The effect of automation levels on US interstate migration
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This study investigates the extent to which job process automation, which has resulted in wage inequality and job polarization in the USA and has affected US interstate migration over the past two decades. The level of automation in each state is calculated using data on the degree of automation of each occupation. In particular, this study examines how the difference in the levels among states explains the movement of migrants. The results show that people move to states with more automation in skilled occupations and less automation in unskilled occupations. This finding implies that automation has a complementary (substitution) effect on skilled (unskilled) occupations. The results also show that the former effect is larger and more robust than the latter one. Further analyses use migration flow data classified into several subgroups and find that both skilled and unskilled workers in most occupations move to states with more automation in skilled occupations and less automation in unskilled occupations.
JEL ClassificationJ24 R23
The author would like to thank Takatoshi Tabuchi, Marcus Berliant, Michael Pflüger, Yasuhiro Sato, and Atsushi Yamagishi. I am also indebted to an anonymous referee and the editor-in-chief, Martin Andersson, for their helpful comments and suggestions. The author also thanks the participants of the JEA meeting at Ritsumeikan University, the Asian Seminar in Regional Science at National Taiwan University, and of seminars at Tohoku University, Kyushu Sangyo University, Kyoto University, the University of Tokyo, and Kagawa University.
- Acemoglu D, Restrepo P (2017) Robots and jobs: evidence from US labor markets, NBER Working Paper No. 23285Google Scholar
- Executive Office of the President of the United States of America (2016) Artificial intelligence, automation, and the economy. Technical representative, Washington, DCGoogle Scholar
- McFadden D (1973) Conditional logit analysis of qualitative choice behavior. In: Zarembka P (ed) Frontiers in econometrics. Academic Press, New YorkGoogle Scholar
- US Census Bureau (2018) Understanding and using American Community Survey data: What all data users need to know. Tech. Rep. July, Washington, DCGoogle Scholar