; THE EFFECTS OF SELECTED. - WATER POLLUTION CONTROL RULES, ; i } -:. g_’ _ ONVTHESIMULATEDBEHAVIOROF : 5 IBEEFFEEDLOTS.197445“ ~ ’ DisSertatidn for the Degree'ofPh.D. " f 7 Ml-CHIGAN‘STATE‘UNWERSITY ' ‘ ‘ DAVID mm FORSTER' * ' , '1974 ‘ ' Ill/lullwillingly/WMlull/m _ if: 1 : .- 3 -» {5471/ w 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 has been accepted towards fulfillment of the requirements for Ph.D. Ag. Econ. degree in Kym rZ’ aha/“*7 Aajoy professor Date JULY 29, 1974 0-7639 ”3'": a... m fix. 5' amomo av i new 3m st: ,‘K BlNDERY INC. ‘ “up 'I‘5i l’. l I “J." '- 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 AK 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. .A‘pJ V» O. 71 V! c O- r 5 Pi" wk,: "l e, ”E David Lynn Forster 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 'M‘ -» . A a ' v 1 "ucr 4» 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 3. A,” v ., , f I .TQ p U La ~ni- 1' PA '1‘ if! I; p “i V Flt. 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. *‘k'k'k'k 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. 13’ in 1 at: c \ L »\ lib (M iii. 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 mammm< Poppamu mo mm< cmzopaEm mpaacH .umuauoca Comm meowumzcm mopsnl .coNPLo: gmm> mpawppzz gm>o Low>mswm uopummu we Pave: .o mesmwd cowuuczm corpuzmmma muc< xm cowuuczg mmmuoca _ mpcwmgumcou. , - =o_uozcogm mcwxmz Loam; new znwzcm_ umoa.mm copmmumo mcwzoggom . , s .. mcowpmscm ouwsnl muc< xm - mummm< mmwuocm _ ww mm“ new 9.5.580: Y PS m .3 , TL . :owuwmoaeou - 5.55 mmzpm> mgapuacpm mmm>me xm» umoa xm 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 .mgmpwEmcma czocxc2 Low mmspm> use; on wcsuwuosa cowum~wswuao .u mesmwu usauzo pmzuu< Co pcaoe< “A Nmuommp 3.2., meszLLon u zfiam cmmwguwz mumo 2wmu pmou gum: u 2 qucc< co mpuumu umpcoawm , muczm mappmm>cw Low umoo xuwcspcoaao u m , cowazamgpmwu spec: pm: $0 smpwsmsmg czocxcz u x m .2H2m .2 .2 # mmzpm> 3oz pumpmm op pcmwu_mwmoo culllllmy meaumuoca cowum~wewpao cowumpmgcou pamp=OI# . fl; om sewn . an a - - a .zHAm .2 a u o m .2H2m .2 pcaoe< Fm===< spec: pmz mepwcH venumpmm cowuzawcpmpo xpeoucmm .2oga m>wpmpaszu N~-oem_ p Lam> _,m meampd spec: pmz spec: pmz. mgmm> cw azauso — N Sew; x magma umpmpasmm 1T1. - 4o psapso , - .2oca p Lmm> ago: umz . 23.5 #8 95m: _. P E: 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. .ucmcogeou corpuzvoga popumoulscmd .m wgzmwm Lona; pmmoammo evoczm Almm—mwwvxxxlxxtg 6£3 “tbs—~— co 0: L 3.33.9 _ .3 we a run: _, uo_vomu mama: e_Fom acosnrscm mungoum ”395395 a eumm Loam; mauvupuOOmcm 22o ‘, mae.u.n.a= wmagoum _ ceou pave: il—wm.3.>_pu<_ _ acoamcog» covuuauocg coco 2cm maapwm acmsqvacu Famoamwo mama: uvpom mcwvmopc2 2cm mopwm 11%, UL 32.22.: v LONp—wusum 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. BIBLIOGRAPHY BIBLIOGRAPHY Bernhard, Richard H. "Mathematical Programming Models for Capital Budgeting--A Survey, Generalization and Critique." Journal of Financial and Quantitative Analysis, June 1969. Beveridge, G. S., and R. S. Schecter. Optimization Theory and Practice. New York: McGraw-Hill, 1970. Black, J. R. Personal communication. Agricultural Economics Department, Michigan State University, April 1974. , and H. D. Ritchie. "Average Daily Gain and Dry Matter Intake of Various Kinds of Cattle Fed Three Different Rations Under Several Environmental Situations." Staff Paper 1973-l. Agri- cultural Economics Department, Michigan State University, 1973. Bonnen, James T. Lectures in Agricultural Economics Department, Michigan State University, 1974. Buckley, J. L. "Agriculture and the Environment." Waste Management Research--Proceedings of the 1972 Cornell WasteTManagement Conference. Cornell University, 1972. Butchbaker, A. F., et g1, Evaluation of Beef Cattle Feedlot Waste Management ATternatives. U.S. Environmental Protection Agency, November 19711 Byrkett, Donald. Personal communication. Ohio State University, March 1974. Cohen, Kalman M., and Richard J. Cyert. Theory of the Firm: Resource Allocation in a Market Economy. Englewood Cliffs, N.J.: PFEntice-Hall, Inc., 1965. Connor, L. J. Personal communication, April 1974. , et 21, "Beef Feedlot Design and Management." Unpublished woFEing paper. Michigan State University, 1972. Cross, George R. "Economic Impact of Environmental Quality Legislation on Confined Animal Feeding Operations in Oklahoma." Unpublished M. S. thesis, Oklahoma State University, 1971. 