F rom the perspective of many economists, motives other than self-interest are peripheral to the main thrust of human endeavor, and we indulge them at our peril. In Gordon Tullock's (1976) words (as quoted by Mansbridge, 1990, p. 12), "the average human being is about 95 percent selfish in the narrow sense of the term." In this paper we investigate whether exposure to the self-interest model commonly used in economics alters the extent to which people behave in self-interested ways. The paper is organized into two parts. In the first, we report the results of several empirical studies-some our own, some by others -that suggest economists behave in more self-interested ways. By itself, this evidence does not demonstrate that exposure to the self-interest model causes more self-interested behavior, since it may be that economists were simply more self-interested to begin with, and this difference was one reason they chose to study economics. In the second part of the paper, we present preliminary evidence that exposure to the self-interest model does in fact encourage self-interested behavior.

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Does Studying Economics Inhibit Cooperation

Adaptation in agriculture to climate change is important for impact andvulnerability assessment and for the development of climate change policy. A wide variety of adaptation options has been proposed as having thepotential to reduce vulnerability of agricultural systems to risks related toclimate change, often in an ad hoc fashion. This paper develops atypology of adaptation to systematically classify and characterize agriculturaladaptation options to climate change, drawing primarily on the Canadiansituation. In particular, it differentiates adaptation options in agricultureaccording to the involvement of different agents (producers, industries,governments); the intent, timing and duration of employment of theadaptation; the form and type of the adaptive measure; and the relationshipto processes already in place to cope with risks associated with climatestresses. A synthesis of research on adaptation options in Canadianagriculture identifies four main categories: (i) technological developments,(ii) government programs and insurance, (iii) farm production practices,and (iv) farm financial management. In addition to these `directadaptations', there are options, particularly information provision, that maystimulate adaptation initiatives. The results reveal that most adaptationoptions are modifications to on-going farm practices and public policydecision-making processes with respect to a suite of changing climatic(including variability and extremes) and non-climatic conditions (political,economic and social). For progress on implementing adaptations to climatechange in agriculture there is a need to better understand the relationshipbetween potential adaptation options and existing farm-level andgovernment decision-making processes and risk management frameworks.

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Adaptation options in agriculture to climate change: a typology

Role playing can be used to forecast decisions, such as “how will our competitors respond if we lower our prices?” In role playing, an administrator asks people to play roles and uses their “decisions” as forecasts. Such an exercise can produce a realistic simulation of the interactions among conflicting groups. The role play should match the actual situation in key respects, such as that role players should be somewhat similar to those being represented in the actual situations, and roleplayers should read instructions for their roles before reading about the situation. Role playing is most effective for predictions when two conflicting parties respond to large changes. A review of the evidence showed that role playing was effective in matching results for seven of eight experiments. In five actual situations, role playing was correct for 56 percent of 143 predictions, while unaided expert opinions were correct for 16 percent of 172 predictions. Role playing has also been used successfully to forecast outcomes in three studies. Successful uses of role playing have been claimed in the military, law, and business.

