FIELDS
Experimental Economics, Econometrics, and Microeconomics Theory
|
WORKING PAPERS
Ever Since Allais [R&R JPE]
with Shachar Kariv, Matthew Polisson, and John K.-H. Quah
working paper; appendix I; appendix II; appendix III
The Allais critique of expected utility theory (EUT) has led to the development of theories of choice under risk that relax the independence axiom, but which adhere to the conventional axioms of ordering and monotonicity. Unlike many existing laboratory experiments designed to test independence, our experiment systematically tests the entire set of axioms, providing much richer evidence against which EUT can be judged. Our within-subjects analysis is nonparametric, using only information about revealed preference relations in the individual-level data. For most subjects we find that departures from independence are statistically significant but minor relative to departures from ordering and/or monotonicity.
with Shachar Kariv, Matthew Polisson, and John K.-H. Quah
working paper; appendix I; appendix II; appendix III
The Allais critique of expected utility theory (EUT) has led to the development of theories of choice under risk that relax the independence axiom, but which adhere to the conventional axioms of ordering and monotonicity. Unlike many existing laboratory experiments designed to test independence, our experiment systematically tests the entire set of axioms, providing much richer evidence against which EUT can be judged. Our within-subjects analysis is nonparametric, using only information about revealed preference relations in the individual-level data. For most subjects we find that departures from independence are statistically significant but minor relative to departures from ordering and/or monotonicity.
Destructive Behavior, Judgment, and Economic Decision-making Under Thermal Stress [R&R JEEA]
with Ingvild Almås, Maximilian Auffhammer, Tessa Bold, Ian Bolliger, Solomon Hsiang, Shuhei Kitamura, Edward Miguel, and Robert Pickmans
working paper; pre-analysis plan
Accumulating evidence indicates that environmental temperature substantially affects economic outcomes and violence, but the reasons for this linkage are not well understood. We systematically evaluate the effect of thermal stress on multiple dimensions of economic decision-making, judgment, and destructive behavior with 2,000 participants in Kenya and the US who were randomly assigned to different temperatures in a laboratory. We find that most dimensions of decision-making are unaffected by temperature. However, heat causes individuals to voluntarily destroy other participants' assets, with more pronounced effects during a period of heightened political conflict in Kenya.
with Ingvild Almås, Maximilian Auffhammer, Tessa Bold, Ian Bolliger, Solomon Hsiang, Shuhei Kitamura, Edward Miguel, and Robert Pickmans
working paper; pre-analysis plan
Accumulating evidence indicates that environmental temperature substantially affects economic outcomes and violence, but the reasons for this linkage are not well understood. We systematically evaluate the effect of thermal stress on multiple dimensions of economic decision-making, judgment, and destructive behavior with 2,000 participants in Kenya and the US who were randomly assigned to different temperatures in a laboratory. We find that most dimensions of decision-making are unaffected by temperature. However, heat causes individuals to voluntarily destroy other participants' assets, with more pronounced effects during a period of heightened political conflict in Kenya.
External Validation of Homo economicus Outside the Lab [in preparation, draft available on request]
with Shachar Kariv, Raja Sangupta, and Sid Feygin
All models of economic decision-making assume that a person has a consistent set of preferences that governs their choice behavior. Whenever choices are in this way rational, there exists a utility function which, when maximized, rationalizes an individual's choice behavior. Revealed preference techniques can test if observed behavior is consistent with utility maximization, without imposing a particular utility functional form. Laboratory experiments generate sufficiently rich datasets for testing rationality, and the overarching results from past experiments is that choices are sufficiently consistent to be considered rational. However, questions of external validity remain -- are subjects utility maximizers due to the laboratory setting itself, and short time span of the experiment? To answer this, we replicate the laboratory computer interface on a custom application which subjects download onto their smartphones. Subjects make choices throughout the day over a period of 5 days, while going about their lives, instead of over one hour in the laboratory. We find that scores on standard measures of rationality are as high among subjects in the mobile experiment as those in the lab, and that most are close to the ideal of perfectly rational behavior. Our study provides temporal and environmental external validation for the laboratory results, as well as support for rational behavior in other lab-in-field smartphone experiments.
