean Change Mean Equity

Year in Capacity Change Per Firm in Capacity Change Per Firm
1974 0 0 0 0
1975 0 0 0 0
1976 0 222 0 272
1977 2 45 882 2.50 943
1978 -1 40 436 -1.30 514
1979 2 10 1,058 2.30 1,164
1980 -0 30 703 0.05 833
1981 l 55 1,060 1.70 1,195
1982 -0 60 736 -0.45 828
1983 1 80 925 1.95 1.095
1984 l 30 787 1.65 1.012
1985 2 35 1,061 2.70 1,265

 

141

Table 22. Simulated Firms' Mean Change in Output and Equity, 1974-85,
as a Result of Four Environmental Rules and Two Initial
Equity Levels

 

 

 

 

 

Assumption Set 1 Assumption Set 2
Mean Mean
Mean Change Discounted Mean Change Discounted
in Output Equity Loss in Output Equity Loss
(1999.) (.9) (11m) (5.)
Rule A 7.0 3,724 7.55 3,281
Rule B 7.2 3,911 8.0 3,479
Rule C 37.95 4,800 11.25 4,983
Rule D 38.3 5,990 13.4 5,746

 

Sensitivity Analysis

 

Assumption set 1 is used to identify the changes in performance
variables occurring under selected water pollution control rules.
Assumption set 2 is used to identify the differential effect of the
rules on firms of different equity positions; furthermore, the assump-
tion is used to test the sensitivity of the simulation model to changes
in the initial net worth assumption. The remaining ten assumptions are
used to test the sensitivity of the model's results to small changes in
the values of critical parameters in the model.

In each of the remaining ten assumption sets used for the
sensitivity analysis, only rule D or the most severe environmental

policy is used. This rule has the most effect on feedlots, and results

142

from this rule should be the most sensitive to changes in parameter
values. Since the purpose of the sensitivity analysis is to determine
the impact of small changes in parameter values on model results,
results under rule 0 should demonstrate this sensitivity more clearly
than any of the other rule alternatives.

To review assumption set 1, the values of the parameters are
determined through the optimizing procedure. These assumptions are
(l) the opportunity cost of funds (R) = 0.06, (2) the borrowing limit
(Blim) = 1.25, (3) the determinant of user cost (U) = 0.9, and (4) the
determinant of the net worth distribution (K) = 2. In addition, assump-
tions are made concerning the initial mean net worth of the feedlots and
the initial age of the feedlots. These assumptions are (5) the mean net
worth in 1960 is $80,000, and (6) the initial age of facilities is uni-
formly distributed between one and fifteen years.

The sensitivity of the initial mean net worth is tested in
assumption set 2. Assumption sets 3 and 4 test the sensitivity of the
rate of return on off-feedlot investment or R. Assumption sets 5 and 6
concern the value of K or the determinant of the shape of the net worth
distribution. The sensitivity of the results to changes in the borrow-
ing limit is addressed by assumption sets 7 and 8. The value of U or
the determinant of the user costs is addressed in assumption sets 9 and
10, and the last two assumption sets, sets 11 and 12, test the sensitiv-
ity of the results to the initial age assumption. The value of the

parameters under each assumption set is shown in Table 23.

143

Table 23. Assumption Sets Used in Determining the Effects of Selected

Water Pollution Control Rules and in the Sensitivity

 

 

 

 

Analysis
Values of
Initial
Assumption Age of Initial
Set R K Blim U Durables Equity
(3;)

l 0.06 2. 1.25 0.9 * 80,000
2 0.06 2. 1.25 0.9 * 60,000
3 0.054 2. 1.25 0.9 * 80,000
4 0.066 2. 1.25 0.9 * 80,000
5 0.06 l. 1.25 0.9 * 80,000
6 0.06 3. 1.25 0.9 * 80,000
7 0.06 2. 1.125 0.9 * 80,000
8 0.06 2. 1.375 0.9 * 80,000
9 0.06 2. 1.25 0.81 * 80,000
10 0.06 2. 1.25 0.99 * 80,000
11 0.06 2. 1.25 0.9 5 80,000
12 0.06 2. 1.25 0.9 10 80,000

 

*Initial age randomly selected from uniform distribution of one

to fifteen years.

144

The purpose of exploring the results under various sensitivity
tests is twofold. The first is to test which of the variables have the
greatest impact on the results; the second is to test the consistency
of the model. Under assumption set 3 with the lower opportunity cost
of funds (decreased off-feedlot return on investments), it is expected
that capacity would be greater than or equal to capacity under assump-
tion set 4 (with a high opportunity cost for funds). It is expected
that further skewing the net worth distribution to the right (assumption
set 5) would result in lower equity changes than under the assumption
set 6 due to the greater concentration of low equity feedlots. Low-
ering the Blim in assumption set 7 raises the capacity of the firm to
borrow from external sources. The expected effect is a substantial
increase in capacity. Lowering the firm's capacity to borrow money,
assumption set 8 is expected to substantially decrease the capacity
of the firms throughout the 1960-85 horizon. A lower U in set 9 is
expected to decrease net worth throughout the period relative to
assumption set 10. Lower salvage values and less borrowing ability
should result in lower equities and lower earning. Assumption sets 11
and 12 are employed to test the effects of water pollution control rules
on feedlots of various ages. Under assumption set 11, the initial age
of feedlots is 5 years old, and the initial age under assumption set 12
is 10 years old. The hypothesis is that the environmental rules have
little if any differential effect on feedlots of various ages and that
the value of durable assets in the feedlot is not materially changed

after the imposition of control technology.

145

Appendices B-1 and B-2 show the performance variables under
assumption sets 3 and 4. Generally, small changes in off-feedlot rate
of return affect the performance variables very little. Total produc-
tion (capacity per year times the turnover rate) during the 1960-85
period is only 175 head per firm greater under the lower off-feedlot
rate of return than under the higher off-feedlot rate of return. Other
performance variables are nearly the same under both assumptions.
Equity increases are slightly higher under the higher off-feedlot rate
of return assumption reflecting the higher off-feedlot earnings. Thus,
the sensitivity of model results to small changes in the rate of return
in off-farm investments is quite slight.

The effect of changes in the shape of the initial net worth is
consistent with expected results. Assumption set 5 (further skewness
to right in equity distribution) consistently results in a lower annual
change in equity than under assumption set 6 due to the initial net
worth differences. Figure 13 illustrates the annual change in net worth
under both assumptions. In addition, returns to equity are slightly
higher when the distribution is relatively skewed to the left (assump-
tion set 6) reflecting the economies of size associated with the higher
net worths. The values of the performance variables in 1960-85 are
shown in Appendices B-3 and B-4.

Figure 14 illustrates the difference in capacity under assump-
tion sets 7 and 8. Assumption set 7 allows the firm's debt to be a
larger proportion of total assets than set 8. As expected, assumption

set 7 allows capacity and total production to be larger than under

146

Annual
Equity
Change

(5;)

80,000 Assumption

Set 6

7

70,000 ~

60,000 ..

50,000 _

40,000 - // Assumption
/ Set 5

30.000

20,000 L

10,000 -

 

60 64 68 72 76 80 84
Year

Figure 13. Annual Change in Net Worth Per Simulated Firm Under
Assumption Sets 5 and 6, 1961-85. (Assumption Set 5 causes
the net worth distribution to be further skewed to the left
than assumption set 6.)

Annual Simulated Capacity
1960 Simulated Capacity

 

1.8 '-

 

147

Annual Capacity Set 7
1960 Capacity Set 7

 

Annual Capacity Set 8
1960 Capacity Set 8'

 

Year

Figure 14. Annual Indices of Capacity of Simulated Firms Under
Assumption Sets 7 and 8, 1960-85 (1960==1.0). (Assumption
set 7 allows firm's debt to be a larger proportion of total
assets than does assumption set 8.)

148

assumption 8. Figure 14 illustrates the ability of the firms to expand
under the liberal credit provision. Not only does the liberal credit
enable 1960 feedlot capacity to be larger but in all years except the
last three the firms with the liberal credit policy are able to expand
this initial capacity at a faster rate relative to those firms facing
restrictive credit. The performance variables for the 1960-85 period
are shown in Appendices B-5 and B-6.

The user cost determinant has a substantial impact on the
performance variables, and the results are the most sensitive to changes
in the parameter. With U equaling 0.99, durables do not decline in
value or the economic depreciation is zero. As a result, the firm is
easily able to shift resources from the present housing facilities to
new more profitable facilities. The near equality of acquisition and
salvage values enables the feedlots expansion ability to be substan-
tially higher than under the more realistic situation where acquisition
and salvage prices differ for durables. Of course, equity increases
much more rapidly under the near zero user cost assumption (assumption
set 10) than under the high user costs assumption (assumption set 9).
Durables do not decline in value as rapidly and equity becomes almost
explosive under the assumption of near zero user cost. Appendices B-7and
B-8 list the performance variables under these assumption sets. Figure
15 illustrates the explosive nature of the capacity under the low user

cost assumption.

