Estimation Of Risk Preferences Research Articles

The (in)stability of farmer risk preferences

AbstractWe test and quantify the (in)stability of farmer risk preferences, accounting for both the instability across elicitation methods and instability over time. We use repeated measurements (N = 1530) with Swiss fruit and grapevine producers over 3 years, using different risk preference elicitation methods (domain‐specific self‐assessment and incentivised lotteries). We find that farmers' risk preferences change considerably when measured using different methods. For example, self‐reported risk preference and findings from a Holt and Laury lottery correlate only weakly (correlation coefficients range from 0.06 to 0.23). Moreover, we also find that risk preferences vary considerably over time, that is, applying the same elicitation method to the same farmer in a different point in time results in different risk preference estimates. Our results show self‐reported risk preferences are moderately correlated (correlation coefficients range from 0.42 to 0.55) from one year to another. Finally, we find experiencing crop damages due to climate extremes and pests is associated with farmers becoming more risk tolerant over time in specific domains.

Behavioral welfare economics and risk preferences: a Bayesian approach

We propose the use of Bayesian estimation of risk preferences of individuals for applications of behavioral welfare economics to evaluate observed choices that involve risk. Bayesian estimation provides more systematic control of the use of informative priors over inferences about risk preferences for each individual in a sample. We demonstrate that these methods make a difference to the rigorous normative evaluation of decisions in a case study of insurance purchases. We also show that hierarchical Bayesian methods can be used to infer welfare reliably and efficiently even with significantly reduced demands on the number of choices that each subject has to make. Finally, we illustrate the natural use of Bayesian methods in the adaptive evaluation of welfare.

Eliciting risk preferences that predict risky health behavior: A comparison of two approaches.

Information on attitudes to risk could increase understanding of and explain risky health behaviors. We investigate two approaches to eliciting risk preferences in the health domain, a novel “indirect” lottery elicitation approach with health states as outcomes and a “direct” approach where respondents are asked directly about their willingness to take risks. We compare the ability of the two approaches to predict health‐related risky behaviors in a general adult population. We also investigate a potential framing effect in the indirect lottery elicitation approach. We find that risk preferences elicited using the direct approach can better predict health‐related risky behavior than those elicited using the indirect approach. Moreover, a seemingly innocuous change to the framing of the lottery question results in significantly different risk preference estimates, and conflicting conclusions about the ability of the indicators to predict risky health behaviors.

The risk elicitation puzzle revisited: Across-methods (in)consistency?

With the rise of experimental research in the social sciences, numerous methods to elicit and classify people’s risk attitudes in the laboratory have evolved. However, evidence suggests that attitudes towards risk may vary considerably when measured with different methods. Based on a within-subject experimental design using four widespread risk preference elicitation tasks, we find that the different methods indeed give rise to considerably varying estimates of individual and aggregate level risk preferences. Conducting simulation exercises to obtain benchmarks for subjects’ behavior, we find that the observed heterogeneity in risk preference estimates across methods is qualitatively similar to the heterogeneity arising from independent random draws from the choice distributions observed in the experiment. Our study, however, provides evidence that subjects are surprisingly well aware of the variation in the riskiness of their choices. We argue that this calls into question the common interpretation of variation in revealed risk preferences as being inconsistent.

Behavioral Welfare Economics and Risk Preferences: A Bayesian Approach

We propose the use of Bayesian estimation of risk preferences of individuals for applications of behavioral welfare economics to evaluate observed choices that involve risk. Bayesian estimation provides more systematic control of the use of informative priors over inferences about risk preferences for each individual in a sample. We demonstrate that these methods make a difference to the rigorous normative evaluation of decisions in a case study of insurance purchases. We also show that hierarchical Bayesian methods can be used to infer welfare reliably and efficiently even with significantly reduced demands on the number of choices that each subject has to make. Finally, we illustrate the natural use of Bayesian methods in the adaptive evaluation of welfare.

The Risk Elicitation Puzzle Revisited: Across-Methods (In)consistency?

With the rise of experimental research in the social sciences, numerous methods to elicit and classify people’s risk attitudes in the laboratory have evolved. However, evidence suggests that people’s attitudes towards risk may change considerably when measured with different methods. Based on a within-subject experimental design using four widespread risk preference elicitation methods, we find that different procedures indeed give rise to considerably varying estimates of individual and aggregate level risk preferences. Conducting simulation exercises to obtain benchmarks for subjects’ behavior, we find that the observed heterogeneity in risk preference estimates across methods looks qualitatively similar to the heterogeneity arising from independent random draws from choices in the experimental tasks, despite significantly positive correlations between tasks. Our study, however, provides evidence that subjects are surprisingly well aware of the variation in the riskiness of their choices. We argue that this calls into question the common interpretation of variation in revealed risk preferences as being inconsistent.

