Agricultural Risk Management 9781685855901

Citation preview

AGRICULTURAL RISK MANAGEMENT

AGRICULTURAL RISK MANAGEMENT Beverly Fleisher

Lynne Rienner Publishers · Boulder & London

Published in the United States of America by Lynne Rienner Publishers, Inc. 1800 30th Street, Boulder, Colorado 80301 www.rienner.com and in the United Kingdom by Lynne Rienner Publishers, Inc. 3 Henrietta Street, Covent Garden, London WC2E 8LU © 1990 by Lynne Rienner Publishers, Inc. All rights reserved ISBN 978-1-55587-169-7 (hardcover. : alk. paper) Printed and bound in the United States of America The paper used in this publication meets the requirements of the American National Standard for Permanence of Paper for Printed Library Materials Z39.48-1992.

To Gert's zydeco man

Contents

List of Tables and Figures Preface

1

xi xiii

Introduction

1

Concerns About Risk in Agriculture Tools for Analyzing Risk and Its Management The Optimal Amount of Risk and Risk Management Organizing Our Inquiry Concluding Comments Selected Readings

1 4 6 6 9 9

PART ONE. RISK AND ITS EFFECTS ON AGRICULTURE AND AGRICULTURAL DECISIONMAKING 2

3

What Is Risk?

13

What Creates Risk? Measuring Risk Likelihood of Events Risk Versus Variability Concluding Comments Selected Readings

13 17

22 22 25 26

Sources and Effects of Risk in Agriculture

27

Production and Marketing Risk Risks Introduced by Agriculture's Integration into the Global Economy Policy Risk What Are the Effects of Risk? Is Risk Necessarily Bad? Concluding Comments Selected Readings

27

vii

29 33

36 38

39 40

viii

4

Contents

Agricultural Producers' Attitudes Toward Risk

43

Types of Risk Attitudes Risk Premiums Measuring Risk Attitudes Decision Rules Concluding Comments Selected Readings

43

45 47 48

49 49

PART TWO. AGRICULTURAL PRODUCERS' TOOLS FOR MANAGING RISK

5

6

7

Approaches to Risk Management

55

Characteristics of Risk Management Strategies How Risk Management Tools Work The Effects of Tools on the Distribution of Outcomes The Effect of Cost on the Choice of a Strategy Concluding Comments Selected Readings

55 58 60 63 66 67

Some Common Tools for Managing Agricultural Risks

69

Risk-Reducing Inputs Production Diversification Holding Reserves Information Insurance Concluding Comments Selected Readings

69 72 73 75 82 83

Forward Pricing

87

Forward Contracting Futures Options Concluding Comments Selected Readings

87 90 93 97 97

71

PART THREE. GOVERNMENT ACTION AND AGRICULTURAL RISK MANAGEMENT

8

The Role of Commodity Programs in Risk Management

101

Policy Risk Revisited Price Distributions in the Absence of Commodity Programs Price Stabilization and Support Programs

102 103 105

Contents

9

ix

Income Stabilization and Support Programs Decoupled Payments Mechanisms for Setting Support Levels Methods of Payment The Effect of Federal Commodity Programs on Nonprogram Commodities Concluding Comments Selected Readings

110 113

Alternatives for Managing Agricultural Risks

125

The Government's Role in Agricultural Risk Management Who Pays for Government Commodity Programs? Evaluating the Performance of Government Programs Are Futures and Options Substitutes for CCC Commodity Programs? Can the Costs of CCC Programs Be Transferred to the Private Sector? Privatizing the Cost of Risk Management Concluding Comments Selected Readings

126 127 128

Index About the Book and the Author

145 149

114 116

120 122 122

133 137 140 141 142

Tables and Figures

Tables 3.1 Producers' Ranking of Important Sources of Variability in Production and Marketing 5.1 Producer Responses to Variability 5.2 The Design of Strategies to Manage Variability 5.3 Cost Relationships for Risk Management Tools That Are Self-Protection, Self-Insurance, or Market Insurance 8.1 Program Tools and Parameter Levels Used to Attain Policy Goals Figures 1.1 Variability of Income: Farm Net Cash Income Adjusted for Inflation 2.1 Uniform and Normal Distributions of Outcomes 2.2 Random Component of Market Price for Rice 3.1 Annual Percentage Changes in Prices Received for Agricultural and Industrial Products 4.1 Individuals' Load Factor and the Premium They Are Willing to Pay for Insurance 5.1 Four Ways That Risk Management Strategies Can Alter the Probability Distribution of Events or Outcomes 6.1 Effect of the Variability of Yields on the Degree of Protection Offered by Multi-peril Crop Insurance 8.1 Probability Distribution Where Outcomes Have Equal Percentage Deviations from the Mean 8.2 Effect of a Buffer Stock on the Distribution of Market Prices 8.3 Effect of Deficiency Payments on Market Prices and Farm Prices for Eligible Production

xi

28 56 57

65 103

2 20 25 31 47

61 79 104 106 112

Preface

The goal of Agricultural Risk Management is to provide nonspecialists with a guide to the many facets of risk and risk management that are instrumental in understanding today's agricultural sector and agricultural policy choices. The topics covered include risk's effects on agriculture, the individual agricultural decisionmaker's responses to risk, the tools available to producers for managing risk, and the effect of government commodity policy on agricultural risk and its management. The possibility of substituting privately sponsored risk management programs for those currently provided by the government is also explored. An understanding of risk and risk management can help those concerned with agriculture and agricultural policy translate constituents' concern about the riskiness of agriculture into policy recommendations, understand how decisionmakers' responses to a risky environment affect the outcomes of policies, discover how both sector-specific and general macroeconomic policies affect the set of risk management strategies available to, and selected by, agricultural producers, and make explicit decisions about the distribution of risk within the agricultural sector and between this sector and other sectors of the economy. Numerous books and countless articles have been written on agricultural policy, risk, decisionmaking, risk management, and commodity policy. But, in general, these works are accessible only to specialists, and each looks at only one facet of the broad topic of agricultural risk management. This book, in contrast, provides an integrated overview that can be used as a framework for understanding the broad picture and general issues. For the student of agricultural policy, the book also provides a gateway to the literature on agricultural risk management. Because of its breadth of scope, coverage of each topic necessarily is cursory. At the end of xiii

xiv

Preface

each chapter, however, the reader is provided with a list of pertinent literature. These lists include selected technical articles as well as broader survey articles and books, most of which include extensive bibliographies. As readers of murder mysteries know, the temptation exists to skip to the end of the book to find the solution to the mystery. Although the reader will find that each chapter can stand alone, the greatest understanding of the topic will be obtained by proceeding from start to finish. As in a mystery, each chapter gives further insights into the characters and their motives, making the ending more meaningful. This book is organized in a series of building blocks that can be divided into three major areas: Part 1 explores what is known about the risks common to agricultural firms and how producers respond to them. Part 2 examines the risk management tools available to agricultural producers, the aspects of those tools that influence their selection by producers, and the effects of risk management strategies on the farm firm. Part 3 considers the effects of government policies on producers' risks and selection of risk management strategies. The prospect for substituting privately sponsored risk management tools for those currently supported by the government also is examined in this third section. Each chapter includes concepts and definitions that are important aids in understanding succeeding chapters. This book evolved from my experience in research on decisionmaking under uncertainty and in subsequent agricultural policy work at the Department of Agriculture's Economic Research Service. Although tools for analyzing policy in the absence of risk are fairly well developed, inclusion of the effects of risk is only now becoming more widespread. Many of the models and methods being developed that include a risk component are internally consistent but have yet to be tested for their ability to predict realworld behavior and outcomes. Because quantitative models and methods currently in use do not explicitly consider the effects of risk in their numerical results, policy analysts and decisionmakers need a qualitative understanding of the field of agricultural risk management in order to best interpret the quantitative results they receive. This book is designed to provide that information. As with any undertaking of this size and scope, I am indebted to many individuals for providing both technical information and careful review of the manuscript. I am particularly appreciative of the generosity of my colleagues at the Economic Research Service in sharing their expertise in many of the areas covered. Many other experts and nonexperts provided me with constructive criticism on

