I am an Assistant Professor of Economics at Boston University.
I work in labor, public, and behavioral economics. A theme in my research focuses on understanding the role of information and beliefs in labor market outcomes, social interactions, and household decisions. I am also interested in the economics of gender.
I received my Ph.D. in Economics from Harvard University in 2019.
We find that taxi driver labor supply behavior exhibits small departures from the neoclassical model and uncover a substantial role for recency: Violations of intertemporal optimization arise due to recently accumulated earnings, inconsistent with the notion of daily income targeting. To explain these facts, we provide and estimate an operational model of how reference points adjust.
This paper provides field evidence on how reference points adjust, a degree of freedom in reference-dependence models. Examining this in the context of cabdrivers’ daily labor-supply behavior, we ask how the within-day timing of earnings affects decisions. Drivers work less in response to higher accumulated income, with a strong effect for recent earnings that gradually diminishes for earlier earnings. We estimate a structural model in which drivers work towards a reference point that adjusts to deviations from expected earnings with a lag. This dynamic view of reference dependence reconciles conflicting “neoclassical” and “behavioral” interpretations of evidence on daily labor-supply decisions.
A windfall that is relatively less anticipated leads to a bigger surprise, less patience, and higher consumption. This paper provides the theory and empirical evidence for this new fact in both developed and developing contexts: 2008 stimulus payments in the US and cash transfers in Kenya and Malawi.
This paper theoretically and empirically examines the timing of information about consumption opportunities. We present a model in which consumers form intertemporal plans and experience utility from anticipating future consumption. We show that more time to anticipate leads to more patient decisions. Anticipation therefore provides a role for the timing of information as a novel policy instrument. We test the model in two distinct domains. Using Nielsen Consumer Panel data to examine responses to the 2008 Economic Stimulus Payments, we find higher marginal propensities to spend for households that receive payments sooner after they are announced. Using data from randomized experiments in Kenya and Malawi which induced variation in the timing of lump-sum unconditional cash transfers, we find higher savings and lower spending on temptation goods among households that wait longer to receive payment.
Following childbirth, there is an information asymmetry between firms and mothers about their attachment to work. Consequently, mothers forgo paid leave in order to signal their higher value to firms and earn higher wages. This paper provides a signaling model of parental leave and model-based empirical tests using a parental leave extension and administrative data from Denmark.
This paper provides empirical tests based on signaling theory in the context of workers choosing to forgo paid parental leave to signal value to employers. Using administrative data from Denmark and an unanticipated increase in the maximum allowed duration of parental leave, I show how signaling contributes to a divergence in wages due to the information that workers’ choices convey upon a leave extension. In contrast to human capital theory, an individual can take longer leave but gain in wages as long as their relative leave position in the population decreases. The results demonstrate unanticipated impacts of parental leave policies and highlight the importance of asymmetric information in the labor market.
Discussions
Fabian Eckert, Mads Hejlesen, and Conor Walsh, The Return to Big City Experience: Evidence from Danish Refugees. Paper, Discussion at the NBER Summer Institute, July 2018
Meiping Sun, The Puzzle of Mistaken Millions: The MTA Surcharge and the Surge of Money onto MetroCards. Paper, Discussion at the NBER Summer Institute, July 2016