The Psychology of Human Risk Preferences and Vulnerability to Scare-Mongers: Experimental Economic Tools for Hypothesis Formulation and Testing

The Internet and social media have opened niches for political exploitation of human dispositions to hyper-alarmed states that amplify perceived threats relative to their objective probabilities of occurrence. Researchers should aim to observe the dynamic “ramping up” of security threat mechanisms under controlled experimental conditions. Such research necessarily begins from a clear model of standard baseline states, and should involve adding treatments to established experimental protocols developed by experimental economists. We review these protocols, which allow for joint estimation of risk preferences and subjective beliefs about probabilities and their distributions. Results we have obtained on such estimates, from populations in various countries, are gathered for comparison. Most people show moderate risk aversion in non-alarmed states. We also find universal heterogeneity in risk preference structures, with substantial sub-samples weighting probabilities in such a way as to display “probability pessimism” (rank dependent utility), while others make risky choices in accordance with expected utility theory.

Controlling for Compromise Effects Debiases Estimates of Preference Parameters

The compromise effect - a tendency to choose options close to the “middle” of a choice - has been shown to confound measurement of preferences. In an experiment with 550 participants, we study risk preferences elicited with Multiple Price Lists. Following prior work, we manipulate the compromise effect by varying the middle options of each Multiple Price List and find that measured risk-preference estimates are sensitive to this change in the choice set. To eliminate this bias, we incorporate context effects directly into a structural econometric model. We show that this method generates robust estimates of preference parameters.

Health Insurance for “Humans”: Information Frictions, Plan Choice, and Consumer Welfare

Traditional models of insurance choice are predicated on fully informed and rational consumers protecting themselves from exposure to financial risk. In practice, choosing an insurance plan is a complicated decision often made without full information. In this paper we combine new administrative data on health plan choices and claims with unique survey data on consumer information to identify risk preferences, information frictions, and hassle costs. Our additional friction measures are important predictors of choices and meaningfully impact risk preference estimates. We study the implications of counterfactual insurance allocations to illustrate the importance of distinguishing between these micro-foundations for welfare analysis.

Estimating Risk Attitudes in Conventional and Artefactual Lab Experiments: The Importance of the Underlying Assumptions

Abstract In this paper we assess the importance of sample type in the estimation of risk preferences. We elicit and compare risk preferences from student subjects and subjects drawn from the general population, using the multiple price list method devised by Holt and Laury in their paper Risk Aversion and Incentive Effects (2002). We find evidence suggesting that under rank dependent utility, students exhibit approximately risk neutral preferences while subjects drawn from the general population exhibit risk loving preferences. However, when we assume an incorrect characterization of risk preferences, in particular we adopt the framework of expected utility theory, our estimation results lead to erroneous inferences. In this case, students are on average risk averse, while subjects drawn from the general population exhibit risk neutrality. Our results have implications for economic policy making under uncertainty.

Estimating Risk Attitudes in Conventional and Artefactual Lab Experiments: The Importance of the Underlying Assumptions

In this paper the authors assess the importance of sample type in the estimation of risk preferences. The authors elicit and compare risk preferences from student subjects and subjects drawn from the general population, using the multiple price list method devised by Holt and Laury (Risk aversion and incentive effects, 2002). The authors find evidence suggesting that under Rank Dependent Utility and an expo-power function, students exhibit similar risk attitudes to subjects drawn from the general population. However, when the authors assume an incorrect characterization of risk preferences, in particular they adopt the framework of Expected Utility theory and a Constant Relative Risk Aversion function, their estimation results lead to erroneous inferences. In this case, students are on average risk averse, while subjects drawn from the general population exhibit risk loving preferences. The results have implications for economic policy making under uncertainty.

Estimating Risk Preferences in the Presence of Bifurcated Wealth Dynamics: Do We Misattribute Dynamic Risk Responses to Static Risk Aversion?

Estimating risk preferences is tricky because controlling for confounding factors is difficult. Omitting or imperfectly controlling for these factors can attribute too much observable behavior to risk aversion and bias estimated preferences. Agents often modify risky decisions in response to dynamic wealth or asset thresholds, where they exist. Ignoring this dynamic risk response introduces an attribution bias in static estimates of risk aversion. We demonstrate this pitfall using a simple model and a Monte Carlo simulation to explore the implications of this problem for empirical estimation. Joint estimation of risk preferences and wealth dynamics may remedy the problem, but can be empirically challenging.

