How Do Restrictions on High-Skilled Immigration Affect Offshoring? Evidence from the H-1B Program

Abstract

Highly skilled workers are not only a crucial and relatively scarce input into firms’ productive and innovative processes, but are also a critical resource determining competitive advantage. An increasingly high proportion of these workers in the United States were born abroad and permitted to work on skilled worker visas. How do multinational firms respond when artificial constraints, namely, policies restricting skilled immigration, are placed on their ability to hire scarce human capital? This paper combines visa microdata and comprehensive data on U.S. multinational firm activity to demonstrate that firms respond to restrictions on H-1B immigration by increasing foreign affiliate employment at the intensive and extensive margins, particularly in China, India, and Canada. The most impacted jobs were R&D-intensive ones, but there is some evidence that non-R&D employment was also affected. The paper highlights a means by which firms can circumvent constraining policies and mitigate country-level risk, and it also suggests that, for the average multinational company (MNC), this means is imperfect; for every visa rejection, they hire 0.4 employees abroad. The most globalized MNCs are the most likely to respond to these restrictions by offshoring, highlighting that firm capabilities—in the form of prior internationalization—shape the decision and ability to offshore in response to skilled immigration restrictions; indeed, these firms hire 0.9 employees abroad for every visa rejection. More broadly, the paper provides evidence of a push factor for internationalizing knowledge activity: artificial constraints on resources result in firms circumventing restrictive policies in ways that may not be anticipated by policy makers. This paper was accepted by Alfonso Gambardella, business strategy. Funding: This work was supported by the Mack Institute for Innovation Management. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4715 .