Preface

XV

earlier drafts of this manuscript, including Ken Baum, Neil Conklin, Clark Edwards, Joseph Glauber, Richard Heifner, Tom Miller, Susan Offutt, Lindon Robison, Lloyd Teigen, and David Trechter. Despite their valiant efforts, any errors that remain are, of course, my sole responsibility. It must also be noted that though the majority of this book was written while I was at the Department of Agriculture and it was completed while I was on leave from the National Science Foundation, the views expressed herein are my own and should not be attributed to either organization. Beverly Fleisher

1 Introduction

Agriculture is inherently risky. Output from the farm or ranch depends on weather and biological processes over which producers have little control. The competitive structure of domestic and international agricultural product markets exposes producers to unanticipated fluctuations in prices. At the same time, producers have limited control over the price of the inputs needed for production. The capital-intensive nature of agricultural production firms makes them particularly sensitive to fluctuations in general economic conditions in both the United States and abroad. Risk affects both individual producers and the performance of the agricultural sector as a whole. The presence of risk, and producers' reactions to it, also influence the formation, conduct, and outcomes of agricultural policies. In fact, instability, variability, and risk have played an important role in motivating and justifying policy intervention in the agricultural sector. Many government policies and programs directly affect the level and distribution of risk within the agricultural sector; agricultural policy can be viewed as one way to allocate risks in the farm sector and between the farm sector and the rest of the economy. But policies designed to ameliorate one risk sometimes create new ones.

Concerns About Risk in Agriculture

The problems of agricultural price and income instability date back to the advent of commercial agriculture in the United States. After a period of relative stability in agricultural markets and incomes, shocks to the agricultural sector from weather, the price of inputs, and unexpected changes in U.S. export prices, combined with reduced inventories and changes in commodity programs, caused

2

Introduction

FIGURE 1. 1 Variability of Income: Farm Net Cash Income Adjusted for Inflation Billions of Dollars 00 r---------------------------------------------~

70 00

:

30

}~ f~ ~t~;tf;,~il!' ~i'1W'1;,it'l~!,:g~-:'[j]'jtJ:%1i~l1Ji:'0c; ; fc:

>tY ',:

~~~~~~~~~~~~~~~~~~~~~~~~

1950

1955

1960

1965

1970

1975

1900

1985

deflated dollars

the problems associated with risk to regain prominence in agricultural policy debates in the early 1970s. Figure 1.1 illustrates the variability in net farm income even after the influence of inflation is removed. Shocks to, and changes in, the agricultural sector not only influence market prices for several years but also cause legislative and administrative changes in policy variables. The effects of unanticipated variability and risk in agriculture can be viewed from three interrelated perspectives: societal concern about the effects and costs of risk and its management, agricultural producers' concern about sustaining the viability of their farm firms, and policymakers' ability to predict the sectors' response to changes in conditions and the subsequent effect on the likelihood that government policies will meet their goals. Social concerns about risk in agriculture include the effect of uncertainty on production decisions, the cost of managing risk and adjusting to changes in the economic or physical environment, imperfect substi-

Introduction

3

tution of consumption across different periods of time, and the economic cost to society from mistakes that may be made when the outcomes of action choices are incorrectly predicted. The management of agricultural risk historically has required the commitment of substantial resources from farmers, agricultural lenders, agribusiness firms, and the public sector. There are few quantitative measures of the total indirect costs of risk in agriculture to society. But one proxy measure of the cost of providing protection against price and income risk for crops covered by government programs is the Commodity Credit Corporations' (CCC) investment in price support operations. In the first quarter of 1987, total investment in CCC operations, including loans held, the value of inventory, and total loans outstanding, was over $36 billion, up from nearly $3 billion in the first quarter of 1977. Direct government payments to farmers for all programs was more than $16.7 billion in 1987, over a ninefold increase from the $1.8 billion paid in 1977. Even when adjusted for inflation, payments in 1987 were nearly five times greater than those in 1977. Although agricultural producers have little capacity to influence resource or commodity prices or the physical environment in which they operate, they do not simply accept changes. Instead, they may choose to respond by either attempting to control exposure to risk or by controlling the impact of the effects of risk on the farm firm. Consider an agricultural producer who is making plans at the beginning of a production cycle. The farmer or rancher must decide what will be produced, where it will be raised, and the amounts and types of inputs to be used. At the same time, the producer must decide whether to finance production by borrowing money or by using reserves already held by the farm firm. The producer also must select a marketing strategy; the choices range from forward pricing of the expected outputs at a price set before the production is begun to accepting the prevailing market price at the end of the production cycle. For those products eligible for CCC programs, the producer must decide whether to enroll in the program for the current cycle; this decision may affect eligibility in future cycles as well. In a world without risk, the farmer or rancher would know at the time the decisions were made what the final impacts on his or her firm would be. Simple optimization rules could be used to determine the combination of products, inputs, marketing tools, and financing that would yield the best outcome for the firm. But producers are subject to uncertainty about weather and other conditions that affect yields, prices, and government program provisions. Thus, even a producer who is not averse to risk must make decisions regarding the

4

Introduction

risk management strategies to employ in order to maximize the chances that the choices made at the beginning of the production cycle will yield the best possible outcome for the firm in the current production cycle as well as leave it in the most favorable position for future production. When viewed from the firm's perspective, risk may be seen as creating an additional cost that must be met when planning for and carrying out the optimal organization of activities. Uncertainty about the decisions that will be made by agricultural producers creates risk for agricultural policymakers. These decisionmakers are concerned about the cost to the government of providing producers with some of the tools used to manage risk and the difficulty in predicting supply of commodities to be provided to the market in response to changes in risk, environmental, and economic conditions, and modifications to general economic policies and those specifically directed toward agriculture.

Tools for Analyzing Risk and Its Management

Different disciplines provide those concerned with agricultural risk and its management with a wide variety of tools for use in its study. Although general principles are applicable to a wide variety of situations, models and methods must be applied on a case-by-case basis as firm response and aggregate sector effects can be altered significantly by a change in the specification of only one of the multitude of parameters in the firm's decision environment. During the 1970s and 1980s, significant advances were made in the development of analytic and computational models for examining the economics of a firm's allocation of resources under uncertainty. By adding the possibility of randomness to standard economic models, the study of microeconomics under uncertainty has enabled analysts to predict a firm's response to risk. However, the individual models are not very robust; the optimal solution depends heavily on the assumptions made about the types of uncertainty that are present, the shape of the probability distribution associated with the random variable, and the means through which it is entered into the model. The general conclusion that can be drawn from the literature is that risk does affect a firm's allocation of resources and, under most circumstances, will result in a decrease in output from the individual firm. Much of the work on microeconomics under uncertainty has been motivated by a desire to improve the micro-foundations of

Introduction

5

macroeconomics. The study of macroeconomics under uncertainty, constructed on the foundation of the new microeconomic models, is still in its infancy. This state can be attributed both to the difficulties in generalizing the results of the microeconomics literature and problems that exist in aggregating the effects of multiple small agents' actions into workable formulations of the market and other institutions that are affected by, and in tum affect, individual behavior. Important components of any model of firm optimization under risk are the specification of the decisionmaker's attitude toward risk and the decision rule that is used. The study of attitudes toward risk and their formal use in analysis is part of a broader field of inquiry known as decision theory or decision analysis. Although used extensively by economists and agricultural economists, many disiciplines use and develop decision theory, including economics, management science, mathematical psychology, finance, anthropology, sociology, statistics, and systems science. Models of decisionmaking and their applications are as diverse as decision theory's bases. Some models of decisionmaking are descriptive, attempting to capture and explain the cognitive processes used in making actual decisions, and others are prescriptive and used to help individuals make better decisions. Yet others are predictive, making no attempt to formally model decisionmaking processes. Instead, they treat the cognitive decision process as a black box; individuals' preferred action choices are predicted as if they followed a certain set of procedures without assuming that these are the procedures actually used. It is this latter type, predictive models, that is most commonly used by policymakers and analysts in the study of risk management in agriculture. Robert Jolly argues that there can be no distinction between risk management and what has traditionally been defined as farm management because virtually all actions that might be undertaken by a farm manager are subject to risk. On the micro or individual firm level this argument carries weight; advances in the understanding of risk management can be viewed as extensions of traditional farm management. However, at the macro, sector, or societal level, the study of risk management in agriculture extends well beyond the boundaries of farm management to the study of how agricultural markets and markets for risk operate and the aggregate effect of individual farm management decisions on the agricultural economy. But experience with farm management provides an important guide in highlighting the role that technical, statistical, and social sciences other than economics play in the analysis of agricultural risk management.

6

Introduction

The Optimal Amount of Risk and Risk Management

The optimal amount of risk in the agricultural sector, and the degree to which it should be managed, are still topics of debate among economists. Kenneth Boulding has stated that efficiency is promoted by at least one risk management tool-price supports-because "the uncertainty involved in meaningless market fluctuations discourages innovation and investment and limits our getting richer." On the other hand, Bruce Gardner argues that "variability in production conditions and input prices encourages farmers to try different production methods and this experimentation can lead to progress that would never occur in a purely static world. Variability in output price encourages investment in information and innovation in marketing." Clearly risk or instability does affect the behavior of economic agents whether or not they are averse to its presence. Thus, there is potential to improve economic performance if risk is managed. But the question of the optimal amount of risk management remains open. B. Delworth Gardner has argued that "in the world of reality the economic issues are very complex. For example, in discussions of the instability problem, it is seldom pointed out that stabilization policies in principle can also create resource misallocations. If real shifts in demand and/or supply occur, then resulting fluctuations in prices are indeed necessary signals to consumers and producers that consumption and production should be altered. To prevent these fluctuations in prices by stabilization devices is to distort the signals and produce misallocations." The goal of this book is to provide nonspecialists with the information necessary to evaluate these arguments, understand the importance of risk, and determine how different facets of risk and risk management interact to affect today's agricultural sector and shape agricultural policy choices. Among the issues covered are sources of risk, agricultural producers' decisionmaking processes, government policies, and the characteristics of risk management tools available through the private market and government programs. Because this book is written for nonspecialists, no previous knowledge of economics, statistics, or mathematics beyond the most basic level is required. Organizing Our Inquiry