149

Annual Simulated Capacity
1960 Simulated Capacity

 

3.4

1.0

Figure

Annual Capacity Set 10
1960 Capacity Set 10

 

Annual Capacity Set 9
~ 1960 Capacity Set 9

 

 

L l 1 l I J

62 66 7O 74 78 82
Year

Annual Indices of Capacity of Simulated Firms Under
Assumption Sets 9 and 10, 1960-85 (1960==l.0). (Durable
assets are used up at a faster rate under assumption set 9
than under assumption set 10.)

150

Finally, the sensitivity analysis concerning the initial age
of feedlots would suggest the rejection of the hypothesis that initial
age has no effect on feedlot performance. From observing Figure 16 and
Appendices B-9 and B-lO, it is obvious that the age of feedlots does
affect the performance variables. In assumption set 11 the initial age
of all feedlots is 5 years. Due to the relatively large salvage value
for durable assets, expansion occurs slowly during the first few years
(1960-68). However, for the older firms (assumption set 11), equity
increases at a faster rate than under those firms with new facilities
since the newer facilities depreciate at a relatively rapid rate; more-
over, the older firms expand at a faster rate than the newer firms.

Both sets of assumptions cause the firms to expand at approximately

the same rate and to increase equity by approximately the same rate
during the period of the imposition of the environmental policy. From
1977 to 1985 feedlot capacity increases by 6.2 percent under assumption
set 11 (newer assets at the time of rule imposition) and 7.9 percent
under assumption set 12 (older assets when rules are imposed). Equity
increases by 10.5 percent annually under assumption set 11 during the
1977-85 period while increasing by 10.8 percent annually under assump-
tion set 12.

To summarize: (1) Small changes in the rate of earnings on off-
feedlot investment has only a minor impact on changes in simulated per-
formance. The paths of the performance variables are nearly the same
over the 1960-85 period under the higher opportunity cost assumption set
as the set with the lower opportunity cost on funds. (2) Changes in the

151

Annual Simulated Capacity
1960 Simulated Capacity

 

1.9

Annual Capacity Set 12

 

1960 Capacity Set 12

 

  

Annual Capacity Set 11
apac1 y at

 
 

 

0.9 F

 

Figure 16.

Annual Indices of Capacity of Simulated Firms Under
Assumption Sets 11 and 12, 1960-85 (1960==l.0). (Age of
durable assets in 1960 is 5 years under assumption set 11
and 10 years under assumption set 12.)

152

shape of the net worth distribution affect the performance variables

as expected; however, the differences in the variables are small.

(3) Small changes in the maximum proportion that debt is of total

assets strongly influence the ability of the firm to expand. Capacity
and output are able to increase rapidly when the firm is allowed to
assume relatively more debt. (4) Small changes in the determinant of
the user cost of durable assets have a major impact on the performance
of the simulated firms. Small user costs produce near explosive effects
on simulated capacity and equity variables. (5) Finally, the assumption
concerning the initial age of durable assets is important in determining
the level of performance variables. Results differ markedly under the
two assumption sets concerning age. However, the imposition of the most
severe water pollution control rule does not produce any noticeable dif-
ferences in the performance variables under the two initial age

assumptions.

Summary of Major Findings

 

1. Each of the four policy alternatives under investigation has
a small impact on the cost structures of the simulated feedlots. For
example, the requirement that feedlots have the capacity to retain a
25-year, 24-hour rainfall event by 1977 increases the total cost by
$1.39 per head sold in the 500 head capacity drylot unpaved feedlot.

2. There exist economies of size in runoff abatement technology
or waste spreading technology. For example, the 25-year, 24-hour storm

runoff capacity requirement increases the cost per pound sold by $0.005

153

for the 100 head capacity drylot, unpaved lot. This cost declines
exponentially with the policy costing the 900 head capacity drylot,
unpaved feedlot $0.001 per pound sold.

3. The optimization procedure enables the simulation model to
assume the "best" values of unknown parameters. These "best" values
are chosen from a range selected by a_p§jgrj_reasoning, and these "best"
values enable the simulation model to "accurately" reflect the real
world. The optimization procedure found values for the unknown param-
eters which allowed the simulation model to explain 93.5 percent of the
variation in historical data.

4. The simulation model employing the theory reviewed in
Chapter 3 is tentatively accepted as being valid. The tests of (1)
internal consistency and logic, (2) external consistency with known
results from Michigan feedlots, and (3) workability were applied
throughout the construction of the model.

5. Five policy alternatives (four action rules and one "do
nothing" rule) are imposed separately on the firms, and the firms'
behavior is simulated during the 1974-85 period. It is assumed that
all firms comply with the regulations of the policies. Under the
parameter values found throughout the optimization procedure, the
four action rules have the following results:

a. Under the rule of requiring the capacity to control the runoff

from a 10-year, 24-hour rainfall event by 1977 and from a

25-year, 24-hour rainfall event by 1983, the relative decline

in production is 7.0 head per firm (a decline of 0.167 percent)

154

over the entire 1974-85 period. Equity losses over this
period have a mean present value of $3,734 per firm.

b. Under the rule of requiring the capacity to control the runoff
from a 25-year, 24-hour storm by 1977, the relative decline in
production is 7.2 head per firm (a decline of 0.17 percent) over
the entire 1974-85 period. Equity losses for the firms have a
present value of $3,911 per firm.

c. Under rule of requiring the capacity to control the runoff from
a 6 month rainfall by 1977, the relative decline in production
totals 37.7 head per firm for the entire twelve year period (a
decline of 0.90 percent). Equity losses per firm over this
period have a mean present value of $4,800 per firm.

d. The addition of the requirement that no winter spreading is to
occur to the requirement of controlling runoff from a 6 month
rainfall has minimal effects on the firms' behavior. Assuming
the requirement is that firms must have the capacity to control
runoff from a 6 month rainfall plus be prohibited from spreading
solid waste in the winter, the relative decline in production is
38.3 head per firm (a decline of 0.91 percent). Equity losses

over the period have a mean present value of $5,990 per firm.

6. The rules used in this analysis affect the distribution of
wealth of feedlot operators. Given the mean 1973 net worth of feedlot
owners is $220,000, the rule of requiring the retention capacity for a

lO-year, 24-hour storm by 1977 and for a 25-year, 24-hour storm by 1983

155

(rule A) costs the firms an average of 1.69 cents over the next twelve
years per dollar of 1974 net worth. Rules 8, C, and 0 costs the firms

a mean value of 1.78 cents, 2.18 cents, and 2.72 cents per dollar of
1974 equity, respectively. Reducing the original mean net worth assump-
tion to $105,000 increases the cost per dollar equity under all the
selected rules to nearly twice the costs under the $220,000 mean equity
assumption. The economies associated with controlling runoff and solid
wastes produce a regressive effect on feedlot operators.

7. The simulation model constructed for the analysis appears
quite sensitive to several critical parameters. Those parameters which
strongly affect model results are the mean net worth of the simulated
firms, the credit limitation on the firms, the determinant of the annual
user cost of durable inputs and the initial age of feedlots. Parameters
which affect results slightly in the sensitivity analysis include the
rate of earnings in off-feedlot investment and the determinant of the
shape of the net worth distribution of farm-feedlots.

8. The paths of adjustment of the simulated feedlots to the
four selected rules are nearly identical under changes in the assumption
regarding the initial age of the feedlots. The capital outlay required
upon the adoption of any of the four rules has a minor impact on the
capital structure of the firm regardless of feedlot age. The result
is that the rules have a minor impact on the decision process for

feedlots of all ages.

CHAPTER VI

SUMMARY AND IMPLICATIONS

Summary

Market failure is often evident in a market economy. Several
types of market failure are possible-~technical externalities, indivis~
ibilities and collective consumption. Interdependence in production
processes, interdependence of a production process and a consumption
activity, and interdependence of two or more consumption activities
are classifications of technical externalities. Indivisibilities might
be exemplified by public utilities where economies of size and lumpiness
of assets necessitate monopoly conditions. Public provisions for
national defense exemplifies the market failure in collective consump-
tion and the resulting need to rely on government intervention rather
than a market solution. Agriculture is faced with technical external—
ities in most of its instances of market failure. The focus of this
study was on one externality occurring in the agricultural sector,
feedlot pollutants. The analysis was an economic evaluation of selected
water pollution control rules and suggested methods and practices which
could be employed to achieve the environmental policy of no discharge

into navigable waters.

