Understanding the Flows of Goods and Workers: General Equilibrium Implications of Migration Policy

Abstract

This dissertation uses a combination of methods from International Trade and Labor Economics to measure the general equilibrium effects of immigration policy. In Chapter II, I quantify the effects of high-skill migration on the location of highskill industries and multinational activity. To establish empirically the link between multinational enterprises (MNEs) and migration, I assemble a novel firm-level dataset on high-skill visa applications and show that there is a large home-bias effect, demonstrating that foreign MNEs in the US tend to hire more migrant workers from their home countries compared to US firms. To quantify the general equilibrium implications for production and welfare, I build a quantitative model that includes trade, MNE production, and the migration decisions of high-skill workers. The estimated model is used to run two main counterfactual exercises. The first one evaluates the implications of a more restrictive immigration policy in the US in line with recent proposals whose aim is to reduce high-skill immigration. I find that a restriction on immigration to the US that decreases its total workforce by 2.1% would decrease by 3%-4% the US share of production in industries that rely heavily on high-skill migrants, such as IT and High-Tech manufacturing. This decline in US production would coincidently fuel IT sector growth predominantly in India (4.4%) and Canada (1.2%) and would decrease welfare for US workers by 0.98%. In the second counterfactual exercise I increase the barriers to MNE production to calculate the welfare gains generated by MNEs. I show that a model not incorporating migration would overestimate the MNE welfare gains for high-skill workers by 34% and underestimate welfare gains for low-skill workers by 7%. Chapter III studies how US immigration policy and the Internet boom affected not just the US economy, but also led to a tech boom in India. Indian students enrolled in engineering schools to join the rapidly growing US IT industry, via the H-1B visa program. As visas are capped, many could not join the US workforce and remained in India, enabling the growth of an Indian IT sector. The increase in IT productivity allowed India to eventually surpass the US in software exports. Our general equilibrium model captures firm-hiring across various occupations, innovation and technology diffusion, and dynamic worker decisions to choose occupations and fields of major in both countries. Using the estimated model, we find that high-skill migration raised the average welfare of workers in each country. The H-1B program induced Indians to switch to computer science (CS) occupations, increasing the CS workforce and overall IT production in India by 15%, and induced US workers to switch to non-CS occupations, reducing the US native CS workforce by 4.7%. Finally, chapter IV quantifies the gains of high-skill immigration for the US leading to the dot-com boom experienced in the late 1990s. We construct a general equilibrium model of the US economy and calibrate it using data from 1994 to 2001. Built into the model are positive effects high skilled immigrants have on innovation. Counterfactual simulations based on our model suggest that immigration increased the overall welfare of US natives, and raised workers’ incomes by 0.2% to 0.3%. High-skill immigration did, however, have significant distributional consequences.