Although our primary focus is on the management of risk in agriculture from an aggregate or policymaking perspective, this study

Introduction

7

would be incomplete without careful consideration of the actions of those individuals who actually make the decisions regarding risk management at the firm level-the agricultural producer. Therefore, the following sections of this chapter provide an overview of the remainder of the book and show how understanding the individual producer and his or her reaction to risk and selection of risk management tools affects the functioning of the agricultural sector and the outcome of agricultural policies. This book is organized in a series of building blocks that can be divided into three major areas. Part 1 explores what is known about the risks common to agricultural firms and how producers respond to them. Part 2 examines the risk management tools available to agricultural producers, the characteristics of those tools that influence their selection by producers, and the effects of risk management strategies on the farm firm. Part 3 considers the effects of government policies on producers' risks and selection of risk management strategies as well as the prospects for substituting privately sponsored risk management tools for those currently supported by the government. Each part contains concepts and definitions that are important aids in understanding subsequent discussions. For policymakers or students of policy interested in further exploration of a particular area, I have provided a list of selected technical articles and more general books and survey articles, each with its own extensive bibliography, at the end of each chapter. Risk and Its Effects on Agriculture and Agricultural Decisionmaking

As with many subjects in which people from diverse backgrounds join its exploration, the topic of agricultural risk management is fraught with misunderstandings stemming from different interpretations of seemingly common words. Therefore, our first step is to develop a definition of risk and related terms, such as uncertainty, that will be used throughout the remainder of the book. Chapter 2 also examines how risk is created and measured. Chapter 3 categorizes the types of risk in agriculture about which we are concerned and changes in the relative importance of different sources of risk over the last half century. Among the risks considered are those stemming from production and marketing activities, risks introduced by agriculture's integration into the global economy, and risks brought about by government policymaking and implementation. This chapter also examines, in general, the

8

Introduction

effects of risk on the agricultural sector's use of resources. Because the riskiness of any event is dependent, in part, on the perceptions of individuals affected, Chapter 4 focuses on agricultural producers' attitudes toward risk and their decisionmaking processes. Agricultural Producers' Tools for Managing Risk

Agricultural producers commonly use risk-reducing inputs, diversification of production practices, holding reserves, gathering information, forward pricing, and insurance to manage risk. In selecting from among the many tools available, decisionmakers are concerned with both the monetary and nonmonetary costs involved and how those costs vary with the size and probability of risk-related loss. Even decisionmakers who are averse to risk will not pay an unlimited amount to avoid risk; the amount producers are willing to pay is directly related to their attitude toward risk. Chapter 5 develops the framework for evaluating specific risk management tools by examining the characteristics of major classes of risk management tools and how they work, their effect on the results obtained by producers, and the effect of the tools', monetary and nonmonetary cost on their selection by agricultural producers. Chapters 6 and 7 examine specific risk management tools available to agricultural producers using the framework developed in the preceding chapter. Government Action and Agricultural Risk Management

Government-sponsored risk management strategies, such as commodity price support and stabilization, do affect producers' selection from among the portfolio of risk management tools available through the private market. However, government programs serve to manage some risks, such as variation in prices between years, for which no other mechanisms exist. Chapters 8 and 9 explore government-sponsored risk management tools and the possibility of the existence of private market mechanisms for providing producers with similar risk protection. In addition to describing the tools that are commonly used, Chapter 8 examines how the agricultural policymaking and implementation processes affect the risks faced by producers. In addition to examining alternatives to the current mix of risk management tools available to the producer, Chapter 9 also broaches the topic of the welfare implications and distribution of benefits from various strategies for managing agricultural risks both within the agricultural sector and between sectors of the economy.

9

Introduction

Concluding Comments

In this chapter, the subject matter of the book was introduced and the approach to be taken in its examination was outlined. Although the exact effects of risk in agriculture and the optimal means for risk management are still the subject of heated debate among economists and policymakers, there is little question that the presence of risk affects agricultural producers' decisions and welfare as well as the outcome of agricultural policies. In the following chapters, the reader will be provided with the information needed to begin to unravel the extensive debate about agricultural risk management and make informed decisions on his or her own. As with each chapter in the book, the selected readings listed below are designed for those interested in a more detailed discussion of the issues raised here.

Selected Readings Antle, J. "Incorporating Risk in Production Agriculture," American Journal of Agricultural Economics 65 (1983):413-417. Barry, P, ed. Risk Management in Agriculture. Ames: Iowa State University Press, 1984. Borch, K. The Economics of Uncertainty. Princeton, N.J.: Princeton University Press, 1968. Bouiding, K. "The Irrelevance of Conventional Economics," Journal of Economic Literature 21 (1983):554-555. Brandon, G. "Policy for Commercial Agriculture." Pp. 209-292 in L. Martin, ed., A Survey of Agricultural Economics Literature, Volume 1. Minneapolis: University of Minnesota Press, 1977. Day, R. "Farm Decisions, Adaptive Economics, and Complex Behavior in Agriculture." Pp. 18-49 inK. Baum and L. Schertz, eds., Modeling Farm Decisions for Policy Analysis. Boulder, Colo.: Westview Press, 1983. Dillon, J. "Response Efficiency Under Risk." Pp. 102-148 in J. Dillon, The Analysis of Response in Crop and Livestock Production. 2nd ed., Oxford: Pergamon Press, 1977. Dixit, P., and M. Martin. Policymaking for US. Farm Commodity Programs: A Case Study of the Coarse Grains Sector. FAER 219, Washington, D.C.: U.S. Department of Agriculture Economic Research Service, 1986. Gardner, B. "Instability and Risk." Pp. 273-313 in B. Gardner, Economics of Agricultural Policies. New York: Macmillan Publishing Company, 1987. Gardner, B., R. Just, R. Kramer, and R. Pope, "Agricultural Policy and Risk" Pp. 231-261 in P. Barry, ed., Risk Management in Agriculture. Ames: Iowa State University Press, 1984. Gardner, B. D. "Instability in U.S. Agriculture: Discussion," American Journal of Agricultural Economics 59 (1977):188-191. Houthakker, H. Economic Policy for the Farm Sector. Washington, D.C.: American Enterprise Institute for Public Policy Research, 1967.

10

Introduction

Johnson, G. "Contributions of Economists to a Rational Decision Making Process in the Field of Agricultural Policy." In T. Domes and K. Hunt, eds., Decision Making in Agriculture. Oxford: Economics Press, 1977. folly, R. "Risk Management in Agricultural Production," American Journal of Agricultural Economics 65 (1983):1107-1113. Just, R. "An Investigation of the Importance of Risk in Farmers' Decisions," American Journal of Agricultural Economics 56 (1974):14-25. Kunreuther, H., J. Linneworth, and J. Vaupel. "A Decision-Process Perspective on Risk and Policy Analysis," Management Science 30 (1984):475-485. Lin, W. "Measuring Aggregate Supply Response Under Instability," American Journal of Agricultural Economics 59 (1977):903-907. MacCrimmon, K., and D. Wahrung. Taking Risks: The Management of Uncertainty. New York: The Free Press, 1986. Nieuwoudt, W, A. Womack, and S. Johnson. "Measurement of Importance of Risk on Supply Response of Corn and Soybeans," North Central Journal of Agricultural Economics 10 (1988):281-292. Robison, L., and P. Barry. The Competitive Firm's Response to Risk. New York: Macmillan Publishing Company, 1987. Roumasset, J., J. Boussard, and I. Singh, eds. Risk, Uncertainty, and Agricultural Development. New York: Agricultural Development Council, 1979. Schultz, T. Agriculture in an Unstable Economy. New York: McGraw-Hill, 1945. Sumner, D., ed. Agricultural Stability and Farm Programs. Boulder, Colo.: Westview Press, 1988. Tweeten, L. "Farm Problems: Instability." Pp. 202-235 in L. Tweeten, Foundations of Farm Policy. 2nd ed. Lincoln: University of Nebraska Press, 1979. U.S. Department of Agriculture. Agricultural Statistics, 1987. Washington, D.C.: U.S. Government Printing Office, 1988.

PART 1 Risk and Its Effects on Agriculture and Agricultural Decision making

2 What Is Risk?

An eminent economist, Joseph Stiglitz, said, "Risk is like Jove; we all

know what it is, but we don't know how to define it." Although there is no universally accepted definition of risk, several working definitions commonly are used. None correspond to the colloquial definition of risk as a hazard or chance of a loss. To avoid confusion, we develop a working definition here to be used throughout the book.

What Creates Risk?