156

157

The purpose of this study was to investigate some of the costs
involved in applying a selected set of rules and/or suggested methods
and practices. Costs investigated included the costs of the rules in
terms of a reduction in feedlot production and costs incurred by feed-
lot operators in complying with the rules. A simulation model was
developed to allow the observation of the behavior of feedlots under the
selected set of rules and acceptable methods and practices. The feed-
lots represented by the simulation model were intended to be those in
Michigan and other areas similar to Michigan in the economic and
physical environment.

Rules and acceptable methods and practices for water pollution
control have been contemplated by the Environmental Protection Agency
(EPA). Authority to establish and administer rules regarding pollution
abatement was granted to the EPA by Congress in the Water Pollution Con-
trol Act of 1972.

The framework established by Congress is that point sources of
pollution would be subject to the National Pollution Discharge Elimina-
tion System (NPDES). The authority to administer the NPDES rests in the
hands of the EPA, but this authority is delegated to the appropriate
state agency, assuming certain federal requirements are met. In
Michigan authority to administer the NPDES has been delegated to
the Water Resources Commission. All point sources subject to the
NPDES would apply for permits in order to emit pollutants. Included
in the permits is a compliance schedule which requires a step-by-step

reduction in pollutants over a specific time interval.

158

EPA has announced point source water pollution effluent
limitation guidelines for feedlots by requiring existing firms of over
1,000 head capacity to construct retention facilities to control process
generated waste water and the runoff from a local lO-year, 24-hour,
rainfall event by 1977. By 1983, these feedlots must have the capabil-
ity of controlling process generated waste water and the runoff from a
25-year, 24-hour rainfall event. For any new feedlots with 1,000 head
or greater capacity, control facilities must have capacity to control
process generated waste water and runoff from a 25-year, 24-hour rain-
fall event.

Michigan feedlots are generally less than 1,000 head capacity;
therefore, they are not explicitly covered by rules made by EPA to date.
However, regulations are to be made in the near future to deal with the
smaller feedlots of less than 1,000 head capacity or the type generally
found in Michigan and surrounding states.

Before establishing the two level compliance schedule for feed-
lots with 1,000 head or greater capacity, the EPA completed a study of
the abatement technologies that might be used to control feedlot pol-
lutants.1 From this study and from interaction with those concerned
with feedlot production and pollution, the two level runoff compliance
rule was established for feedlots of greater than 1,000 head capacity
to be effective April 15, 1974. During the interaction period prior
to the establishment of the initial set of EPA regulations, the EPA

 

‘Environmental Protection Agency, op. cit.

159

commissioned a study of the economic effects of the application of the
two level compliance schedule to all feedlots including those of less
than 1,000 head capacity.2 This static analysis made by Development
Planning and Research Associates, Inc. considered price effects, finan-
cial effects, production effects, and effect on community and employment.
The study concluded that feedlots of less than 1,000 head capacity would
be affected the most severely while changing the overall industry supply
relationship minimally.

A study completed prior to the initial proposal of effluent
limitation guidelines by EPA identified economies of size that prevailed
in feedlot runoff abatement.3 Initial capital requirements and annual
operating costs were estimated for feedlots which would be subject to
the two level runoff control program. This study found substantial
economies of size in adjustments to the proposed guidelines. It was
estimated that approximately 95 percent of the investment required would
be incurred by operations of less than 1,000 head capacity if all feed-
lots with point source control problems were included in the two level
abatement program.

Studies in Oklahoma,“ Nebraska,5 and Minnesota6 analyzed abate-
ment rules similar to the two-level abatement program established by the

EPA. In each study economies of size in runoff were identified and

 

zDavid, Seltzer, and Eickhoff, op. cit.
3Johnson and Davis, op. cit.

I’Cross, op. cit.
sDaiss, op. cit.
6Pherson, op. cit.

160

estimates were made concerning the different impact that these
technologies would have on feedlots of different sizes.

While these studies are helpful in identifying some of the
economies associated with runoff control, little can be said about
the costs of runoff control in terms of its effect on production and
its costs to feedlot owners. To paraphrase Johnson and Davis, the
static analysis is somewhat limited in nature. In order to fully
understand the effects of rules for the control of water pollution,
paths of feedlot adjustment must be identified. Knowledge of production
systems, costs relationships, operator equity positions, access to
capital sources, and expectations concerning beef and input prices
would have to be included in the analysis.

The simulation model constructed for this study attempted to
investigate the paths of adjustment of feedlots before and after being
subjected to selected rules and acceptable methods and practices for
water pollution control. The simulation model simulated the production
of several individual farm-feedlot firms through a specified time
horizon. Each firm was given certain initial financial and production
characteristics. It was then allowed to develop expectations concerning
exogenous prices and expectations concerning its production function and
to use a profit maximizing objective function in making a decision con-
cerning the inputs to employ during a given time period. The firm
attempted to produce the level of output which it considered to be the
most profitable and employed those inputs which it expected to achieve
the most profitable level of output. The model simulated the firm's

161

operation with the actual prices received (gx_pp§t_prices) being
different than the expected prices (gx_pptg_prices). Similarly, the
firms gx_pp§t_production function was different than the §x_aptg.
production expected when the production decision was made. It made
decisions based upon ex.gptg_functions but had its financial success
determined by exogenous gx_pp§t_functions.

Rules for water pollution control affected the firm's behavior
by changing the gx_pptp_and gx_pp§t_production functions. Upon the
imposition of a rule and/or method and practice, the cost structure of
the firm was changed with the addition of pollution abatement controls.
The firm made a decision concerning the resources to employ based on
the expectations of how the pollution abatement control would affect
the profitability of various types of feedlot investment and off-feedlot
investment. This decision determined inputs to be used and could have
affected the firm's output relative to its performance when no rules
for pollution abatement was imposed. Thus, the imposition of each rule
could have affected not only the cost structure of the feedlot, but also
the amount of beef fed.

The price expectations for inputs and outputs were "naive"
models which base future prices on past prices. Salvage values that
were anticipated for durable assets were a function of age, user cost
(U) and replacement prices of similar assets. User cost of the economic
depreciation was treated as some constant percentage of the salvage
value in the current year. The effect of this assumption was that the

anticipated salvage value of a durable asset declined in a decay function

162

manner through time. Feeder cattle price expectations were a function
of expected slaughter prices and the current price margin. Slaughter
cattle price expectations were a function of current feeder cattle
prices, the current margin, and the change in slaughter prices over
the past six months. Nondurable input expected prices and land
expected prices were a linear trend of current prices.

The expected input and output relationship on simulated feedlots
was a function of the type of feedlot technology used on the feedlot.
The firm was assumed to face several mutually exclusive alternatives
for its assets. It may have retained the current feedlot technology
at a size level less than or equal to capacity; it may have invested
in off-feedlot investment; or it may have invested in one of ten feedlot
technologies. The firm expected that each of the alternatives would
combine inputs in fixed proportions and attain constant return to scale.
Capacity was constrained by labor requirements and by the borrowing
limitation (Blim) which placed a constraint on the proportion of total
assets that could have been obtained through external financing.

The decision making process was a mathematical programming
formulation to a capital budgeting problem. The firm faced twelve
mutually exclusive investment alternatives and the objective was to
maximize the expected present value of cash flows from the investments.
Continued production in the old feedlot was constrained by four factors:
labor, capacity, equity, and borrowing limitations. Investment in off-
feedlot investments was constrained by the equity position of the firm.

Each firm evaluated these investment alternatives during each year of

163

the 1960-85 simulated time period. The firm either salvaged the
present facility and invested in new facilities, retained the present
facilities, or salvaged the present facilities and invested in off-
feedlot investments. The salvaging of durable assets could have
occurred by either selling the durable assets to another or using

the durable asset in another activity where the marginal value product
was equal to the stated salvage prices.

Once the production decision was made in a year, the decision
was simulated by using a component developed from the Hughes simulation
model as the gx_pp§t_input-output relationship. The model employed a
whole farm approach to feedlot production by simulating not only feedlot
design and beef production, but also the production of crops necessary
to feed the cattle, transportation and storage function, and waste
removal function. In addition, the model was modified to simulate
runoff abatement requirements and costs and solid waste management
investment requirements and costs.