198 199 Daiss, Bill J. "Economics of Water Pollution Abatement from Beef Cattle Feedlots." Unpublished M. S. thesis, University of Nebraska, 1971. David, M. L., R. E. Seltzer, and W. D. Eickhoff. "Economic Analysis of Proposed Effluent Guidelines--Feedlot Industry." Environmental Protection Agency, August 1973. Day, R. H., 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. Environmental Protection Agency. "Development Document for Effluent Limitations Guidelines and New Source Performance Standards-- Feedlot Point Source Category." August 1973. "Methods and Practices for Controlling Water Pollution from Agricultural Nonpoint Sources." October 1973. Eveleigh, V. W. Adaptive Control and Optimization Techniques. New York: McGraw-Hill, Inc., 1967. Franzmann, John R., and Rodney L. Walker. "Tread Models of Feeder, Slaughter and Wholesale Beef Cattle Prices." American Journal of Agricultural Economics, August 1972. Friedman, Milton. "The Methodology of Positive Economics." Essa s in Positive Economics. Chicago: The University of Chicago Press, 1973. Gailey, Donald. Forthcoming Ph.D. thesis, Michigan State University. Hardin, Garret. "The Tragedy of the Commons." Science, December 13, 1968. Haveman, Robert H. "Efficiency and Equity in Natural Resource and Environmental Policy." American Journal of Agricultural Economics, December 1973. Hensler, C. F. "Cattle Manure: I. Effect on Crops and Soils. II. Retention Properties of CV, Mn, An." Ph.D. thesis, University of Wisconsin, 1970. Hicks, J. R. Value and Capital. 2nd edition. London: Oxford University Press, 1946. Hughes, Harold A. "Energy Consumption in Beef Production Systems as Influenced by Technology and Size." Unpublished Ph.D. thesis, Michigan State University, 1973. 200 Johnson, Glenn L. "Alternatives to the Neo-Classical Theory of the Firm." American Journal of Agricultural Economics, May 1972. , et a1. Managerial Processes of Midwestern Farmers. Ames, Iowa: —The Iowa State University Press, 1961. Johnson, James 8. "Biological, Chemical and Engineering Factors Related to Economic Analyses of Dairy and Fed Beef Waste Management and Pollution Abatement." Unpublished paper, Michigan State Univer- sity, 1972. , 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 Unitersity, August 1972. , and Gary A. Davis. "The Economic Impacts of Imposing EPA Effluent Guidelines on the U.S. Fed-Beef Industry." Cornell Waste Management Conference, March 1974. J. Rod Martin, and C. Kerry Gee. "Economic Impacts of Controliing Runoff Arising from Fed- Beef Production Facil- ities. " Unpublished paper, 1973. Keynes, John Maynard. The General Theory of Employment, Interest and Money. New York: Harcourt, Brace and WOrld,—Inc., 1964. Kneese, Allen V. The Economics of Regional Water Quality Management. Resources for the Future, Inc. Baltimore: John HOpkins Press, 1971. Knight, Frank H. Risk, Uncertainty and Profit. Boston: Houghton Mifflin Company, 1921. Kyle, Leonard R. "Business Analysis Summary for Cattle Feeding Farms." Agricultural Economics Report, Michigan State University, selected annual issues. Lerohl, Milburn L. "Expected Prices of U.S. Agricultural Commodities, 1917-62." Unpublished Ph.D. thesis, Michigan State University, 1965. Madden, John M., and J. N. Dornbush. "Measurement of Runoff and Runoff Carried Waste from Commercial Lots." Proceedings International Symposium on Livestock Wastes, 1972. Manetsch, Thomas J., and Gerald L. Park. System Analysis and Simulation with Applications to Economic and Social Systems. Michigan State University, 1973. 201 Michigan State University. ”Research Proposal for the Ecosystem Design and Management." December 8, 1971. Nerlove, Marc. The Dynamics of Supply: Estimation of Farmers' Response to Price. Baltimore: John Hopkins Press, 1958. Newhauser, G. L. Dynamic Programming. New York: John Wiley & Sons, Inc., 1966. Office of the Federal Register. Federal Register. Vol. 39, No. 2. National Archives and Records Service, General Services Administration, Washington, D.C. Pherson, Carl L. ”Beef Waste Management Economics for Minnesota Farmers-Feeders." Cornell University Waste Management Conference, March 1974. Randall, Alan. "Market Solution to Externality Problems: Theory and Practice." American Journal of Agricultural Economics, May 1972. Schmid, A. Allan. "Analytical Institutional Economics: Challenging Problems in the Economics of Resources for a New Environment." American Journal of Agricultural Economics, December 1972. Schulz, A. H. "Basic Requirements for Beef Cattle Housing, Feeding and Handling." Agricultural Engineering, No. 41, 1960. Talpaz, Hovav. "Simulation, Decomposition and Control of a Multi- Frequency Dynamic System: The United States Hog Production Cycle." Unpublished Ph.D. thesis, Michigan State University, 1973. Trimble, Richard L. "An Economic Analysis of the Effect of Monetary Policy on the Beef Industry." Unpublished Ph.D. thesis, Michigan State University, 1973. U.S., Congress. Public Law 92-50, October 18, 1972. House of Representatives. "Control of Pollution from Animal Feedlots." Hearings Before a Subcommittee of the Committee on Government Operations, 93rd Congress, November 30, 1973. U.S., Department of Agriculture. "Index of Prices Paid by Farmers." Agricultural Prices. 1960-73 issues. Cattle on Feed. Selected issues. Livestock and Meat Situation. 1959-73 issues. 202 U.S., Department of Commerce. Bureau of Census. Census of Agriculture, 1969. Van Horne, J. C. Financial Management and Policy. Englewood Cliffs, N.J.: Prentice-Hall, Inc., 1971. "7'1110111111'1111115