Abstract

We demonstrate pitfalls when extrapolating behavioral findings from static to dynamic settings. We focus on regret theory and the design of “regret lotteries”, which have been advocated as more effective than standard incentives. Findings from one-shot settings have been used to promote regret as a tool to boost incentives in recurrent decisions across a variety of settings. Using theory and experiments, we replicate regret lotteries as the superior one-shot incentive; however, for repeated decisions we show the comparative static is entirely reversed. The results highlight the issues extrapolating from static to dynamic settings, particularly for behavioral policy design.

Abstract

We study the effect of on-the-job experience on base-rate neglect using experiments with both medical workers — who are routinely exposed to probability-updating problems — and non-medical workers — who are not. Though the incidence of the bias is high for both groups, we find that more experienced medical workers (a) have lower rates of base-rate neglect, (b) provide more accurate estimates, and (c) adjust their estimates more in response to changes in the base rates. We observe no such difference for non-medical workers. We conclude that on-the-job experience mitigates, but does not eliminate, base-rate neglect.

Abstract

Wages in the public sector might respond to political, rather than market, forces, resulting in persistent differences relative to the private sector. Economists have long been interested in studying public-private wage gaps, as the presence of a gap could redirect resources in ways that have major impacts for the economy. This paper studies the public-private wage gap while controlling for selection bias, which has been the main empirical challenge in this literature. I focus on the Brazilian labor market, where workers can only obtain a government job by securing a sufficiently high score in public-sector exams. I construct a novel dataset with over 2 million individuals that took an exam at least once. Using a fuzzy regression discontinuity design exploring discontinuities around the approval cutoffs, I find a large and significant public-sector wage premium. The estimated coefficients are almost twice as large as OLS coefficients, resulting from a negative selection bias term. Finally, a survey experiment with Brazilian undergraduates show that students who prefer to work in the public sector expect a positive and large public-private wage gap, while those not interested in the public sector expect a (small) negative wage gap. The survey results lend support to an interpretation of negative selection on unobserved ability or productivity.

Media: InfoMoney (Brazil)