High-Skilled Migration to the United States and Its Economic Consequences

Gordon H. Hanson; William R. Kerr; Sarah  Turner

Book | 2018

High-Skilled Migration to the United States and Its Economic Consequences

by Gordon H. Hanson, William R. Kerr and Sarah Turner

Abstract

Immigration policy is one of the most contentious public policy issues in the United States today. High-skilled immigrants represent an increasing share of the U.S. workforce, particularly in science and engineering fields. These immigrants affect economic growth, patterns of trade, education choices, and the earnings of workers with different types of skills. The chapters in this volume go beyond the traditional question of how the inflow of foreign workers affects native employment and earnings to explore effects on innovation and productivity, wage inequality across skill groups, the behavior of multinational firms, firm-level dynamics of entry and exit, and the nature of comparative advantage across countries.

Keywords: Immigration; Policy; Economics; Outcome or Result; United States;

Format: Print

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Hanson, Gordon H., William R. Kerr and Sarah Turner, eds. High-Skilled Migration to the United States and Its Economic Consequences. Chicago, IL: University of Chicago Press, 2018.

We study immigrant entrepreneurship in 2007 and 2012 using the Survey of Business Owners. First-generation immigrants create about 25% of new firms in America, but this share exceeds 40% in some states. Immigrant-owned firms tend to create fewer jobs than native-owned firms, have comparable pay levels, offer fewer benefits, and engage more in international activities. Immigrant-founded firms in high-tech sectors more closely resemble native-founded firms than in low-tech sectors. Prominent tech clusters display quite pronounced shares of immigrant entrepreneurs, with stronger high-tech immigrant entrepreneurs being especially present. Second-generation immigrants tend to show intermediate firm traits indicative of business assimilation.

This primer is meant to be a field guide to the late 2010s' surge in business use of "Artificial Intelligence" (AI), or enterprise software based in machine learning. First, it provides an overview of the key trends - digitization, connectivity, the continuation of Moore's law, and advancements in machine learning algorithms - which led to the inflection point in adoption of AI. Then, the primer describes the range of use cases of state-of-the-art enterprise AI organized in a taxonomy designed to build generalized understanding of the types of work to which AI can be applied. This knowledge is useful not only to managers looking to best leverage the technology but to those working to manage resulting organizational change and prepare the workforce for transitions into complementary tasks. Finally, key issues and implications of AI adoption are also discussed.

Driven largely by advances in perception and situational awareness, robots in the 2010s were gaining functionality that allowed them to be applied to fundamentally new types of work. The expanding range of new tasks that could be completed by machines had significant implications for businesses, the workforce, and society. This primer grounds conversations about these implications by describing the advances in underpinning technology that moved the boundaries of where robots could be deployed and illustrating real-world examples of the new types of activities that robots were becoming able to perform.

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High-Skilled Migration to the United States and Its Economic Consequences

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