Felipe A. Araujo, PhD

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I'm an Assistant Professor of Economics at the College of Business at Lehigh University. I do research on Behavioral and Labor Economics using both experimental and observational data.

CURRICULUM VITAE

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RESEARCH

Publications

Working Papers

Work in Progress

Publications

"The Effect of On-the-Job Experience on Base-Rate Neglect: Evidence from Medical Professionals" (w/ Chris F. Chabris and Michelle N. Meyer ). [Online Appendix]. Forthcoming at Management Science

Abstract
Abstract
We study the effect of on-the-job experience on base-rate neglect, which is a common bias in assessing conditional probabilities. We do so by carrying out experiments with medical professionals, who are routinely exposed to conditional-probability problems in the form of diagnostic tests, and non-medical professionals, who are not. As such, medical workers with more years of experience will have had more exposure to base-rate type problems than non-medical workers with similar years of experience. We estimate the effect of on-the-job experience by comparing the answers of more or less experienced professionals in both the medical and non-medical domains. Though the incidence of the bias is high for both groups and all levels of experience, we find that more experienced medical workers (a) have lower rates of perfect base-rate neglect (i.e., completely ignoring the base rates), (b) provide more accurate posterior 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 conduct a number of robustness checks and consider possible mechanism, such as education, job or survey attrition, selectivity into medical professions, and experience with false positives. Our results suggests that on-the-job experience mitigates, but does not eliminate, base-rate neglect.

"Limits on Regret as a Tool for Incentive Design" (w/ Alex Imas and Alistair Wilson ). [Online Appendix]. Forthcoming at the Journal of Political Economy: Microeconomics.

Abstract
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.

"Unawareness and risk taking: The role of context” (with Evan Piermont). Journal of Economic Behavior and Organization, 208, 61-79. 2023.

Abstract
Abstract
We study the effects of exposure to unawareness on risk preferences using a novel experimental task. The task has solutions that are difficult to find, but easy to verify and so exposes subjects to unawareness in a natural way. We find that increased exposure to unawareness alone does not affect risk taking. The role of context, however, is shown to be important. For treatments inducing higher unawareness, subjects are more risk averse when the risk elicitation task is framed in the same context as the unawareness-inducing task versus framed in a neutral way; we observe no such differences for the control treatment. We propose a novel decision theoretic model that guides the interpretation of the experimental findings. Our results could inform the decision and game-theoretic literatures, as most models of unawareness assume risk preferences are orthogonal to varying awareness.

"A Reference-Dependent Regret Theory” (with Yuval Erez, and Pengfei Zhang). Decision, 9(1), 1-20. 2022.

Abstract
Abstract
We propose an extension of the classical regret theory model (Loomes & Sugden, 1982; henceforth LS) incorporating the notion of a reference point. As in LS, the model can account for a number of documented deviations from expected utility theory. In addition, we show that our model is consistent with a class of behaviors known as omission bias, for example, a reluctance to exchange lottery tickets, and generates predictions that are consistent with recent empirical evidence on the common-ratio effect with correlated outcomes. The model also provides a novel interpretation for risk aversion in small stakes, equiprobable gambles. The predictive power of the theory, as well as its relative shortcomings and advantages, is examined and compared to that of other extensions of regret theory and three alternative reference-dependent models.

"The Times They Are A-Changing: Experimenting with Dynamic Adverse Selection” (with Stephanie W. Wang, and Alistair J. Wilson). American Economic Journal: Microeconomics, 13(4): 1-22, 2021.

Abstract
Abstract
We examine a common value dynamic matching environment where adverse selection accrues slowly over time. Theoretical best responses are therefore time varying, and the prior experimental literature suggests that sequential environments might lead to greater understanding of adverse selection in this dynamic setting. However, while a sophisticated minority in our experiment do condition on time and are close to a best response, the majority use a stationary response, even after extended experience. In an environment with persistent uncertainty, our results indicate that sequentiality is insufficient for the large majority of participants to recognize the effects of adverse selection.

"The slider task: An example of restricted inference on incentive effects” (with Erin Carbone, Lynn Conell-Price, Marli W. Dunietz, Ania Jaroszewicz, Rachel Landsman, Diego Lamé, Lise Vesterlund, Stephanie W. Wang, and Alistair J. Wilson). Journal of the Economic Science Association, 2(1): 1-12, 2016.

