Valeria Zurla, Brown University PhD Class of 2022, has won the NTA’s Outstanding Dissertation Prize for 2022. She will accept the award at the 2022 NTA Annual Conference in November.
Valeria Zurla is a Postdoctoral Research Fellow at the Population Wellbeing Initiative at the University of Texas at Austin and an Assistant Professor of Economics at CSEF and the University of Naples Federico II. Her research interests lie at the intersection between public economics, labor economics, and gender economics, with a focus on social insurance programs and labor market inequalities. In particular, her current work examines how individuals’ and firms’ behavioral responses to policy changes affect policy design.
Valeria received her Ph.D. in Economics from Brown University in May 2022. In her dissertation, entitled “Essays in Public and Labor Economics”, she uses rich population-wide administrative data from Italy to study the employment and welfare effects of social programs and government interventions aimed at reducing inequalities. In the first chapter, she provides novel insights into the role of different policy instruments in the design of parental leave policies. Taking advantage of a unique environment that allows mothers to choose between social programs after childbirth, the analysis disentangles the effects of different parental leave parameters on women’s decisions, labor market outcomes, and welfare. The second chapter explores the incidence effects of earned income tax credits (EITCs), focusing on the role of firms in the transmission of incidence. The analysis investigates the introduction of a large EITC program in Italy and finds that firms are an essential vector of transmission of incidence: firms more exposed to the tax credit respond to the program by decreasing their employees’ earnings relative to less exposed firms. The final chapter, co-authored with Giulia Buccione, studies the unintended effects of government integration policies in the context of forced displacement and the optimal design of reception systems.