Abstract: How do trade shocks affect welfare and inequality when human capital is endogenous? Using an external IT demand shock and detailed internal migration data from India, I first document that both IT employment and engineering enrollment responded to the rise in IT exports, with IT employment responding more when nearby regions have higher college age population. I then develop a quantitative spatial equilibrium model featuring two new channels: higher education choice and differential costs of migrating for college and work. Using the framework, I quantify the aggregate and distributional effects of the IT boom, and perform counterfactuals. Without endogenous education, estimated aggregate welfare gain from the export shock would have been half and regional inequality about a third higher. Reducing barriers to mobility for education, such as reducing in-state quotas for students at higher education institutes, would substantially reduce inequality in the gains from the IT boom across districts.

(with Kerem Cosar, Banu Demir Pakel and, Nathaniel Young) [Under Revision, New version coming soon! ]

Abstract: What is the impact on intra-national trade and regional economic outcomes when the lane-capacity of an existing paved road network is expanded significantly? We investigate this question for the case of Turkey, which undertook a large-scale public investment in roads during the 2000s. Using spatially disaggregated data on road upgrades and domestic transactions, we estimate a large positive impact of reduced inter-provincial travel times on trade as well as regional industrial sales and employment.

Offshoring Response to High-Skill Immigration: A Firm-Level Analysis

(with Zhiling Wang)

(draft available upon request)

Abstract: Immigration, by increasing the supply of foreign labor to firms, may change the incentives of firms to offshore. This paper studies the relationship between immigration and offshoring by examining a policy change in the Netherlands in 2012 that made it easier for firms to employ high-skilled workers from non-EU countries. Using confidential employer-employee matched microdata from the Netherlands, we show that firms in high-skill industries respond by both employing a higher share of non-EU immigrants and reducing the total amount of offshoring to non-EU countries. The results also hold for the extensive margin of offshoring, that is, some firms that were offshoring to non-EU countries stopped offshoring to these countries after the 2012 policy change. We find evidence that non-EU immigrant workers have a different skill-set that complement the skills of native and EU workers but can substitute for offshoring to non-EU countries.


Competition, Wages and the Emergence of Computer Science Degree Programs in the US

(with Emily Cook and Ekaterina Khmelnitskaya)


This paper investigates the determinants of universities’ decisions to introduce computer science programs, and how these decisions affect equilibrium wages in computer science industries. Computer science (CS) departments first emerged in the 1960s and were rapidly introduced at U.S. universities in the subsequent decades. As of the Spring of 2017, 60% of U.S. public and private non-profit four-year universities offered an undergraduate CS major, and nearly 63,000 students graduated with a CS major from these institutions. The introduction of these programs—and the number of graduates they produced—was shaped by government subsidies, competition between institutions, and industry and faculty wages. The paper investigates to what extent these factors affected the supply of CS programs and graduates, and in turn, the equilibrium industry and academic wages for computer scientists. We model universities’ decisions about whether to offer a CS program and the size of their program. In the model, these decisions are based on equilibrium wages for faculty, which drive costs, and industry wages for CS graduates, which drive demand. We use historic data on CS program adoption at US universities supplemented by unique panel data on faculty compensation to estimate the model. We apply the estimated model to study the effects of counterfactual subsidies, competition, and industry demand on CS programs, graduation and wages over time.