Eliciting risk preferences: When is simple better?

We study the estimation of risk preferences with experimental data and focus on the trade-offs when choosing between two different elicitation methods that have different degrees of difficulty for subjects. We analyze how and when a simpler, but coarser, elicitation method may be preferred to the more complex, but finer, one. Results indicate that the more complex measure has overall superior predictive accuracy, but its downside is that subjects exhibit noisier behavior. Our main result is that subjects’ numerical skills can help better assess this tradeoff: the simpler task may be preferred for subjects who exhibit low numeracy, as it generates less noisy behavior but similar predictive accuracy. For subjects with higher numerical skills, the greater predictive accuracy of the more complex task more than outweighs the larger noise. We also explore preference heterogeneity and provide methodological suggestions for future work.

Are risk preferences stable? Comparing an experimental measure with a validated survey-based measure

We examine the stability of risk preference within subjects by comparing measures obtained from two elicitation methods, an economics experiment with real monetary rewards and a survey with questions on hypothetical gambles. The survey questions have been validated by numerous empirical studies of investment, insurance demand, smoking and alcohol use, and recent studies have shown the experimental measure is associated with several real-world risky behaviors. For the majority of subjects, we find that risk preferences are not stable across elicitation methods. In interval regression models subjects’ risk preference classifications from survey questions on job-based gambles are not associated with risk preference estimates from the experiment. However, we find that risk classifications from inheritance-based gambles are significantly associated with the experimental measure. We identify some subjects for whom risk preference estimates are more strongly correlated across elicitation methods, suggesting that unobserved subject traits like comprehension or effort influence risk preference stability.

Specification and Estimation of Production Risk, Risk Preferences and Technical Efficiency

AbstractThis article deals with specification and estimation of risk preferences, production risk, and technical inefficiency. It makes contribution in three separate areas of production economics. First, we model producers' attitude toward risk and derive risk preference functions (without assuming any parametric form of the utility function and any distribution of the error term representing production risk) when risk arises from production uncertainty and technical inefficiency. Second, the standard production risk model is extended to accommodate technical inefficiency and producers' attitude toward risk. Finally, the technical efficiency model is generalized to accommodate production risk and producers' attitude toward risk.

RISK PREFERENCES UNDER PRICE UNCERTAINTIES AND PRODUCTION RISK

This paper deals with estimation of risk preferences of producers when they face uncertainties in output and input prices, in addition to uncertainty in production (usually labeled as production risk). All these uncertainty components are modeled in the context of production theory where the producers maximize expected utility of anticipated profit. Risk preference functions associated with these uncertainties are derived without assuming a specific form of the utility function. Moreover, no distributional assumptions are made on the distributions of the random variables representing price and production uncertainties. A multi-stage estimation procedure is developed to estimate the parameters of the production function and risk preference functions associated with output price uncertainty, input price uncertainty and production risk. Production risk is specified in such a way that one can identify inputs with increasing, decreasing and constant production risks. Similarly, risk aversion behavior is specified in such a way that one can test for different types of risk aversion behavior.

Poverty, market imperfections and time preferences: of relevance for environmental policy?

Rates of time preference (RTPs) of rural households in Indonesia, Zambia and Ethiopia have been measured using hypothetical questions about preferences for current versus future consumption. In general, the rates were found to be very high. Factors influencing or correlated with the personal rates of time preference were investigated through regression methods. OLS was the technique used in the estimation. Market imperfections, particularly in credit and insurance markets lead to variation in RTPs. Poverty in assets, or cash liquidity constraints, was leading to or correlated with higher rates of time preference. The poor are, therefore, less likely to invest in environmental conservation. In Zambia, independent estimates of risk preferences were made. More risk-averse people tended to have lower RTPs. The results support the hypothesis that poverty and/or liquidity scarcity lead to high RTPs. Poverty reduction may thus reduce the RTPs of the poor and reduce the 'intertemporal externality' due to high RTPs. The high average RTPs indicate, however, that complementary policies may be needed to ensure sufficient levels of investment in conservation. Another logical implication is that institutionalization of private property rights may not be a sufficient tool to initiate sustainable resource management.

Application of Risk Preference Estimates in Firm‐Household and Agricultural Sector Models

Application of Risk Preference Estimates in Firm‐Household and Agricultural Sector Models