Agricultural producers must often select a course of action before they know its consequences. The consequences for decisionmakers often depend both on the actions they choose (action choice) and on future events that are beyond their control. Even the common decision of whether to put cash into a checking account, a savings account, or the stock market-shown in Example 2.1-has all of the components of the most complex decision problem. When a decision is made under certainty, each possible action has only one possible consequence. This one-to-one corresponComponents of a decision problem under risk: • A choice of possible actions. • A set of possible events. • A probability or likelihood associated with each event. • A set of possible but not equally desirable consequences brought about by an event and an action choice. • A rule for deciding between action choices.

13

14

Risk and Its Effects on Agricultural Decisionmaking

dence between the action and its consequences occurs because the decisionmaker knows both the event that will occur and its effect on the action selected. When money is put in either a checking or a savings account, the decision is made with knowledge of the outcome that will occur; money in a checking account will earn no interest, while money in a savings account will earn interest at a rate specified by the bank prior to the deposit. EXAMPLE2.1

A common decision made under certainty is whether to put money into a checking account or a savings account. In this case the set of possible events might be a 100 percent likelihood of 0 percent interest given on checking accounts and a 100 percent likelihood of 7 percent interest given on savings accounts, and the possible actions are to put money in the checking or savings account. The possible consequences are earning different rates of return on the money.

Certainty Scenario Action Deposit money in a savings account

Event 7 % interest

Likelihood 100 %

Consequences Earn 7% return

Deposit money in a checking account

0 % interest

100 %

Earn 0 % return

A common decision involving uncertainty is whether to put money into a savings account, which has a guaranteed return, or the stock market, where there is a distribution of possible returns. Note that in this case one of the possible actions has more than one possible result or consequence. The final consequence depends both on the action choice that is selected and the event that occurs.

Uncertainty Scenario Action Deposit money in a savings account

Event 7% interest

Likelihood 100%

Consequences Earn 7 % return

Invest money in the stock market

bull market stable market bear market

40% 30% 30%

Earn 15 % return Earn 5 % return Earn -15 % return

What Is Risk?

15

In contrast, a decision made under uncertainty has at least one action choice with more than one possible consequence. Many different events may occur between the time the decision is made and the time the consequences are felt. When an investment is made in the stock market, the decisionmaker does not know in advance what the return on that investment will be. If the market is stable between the time the investment is made and withdrawn only a small gain or loss will occur. If the market moves up or down during the time the investment is in place, chances exist that either large gains or large losses will occur. In the personal investment decision shown in Example 2.1, the possible actions from which the decisionmaker can choose are the placement of funds in one of three possible financial arrangements. The set of possible events to which those funds will be subjected are known with certainty in the case of a checking or savings account, but they are not known with certainty in the case of the stock market. However, the decisionmaker usually has beliefs about the likelihood of the stock market going up or down before the investment is made. Thus, the decisionmaker can speculate on the consequences of investing in the market versus placing funds in a financial institution. The decisionmaker will then use an often unconscious decision rule to decide where to put the money. An uncertain situation does not necessarily create risk for all decisionmakers; risk is created for an individual or group of decisionmakers only when the outcome will affect them. For those who have all of their money in a savings account, events that affect the movement of the stock market do not create risk, although these individuals may, of course, regret their actions if the market moves upward and they miss out on the action! Risk involves the chance of gain as well as loss. Negative consequences or losses that may result from risk are often referred to as downside risk, and positive consequences or gains from the same risk are termed upside risk. We often forget that these are two sides of the same coin. We talk about downside risk as the "burden" of risk and the upside risk as "luck." Thus, risk is a situation in which the resolution of uncertainty will affect the well-being of a firm or decisionmaker and which involves the chance of gain or loss. This definition of risk differs from the colloquial use of the term. In one respect, our definition is broader; risk is defined as the chance of either loss or gain. It is narrower in another respect; a situation is risky only if it affects an individual or group of concern. The distinction between the uncertainty surrounding events and the riskiness of results or consequences is vital. We will distinguish between risk management strategies that alter the possible set of

16

Risk and Its Effects on Agricultural Decisionmaking

Certainty: A situation in which the decisionmaker knows the outcome of every action in the choice set when the decision is made. Uncertainty: A situation in which the decisionmaker does not know the outcome of every action when the decision is made because at least one action has more than one possible outcome. Risk: A situation in which the resolution of uncertainty will affect the well being of the firm or decisionmaker and which involves the chance of gain or loss.

events and those that leave the possible set of events unchanged but alter the set of possible consequences. The definition of the relevant event and consequence depends on the decision problem. For a producer concerned with soil moisture levels, amount of rainfall is the event, and soil moisture level is the consequence. Framing the decision problem slightly differently, soil moisture could be an event, the consequence of which could be yield. Respecifying the event and consequence can continue until the ultimate consequence of firm survival or failure is reached. What is defined as the event often depends on the decision being made. Firm survival or failure often is the consequence of concern to decisionmakers. But a myriad of factors interact in complex ways to affect firm survival. Therefore, the initial focus must be on many individual events and their consequences. Only after each factor is understood can they be combined to ascertain their interactive effect on a firm's well-being. The definition of risk and uncertainty developed here was first introduced by Lindon Robison and myself and differs from earlier definitions in two important respects. First, one criterion used to determine the riskiness of an action is whether or not the consequences of that action choice are of direct concern to an individual or group of decisionmakers. For example, movement of the stock market is risky to individuals who invested money there but is not risky to those who put their money in a checking or savings account. Second, the riskiness of the action choice is determined prior to the decision, based on an individual's belief about what will happen-not on some measure of variation or possible set of consequences determined using "objective" historical data. In his seminal work Risk, Uncertainty and Profit published in 1921, Frank Knight distinguished between risk and uncertainty on the basis of the amount of information available to the decisionmaker about the likelihood of outcomes of action choices. More specifically, his

17

What Is Risk?

distinction between the two was based on the characteristics of the situation that would or would not allow the use of general principles or empirical information to generate probabilities. If the situation is similar to others that had occurred in the past, and information about the outcomes of previous action choices could be used in the formation of a probability density function for the outcome of an action choice in the present situation, then the situation is risky. However, if the situation is unique, so that no information from similar situations in the past is available to use in the formation of probabilities, the situation is uncertain. Knight associated objective probabilities with risk and subjective probabilities with uncertainty. While many decision theorists still use Knight's definitions, others have incorporated research results from psychology and argue that because all information is subjectively perceived, measured, and interpreted, to base definitions on its quality is to build a definition on concepts that do not correspond to personal experience. Thus, there has been a growing trend toward treating all probabilities as subjective and making Knight's distinction moot. Measuring Risk

There is no universal agreement on the definition of risk. There is even less agreement on how to measure risk or determine whether or not one action is riskier than another. The riskiness of a choice depends on its context. Nevertheless, there are common ways to describe the characteristics of possible outcomes from an action choice. One way to summarize the consequences of an uncertain event is by using expected values. Like our definition of risk, the definition of expected value used in decision theory differs from the colloquial use of the term. Expected value does not mean the outcome or value that the decisionmaker thinks is most likely to occur. Nor does it mean that the expected value will occur. The calculation of expected values is done in a manner similar to that used to calculate an average; each consequence is first weighted by its likelihood of occurrence, then the average value of the weighted consequences is taken. Example 2.2 shows how an expected value is calculated. Even though the expected value of a set of possible outcomes can be used to characterize that set of outcomes, the expected value rarely is the outcome that actually occurs. For example, even though the expected value of possible rainfall during a year is 2 inches, 2 inches will not fall every time it rains (as is shown in Example 2.3). Another summary measure that is often used in discussing the

Risk and Its Effects on Agricultural Decisionmaking

18

EXAMPLE 2.2 Calculating An Expected Value