The accounting function then calculated and recorded the
financial success of each firm during each year. §x_pp§t_prices for
inputs and outputs were used to calculate the earnings for the year.
§x_pp§t_price models for land, nondurable, and durable inputs were
linear trends of past prices. §x_pp§t_price models for feeder cattle
and slaughter cattle were each comprised of a Fourier series which
enabled the price equation to closely approximate historical cyclic
movements. Along with earnings, calculations were made of taxes and
changes in salvage values of durable assets in order to determine the

equity positions of the firm at year's end.

164

The path of the simulated feedlots behavior was ready to
observe except for a few critical unknowns. These unknowns included
the determinant of the firm's initial financial positions (K), the debt
limit faced by the firm (Blim), the off-feedlot opportunity cost of
capital (R), beginning age of feedlot (B) and annual user costs (U).
The variable K determined the shape of the net worth distribution of
Michigan feedlots. By changing this value, the distribution (an Erlang
function) could have assumed a variety of shapes from an exponential
distribution to a normal distribution. After a mean net worth was
selected and the parameter K was chosen, initial net worths of the
simulated firms were selected randomly from the resulting probability
density function. These firms were simulated through the 1960-85
period under assumed values for the borrowing limit (Blim), opportunity
cost of capital (R), determinant of the user cost (U), and the beginning
age of feedlots (8).

Infinite combinations of values for the unknown variables were
possible. What was desired was that combination of values which made
the simulated firms' performance duplicate the performance of the feed-
lots represented by the model. In an effort to find values for the
unknown parameters which enabled the model's results to approximate the
real world, an optimization procedure was employed. This optimization
procedure was composed of (l) the "simplex" method (not to be confused
with the linear programming simplex method) to search for a local
optimum, and (2) a coarse grid approach to find if the local optimum

found through the simplex method was the optimum over all values of the

165

unknowns. In both, the simplex method and the coarse grid approach,
the idea was to systematically search for that combination of parameter
values which resulted in the simulated firms‘ most accurate representa-
tion of real world data.

When the optimization procedure was applied to the simulation
model constructed for this study, it determined the values of K, Blim,
U and R. (K==2, a distribution skewed to right; Blim==1.25, net worth
must have been greater than or equal to 1.25 times debt for each firm;
R==0.06, the return on off-feedlot investment was equal to 6 percent;
and U==0.9, the durable asset user cost determined where salvage

e = U(age Of asset) replacement value.) The values for the mean

valu
net worth were assumed to be equal to $80,000 in 1960, and the initial
age of each simulated feedlot was randomly selected from a uniform dis-
tribution with a range of one to fifteen years.

The performance of simulated feedlots over the 1960-85 period
was observed through four variables calculated each year during the
simulated period. The four variables were (1) the total capacity for
the simulated firms, (2) the ratio of production costs to total assets,
(3) the mean annual return to equity, and (4) the annual change in the
equity position. The purpose of these performance measures was twofold.
First, they provided a method to test the consistency of the model with
the real world. Second, they provided a method of calculating the costs

of selected rules and acceptable methods and practices to the simulated

firms and the effects that these policies had on production.

166

The rules analyzed included requirements that (1) all firms
have the capacity to control the runoff from a lO-year, 24-hour storm
by 1977 and to control the runoff from a 25-year, 24-hour storm by
1983; (2) all firms have the capacity to control the runoff from a
25-year, 24-hour storm by 1977; (3) all firms have the capacity to
control runoff from a 6 month rainfall; and (4) the acceptable method
and practice of no winter solid waste spreading occur plus the rule
that all firms have the capacity to control runoff from a 6 month
rainfall.

The performance of feedlots were analyzed over 12 assumption
sets concerning values for the unknown variables. The first assumption
set was employed to estimate the costs involved with each of the four
selected rules. The second set of assumptions was employed to describe
their regressive nature. Assumption sets 3-12 were used to test the
sensitivity of the model to small changes in the values of critical
parameters.

The four rules each reduced production and imposed costs on
producers over the 1974-85 period relative to the "do nothing" rule.
The rule that all firms have the capacity to retain runoff from a 10-
year, 24-hour rainfall event by 1977 and from a 25-year, 24-hour rain-
fall event by 1983 resulted in a 7.0 head per firm relative decline in
production and a present value of equity losses of $3,724 per firm over
the entire 1974-85 period. Assuming the number of feedlots under 1,000
head remains constant, this loss was equal to 11,200 head in Michigan

feedlot production or 0.167 percent of the total. The present value of

167

The equity loss to the Michigan feedlot industry was $6.26 million

over the 1974-85 period. The second rule, a requirement that firms
have the capacity to retain a 25-year, 24-hour rainfall event by 1977,
had nearly the same impact as the first rule.7 The relative decline

in production over the entire period was 7.2 head per firm or 11,800
head for the twelve years for Michigan feedlots or 0.17 percent of the
total. The present value of the loss to feedlots was $3,911 per firm
for the period and $6.57 million for the Michigan feedlot industry for
the 1974-85 period. The third rule, a requirement that feedlots have
the capacity to retain a 6 month rainfall, resulted in a cost of $4,800
per firm and a relative decline in production of 37.7 head per firm over
the period. This decline represents approximately 0.90 percent of the
total production. In the Michigan feedlot industry for the 1974-85
period the cost was $8.06 million with a 63,000 head relative decline
in production. The last rule, controlling runoff from a 6 month rain-
fall with an acceptable method and practice of not permitting winter
spreading was the most severe. Equity losses amounted to $5,990 per
firm and $10.06 million for Michigan feedlots. Production declined by
38.3 head per firm and 64,000 head for the industry relative to the "do

 

7This finding conflicts with recent Department of Agriculture
testimony before the House Subcommittee of the Committee on Government
Operations.’ Their testimony was ". . . costs would average 10 to 15
percent higher, and possibly as much as 45 percent, to provide a system
for containing required process waste water and runoff from a 25-year,
24-hour rainfall event than for containing required process waste water
and runoff from a lO-year, 24-hour rainfall event." U.S., Congress,
"Control of Pollution from Animal Feedlots," Hearing before a Subcom-
mittee of the Committee on Government Operations, November 30, 1973,
p. 893.

168

nothing" rule or 0.91 percent of the total. In any of the four policy
situations, the asset structure of the feedlot changed very little. The
ratio of variable cost to total assets changed little among the policy
alternatives.

Any of the above policies had a regressive impact on feedlot
producers. After reducing the 1973 net worth from $220,000 to $105,000
the simulated firms suffered substantially more than their more wealthy
counterparts. A measure of this regressive impact was the comparison
of the cost of a rule over the 1974-85 period as a proportion of 1974
equity. The cost of a policy to the feedlot owner was the discounted
difference between the annual change in net worth under the policy and
the annual change in net worth under a “do nothing" rule. For the feed-
lots with a 1974 equity position of $220,000, the present value of
equity losses equaled 1.69 cents, 1.78 cents, 2.18 cents, and 2.72 cents
per dollar initial equity for the four rules. For the lower equity
firms, the present value of equity losses totaled 3.13 cents, 3.31 cents,
4.74 cents and 5.46 cents per dollar initial equity for the four rules.

The sensitivity analysis demonstrated the sensitivity of model
results to small changes in critical parameters. Small changes were
made in the parameters from those values found through the optimizing
procedure and used in calculating cost estimates. The parameter R or
the off-feedlot rate of return had relatively little impact on the
results. The determinant of the shape of the net worth distribution (K)
also had a relatively small impact. Parameters that were critical to

the simulation model results included the determinant of the amount that

169

can be borrowed, the determinant of the user cost of durable assets,
the mean initial net worth of the simulated firms, and the initial age
of the feedlots; furthermore, the user cost determinant appeared to be
the most critical parameter. The effects of the environmental selected

rules appeared to be nearly the same regardless of initial feedlot age.

Implications

 

The focus of this study is to trace the changes in feedlot
behavior as a result of various water pollution control rules and
acceptable methods and practices. Associated with these changes are
costs and benefits accruing to the feedlot owners, those individuals
who are in the proximity of feedlots and are affected by feedlot pol-
lutants, and to those who are not directly affected by the pollutants
but whose welfare is touched by the change in production. The effects
of the four rules on each of these groups are approximated. Further-
more, these effects have implications for the agencies implementing
the policies.

The feedlot operators witness three changes in their welfare
as a result of the rules. First, their equity positions decline.