Principles of forecasting

Introduction References and Suggested Readings PART I REAL DYNAMIC MACROECONOMIC MODELS 1. Dynamic Programming A General Intertemporal Problem A Recursive Problem Bellman's Equations Nonstochastic Examples The Optimal Linear Regulator Problem Stochastic Control Problems Examples of Stochastic Control Problems The Stochastic Linear Optimal Regulator Problem Dynamic Programming and Lucas's Critique Dynamic Games and the Time Inconsistency Phenomenon Conclusions Exercises References and Suggested Readings 2. Search Nonnegative Random Variables Stigler's Model of Search Sequential Search for the Lowest Price Mean-Preserving Spreads Increases in Risk and the Reservation Price Intertemporal Job Search Waiting Times Firing Jovanovic's Matching Model Conclusions Exercises References and Suggested Readings 3. Asset Prices and Consumption Hall's Random Walk Theory of Consumption The Random Walk Theory of Stock Prices Lucas's Model of Asset Prices Mehra and Prescott's Finite-State Version of Lucas's Model Asset Pricing More Generally The Modigliani-Miller Theorem Government Debt and the Ricardian Proposition Remarks on Testing and Estimation Conclusions Exercises References and Suggested Readings PART II MONETARY ECONOMICS AND GOVERNMENT FINANCE 4. Currency in the Utility Function The Price of Inconvertible Government Currency in Lucas's Tree Model Issues and Models in Monetary Economics Government Debt in the Utility Function Government Currency in the Utility Function Seignorage and the Optimum Quantity of Currency A Neutrality Proposition Conclusions References and Suggested Readings 5. Cash-in-Advance Models A One-Country Model Fisher Equations Inflation-Indexed Government Debt Interactions of Monetary and Fiscal Policies Interest on Reserves A Two-Country Model Exchange Rate Indeterminacy Conclusions Exercises References and Suggested Readings 6. Credit and Currency with Long-Lived Agents The Physical Setup Optimal Allocations Competitive Equilibrium A Digression on the Balances of Trade and Payments The Ricardian Doctrine about Taxes and Government Debt The Model with Valued Currency and No Private Debt An Interventionist Optimal Monetary Equilibrium Townsend's \"Turnpike\" Interpretation Conclusions Exercises References and Suggested Readings 7. Credit and Currency with Overlapping Generations The Overlapping-Generations Model The Ricardian Doctrine about Taxes and Government Debt Again A Ricardian Proposition Currency, Bonds, and Open-Market Operations Computing Equilibria Interpretations as Currency Equilibria Optimality Four Examples on Inflation and Its Causes Seignorage and the Laffer Curve Dynamics of Seignorage Forced Saving International Exchange Rates Conclusions Exercises References and Suggested Readings 8. Government Finance in Stochastic Overlapping-Generations Models The Economy Some Examples A General Irrelevance Theorem Wallace's Modigliani-Miller Theorem for Open-Market Operations Chamley and Polemarchakis's Neutrality Theorem Interpretation as a Constant Fiscal Policy Indexed Government Bonds A Ricardian Proposition Further Irrelevance Theorems Conclusions Exercises References and Suggested Readings Appendix. Functional Analysis for Macroeconomics Metric Spaces and Operators First-Order Linear Difference Equations A Formula of Hansen and Sargent A Quadratic Optimization Problem in R A Discounted Quadratic Optimization Problem Predicting a Geometric Distributed Lead of a Stochastic Process Discounted Dynamic Programming A Search Problem Exercises References and Suggested Readings Index

Dynamic Macroeconomic Theory

The risks confronted by grain and cotton farmers are of particular interest, given the changing role of the Government after passage of the 1996 Farm Act. With the shift toward less government intervention in the post-1996 Farm Act environment, a more sophisticated understanding of risk and risk management is important to help producers make better decisions in risky situations and to assist policymakers in assessing the effectiveness of different types of risk protection tools. In response, this report provides a rigorous, yet accessible, description of risk and risk management tools and strategies at the farm level. It also provides never-before-published data on farmers' assessments of the risks they face, their use of alternative risk management strategies, and the changes they would make if faced with financial difficulty. It also compares price risk across crops and time periods, and provides detailed information on yield variability.