Calculating an expected value is like calculating an average. However, the computation involves an additional step: Each consequence is multiplied by its likelihood, and then these numbers are averaged. If every consequence is equally likely, the average and the expected value will be the same. Rainfall

Likelihood

Rainfall times the Likelihood

1 inch 2inches 3inches 4inches

40% 30% 20% 10%

40 60 60 40

100%

200

EXPECTED VALUE = 2

riskiness of an action choice is the coefficient of variation, which is a statistical measure of the dispersion of data relative to the average value. By using the coefficient of variation, formally defined as the standard deviation of the distribution divided by its mean, the effect of the size of the numbers measured is removed. Although this measure is useful when discussing instability (movement about a known point), it is not a good way to measure the riskiness of an action choice. For risk, one needs to measure variations around a decisionmaker's expectations rather than around a historical mean. Decisions between action choices are based not only on the expected value of the possible set of outcomes but also on the maximum amount that can be lost or gained and the relative likelihood of losing or gaining. The perceived riskiness of a particular decision EXAMPLE2.3

Consider a coin toss in which the outcomes "heads" and "tails" each has a 50 percent chance of occurring. Suppose you will win $100 if you get "heads" and lose $100 if you get "tails." The average of the possible outcomes is zero for any one coin toss. But you do not need to ever actually experience this average or expected outcome.

What Is Risk?

19

also depends on the decisionmaker's situation and the particular outcome of concern . Consider a producer who has few cash reserves or other means of sustaining the farm in the event of a loss. In this case, the producer may refuse to take a risky choice that could result in a cash shortfall even if the potential gains were large. In contrast, consider a producer who will lose his or her farm through bankruptcy unless a major gain can be realized. It would not necessarily be perverse behavior for a nearly insolvent individual to invest money in a risky venture rather than in one with a guaranteed gain that would be too small to forestall bankruptcy. It might, in fact, be prudent to take the "long shot" approach and invest in the risky venture. This action would yield the chance of earning enough to meet obligations. The likelihood of bankruptcy resulting from the riskier action choice may be no more unsatisfactory than the almost certain bankruptcy resulting from an investment in the less risky venture. In many cases, the scope of the analysis is an important factor in understanding the decisionmaker's choice. If we were only looking at the actual choice, without regard to the decisionmaker's entire situation, we might conclude that the producer had acted unwisely by choosing a very risky action. But by broadening the context or scope of analysis to include the firm's survival, the choice of the riskier action appears rational. The idea that there is a set of events or consequences that have a likelihood of occurring indicates that we must be aware of many dimensions of the distribution of likely consequences rather than just one summary value. One reason for this is that the decisionmaker is unlikely to receive the expected value of the distribution. The possible set of consequences of any action choice, and their attendant likelihood of occurring, can be illustrated using a probability distribution. We are accustomed to thinking of events or

Factors that affect the perceived riskiness of an action choice: • Expected value of distribution of outcomes. • Dispersion of outcomes. • Time interval assumed. • Decisionmaker's situation. • Scope of the analysis. • Level of aggregation.

20

Risk and Its Effects on Agricultural Decisionmaking

outcomes as evenly distributed-a uniform distribution-or as a symmetric, bell-shaped curve-a normal distribution. Another important factor to examine is whether the likelihood of losing is greater than, less than, or equal to the likelihood of gaining something from accepting a risk. For both the uniform and normal distributions shown in Figure 2.1, there is both an equal likelihood and an equal total likelihood weighted value of outcomes above and FIGURE 2. 1 Uniform and Normal Distributions of Outcomes Uniform Distribution Probability

Outcome

Normal Distribution Probability

Outcome

21

What Is Risk?

below the expected value. Lottery 1 in Example 2.4 could have come from a normal distribution. In agriculture, however, very few events of concern to decisionmakers, such as rainfall, yields, and prices, are either uniformly or normally distributed. Instead, events or outcomes tend to be distributed in skewed or lopsided patterns, such as in Lotteries 2 and 3 of the example. Risk is always implicitly measured over some time interval, and perceived riskiness of an action can vary with the length of the interval. For example, the probability of an accident occurring in the next year is much different than the probability of an accident occurring tomorrow. One of the difficult tasks in analyzing risk is aggregating measures of short-term risk into meaningful measures of long-term risk. The intervals over which different risks are experienced are often not the same; the production season and the marketing year for one crop, for example, may not coincide with either the calendar year or the production and marketing period for another crop. The perceived riskiness of an action choice will also vary with the level of aggregation at which its consequences are measured. When looking only at the returns from one farm enterprise, a particular crop may be quite risky because its yields are variable. EXAMPLE2.4

Consider the following lotteries, each of which has the same expected value but different distributions of possible outcomes in terms of the range of outcomes and the relative chances of losses and gains. Lottery 1:

50 % chance of winning $50,000 50% chance of losing $50,000 expected value = 0

Lottery 2:

25 % chance of winning $75,000 75 o/o chance of losing $25,000 expected value = 0

Lottery 3:

75 o/o chance of winning $25,000 25% chance of losing $75,000 expected value = 0

Would your choice between the gambles be based on their expected values alone or also on the dispersion of the outcomes? Would your choice be affected by your financial position?

22

Risk and Its Effects on Agricultural Decisionmaking

However, when considered in conjunction with other farm enterprises, the same crop may actually decrease the firm's overall risk because it complements the farm's other activities. Likelihood of Events

Decisionmakers presented with the historically based probabilities of events actually use different, subjectively formed probabilities when they evaluate choices. The use of subjective probabilities in decisionmaking behavior makes it difficult to accurately predict producers' reactions to policies. The reported likelihood of an event often is based on the frequency of similar events in the past. Historically based likelihoods are termed objective probabilities. However, individuals often use different probabilities when actually making decisions. People may reinterpret the objective probabilities using their past experiences, their expectations about the likelihood of different trends developing in the future, or many other factors. Recognition of the difference between objectively reported and subjectively formed probabilities can make us aware of the fact that predictions about producer responses to policy predicated on the use of objective probabilities may not indicate their most likely response. In considering the likelihood of events, distinctions must be made between those that have a continuous range of values and those that are discrete. Some events, such as temperature, rainfall, or prices, have a continuous range of values. Others, termed discrete events, either occur or do not occur (bankruptcy, fire, hail, or earthquakes, for example). Decisionmakers often assign subjective probabilities to both types of events. Are there events that are not given subjective probabilities? The stock market crash of 1929, the oil cartel of 1973, and the grain embargo of 1980 were all events that had important consequences for agricultural producers. Although in theory one could argue that each of these events was assigned a subjective probability of zero, few people anticipated these events, assigned them probabilities, or incorporated them into their decisionmaking processes. Risk Versus Variability

The riskiness of an action choice depends, in part, on the ability to predict what will happen in the future. Although risk often accompanies variability or instability, the existence of variability or instability does not necessarily create risk. It is unexpected variation-not variation per se-that fosters risk. This is why pro-

What Is Risk?

23

Variation in agricultural prices arises from: • Trends in demand and supply or general economic conditions. • Seasonal factors. • Economic or biological cycles. • Random variation or "noise." • Policy "shocks."

ducers often cite information as one of their most important tools for managing price or market risk. Not all price variation creates risk. For example, producers' familiarity with the marketing year price cycle allows them to incorporate its effects into their price predictions. Producers develop expectations about future prices from past experience, the current situation, and future known or predicted events. If past prices were stable or closely followed a trend-and nothing foretells a change in trend-producers are able to accurately predict future prices. But highly variable past prices make it hard to discern past price trends and to accurately predict future prices. The difficulty of predicting prices increases in step with the amount of variability or instability. The resultant uncertainty over future prices creates risk for the seller of agricultural products. Care must be taken to separate aspects of variation that create risk from those that do not. Consider, for example, the variation about the mean of observed market prices for rice that are shown in Figure 2.2. Not

EXAMPLE2.5 Suppose you are playing darts. There is no guarantee that you will hit the bull's eye on every throw, but based on your past experience, you have a fairly good idea what your chances are of hitting particular parts of the board. Now transfer your game to the ocean, where you are standing on a floating platform. If the ocean is fairly calm, you will eventually figure out the cyclic pattern of the swells and be able to compensate in aiming and throwing the dart. Suppose, however, that it is stormy and the regular pattern of the swells is hard to discern because of the erratic turbulence of the water. In this case, your dart throws are likely to be wild.