Rule A has a mean cost of $3,724 per firm, rule 8 costs $3,911 per firm,
the cost of rule C is $4,800 per firm, and rule 0 costs a mean of $5,990
per firm over the 1974-85 period. These costs are mean values and vary
with the feedlot technology type and size. For the feedlot with open
lot construction, the abatement costs are going to be large relative

to the costs of the more confined facilities. These high abatement

170

costs for the open lot construction may even result in a shift to more
land intensive feedlot construction in many feedlots. Economies of size
result from the imposition of the rules investigated in this study. The
cost of these policies per pound of beef produced may be as high as one-
half cent per pound for the 100 head capacity lot compared to one-tenth
cent per pound for the 900 head capacity lot. Second, feedlot operators'
asset structure may be changed slightly with the imposition of a rule.
This change may be important to feedlot operators since it would cause
additional fixity in the asset structure with an increase in proportion
of durable assets required. Each of the four rules is found to have a
minor impact on the asset structure of the firm; therefore, this cost is
insignificant. Third, the distribution of wealth of the feedlot owners
is influenced by these policies. Due to the economies of size asso-
ciated with feedlot input standards, runoff control and acceptable
methods and practice for animal wastes are highly regressive in nature.
By reducing the simulated firms' equity positions by one-half, the cost
per dollar equity nearly doubled under the four action rules under
investigation.

For those living in close proximity to feedlots, few costs are
imposed by these rules. The benefits include (1) zero runoff from feed-
lot into local streams, rivers and lakes, and (2) possible reduction in
odoriferousness. In addition, a practice of no winter spreading (rule
0) would decrease the runoff from solid waste spread on fields. Again,
these benefits must be expressed in qualitative terms since a unit of
measure is not available; however, they should be a consideration in

any policy development.

171

Those not in close proximity to feedlots may be affected by

the reduction in feedlot production due to the effects the rules have

on their consumption pattern. Consumers would be affected by any higher
prices and reduced quantities. A rough estimate of the loss suffered by
consumers would be the loss in consumer surplus as a result of the rule.
Small feedlot production (less than a 1,000 head capacity) accounts for F1
approximately 48 percent of the total fed beef marketings. Assuming
that all small feedlots' behavior changes are similar to changes in

Michigan feedlot behavior, small feedlots' fed beef marketings would

 

decline by 0.167 percent under rule A, 0.17 percent under rule 8, L3
0.90 percent under rule C, and 0.91 percent under rule 0 vis a vis a

I'do nothing" policy. Assuming the demand price flexibility is 1.73 for

beef,8 the change in consumer surplus would be approximated under each

rule by the following:
s=f9§py

where s - consumer surplus,

f

price flexibility,
%§-- percent change in quantity produced as a result of a rule,

py = discounted value of livestock production over the twelve
year time horizon.

 

°R. L. Trimble, "An Economic Analysis of the Effect of Monetary
Policy on the Beef Industry" (unpublished Ph.D. thesis, Michigan State
University, 1973).

172

A rough estimate of the loss in consumer surplus is $13.11 million

from rule A, $13.35 million from rule 8, $70.65 million from rule C

and $71.44 million from rule 0 over the 1974-85 period. Furthermore,
this estimate is made under the assumption that feedlots of greater
than 1,000 head capacity do not increase production. It is likely that
the effect on consumer surplus would be even less than these estimates
as some of the production decline by the small feedlots of greater than
1,000 head capacity. Thus, the effect on the individual consumer is
near zero.9

The implication of this study for the Environmental Protection
Agency is that the rules considered in this study appear to have (1)
minimal impact on the consumption pattern of individual consumers,

(2) an effect on the net worth position of feedlot owners, (3) a
regressive impact on feedlots of smaller sizes, (4) increasing incen-
tives to not comply with the rules as feedlot capacity decreases, and
(5) highly uncertain and unidentified benefits.

The discounted value of consumer losses over the entire 1974-75
period averages less than three dollars per consumer under any of the
four policies. Prices of beef would increase by less than 1.5 percent
under each of the rules and quantities of fed beef marketings would
also decline by less than 1 percent.

The equity loss per feedlot owner is not minimal and cannot be
ignored. The present value of equity losses over the twelve year period
have a mean value of $3,700, $3,900, $4,800 and $5,900 per firm for

the four rules.

 

9See Appendix D-l.

 

173

The skewed nature of the net worth distribution of feedlot
operators and the regressive nature of the water pollution control
rules produce equity questions that cannot be ignored. Since the size
distribution is skewed to the right, a large proportion of feedlots
produce less than the mean and have net worths less than the mean.

For these operators the relative cost of compliance is much greater
than their wealthier competitors.

In addition, this relativelyhigh cost (cost/equity) produces
larger incentives for the small firms to not comply with the standards.
If compliance by all lots is desired, most of the administrative costs
would be spent on monitoring small feedlots.

The benefits of the rules considered would be a reduction in
the runoff from feedlots and from frozen fields to which feedlot wastes
are applied. Undoubtedly many feedlots of less than 1,000 head capacity
produce pollutants which are destructive to the environment. A drive
through a rural country side enables one to see many instances of live-
stock which has direct access to streams that allow livestock wastes to
flow to rivers and lakes. However, other small feedlots may be long
distances from streams, drainage ditches, or tile which feed navigable
waters, and the environmental damage caused by these feedlots may be
nonexistent. While there exist benefits from each of these rules in
terms of improved water and air quality, the quantification of these
environmental benefits remains to be achieved. As a result, an approx-
imation of costs to consumers and feedlot owners is possible, but the

benefits to producers, those living in proximity to feedlots, and those

_‘w
' .J

 

11.1w!” Jo Ind” A. . 1H .‘ain .
l- ‘1

174

individuals whose water supply is damaged by livestock pollutants
are uncertain.

This study also has implications for the Michigan Water Resources
Commission or any state agency given the responsibility of guarding the
state's water quality and/or administering federal rules. More severe
rules than the extension of the EPA guidelines to feedlots of less than
1,000 head capacity may present penalties to the state's feedlot industry.
In the case of requiring Michigan feedlots to retain the runoff from a
six month rainfall, the mean present value of the cost over the next
twelve years is approximately $1,000 per firm above the costs associated
with extending current EPA guidelines. The imposition of the acceptable
method and practice of abolishing winter spreading of solid wastes also
seriously affects the mean feedlot equity. The magnitude of these
equity losses over 1974-85 is approximately $2,200 per firm greater than
those costs per firm when the EPA guidelines are extended. In addition,
the costs associated with enforcing these more severe rules would be
higher due to the incentives made available for small firms to offer
less than their full cooperation. If feedlot owners have sufficient
incentives to disregard the rules, nothing is gained by establishing

the severe rules.

Suggestions for Future Research

 

Interaction between the public, feedlot operators, and the
decision makers is needed to identify those society goals that are

touched by rules such as the type investigated. This study has focused

 

175

on the influences that several rules have on production and feedlot
owners' positions. Other output variables that are to be measured
include those influencing environmental quality. Through interaction
between those affected by the policies and the decision makers in the
environmental area, these unknown variables can be better identified.
Future research would estimate the effects of rules on those parameters
identified as being important to those individuals affected by feedlot
pollutants.

The geographic scope of study should be extended to include
major corn belt beef producing states. The number of feedlots in this
area is large in comparison to the total number of United States feed-
lots and produce a significant amount of the nation's beef supply.

Finally, the simulation approach lends itself well to research
in the environmental area. The lack of an objective function for the
decision maker to maximize, the lack of a common denominator, and the
uncertainty concerning the relevant unit of measurement requires a
display of several output variables in order to assist the decision
making. Furthermore, these output variables must be amenable to change
in order to accommodate new variables produced by the interactive
process. Simulation by computer enables the investigator to accommodate
these requirements while enabling the decision makers to view an array

of outputs for the feasible rules alternatives in a short time period.