Abstract
Abstract
Real-effort experiments are frequently used when examining a response to incentives. For a real-effort task to be well suited for such an exercise its measurable output must be sufficiently elastic over the incentives considered. The popular slider task in Gill and Prowse (Am Econ Rev 102(1):469–503, 2012) has been characterized as satisfying this requirement, and the task is increasingly used to investigate the response to incentives. However, a between-subject examination of the slider task’s response to incentives has not been conducted. We provide such an examination with three different piece-rate incentives: half a cent, two cents, and eight cents per slider completed. We find only a small increase in performance: despite a 1500 % increase in the incentives, output only increases by 5 %. With such an inelastic response we caution that for typical experimental sample sizes and incentives the slider task is unlikely to demonstrate a meaningful and statistically significant performance response.

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Working Papers

"The Female Sensitivity Hypothesis: Evidence From Experimental Economics" (w/ Neeraja Gupta and Lise Vesterlund ). [Online Appendix].

Abstract
Abstract
Experimental studies on gender differences often refer to women more than men being sensitive to changes in treatment. We assess the empirical support for this female sensitivity hypothesis. First, we examine whether the results of over two hundred experimental economics studies align with the hypothesis. Second, using data from DellaVigna and Pope (2022), we conduct sixty pairwise tests of the hypothesis. Both analyses reveal that gender is not predictive of responsiveness to treatment. We also examine how the female sensitivity hypothesis has been disseminated in the literature. We identify strong confirmation bias, where the hypothesis predominantly is cited by studies that support it, leading to failed reflection of its lacking empirical evidence.

"Paying by waiting in line: Public sector queuing and the public sector wage gap" (w/ Hugo Jales and Andrew Smith).

Abstract
Abstract
We show that public sector jobs in Brazil are characterized by price and quantity controls in the form of wages larger than those of private sector counterparts but with a limited number of employment contracts (analogous to a quota). Entrance to public sector jobs is decided according to the results of a double-blinded admission exam. The resulting combination prevents the usual price mechanism from equating the value of supplying labor to private or public sector jobs. We show that the equilibrium mechanism operates through increases in the candidate-to-vacancy ratios that reduce the likelihood of success at any attempt to access a public sector job. In our empirical analysis, we look at exams administered between 2007 and 2017. We show that the value of time spent waiting is quite close to and sometimes even larger than the average gain, dissipating most, if not all, rents that would otherwise be generated by the public wage premium.

"Selection Bias and the Public-Private Wage Gap: Evidence from Public Sector Exams in Brazil"

Abstract
Abstract
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 on 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 most government jobs are assigned through public sector exams. I construct a novel data set that combines data on individual exam scores and labor market outcomes. 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 the OLS coefficients, resulting from a negative selection bias term. Finally, a survey experiment with Brazilian undergraduates (N = 957) shows that students who prefer to work in the public sector expect a positive and large public sector premium, while those not interested in the public sector expect a negative premium. The survey results lend support to an interpretation of the results as negative selection on unobserved productivity.

Media: InfoMoney (Brazil)

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Work in Progress

"Label Uncertainty and Socially Responsible Market Behavior: An Experiment" (with James A. Dearden and Ernest K. Lai). [In the lab]

"Measuring the Returns to Targeted Nudges with Machine Learning and a Natural Field Experiment" (with Carlos Fernández-Loría, David Hagmann and Nina Mazar). [Field experiment completed]

"MGuideline Adherence and the Psychology of Physician Decision-Making" (with Chris F. Chabris, Michelle N. Meyer and Vini Singh). [Data gathering]

“Laws of Large Numbers and Risk Preferences” (with Alistair J. Wilson and Alex Imas)

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São Paulo, Brazil, the capital of my home state.

TEACHING

Lehigh University

Statistical Methods

Fall 2020, Syllabus

Spring 2021, Syllabus

Spring 2022, Syllabus

Spring 2023, Syllabus

Behavioral Economics

Summer 2021, Syllabus

Fall 2021, Syllabus

Summer 2022, Syllabus

Spring 2023, Syllabus

Fall 2023, Syllabus

University of Pittsburgh

Game Theory Principles

Summer 2016, Syllabus

Summer 2017, Syllabus

CONTACT

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