24

Risk and Its Effects on Agricultural Decisionmaking

all of this variation creates risk if agricultural producers are able to discern marketing year price cycles and trends. The variation that creates risk for producers is that which remains once trend and seasonality are removed. Figure 2.2 shows the price for rice that is observed in the marketplace and the remaining variation because of random events that exists after trend and seasonality factors are removed. This distinction is important when considering the relative price risks associated with two or more crops. One crop may, in fact, be accompanied by less price risk than another, even though the variation about the mean of observed prices is greater. Prediction is made more difficult if the future is not expected to mimic the past-a situation many producers now face. Some of the changes occurring today are macroeconomic in nature, including changing patterns of interest rates, exchange rates, and deficit levels. Others changes are technological and biological, such as biotechnology and shifting global patterns of supply and demand. Added to these more gradual changes in trend are sudden changes in the economic environment because of what are known as policy shocks. The 1983 Payment in Kind (PIK) program is an example of a policy shock that affected agricultural prices. Even the anticipation of policy changes can increase perceived risk: Many producers now anticipate changes in policy and trend factors that will affect income from market receipts and government payments. However, they cannot predict the precise form that the changes will take. For example, producers assume that the secretary of agriculture will use discretionary authority to lower the loan rate for wheat and com to the minimum allowed under current legislation. But producers cannot predict whether new legislation will replace existing legislation. Agricultural policymakers must also be aware of the different sources of price variation and risk faced by producers. Strategies for altering price risk arising from weather are quite different from strategies for reducing uncertainty about government program changes or shifting patterns of international supply and demand. Furthermore, policies that affect the average price level also may affect the amount of price variation. Policymakers are also concerned with disequilibrium, a concept often associated with risk. Variation in short-term prices away from the long-run expected price may create risk. The market is said to be in disequilibrium if today's price is different from a normal longrun price that is justified by underlying conditions of supply and demand. However, even daily prices are, in a sense, equilibrium prices because they reflect that day's relationship between supply and demand. The importance of disequilibrium and instability is that variation in short-term prices away from the long-term expected or equilibrium price creates risk. Ian Dalziel! notes that even predictable instability creates costs because of the presence of fixed capital inputs that may be under-

25

What Is Risk?

FIGURE 2.2 Random Component of Market Price for Rice Cents/CWT

800

1\

600

(-;I l

I' I I I I I I

400

200

I ', \ \ \

0

."

\ :,.,\,\

\

I I I I

-200 -400

,.J

\ I \ '\ I

-600

"v

-000 ~-------------------------------------------r-.

r-. r-.

r-.

z ....,

~ ....,

z ....,

(I)

~

c(

~

(I)

~

c(

mean of observed prices variation about the mean of observed price

..................................

variation about the mean due to random noise

utilized. In addition, intertemporal storage costs are higher under more unstable, though predictable, markets than under stable markets. Concluding Comments

Although colloquial use of the terms risk and uncertainty conveys the general themes of concern, more precise definitions are needed to conduct consistent examinations of risk management from a poli-

26

Risk and Its Effects on Agricultural Decisionmaking

cy perspective. This chapter provided a common set of terms for use throughout the remainder of the book. It also highlighted the distinction between risk, variability, and uncertainty. A theme introduced here that will reappear throughout the book is that riskiness is contingent on numerous factors, and the apparent riskiness of any situation will vary with the type of measure used and the scope of the analysis.

Selected Readings Bar-Hillel, M. "On the Subjective Probability of Compound Events," Organizational Behavior and Human Performance 9 (1973):396-406. Beach, L., and J. Wise. "Subjective Probability and Decision Strategy," Journal of Experimental Psychology 79 (1969):133-138. Bernoulli, D. "Exposition of a New Theory on the Measurement of Risk." Translation from the 1738 original, Econometrica 22 (1954):23-36. Bessler, D. "Subjective Probability." Pp. 43-52 in P. Barry, ed., Risk Management in Agriculture. Ames: Iowa State University Press, 1984. Covello, V., and J. Manpower. "Risk Analysis and Risk Management: An Historical Perspective." Risk Analysis 2 (1985):103-120. Dalziel!, I. "Sources of Market Instability in Agriculture." Ph.D. thesis, Michigan State University, 1985. Fischhoff, B., S. Watson, and C. Hope. "Defining Risk," Policy Sciences 17 (1984):123-139. Gardner, B. "Panel Discussion: Summary and Reactions." Pp. 171-174 in D. Sumner, ed., Agricultural Stability and Farm Programs. Boulder, Colo.: Westview Press, 1988. Hazell, P. Changing Patterns of Variability in World Cereal Prices and Production. Washington, D.C.: International Food Policy Research Institute, 1985. Hey, J. Uncertainty in Microeconomics. New York: New York University Press, 1979. Hogarth, R. "Cognitive Processes and the Assessment of Subjective Probability Distributions," Journal of the American Statistical Association 70 (1975):271-289. Knight, F. Risk, Uncertainty, and Profit. Boston: Houghton-Mifflin Company, 1921. Kramer, R. "Reaction to Stability and Farm Programs: A Case Study of Feed Grain Markets." Pp. 109-112 in D. Sumner, ed., Agricultural Stability and Farm Programs. Boulder, Colo.: Westview Press, 1988. Leroy, S., and L. Singell, Jr. "Knight on Risk and Uncertainty," Journal of Political Economy 95 (1987):394-406. Robison, L., and L. Lev. "Distinguishing Between Indirect and Direct Outcome Variables to Predict Choices Under Risk or Why Woody Chip Went to the Air," North Central Journal of Agricultural Economics 8 (1986):59-67. Stiglitz, J. Quoted in J. Roumasset, "Introduction and State of the Arts." Pp. 3-21 in J. Roumasset, J. Boussard, and I. Singh, Risk, Uncertainty, and Agricultural Development. New York: Agricultural Development Council, 1979. Thompson, G. Statistics for Decisions: An Elementary Introduction. Boston: Little, Brown and Company, 1972.

3 Sources and Effects of Risk in Agriculture

The sources of risk affecting agriculture are numerous, ranging from weather and pests to the policymaking process. When the U.S. agricultural sector was insulated from the world economy, major sources of risk were disease, weather, the structure of local input markets, and fluctuations in domestic demand. As the U.S. farm sector was integrated into the global economy it faced new sources of risk including the general economic policies of both the United States and its trading partners. Even the policy process itself can create risks for agricultural producers. Although the exact effects of risk on the agricultural sector have yet to be quantified, it is clear that these multiple sources of uncertainty and risk interact to shape the agricultural producers' decision environment and the choices that they make. Production and Marketing Risk

A twelve-state survey of agricultural producers hints at the variety of sources of risk they face. One hundred forty-seven crop and livestock producers who responded to the survey were asked to rate seventeen common sources of variability in agriculture according to their importance in production and marketing activities. Table 3.1 shows these rankings. The relative importance of risk sources varies according to production process, enterprise combination, location, resource base, financial condition, and other characteristics of the producer or firm. For example, ranchers in Arizona list government programs as the most important source of risk and crop producers in Mississippi list commodity prices as the most important. Any discussion of the sources of risk important to agricultural producers is made more complicated by the fact that time plays an 27

28

Risk and Its Effects on Agricultural Decisionmaking

Table 3.1 Producers' Ranking of Important Sources of Variability in Production and Marketing

Type of Variability Type of Farm Enterprise

Most Important

2nd Most Important

3rd Most Important

4th Most Important

5th Most Important

Weather

Product prices

World events

Input costs

Inflation

Mainly crops/ Weather some livestock

Product prices

Diseases/ pests

Inflation

Input costs

Livestock only

Weather

Product prices

Input costs

Safety/ health

Inflation

Mainly livestock/ some crops

Product prices

Input costs

Weather

Diseases/ pests

Safety/ health

Crops only

important role in shaping risk and risk management. The interval between when a decision is made and when the outcome or consequence is known can affect risk. The importance of time grows with the need to integrate short-term tactical planning with long-term strategic planning and decisionmaking. The passage of time is an integral part of the continuous nature of decision making, of decisions about gathering information and maintaining flexibility to respond to events, and of choices about the length of the planning period over which resources are assumed to be fixed. Numerous ways to categorize the sources of risk have been suggested. Most rely on dichotomies such as natural risk versus manmade risk, or production risk versus marketing risk or financial risk. However, the factors affecting the riskiness of any given situation Characteristics often used to classify sources of risk: • "Man-made" versus "natural." • Association with different functions performed by the firm, namely production risk, marketing risk, and financial risk. • Frequency of occurrence, namely rare occurrences like natural disasters versus ubiquitous sources such as weather. • Adaptability to sharing through market mechanisms such as insurance or contingent contracts.

Sources and Effects of Risk in Agriculture

29

are not so easily separated. Price risk is often affected by both manmade factors, including institutions and policies, and natural factors, such as weather, through their influences on yields. Each classification system focuses on a different dimension or attribute of the risky situation. No one classification system is "best." Choice of a particular system to categorize risks depends on the problem or objectives at hand.