 

APPENDICES

 

that
c 3‘

“Vi -..a .-

APPENDIX A-l

El ANTE PRICE INDICES PRODUCED BY PRICE EQUATIONS
AND USED IN SIMULATION MODEL

 

 

(l972=l.00)
Inputs
Year Machinery Buildings Fertilizer Other
1960 0.671 0.812 1.000 0.557
1961 0.695 0.828 1.000 0.585
1962 0.719 0.844 1.000 0.614
1963 0.744 0.861 1.000 0.645
1964 0.770 0.879 1.000 0.677
1965 0.797 0.896 1.000 0.711
1966 0.825 0.914 1.000 0.746
1967 0.854 0.932 1.000 0.784
1968 0.884 0.951 1.000 0.823
1969 0.915 0.970 1.000 0.864
1970 0.947 0.989 1.000 0.907
1971 0.980 1.000 1.000 0.952
1972 1.000 1.020 1.000 1.000
1973 1.040 1.040 1.040 1.040
1974 1.082 1.082 1.082 1.082
1975 1.125 1.125 1.125 1.125
1976 1.170 1.170 1.170 1.170
. 1977 1.217 1.217 1.217 1.217
1978 1.265 1.265 1.265 1.265
1979 1.316 1.316 1.316 1.316
1980 1.369 1.369 1.369 1.369
1981 1.423 1.423 1.423 1.423
1982 1.480 1.480 1.480 1.480
1983 1.539 1.539 1.539 1.539
1984 1.601 1.601 1.601 1.601
1985 1.665 1.665 1.665 1.665

176

 

FEEDER AND SLAUGHTER CATTLE PRICE PER POUND PRODUCED
BY PRICE EQUATIONS AND USED IN SIMULATION MODEL

Feeder Cattle

APPENDIX A-3

 

Ex Ante

Ex Post

OOOOOOOOOOOOOOOOOOOOOOOOOO

178

Slaughter Cattle

 

Ex Ante

Ex Post

0.20
0.20
0.20
0.21
0.20

PPOPOPPPOOOOPPPP...
4)
O

APPENDIX B-l

PERFORMANCE VARIABLES 0F SIMULATED FEEDLOTS,
1974-85, ASSUMPTION SET 3

 

 

 

 

 

 

Mean Feedlot Variable Weighted Average Initial Equity

Ca acit Cost7Asset Return to Equity, and'Changew
(Head) (Ratio) (Ratio) (§)
205.6 0.0718 0.0829 77,744
205.9 0.0748 0.0762 4.412
201.8 0.0784 0.0682 4.280
205.6 0.0814 0.0653 4.680
212.0 0.0839 0.0552 4.620
217.1 0.0870 0.0623 5.855
220.0 0.0903 0.0642 7,086
230.1 0.0935 0.0572 7.500
235.1 0.0972 0.0533 8.063

. 245.1 0.1009 0.0606 10,650
247.9 0.1052 0.0565 10,815
262.2 0.1092 0.0621 13,629
270.9 0.1130 0.0687 16.730
285.0 0.1176 0.0697 19,382
276.1 0.1262 0.0659 19.620
317.2 0.1266 0.0729 25.998
327.0 0.1292 0.0749 29.523
337.8 0.1342 0.0709 31.862
353.6 0.1378 0.0757 37,866
356.3 0.1390 0.0712 40.534
364.3 0.1407 0.0745 46.922
367.5 0.1409 0.0719 51,041
367.5 0.1398 0.0725 57,033
367.6 0.1381 0.0713 62,600
367.7 0.1382 0.0698 68,060
368.0 0.1385 0.0687 73.654

179

APPENDIX B-2

PERFORMANCE VARIABLES OF SIMULATED FEELOTS,
1974-85, ASSUMPTION SET 4

 

 

 

 

 

 

Mean Feedlot Variable Weighted Average Initial Equity n
Year Ca acit Cost/Asset Return to Equity and'Change 1’
(Head) (Ratio? (Ratio) (5) ‘
1960 199.1 0.0725 0.0806 77.821
1961 200.3 0.0752 0.0737 4.603
1962 202.3 0.0781 0.0691 4.365
1963 215.6 0.0797 0.0695 5.704
1964 218.9 0.0815 0.0548 5.725
1965 206.3 0.0865 0.0581 5.505
1966 227.8 0.0898 0.0666 8,080
1967 230.6 0.0915 0.0570 8,650
1968 228.5 0.0931 0.0527 9.339
1969 224.9 0.0988 0.0551 9.873
1970 255.7 0.1040 0.0570 11,865
1971 259.6 0.1065 0.0606 14.423
1972 265.4 0.1115 0.0654 16.454
1973 296.2 0.1159 0.0704 20.901
1974 296.1 0.1166 0.0717 24.282
1975 301.2 0.1230 0.0679 24.795
1976 339.5 0.1269 0.0763 31,749
1977 336.5 0.1305 0.0705 32.633
1978 349.3 0.1334 0.0745 38,449
1979 355.8 0.1362 0.0710 41,167
1980 366.6 0.1367 0.0746 48.485
1981 366.6 0.1354 0.0718 52.443
1982 368.0 0.1349 0.0720 58,181
1983 368.1 0.1352 0.0701 63.136
1984 366.0 8.1335 8.0690 58.776
5

1985 367. .1353 .0674 74.632

180

1.. .I -
a.

 

APPENDIX B-3

PERFORMANCE VARIABLES 0F SIMULATED FEEDLOTS.
1974-85, ASSUMPTION SET 5

 

 

 

 

 

 

Mean Feedlot Variable Weighted Average Initial Equity
ngr Ca acit Cost/Asset Return to Eqfiity and Change
(Head) (Ratio) (Ratio) (§)
1960 209.7 0.0713 0.0847 78.541
1961 207.2 0.0748 0.0766 4,359
1962 206.3 0.0779 0.0702 4.454
1963 214.3 0.0803 0.0680 5.446
1964 214.9 0.0838 0.0553 4.612
1965 224.7 0.0863 0.0643 6.831
1966 225.4 0.0900 0.0656 7.499
1967 232.7 0.0936 0.0564 7.397
1968 239.1 0.0968 0.0533 8.295
1969 246.7 0.1008 0.0597 10,357
1970 256.6 0.1048 0.0570 11.548
1971 266.7 0.1091 0.0609 13,930
1972 278.2 0.1130 0.0692 17.187
1973 287.5 0.1176 0.0690 19.337
1974 283.6 0.1261 0.0669 20.064
1975 319.3 0.1264 0.0724 26.015
1976 330.4 0.1297 0.0751 29.665
1977 340.6 0.1335 0.0712 32.356
1978 356.5 0.1374 0.0758 38,279
1979 359.8 0.1381 0.0715 41.191
1980 364.3 0.1394 0.0741 47.220
1981 367.5 0.1384 0.0720 51.835
1982 367.5 0.1380 0.0722 57,463
1983 367.7 0.1358 0.0712 63,432
1984 367.1 0.1368 0.0690 68.213
1985 368.0 0.1370 0.0683 74.068

181

APPENDIX B-4

PERFORMANCE VARIABLES 0F SIMULATED FEEDLOTS,
1974=85, ASSUMPTION SET 6

 

 

 

Mean Feedlot Variable Weighted Average Initial Equity
Ca acit Cost/Asset Return to Eguity and Change
(Head) atio TRatiSTS ($)
219.5 0.0714 0.0853 86.099
227.4 0.0738 0.0812 5,533
221.4 0.0777 0.0722 5,258
227.8 0.0803 0.0705 6.204
232.6 0.0833 0.0559 5.142
248.1 0.0854 0.0669 8.034
241.3 0.0902 0.0645 7,941
256.3 0.0929 0.0578 8,342
256.7 0.0969 0.0524 8.668
269.9 0.1004 0.0611 11.416
272.3 0.1051 0.0556 11,643
290.3 0.1088 0.0621 15.131
293.4 0.1136 0.0678 17,296
311.3 0.1178 0.0700 20.619
323.0 0.1222 0.0726 23,776
344.4 0.1259 0.0727 27.606
347.4 0.1297 0.0751 30.672
363.6 0.1331 0.0713 33.597
367.8 0.1360 0.0747 38,861
370.9 0.1354 0.0711 42.219
374.9 0.1363 0.0738 48,351
377.6 0.1350 0.0720 53.127
381.0 0.1352 0.0728 59.359
383.3 0.1343 0.0717 65.501
381.6 0.1349 0.0692 70,173
384.7 0.1389 0.0686 76.594

182

 

 

gar J -

 

1m“

a.‘_ .-f_

APPENDIX B-5

PERFORMANCE VARIABLES 0F SIMULATED FEEDLOTS,
1974-85. ASSUMPTION SET 7

 

 

 

 

 

. . 'f"

Mean Feedlot Variable Weighted Average Initgal Equity
Year Ca acit Cost7Asset Return to Equity an Chan e
(Head) (Ratio) (Ratio) (5)
1960 207.0 0.0728 0.0843 77.916
1961 217.5 0.0750 0.0814 4,851
1962 214.7 0.0785 0.0727 4.748
1963 226.6 0.0806 0.0722 6,054
1964 222.9 0.0844 0.0568 4.707
1965 237.7 0.0868 0.0672 7.356
1966 233.3 0.0911 0.0660 7.530
1967 248.7 0.0941 0.0603 8.253
1968 251.4 0.0976 0.0548 8.700
1969 262.2 0.1017 0.0621 11.306
1970 271.1 0.1058 0.0583 12,121
1971 285.7 0.1099 0.0635 15.126
1972 292.0 0.1142 0.0703 17.879
1973 310.5 0.1182 0.0718 21,119
1974 296.8 0.1276 0.0682 21,191
1975 339.1 0.1272 0.0739 27.869
1976 326.4 0.1342 0.0710 28,041
1977 356.6 0.1346 0.0725 33.596
1978 363.4 0.1373 0.0757 38,999
1979 366.9 0.1364 0.0723 42,514
1980 367.3 0.1369 0.0743 ' 48.198
1981 367.3 0.1352 0.0718 52,560
1982 367.3 0.1347 0.0721 58,035
1983 367.6 0.1323 0.0711 63.833
1984 360.0 0.1323 0.0694 68,884
1985 367.6 0.1341 0.0678 74,341

183

..4 Ii".o .'