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Managing Risk in Farming: Concepts, Research, and Analysis

This paper analyzes production, hedging, and speculative decisions when both futures and options can be used in an expected utility model of price and basis uncertainty When futures and option prices are unbiased, optimal hedging requires only futures (options are redundant) Options are used together with futures as speculative tools when market prices are perceived as biased Straddles are used to speculate on beliefs about price volatility and to hedge the futures position used to speculate on beliefs about the expected value of the futures price Mean-variance analysis in general is not consistent with expected utility when options are allowed One extension of Sandmo's expected utility model of the competitive firm under price uncertainty considers the use of futures or forward contracts Danthine; Holthausen; and Feder, Just, and Schmitz show that without basis uncertainty the optimal output level is not affected by price risk; also, with an unbiased futures price, the optimal hedging level of the competitive firm is the full hedge, while a biased futures price will result in a partly speculative hedge Related works include Batlin, who allows for basis risk in the form of imperfect time hedging; Paroush and Wolf, and Antonovitz and Nelson, who consider basis risk with the simultaneous availability of futures and forward contracts; Grant, Honda, Losq, Newbery and Stiglitz, and Rolfo, who allow for production uncertainty; Chavas and Pope, who allow for production uncertainty and hedging costs; and Karp, who considers the problem in a dynamic setting This paper provides a further extension of this analysis by allowing options as a means of coping with price risk With the introduction of commodity options on futures for many commodities in the 1980s, this problem appears relevant to a number of production settings, especially in agriculture Specifically, this paper considers the simultaneous choice of a production level and of hedging levels of futures and options within the general expected utility model The model allows for basis uncertainty, but the production process is assumed to be nonstochastic

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Production, Hedging, and Speculative Decisions with Options and Futures Markets

The performance of individual farm yield and area yield crop insurance programs is evaluated for a representative Iowa corn farm using numerical optimization of expected utility and simulation techniques. Several different contract design features are studied, including the nature of the yield index which triggers insurance payouts, alternative restrictions on coverage levels, and alternative pricing structures. Performance is evaluated in terms of impacts on farmer participation and welfare and is examined in a portfolio setting where futures and options are also available to farmers. The relative performance of different crop insurance designs is found to be particularly sensitive to restrictions on coverage levels, the size of premium loadings, and the degree to which individual farm yields are correlated with area yields.

The Effects of Crop Yield Insurance Designs on Farmer Participation and Welfare

Standard commodity option pricing models assume proportional changes in the underlying futures price are i.i.d. normal. Empirical evidence suggests commodity futures price movements exhibit excess kurtosis and time-varying volatility. This paper presents option pricing models when time-varying volatility and excess kurtosis in the underlying futures price can be modeled as a GARCH process. Empirical results suggest that the GARCH option pricing model outperforms the standard Black option-pricing model, which uses historical volatilities. A closed-form approximation model using a variance forecast generated from the estimated GARCH process also outperforms Black's model and in many cases the general GARCH model as well.

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Pricing Commodity Options when the Underlying Futures Price Exhibits Time-Varying Volatility

The known sufficient conditions for the mean-variance framework to produce expected utility results are violated in the presence of truncated probability distributions. A theoretical simulation is conducted to examine the ability of the linear mean-variance model to approximate expected utility results when the income distribution is truncated by the use of commodity option contracts. The mean-variance model is shown to produce solutions that are close approximations to the expected utility model results under the assumptions of constant absolute risk aversion and normally distributed prices. However, some inconsistency was found between the comparative static results of the two models.

Robustness of the Mean-Variance Model with Truncated Probability Distributions

A discrete-time dynamic hedging problem is solved under expected utility maximization and basis risk without imposing a particular parametric form for utility, nor assuming normally distributed cash and futures prices. The solution is valid for any increasing and strictly concave utility function, and for quite general specifications of the joint distribution of cash and futures prices. This generality is achieved by restricting the futures market to be unbiased, and requiring that the size of the cash position be nonstochastic. The dynamic hedging rule can be estimated empirically using similar methods to those used to estimate static hedge ratios.

Steven D. Hanson

Papers

Production, Hedging, and Speculative Decisions with Options and Futures Markets

The Effects of Crop Yield Insurance Designs on Farmer Participation and Welfare

Pricing Commodity Options when the Underlying Futures Price Exhibits Time-Varying Volatility

Robustness of the Mean-Variance Model with Truncated Probability Distributions

Optimal Dynamic Hedging in Unbiased Futures Markets