I am an Assistant Professor in the Economics Department at Middlebury College.
My research interests are primarily in behavioral economics and labor economics. I mainly study cognitive limitations, the selection of talent, fairness views, and inequality.
Here is my CV. You can reach me at
Cognitive endurance—the ability to sustain performance on a cognitively-demanding task over time—is thought to be a crucial productivity determinant. However, a lack of data on this variable has limited researchers' ability to understand its role for success in college and the labor market. This paper uses college-admission-exam records from 15 million Brazilian high school students to measure cognitive endurance based on changes in performance throughout the exam. By exploiting exogenous variation in the order of exam questions, I show that students are 7.1 percentage points more likely to correctly answer a given question when it appears at the beginning of the day versus the end (relative to a sample mean of 34.3%). I develop a method to decompose test scores into fatigue-adjusted ability and cognitive endurance. I then merge these measures into a higher-education census and the earnings records of the universe of Brazilian formal-sector workers to quantify the association between endurance and long-run outcomes. I find that cognitive endurance has a statistically and economically significant wage return. Controlling for fatigue-adjusted ability and other student characteristics, a one-standard-deviation higher endurance predicts a 5.4% wage increase. This wage return to endurance is sizable, equivalent to a third of the wage return to ability. I also document positive associations between endurance and college attendance, college quality, college graduation, firm quality, and other outcomes. Finally, I show how systematic differences in endurance across students interact with the exam design to determine the sorting of students to colleges. I discuss the implications of these findings for the use of cognitive assessments for talent selection and investments in interventions that build cognitive endurance.
Muddled information models posit that higher stakes increase a signal's informativeness about individuals' gaming ability and decrease that of their natural ability. An important question is whether this muddling of abilities degrades the predictive value of a signal for long-run outcomes. We evaluate this question in the context of standardized testing by exploiting the introduction of Brazil's national college admission exam, the ENEM. The staggered adoption of the ENEM by selective universities meant that depending on their location and cohort, students either took a low-stakes school accountability test or the high-stakes ENEM. We link ENEM records to college records to measure the predictive power of ENEM test scores for long-term outcomes. We find that the increase in exam stakes made ENEM scores more informative for students' college outcomes. However, test score gaps between high- and lower-income students increased when selective universities adopted the ENEM. Our results show that the muddling of ability can increase a signal's predictive value, but high-stakes signals can also exacerbate socioeconomic inequality.
Revise and Resubmit, Review of Economics and Statistics
This paper shows that the bunching of wages at round numbers is partly driven by firm coarse wage-setting. Using data from over 200 million new hires in Brazil, I first establish that contracted salaries tend to cluster at round numbers. Then, I show that firms that tend to hire workers at round-numbered salaries are less sophisticated and have worse market outcomes. Next, I develop a wage-posting model in which optimization costs lead to the adoption of coarse rounded wages and provide evidence supporting two model predictions using two research designs. Finally, I examine some consequences of coarse wage-setting for relevant economic outcomes.
We examine how redistribution decisions respond to the source of luck when there is uncertainty about its role in determining opportunities and outcomes. We elicit redistribution decisions from a representative U.S. sample who observe worker outcomes and whether luck could determine earnings directly (``lucky outcomes'') or indirectly by providing one of the workers with a relative advantage (``lucky opportunities''). We find that participants redistribute less and are less responsive to changes in the importance of luck in environments with lucky opportunities. We show that individuals rely on a simple heuristic when assessing the impact of unequal opportunities, which leads them to underappreciate the extent to which small differences in opportunities can have a large impact on outcomes. These findings have implications for models of redistribution attitudes and help explain the gap between lab evidence on support for redistribution and inequality trends.
Published and Forthcoming Papers
Forthcoming, Journal of Labor Economics
We examine the effects of an affirmative action policy at an elite Brazilian university that reserved 45 percent of admission slots for Black and low-income students. We find that marginally-admitted students who enrolled through the affirmative action tracks experienced a 14 percent increase in early-career earnings. But the adoption of affirmative action also caused a large decrease in earnings for the university's most highly-ranked students. We present evidence that the negative spillover effects on highly-ranked students' earnings were driven by both a reduction in human capital accumulation and a decline in the value of networking.
(with Leonardo Gasparini)
The Journal of Economic Inequality, 20: 893-913, 2022
A common assumption in the literature is that the level of income inequality shapes individuals' beliefs about whether the income distribution is fair ("fairness views," for short). However, individuals do not directly observe income inequality (which often leads to large misperceptions), nor do they consider all inequities to be unfair. In this paper, we empirically assess the link between objective measures of income inequality and fairness views in a context of high but decreasing income inequality. We combine opinion poll data with harmonized data from household surveys of 18 Latin American countries from 1997–2015. We report three main findings. First, we find a strong and statistically significant relationship between income inequality and unfairness views across countries and over time. Unfairness views evolved in the same direction as income inequality for 17 out of the 18 countries in our sample. Second, individuals who are older, unemployed, and left-wing are, on average, more likely to perceive the income distribution as very unfair. Third, fairness views and income inequality have predictive power for individuals' self-reported propensity to mobilize and protest independent of each other, suggesting that these two variables capture different channels through which changes in the income distribution can affect social unrest.