 

APPENDIX B-6

PERFORMANCE VARIABLES 0F SIMULATED FEEDLOTS,
1974-85, ASSUMPTION SET 8

Mean Feedlot Variable Weighted Average Initial Equity

 

 

 

 

 

 

Year Ca acit Cost/Asset Return to quity, and Change_
(Head) (Ratio) (Ratid) (§)
1960 203.1 0.0709 0.0824 78,283
1961 191.7 0.0756 0.0694 3.527
1962 194.1 0.0780 0.0663 3,930
1963 201.6 0.0803 0.0643 4,833
1964 203.2 0.0834 0.0526 4.076
1965 208.9 0.0864 0.0605 5,993
1966 211.9 0.0897 0.0631 6,953
1967 216.9 0.0934 0.0537 6,751
1968 222.5 0.0966 0.0509 7.588
1969 228.8 0.1006 0.0570 9.431
1970 236.9 0.1044 0.0544 10.452
1971 246.2 0.1086 0.0587 12,724
1972 253.4 0.1128 0.0656 15,310
1973 246.4 0.1215 0.0602 15,207
1974 282.8 0.1219 0.0715 21.256
1975 295.1 0.1263 0.0703 23,765
1976 311.5 0.1303 0.0743 27.711
1977 322.9 0.1350 0.0700 30,031
1978 336.6 0.1391 0.0745 35.556
1979 346.8 0.1411 0.0711 38.774
1980 352.7 0.1435 0.0748 45.126
1981 360.7 0.1431 0.0723 49.288
1982 365.3 0.1433 0.0735 55.501
1983 367.2 0.1408 0.0729 61.817
1984 360.7 0.1420 0.0707 66,223
1985 367.2 0.1423 0.0697 72.566

184

APPENDIX B-7

PERFORMANCE VARIABLES 0F SIMULATED FEEDLOTS.
1974-85, ASSUMPTION SET 9

Mean Feedlot Variable Weighted Average Initial Equity

 

 

 

 

 

 

Year ca aEit Cos sset Return to Eduity and Change
(Head) (Ratio) (Ratio) (§)
1960 222.8 0.0695 0.0954 79,094
1961 224.0 0.0726 0.0874 5,466
1962 228.8 0.0746 0.0827 6.523
1963 242.9 0.0760 0.0817 8,100
1964 232.1 0.0796 0.0616 3.265
1965 228.9 0.0822 0.0674 4.296
1966 226.9 0.0867 0.0686 4,697
1967 232.7 0.0909 0.0597 3,752
1968 236.0 0.0931 0.0573 6,420
1969 236.1 0.0955 0.0631 9.251
1970 237.3 0.0985 0.0584 10.311
1971 241.1 0.1030 0.0610 11,379
1972 248.6 0.1089 0.0673 12,764
1973 265.3 0.1148 0.0705 13,118
1974 276.9 0.1169 0.0761 18.680
1975 276.7 0.1173 0.0740 21,841
1976 284.5 0.1182 0.0769 25.785
1977 294.2 0.1229 0.0736 27.296
1978 314.3 0.1351 0.0762 27,962
1979 360.7 0.1415 0.0790 36,325
1980 360.1 0.1395 0.0824 43,341
1981 371.5 0.1368 0.0821 51.384
1982 372.8 0.1393 0.0805 53.583
1983 397.8 0.1413 0.0822 64.690
1984 397.7 0.1455 0.0792 65.103
1985 412.0 0.1431 0.0812 77,435

185

.mi' 1‘ .5
ah,
.i, qua—v

 

17.—
l

Year

1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985

PERFORMANCE VARIABLES 0F SIMULATED FEEDLOTS,

Mean Feedlot

 

Cdiacit
(Head)

200.

9

220.0

240.
263.
288.
311.
340.
370.
386.
417.
436.
447.
458.
470.
484.
500.
519.
534.
552.
573.
597.
621.
641.
653.
675.
690.

mono—Imwxi—aw—IooauotowA—uooomm—Imoo

APPENDIX B-8

1974-85, ASSUMPTION SET 10

Variable
Cost7Asset

 

(Ratio)

.0723
.0743
.0764
.0786
.0811
.0839
.0867
.0896
.0934
.0950
.0970
.0986
.0993
.0999
.1007
.1015
.1034
.1071
.1114
.1168
.1225
.1277
.1320
.1363
.1401
.1431

OOOOOOOOOOOOOOOOOOOOOOOOOO

186

Weighted Average

Initial Equity

 

 

Return to Equity

 

(Ratio)

and Changes

83.885
11,848
13.449
15.264
15,898
19,457
23.200
24,635
25,912
32,030
34,670
39,494
46,348
51,244
57,934
63.734
71.675
76.375
85.728
91,004
102.195
110,125
121,785
132,068
143,733
157,324

In ' U.
..
4i

_ A.
..p.

 

APPENDIX B-9

PERFORMANCE VARIABLES 0F SIMULATED FEEDLOTS,
1974-85, ASSUMPTION SET 11

Mean Feedlot Variable Weighted Average Initial Equity

 

 

 

 

 

 

Year Ca acit Cost/Asset Return to Equity and Change_
Hea (Ratio) (Ratio) (§)
1960 226.3 0.0696 0.0921 81.302
1961 212.6 0.0745 0.0778 4.042
1962 219.7 0.0767 0.0744 5,148
1963 212.2 0.0808 0.0655 4,707
1964 228.0 0.0825 0.0595 5.648
1965 226.7 0.0865 0.0630 6.670
1966 239.7 0.0889 0.0690 9.088
1967 236.4 0.0933 0.0559 7.359
1968 252.7 0.0963 0.0554 9,193
1969 255.2 0.1005 0.0602 10.724
1970 271.5 0.1041 0.0592 12,778
1971 272.7 0.1089 0.0607 14.238
1972 286.0 0.1124 0.0717 18.946
1973 293.4 0.1170 0.0685 19.751
1974 328.2 0.1217 0.0753 25.401
1975 326.1 0.1250 0.0709 26.779
1976 352.1 0.1278 0.0767 32,529
1977 347.9 0.1310 0.0712 33.787
1978 362.9 0.1341 0.0751 39,789
1979 366.2 0.1334 0.0717 43,326
1980 368.1 0.1339 0.0739 49.195
1981 368.2 0.1315 0.0716 53.787
1982 368.3 0.1308 0.0719 59.580
1983 368.8 0.1305 0.0701 65.047
1984 368.8 0.1311 0.0684 70.151
1985 369.5 0.1340 0.0666 75.194

187

APPENDIX B-10

PERFORMANCE VARIABLES OF SIMULATED FEEDLOTS,
1974-85, ASSUMPTION SET 12

 

 

 

 

 

 

 

Mean Feedlot Variable Weighted Average Initial Equity
Year Ca acit Cost/Asset Return to Equity and Change
(Head) (Ratio) (Ratio) ($)
1960 200.9 0.0723 0.0805 76.794
1961 208.1 0.0744 0.0779 4.514
1962 195.9 0.0787 0.0657 3,614
1963 213.3 0.0801 0.0702 5.626
1964 209.1 0.0840 0.0543 4.448
1965 224.0 0.0860 0.0652 7.240
1966 218.6 0.0905 0.0631 6.790
1967 233.0 0.0934 0.0574 7.851
1968 233.2 0.0968 0.0525 8.161
1969 245.0 0.1007 0.0603 10.647
1970 255.7 0.1049 0.0561 11,200
1971 266.4 0.1091 0.0617 14.208
1972 270.9 0.1131 0.0681 16.611
1973 288.5 0.1179 0.0702 19.652
1974 299.2 0.1215 0.0721 22.626
1975 321.1 0.1265 0.0727 26.238
1976 326.7 0.1292 0.0744 29.428
1977 340.9 0.1333 0.0712 32.486
1978 355.7 0.1370 0.0757 38.336
1979 359.2 0.1378 0.0715 41,279
1980 364.3 0.1391 0.0741 47.319
1981 367.4 0.1381 0.0720 51,935
1982 367.4 0.1377 0.0722 57.566
1983 367.7 0.1362 0.0710 63.344
1984 367.1 0.1373 0.0688 68,080
1985 367.9 0.1373 0.0682 73.994

188

 

 

APPENDIX C-1

OUTPUT FROM THE HUGHES SIMULATION COMPONENT
UNDER SPECIFIED CONDITIONS

Specified Conditions: Ration = 1% Concentrates; Housing Type = Drylot;
Unpaved Silage Storage==Tower Silo; Runoff Abatement==Storage for 6 Inch
Rainfall Capacity--4ll Head; 1972 Prices.

