Handbook of the Economics of Finance

Is the way that people make risky choices, or tradeoffs over time, related to cognitive ability? This paper investigates whether there is a link between cognitive ability, risk aversion, and impatience, using a representative sample of the population and incentive compatible measures. We conduct choice experiments measuring risk aversion, and impatience over an annual time horizon, for a randomly drawn sample of roughly 1,000 German adults. Subjects also take part in two different tests of cognitive ability, which correspond to sub-modules of one of the most widely used IQ tests. Interviews are conducted in subjects' own homes. We find that lower cognitive ability is associated with greater risk aversion, and more pronounced impatience. These relationships are significant, and robust to controlling for personal characteristics, educational attainment, income, and measures of credit constraints. We perform a series of additional robustness checks, which help rule out other possible confounds.

/pdf/are-risk-aversion-and-impatience-related-to-cognitive-3n71ze8tmw.pdf

Are risk aversion and impatience related to cognitive ability

Economists and psychologists have developed a variety of experimental methodologies to elicit and assess individual risk attitudes. Choosing which to utilize, however, is largely dependent on the question one wants to answer, as well as the characteristics of the sample population. The goal of this paper is to present a series of prevailing methods for eliciting risk preferences and outline the advantages and disadvantages of each. We do not attempt to give a comprehensive account of all the methods or nuances of measuring risk, but rather to outline some advantages and disadvantages of different methods.

https://rady.ucsd.edu/docs/faculty/GneezyRiskElicitation.pdf

Experimental methods: Eliciting risk preferences

We show that unexplained innovations in several variables representing survey responses to forwardlooking questions on the Michigan Survey of Consumers have powerful prognostic implications for the future paths of macroeconomic variables. We attempt to distinguish the hypothesis that these impulse responses indicate a causal channel from autonomous movements in sentiment to economic outcomes (the “animal spirits” view) from the alternative interpretation that the surprise confidence movements summarize information about future economic prospects (the “information” view). In natural rate models, “animal spirits” shocks are associated with “overshooting” of (among other variables) consumption that attenuates when agents come to grips with their overreaction, while “information shocks” about the long future are followed by gradual movements in macroeconomic variables that are not subsequently reversed. In a baseline vector autoregression involving consumption, income, and confidence, the data come down sharply in favor of the information view. The impulse responses of consumption and GDP show no tendency to attenuate even after a number of years. Further, confidence innovations have strong implications for labor productivity many quarters into the future. In somewhat larger VARs with an information block that includes inflation and/or stock prices, the impulse responses to confidence innovations continue to have the permanent shape that defines information shocks, but they are smaller in magnitude. We demonstrate that this is due to the fact that both inflation and stock price innovations have prognostic implications for future productivity that are very similar to the implications of innovations in confidence. Addition of unemployment to the system induces a transitory component that changes the shape of the impulse responses and somewhat weakens the previously airtight case against animal spirits, but it does not provide constructive evidence of such effects.

/pdf/information-animal-spirits-and-the-meaning-of-innovations-in-4lmwbmhgcn.pdf

Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence

Journal of the American Statistical Association: William S. Cleveland, Marylyn E. McGill and Robert McGill, “The shape parameter for a two variable graph” 83 (1988) 289–300

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.

Eliciting risk preferences: When is simple better?

Confirmation bias with motivated beliefs

Methodologies for analyzing the forces that move and shape national economies have advanced markedly in the last thirty years, enabling economists as never before to unite theoretical and empirical research and align measurement with theory. In Structural Macroeconometrics , David DeJong and Chetan Dave provide the unified overview and in-depth treatment analysts need to apply these latest theoretical models and empirical techniques. The authors' emphasis throughout is on time series econometrics. DeJong and Dave detail methods available for solving dynamic structural models and casting solutions in the form of statistical models with empirical implications that may be analyzed either analytically or numerically. They present the full range of methodologies for characterizing and evaluating these empirical implications, including calibration exercises, method-of-moment procedures, and likelihood-based procedures, both classical and Bayesian. The book is complete with a rich array of implementation algorithms, sample empirical applications, and supporting computer code. Structural Macroeconometrics is tailored specifically to equip readers with a set of practical tools that can be used to expedite their entry into the field. DeJong and Dave's uniquely accessible, how-to approach makes this the ideal textbook for graduate students seeking an introduction to macroeconomics and econometrics and for advanced students pursuing applied research in macroeconomics. The book's historical perspective, along with its broad presentation of alternative methodologies, makes it an indispensable resource for academics and professionals.

Introduction to Structural Macroeconometrics

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

Eliciting Risk Preferences: When is Simple Better?

Structural Macroeconometrics provides a thorough overview and in-depth exploration of methodologies, models, and techniques used to analyze forces shaping national economies. In this thoroughly revised second edition, David DeJong and Chetan Dave emphasize time series econometrics and unite theoretical and empirical research, while taking into account important new advances in the field. The authors detail strategies for solving dynamic structural models and present the full range of methods for characterizing and evaluating empirical implications, including calibration exercises, method-of-moment procedures, and likelihood-based procedures, both classical and Bayesian. The authors look at recent strides that have been made to enhance numerical efficiency, consider the expanded applicability of dynamic factor models, and examine the use of alternative assumptions involving learning and rational inattention on the part of decision makers. The treatment of methodologies for obtaining nonlinear model representations has been expanded, and linear and nonlinear model representations are integrated throughout the text. The book offers a rich array of implementation algorithms, sample empirical applications, and supporting computer code. Structural Macroeconometrics is the ideal textbook for graduate students seeking an introduction to macroeconomics and econometrics, and for advanced students pursuing applied research in macroeconomics. The book's historical perspective, along with its broad presentation of alternative methodologies, makes it an indispensable resource for academics and professionals.

Chetan Dave

Papers

Eliciting risk preferences: When is simple better?

Confirmation bias with motivated beliefs

Introduction to Structural Macroeconometrics

Eliciting Risk Preferences: When is Simple Better?

Structural Macroeconometrics: Second Edition