with Shachar Kariv, Raja Sangupta, and Sid Feygin
All models of economic decision-making assume that a person has a consistent set of preferences that governs their choice behavior. Whenever choices are in this way rational, there exists a utility function which, when maximized, rationalizes an individual's choice behavior. Revealed preference techniques can test if observed behavior is consistent with utility maximization, without imposing a particular utility functional form. Laboratory experiments generate sufficiently rich datasets for testing rationality, and the overarching results from past experiments is that choices are sufficiently consistent to be considered rational. However, questions of external validity remain -- are subjects utility maximizers due to the laboratory setting itself, and short time span of the experiment? To answer this, we replicate the laboratory computer interface on a custom application which subjects download onto their smartphones. Subjects make choices throughout the day over a period of 5 days, while going about their lives, instead of over one hour in the laboratory. We find that scores on standard measures of rationality are as high among subjects in the mobile experiment as those in the lab, and that most are close to the ideal of perfectly rational behavior. Our study provides temporal and environmental external validation for the laboratory results, as well as support for rational behavior in other lab-in-field smartphone experiments.
Rationality and Error in Individual Choice Data: A Revealed Preferences Approach [in preparation, draft available on request]
The assumption of rationality is used to infer preferences from observed choices, but classic economic theory provides scant guidance when choice data has error. Methods to estimate preferences from noisy data inevitably invoke additional assumptions on those very preferences. This paper presents a procedure to detect and measure error in an individual's observed choice data when the individual has an underlying rational choice process that has been contaminated with random implementation errors. Using a single individual's choices over many menus, I construct an observed revealed preference relation, and prove it is a random graph whose acyclicity is equivalent to rationality. Exploiting the structure in the graph produced by the contaminating errors, I devise a classifier able to detect which observations are errors and an estimator to measure the rate at which errors occur. These two methods can be applied to any dataset in which an individual makes constrained choices from a sequence of overlapping non-identical menus, regardless of the choice environment. I apply the method to a benchmark dataset of choices observed in the lab (Choi et al. 2007) and show that most individuals have error rates between 5% and 14.5% (interquartile range). I show that three existing measures of goodness-of-fit for rationality, which are often used as proxies for error estimates, are not robust, not identified, or biased when choices are observed with error.
The assumption of rationality is used to infer preferences from observed choices, but classic economic theory provides scant guidance when choice data has error. Methods to estimate preferences from noisy data inevitably invoke additional assumptions on those very preferences. This paper presents a procedure to detect and measure error in an individual's observed choice data when the individual has an underlying rational choice process that has been contaminated with random implementation errors. Using a single individual's choices over many menus, I construct an observed revealed preference relation, and prove it is a random graph whose acyclicity is equivalent to rationality. Exploiting the structure in the graph produced by the contaminating errors, I devise a classifier able to detect which observations are errors and an estimator to measure the rate at which errors occur. These two methods can be applied to any dataset in which an individual makes constrained choices from a sequence of overlapping non-identical menus, regardless of the choice environment. I apply the method to a benchmark dataset of choices observed in the lab (Choi et al. 2007) and show that most individuals have error rates between 5% and 14.5% (interquartile range). I show that three existing measures of goodness-of-fit for rationality, which are often used as proxies for error estimates, are not robust, not identified, or biased when choices are observed with error.
ONGOING RESEARCH
Emotions and Decision Making over Risk: A Smartphone Experiment [preliminary results, rough draft available on request]
with Sid Feygin and Orianna DeMassi
with Sid Feygin and Orianna DeMassi
Ever Since Ellsberg [preliminary results]
with Shachar Kariv, Matthew Polisson, and John K.-H. Quah
with Shachar Kariv, Matthew Polisson, and John K.-H. Quah