Durable Inputs Required

 

1. Corn Storage in Tower Silos
Total Tons Stored: 3,027

 

Numberlof Silos: 3 1
Si 0 Height 0 ameter Cost
1 60 30 $14,843
2 60 30 14,843
3 55 30 13.702
Unloaders 9,172
Land 68
Miscellaneous 302
$52,932
2. Moist Corn Storage
Bushels Stored: 20,857
Number of Sealed Silos: 1
Cost of Silo $28,157
Miscellaneous 114
Land 16
Total Cost $28,287
3. Lot and Buildings Construction Cost
Shelter $20,000
Lot Preparation 750
Bunker 3,120
Waterer 1,800
Fence 1,822
Gates 325
Concrete 8,125
Land 2,210

189

 

190

4. Waste Disposal
Spreaders
Loaders

5. Runoff Abatement
Diversion Terrace
Settling Basin
Pond
Lining
Fence
Pump
Total

6. Silage and Corn Transport
Wagons
Transport Tractors
Blower Tractors
Blowers

7. Field Machinery
Tractor 1
Tractor 2
Combine
Moldboard Plow
Disc
Spring Tooth Harrow
Planter
Cultivator
Forage Chopper
Stalk Chopper
Total

8. Land Acres
Corn 199
Silage 199
Building & Lot 3

Nondurable Inputs Required

 

Annual Hours

 

Labor
Feeding 648
Waste
Disposal 98
Harvest Transport of Crops 1,461
Crops 529

Total 2,737

$1.244
1,200
$7717, 4

$435
172
114
1,143
219
2 219

$4,302

$5,361
1.257
3.670
900

$11,640
3,670
12.097
2.007
3.286
1,280
1.395
1,558
2,879
1,810
$44,692

$197,000

Cost

$13,685

 

191

Fertilizer and Herbicides

Supplement

Seed

Fuel

Repair

Insurance

Property Taxes

Interest on Short-Term Loan

Runoff Abatement Expenses

Feeder Calves @ $47.00/cwt.
Total

$12,126
9.896
3,421
1,005
3,079
289
5,431
17,147
452

128 662

5195.193

 

”14m...—
.. .
|
I

“‘8'

APPENDIX C-2

EXAMPLES OF INITIAL INVESTMENT COSTS FOR TWO HOUSING
SYSTEMS USING THE RUNOFF RETENTION SYSTEM USED
IN SIMULATION MODEL WITH THE CAPACITY TO
RETAIN A 6-MONTH RAINFALL

 

Drylot, Unpaved Housing System :

 

 

100 Head 500 Head 900 Head
Feedlot Feedlot Feedlot
Capacity Capacity Capacity , ,
Diversion Terrace 140 700 1,260
Settling Basin 34 172 '310
Holding Pond and Lining 569 2,578 4,540
Cost of Fence 147 328 441
Cost of Pump 2 145 2,219 2 219
Total 3,035 5,997 8,770

Drylot, Paved Housing,System

 

100 Head 500 Head 900 Head
Feedlot Feedlot Feedlot
Capacity Capacity Capacity
Diversion Terrace 33 163 294
Settling Basin 10 41 72
Holding Pond and Lining 157 656 1,132
Cost of Fence 71 158 313
Cost of Pump 2,145 2,219 2,
Total 2,416 3,237 3,930

192

APPENDIX D-1

FORMULAS USED IN COMPUTING RESULTS

Effect of a rule on production of simulated firms over the
1974-85 period.

20 1985

SPC = Z X C i-C *TR
n-l t=1974 "’p’t "’°’t
where n = simulated firm n

Cn p t = capacity of simulated firm n in tear t under rule p,
Cn o t = capacity of simulated firm n in year t under a "do

’ ’ nothing" rule,

TR = number of head produced per year/capacity of lots, and
SPC = simulated firms' production change.

Effect of a rule on Michigan production over the 1974-85 period.

MPC = SPC *NF/20

where MPC = Michigan production change.
SPC = simulated firms' production change, and
NF = number of Michigan feedlots of less than 1,000 head

capacity.

Cost of a rule to feedlot owners over the 1975-84 period.

i? 1%E4 (EQn,p,t'EQn,p,t)"(EQn.o,t'EQn.o.t.l)

SC =

 

n=l t=l975 (1+r)t

193

 

 

194

where n simulated firm n,

150

n,p,t = equity of firm n under rule p in year t,
r discount rate, and
SC cost of rule p to simulated firms.

Cost of a rule to Michigan feedlot producers.
MC = SC *NF/20 ‘3

where NF = number of Michigan feedlots of less than 1,000 N
head capacity. p

Cost of a rule to consumers. Under the heroic assumption that all
of the nation's small feedlots would behave in the same pattern as i
the simulated Michigan feedlots, the percentage change in fed beef 1*
marketings would be:

 

531:: $0 1985 SPC

q n=1 t=1974 Cn,o,t

E
:-
m
1
m
.018-
i

- percentage change in output from a small feedlot as a
result of a rule,

simulated firms' production change over the 1974-85
period as a result of a rule

C = capacity of simulated firm n in year t under a "do
nothing" rule.

(I)

.0

('3
1|

Supplies of fed beef on small lots would shift to the left by 0.167
percent under rule A, 0.17 percent under rule 8, 0.90 percent under
rule C, and 0.91 percent under rule 0.

Under the assumption that larger feedlots would not pick up this
decreased production pattern, the formula used to estimate consumer
surplus is:

s=fg§py

where 5 consumer surplus,

price flexibility, and

discounted value of feedlot livestock production over
the twelve year period.

195

Estimated consumer surplus is equal to the shaded portion of the
diagram shown below:

Price/Head Fed Beef

 

 

Quantity of Fed Beef
on Small Feedlots

Quantity of beef marketed on lots of less than 1,000 head capacity
are assumed to be equal to 11.344 million head.

Price per head marketed is assumed to equal $400 and beef prices
are assumed to increase annually by the same percentage as the
discount rate.

APPENDIX D-2

GLOSSARY OF TERMS

Regulation--a rule with uniform requirements imposed on the productive
processes of all firms. There is no attempt to prescribe
differences in conduct expected by different finns.

 

Directive--a rule directing the attainment of a particular standard.
It is less specific than a regulation in that it usually leaves
the choice of the combination of inputs necessary to achieve the
standard to the discretion of the operator.

Rule--a collective action initiated by a government agency. It may be
in the form of a prohibition, regulation, directive, zoning or

payment.

Effluent limitation--restriction established by the EPA or appropriate
state agency on quantity or quality of pollutants from point
sources.

 

Standards ofyperformance--quantity or quality of pollutants which may be
discharged from new point sources.

 

lOeyear, 24-hour rainfall event and 25eyear, 24-hour rainfall event--
rainfall event with a probable recurrence interval ofionce in
ten years or twenty-five years as defined by the National
Weather Service or equivalent regional or state rainfall
probability.

 

 

Process generated waste water--water directly or indirectly used in the
operation ofia feedlot or any of the following: spillage or
overflow from animal watering systems, washing cleaning or
flushing pens, barns, manure pits or other feedlot facilities;
direct swimming washing or spray cooling of animals; and dust
control.

 

Process waste water--any process generated waste water and any precipita-
tion which comes into contact with any manure, litter or bedding.
or any other raw material or product used in or resulting from
the production of the animals.

 

196

197

Feedlot waste--anima1 wastes from confined cattle feedlot operations.

Pollutant--solid waste, sewage, garbage, chemicals, biological
materials, munitions, radioactive materials, heat, rock,
sand, industrial, municipal and agricultural wastes.

Pollution--man-made or man-induced alteration of the chemical, physical,
iological, and radioactive integrity of the water.

Point source--any discernible, confined and discrete conveyance
inclUding any pipe, ditch, channel, tunnel, conduit, concen-
trated animal feeding operation, etc. from which pollutants
may be discharged.

Nonpoint sources--fields, crop and forest land, surface and underground
mines, construction activity, subsurface excavation, extraction

of ground water, and changes in movement of navigable waters
and ground waters.

 

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