Consistency and Heterogeneity of Individual Behavior under Uncertainty

Abstract

By using graphical representations of simple portfolio choice problems, we generate a very rich dataset to study behavior under uncertainty at the level of the individual subject. We test the data for consistency with the maximization hypothesis, and we estimate preferences using a two-parameter utility function based on Faruk Gul (1991). This specification provides a good interpretation of the data at the individual level and can account for the highly heterogeneous behaviors observed in the laboratory. The parameter estimates jointly describe attitudes toward risk and allow us to characterize the distribution of risk preferences in the population. (JEL D11, D14, D81, G11)

How Soon Is Now? Evidence of Present Bias from Convex Time Budget Experiments

“…Choi, Fisman, Gale, and Kariv 2007a, Fisman, Kariv, and Markovits 2007, Andersen, Harrison, Lau, and Rutström 2008, Fisman, Jakiela, and Kariv 2014, we observe tremendous individual heterogeneity in preferences, much of which is not explained by demographic and socioeconomic characteristics. The 5 th percentile ofβi is 0.164, and the 95 th percentile is 1.598.…”

“…However, the hypothesis that individual preferences are heterogeneous (across individuals) has now been confirmed in a large number of controlled lab experiments (cf. Andreoni and Miller 2002, Choi, Fisman, Gale, and Kariv 2007a, Fisman, Kariv, and Markovits 2007, Andersen, Harrison, Lau, and Rutström 2008, Von Gaudecker, van Soest, and Wengström 2011, Choi, Kariv, Müller, and Silverman 2014, Fisman, Jakiela, and Kariv 2014. Whether future work will also rule out the hypothesis that preferences are stable over time -at least after one properly controls for variation in income, prices, and other arguments that enter into the utility function -remains to be seen; however, we take this assumption as a natural point of departure for economic research, and focus on explanations for variation in revealed preferences (within individual over time) that are related to predictable variation in income and anticipated expenditures.…”

“…intersecting budget lines) is often quite low (Choi, Fisman, Gale, andKariv 2007b, Andreoni, Gillen, andHarbaugh 2013). Our design creates, in essence, two separate tests of GARP, each of which involves 12 decision problems; though we are able to add the number of violations across the two sets of intersecting budget lines, two GARP tests involving only 12 decisions may not generate sufficient power to be confident that one will detect violations of rationality.…”

“…See Choi, Fisman, Gale, and Kariv (2007a), Fisman, Kariv, and Markovits (2007), Choi, Kariv, Müller, and Silverman (2014), and Fisman, Jakiela, and Kariv (2014) for examples of similar estimation approaches that estimate preference parameters at the individual level. This approach estimate subject-levelβ i ,δ i , andρ i parameters via non-linear least squares while controlling for self-reported background consumption (average daily expenditure).…”

Preferences Under Ignorance

“…1 To quote Echenique, Lee, andShum (2011, p. 1205), " [i]t is fair to say that most of the empirical literature, using both field and experimental data, finds relatively few violations of GARP" 2 Both findings of consistent and heterogenous behavior are confirmed by Choi, Fisman, Gale, and Kariv (2007) in the context of risk-preferences, see also Dean and Martin (2010, Section 5.2…”