WORKING PAPERS:
Trade, Internal Migration and Human Capital: Who Gains from India's IT Boom? (Job market paper)
[New draft coming soon!]
Abstract: How does human capital response to trade affect inequality? This paper presents a new quantitative spatial equilibrium framework to analyze this question in the context of the Indian information technology (IT) boom. Trade-driven changes in job opportunities can affect people's decisions to invest in different types of skills. I add education and location choice in an economic geography model that features the costs of mobility of goods and people, and in which workers typically cannot change their skills. I find that compared with a benchmark model with fixed skill types, incorporating this mechanism significantly increases the aggregate welfare gains from trade and reduces regional inequality. Regional inequalities in welfare gains depend on access to jobs and education. In contrast to previous studies, such access is determined by the costs of both mobility for work and education, estimated separately. Using the model, I find that between 1995 and 2005, India's IT boom increased average individual welfare by 1.16\%. Individuals born in districts with good access to jobs and education gained as much as 3.26\%, while their counterparts in remote districts experienced gains as low as .41\%. In the short-run when skills are fixed, regions with a higher proportion of unskilled workers lose. A policy of reducing education costs by lowering state quotas would have increased aggregate welfare by 3.6\%, compared with the actual aggregate welfare in the post-boom period, with regional increases in gains ranging from .5\% to 7.15\%. This underscores the potential for different education policies---such as reducing in-state quotas for students in institutes of higher education as a means of more equally distributing the gains from trade---as opposed to only targeting the labor market, in which changing jobs often proves to be costly.
Road Capacity, Domestic Trade and Regional Outcomes
(with Kerem Cosar, Banu Demir Pakel and, Nathaniel Young)
[New draft 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.
Do Colleges Spur Local Economic Activity? Regression Discontinuity Evidence from India
(with Maulik Jagnani and Gaurav Khanna)
[New draft coming soon!]
Abstract: Whether colleges spur local economic activity depends on the mobility of graduates, firms, and public infrastructure. We leverage a government program in India that establishes public colleges in districts where college enrollment is less than the national average to examine the impact on local economic activity. Using a regression discontinuity design, we find that districts that received the college-building scheme saw a rise in college enrollment and the growth in certain types of high-skill jobs.
WORKS IN PROGRESS:
Enrollment as Entry into the US Job Market: Evidence from Foreign Student Enrollment in CS
(with Sarah Turner)
Abstract:
The number of foreign students coming to study CS in the US has been steadily increasing over the years. How much of this enrollment increase can be attributed to the fact that an US degree provides an indirect entry into the US job market? Using new immigration data that tracks the nationality, date of entry and choice of study of the universe of F1 visa holders, we find that foreign students respond more to local labor market opportunities than native students in choosing their locations of study. In addition, we find that the magnitudes of these responses vary across the levels of degree: masters students are more likely to study in locations that offer more employment opportunities than either BA or PhD students. To further investigate this channel, we specifically look at foreign students from India: the largest recipient of US H1B Visas and the largest proportion of CS degree holders among all countries.
Competition, Wages and the Emergence of Computer Science Degree Programs in the US
(With Emily Cook and Ekaterina Khmelnitskaya)
Abstract:
How does the presence of endogenous entry costs affect entrant decisions? When deciding whether to introduce a new program universities have to take into account that a large part of their costs, both variable and fixed, depends on the faculty wage. This wage, at the same time, is determined in equilibrium, where it is affected not only by demand from other universities but also by the demand from the industry. The equilibrium faculty wage, in turn, will be endogenous to the entry decisions of all the participants and the industry demand. We introduce a two stage game where in the first stage universities decide whether to enter a market while taking into account the entry costs that will be determined in the second stage through equilibrium faculty wages. We thus develop a framework that allows us to study not only how the standard entry game changes when the costs are endogenized, but also how the competition between the downstream and upstream industry for the same input affects entry. We use historic data on CS program adoption at US universities, university characteristics, faculty wages, and industry wages to understand the timing of each university's decision to introduce CS programs at the undergraduate and graduate levels. Implications for public policy are explored- in particular, we describe how the amount and timing of subsidies to universities affected the growth of CS as a discipline and the distribution of CS programs by university control and selectivity.
POLICY WRITINGS:
Higher Education Response to India's IT Boom: Did State Governments Play a Role?
(WTO edited volume on Trade and Labor Market Adjustment 2019, forthcoming)