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.
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 introduces a model of how the timing of information affects consumption decisions and tests its predictions in both developed and developing contexts. In our model, consumers form intertemporal plans and experience utility from anticipating future consumption. The model predicts excess sensitivity of spending to receiving a windfall, with smaller spending responses when there is more time to anticipate receiving the payment. The prediction that waiting leads to more patient decisions does not depend on whether consumers are liquidity constrained. Using Nielsen Consumer Panel data, we find higher marginal propensities to spend for households scheduled to receive the 2008 Economic Stimulus Payments sooner. Using data from randomized experiments in Kenya and Malawi, we find higher savings and assets among households scheduled to wait longer before receiving lump-sum unconditional cash transfers. Finally, we discuss existing evidence on how consumption responds to gains, losses, and news in light of our model.
We provide a link between impatience and poverty through an intertemporal choice model based on anticipatory utility applied to temptation goods. We empirically test one of the distinct predictions of the model using cash-transfer experiments in Kenya and Malawi.
We present a model of intertemporal choice based on anticipatory utility and examine the consequences of temptation goods, which decision-makers do not fully value prospectively. We discuss implications of the resulting time-inconsistent preferences for the decision making of the poor and show how the model gives rise to a poverty trap. We use data from randomized experiments on cash transfers in Kenya and Malawi to test one of the distinct empirical predictions of the model, that households with more time to anticipate receiving a lump-sum payment spend less on temptation goods, namely tobacco and alcohol.
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.
@article{thakralto2020daily,
title={Daily Labor Supply and Adaptive Reference Points},
author={Thakral, Neil and T{\^o}, Linh T},
journal={American Economic Review},
year={forthcoming}
}
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.