Risks Introduced by Agriculture's Integration into the Global Economy

The agricultural sector has been thrust from a situation in which it was almost totally isolated from the effects of domestic monetary and fiscal policy and international market fluctuations into a position in which it absorbs many costs of changes in these arenas. Up to the early 1970s, the riskiness of agriculture was described in terms of the inherent instability of agricultural commodity markets, caused by physical, technical, and human factors. Physical factors include weather patterns and reproduction cycles; important technical factors are rapid technological change and the nontransferability of some resources among agricultural enterprises or out of the sector; and human factors include poor use of available information in forming expectations of prices. In the 1980s, sources of risk outside the U.S. agricultural sector have become more important, reflecting the integration of the U.S. agricultural sector into the world economy. Deregulation of credit and banking, movement from fixed to flexible exchange rates, and integration of international capital markets have fostered this change. The links between the domestic agricultural sector and the national and international economy have also become more direct and varied. Broad economic policies that affect interest rates, personal income, inflation, and energy costs in turn affect acreage, yield, demand for inputs, and inventory held. Conversely, agriculture influences the general economy. Changes in farm and food prices affect the consumer price index, agricultural program expenditures affect deficits, and the level of agricultural exports affects the U.S. trade balance. In addition, high levels of capital investment in agriculture and the need for short-, medium-, and long-term credit make agricultural producers particularly susceptible to variability in interest rates. With farm sector debt exceeding $200 billion and net farm income ranging between $20 billion and $30 billion, a !-percentage point

30

Risk and Its Effects on Agricultural Decisionmaking

change in interest rates directly reduces or increases net income as much as 10 percent. Stated another way, agriculture's debt-toincome ratio today is nearly ten, while in 1950 it was about one. Agriculture is not the only sector affected by changes in monetary policy, interest rates, or exchange rates. However, it appears to experience more price volatility than other sectors of the economy when these changes do occur. This is evidenced by commodity price overshooting, which is the tendency of agricultural prices to swing beyond the point necessary to adjust to changes in the domestic or international economy. Commodity price overshooting occurs because of two characteristics of agriculture. The first is that agricultural prices generally are determined in a competitive market and adjust rapidly to changes in economic conditions. Rapid adjustment of agricultural commodity prices differs from the price adjustment process in many other sectors of the economy in which producer "markup" on cost of production determines prices. Because production costs are unlikely to respond rapidly to changes in demand and supply, prices in most manufacturing industries tend to be "sticky," "fixed," or inflexible downward. The second feature contributing to agricultural commodity price overshooting is the relatively long time period between the time that production decisions are made and the time when the product is ready for market. Adjustments in quantities produced in agriculture can be made only at the beginning of a production cycle, often once a year, though other industries have more frequent opportunities to adjust. Because of the long production period, producers cannot readily respond to changing market conditions. Manufacturers can respond to changing market conditions by maintaining price and adjusting output or by adjusting sales from inventories. In contrast, agricultural producers' supply is fixed in the short run; instead of adjusting quantity to maintain price, prices must adjust to compensate for changes in market conditions. When a change in the domestic or international economy leads to adjustments in the U.S. economy, the more flexible prices will, in the short run, overadjust to compensate for the fixity or stickiness of other prices. The wide swings in agricultural prices are shown in Figure 3.1, which compares annual percent changes in producer price indexes for agricultural and industrial products. If conclusions about the riskiness of agriculture are based solely on year-to-year variations in commodity prices, the complex problems involved in estimating changes in the absolute level of farm prices are sharply underestimated. For example, most livestock products require a production period of more than one year.

31

Sources and Effects of Risk in Agriculture

When plans made in the first year do not come to fruition for two years, the problem of estimation is greatly increased. In addition, agricultural commodity prices vary greatly throughout the year. This within-year variation is removed by using annual averages. As commodity prices vary, so does the value of the physical capital held by agricultural producers, making highly leveraged producers vulnerable to steep drops in asset values. Modern U.S. agriculture involves large capital investments in specialized equipment that has few alternative uses. The average commercial farm has an investment in land, buildings, and machinery of over $1 million. The value of land and equipment reflects both their current value in alternative uses and expected earning capacity. Instability in current market prices and uncertainty about future market trends ereFIGURE 3. 1 Annual Percentage Changes in Prices Received for Agricultural and Industrial Products Percent Change

~ .-----------------------------------------------~

25 20 15

(

A \ \

\

10

\ \ \ \

5

-5 -10 ~----------------------------------------------~ 1985 1970 1980 1975 1955 1960 1965

- - - - - agricultural

- - - - - - industrial

32

Risk and Its Effects on Agricultural Decisionmaking

ate uncertainty about the value of resources. The sensitivity of asset prices to increases in the variation of net revenue increases with the durability or expected economic life of the asset. This situation creates a problem for farmers relying on long-term financing of land and equipment. Farmland prices can get bidded upward based on buoyant exports and rapid inflation, as they did in the late 1970s. Bright earnings prospects encourage farmers to incur longterm debt. But if prices fall, heavily leveraged farmers have collateral worth less than their loans. Bankruptcy caused by cash flow shortages often leads to the liquidation of some or all of the farm's assets. If the producer has adequate collateral, the bank holding the loan loses only the liquidation costs. The producer, however, loses equity. If the producer has inadequate A study conducted before the passage of the 1985 Food Security Act and Gramm-Rudman-Hollings showed that different courses of economic policy over the following four years would have major and markedly different impacts on the agricultural sector. After looking at the effect of three scenarios on a variety of performance indicators, the authors concluded that they would have markedly different effects on the short- and long-term health of the agricultural sector. The three scenarios were: • High deficits and slow monetary growth resulting in lower net farm income, declining asset values, and a financially weak sector. • High deficits and moderate monetary growth resulting in net farm income that initially increased, then declined, increasing asset values, and a financially weak sector. • Low deficits and moderate monetary growth resulting in an increase in net farm income, increasing asset values, and a financially strong sector. Which scenario should agricultural producers have used in early 1985 to plan their financial strategy over the following decade? Which scenario should they use now? Conventional wisdom may suggest that producers anticipate the continuation of the present scenario, but it was this same advice to farmers in the late 1970s that helped to foster some of the debt problems that the farm sector experienced in the early 1980s. Source: Hughes and Penson.

Sources and Effects of Risk in Agriculture

33

collateral, or if the value of the collateral has fallen, sale of the assets will not be enough to repay the loan. Thus, both the producer and the financial institution may take a substantial loss. Forces shaping commodity prices also directly affect the value of physical capital, particularly land. For example, land may be seen as an investment opportunity when real (rather than financial) assets are deemed a good "hedge" against inflation. The increased demand for land can result in a rise in its price. When the economic environment changes, not all sectors of the economy or all assets in a sector will be affected in the same way. Specific policies, such as tax policy, can alter the value of physical capital and reduce its attractiveness as an investment. For example, provisions of the Internal Revenue Code of 1986 (more popularly referred to as the Tax Reform Bill) governing losses from passive activities and capital gains dampen incentives for nonfarmers to invest in agriculture. At the same time, changes in the investment tax credit and depreciation provisions increased the cost of farm capital about 10 percent and continue a pattern of investment incentives that fluctuate with the inflation rate. Policy Risk

Policy risk is another important source of risk for agricultural producers. The policymaking process and the implementation of subsequent policies foster two different types of risk; one stems from uncertainty about future directions in policy legislation, and the other is created from uncertainty about how administrative officers will use their legally mandated discretionary authority to carry out program provisions. Producers have always faced both types of policy risk; since passage of the 1985 Food Security Act, which gives the secretary of agriculture more discretion in setting policy parameters, these risks have become more prevalent. And with several new farm policies being debated, producers are not sure which basic policies will be in place during the useful life of major purchases made now. In the meantime they face uncertainty over current program decisions governing loan levels, marketing loan programs, and conservation reserve bidding rules, all of which are set by secretarial discretion. Producers are also affe