Coping With Risk in Agriculture

by J. Brian Hardaker; Ruud B. M. Huirne; Jock R. Anderson; Gudbrand Lien

• ISBN13: 9780851998312
• ISBN10: 0851998313
• Edition: 2nd
• Format: Paperback
• Copyright: 2004-06-17
• Publisher: Cab Intl

Summary

The popular first edition of this standard text on risk analysis and management in agriculture has been almost wholly revised. The second edition includes much new material. There is a revised chapter on incorporating decision makers' preferences into the analysis of risky choices that recognizes and gives consideration to some recently published challenges to the legitimacy of the expected utility hypothesis. While it is argued that the theory is still the best way to handle risk aversion, at least in prescriptive analyses, more attention is given to the practical problems of utility function elicitation. It is shown how estimates of (or ranges of) degree of risk aversion might best be obtained and consistently applied. The new edition has a much more thorough treatment of stochastic simulation, including some novel yet simple methods for dealing to stochastic dependency between uncertain quantities. The treatment of policy aspects of risk in agriculture has been revised and extended to account for such important current issues as new approaches to crop insurance, the management of serious animal and crop diseases and food safety issues. As with the first edition, the book contains a blend of theory with simple illustrative examples to enable readers to see how the principles being discussed can be made operational using modern software.

Table of Contents

PREFACE	ix
Preface to the second edition	ix
Preface to the first edition	x
1. INTRODUCTION TO RISK IN AGRICULTURE	1	(22)
Examples of risky decisions in agriculture, and their implications	1	(3)
The need to take account of risk in agriculture	4	(1)
Risk and uncertainty	5	(6)
Who needs to think about risk in agriculture?	11	(2)
A general approach to risk management in agriculture	13	(5)
When formal decision analysis is needed	18	(2)
Outline and general approach of the book	20	(2)
Selected additional reading	22	(1)
2. DECISION ANALYSIS: OUTLINE AND BASIC ASSUMPTIONS	23	(15)
Basic concepts	23	(2)
A simple risky decision problem	25	(2)
Structuring the problem: influence diagram representation	27	(1)
Decision tree representation	28	(2)
Analysing the decision tree	30	(4)
Components of decision analysis and its axiomatic foundation	34	(2)
Other assumptions	36	(1)
Rational choice under risk	37	(1)
Selected additional reading	37	(1)
3. MEASURING UNCERTAINTY WITH SUBJECTIVE PROBABILITIES	38	(24)
Probabilities to calibrate beliefs	38	(3)
Eliciting and describing probability distributions	41	(14)
Accounting for new information	55	(6)
Selected additional reading	61	(1)
4. MAKING BETTER PROBABILITY JUDGEMENTS	62	(30)
Introduction	62	(1)
The relevance of data in probability assessment	62	(9)
Taking expert advice	71	(3)
Obtaining joint probability distributions	74	(12)
Psychological pitfalls in making probability judgements	86	(4)
Selected additional reading	90	(2)
5. ATTITUDES TO RISKY CONSEQUENCES	92	(29)
Introduction	92	(3)
Utility function elicitation	95	(5)
Risk aversion	100	(5)
Utility function fitting	105	(1)
From expected utility to certainty equivalent	105	(1)
Problems in utility function elicitation	106	(2)
Alternatives to direct elicitation of utility functions	108	(2)
Rationalizing risk aversion	110	(3)
The importance of risk aversion	113	(5)
Group decision making	118	(1)
Conclusion	119	(1)
Selected additional reading	120	(1)
6. INTEGRATING BELIEFS AND PREFERENCES FOR DECISION
ANALYSIS	121	(1)
Decision trees revisited	121	(9)
Payoff table approach	130	(1)
Incorporating new information	131	(3)
Beliefs and preferences in analysing production under risk	134	(4)
Selected additional reading	138	(2)
7. DECISION ANALYSIS WITH PREFERENCES UNKNOWN	140	(17)
Efficiency criteria	140	(2)
Analysis using moments of the distribution	142	(5)
Stochastic efficiency methods	147	(9)
Concluding comment	156	(1)
Selected additional reading	156	(1)
8. STOCHASTIC SIMULATION	157	(25)
Introduction	157	(1)
Stochastic simulation as a tool in decision analysis	158	(6)
Basic sampling techniques	164	(4)
Methods to account for stochastic dependency	168	(8)
Combining stochastic simulation and optimization	176	(5)
Concluding comments	181	(1)
Selected additional reading	181	(1)
9. RISK AND MATHEMATICAL PROGRAMMING MODELS	182	(29)
A brief introduction to mathematical programming	182	(2)
A basic example	184	(1)
Mathematical programming approaches to whole-farm system planning under risk	185	(2)
Risk programming	187	(16)
Stochastic programming	203	(6)
Concluding comment	209	(1)
Selected additional reading	210	(1)
10. DECISION ANALYSIS WITH MULTIPLE OBJECTIVES	211	(23)
Introduction with some examples	211	(2)
Objectives and attributes	213	(1)
Structuring the decision problem	213	(5)
Basic concepts in multi-attribute utility	218	(6)
Assessing attribute utilities	224	(3)
Methods for weighting attribute utilities	227	(3)
Multi-attribute utility analysis under uncertainty	230	(2)
Other forms of multi-attribute utility analysis	232	(1)
Selected additional reading	233	(1)
11. RISKY DECISION MAKING AND TIME	234	(31)
The time factor in decision analysis	234	(2)
Investment appraisal under uncertainty	236	(8)
Dynamic decision analysis	244	(8)
Stochastic dynamic modelling methods	252	(12)
Selected additional reading	264	(1)
12. STRATEGIES DECISION MAKERS CAN USE TO MANAGE RISK	265	(22)
Introduction	265	(3)
On-farm strategies	268	(7)
Strategies to share risk with others	275	(11)
Concluding comment	286	(1)
Selected additional reading	286	(1)
13. RISK CONSIDERATIONS IN AGRICULTURAL POLICY MAKING	287	(22)
Introduction	287	(1)
Government intervention and farm-level risk	288	(5)
Market failure for risk transfer	293	(6)
Experience with public risk-management instruments	299	(4)
Emerging issues in risk management	303	(5)
Concluding comment	308	(1)
Selected additional reading	308	(1)
REFERENCES	309	(11)
SELECTED SOFTWARE FOR DECISION ANALYSIS	320	(2)
INDEX	322