Essays on Automation and Labor Markets

Abstract

How do recent automation technologies affect labor markets? And what can policymakers do to alleviate adverse impacts on workers? In this collection of essays, I provide empirical evidence on how automation shapes labor markets.

In Chapter 1, I use administrative data that link workers, firms, and robots in Denmark to study the distributional impact of industrial robots. I structurally estimate a dynamic model of the firm that rationalizes how firms select into and reorganize production around robot adoption. To understand the macroeconomic implications of robot adoption, I embed the firm model into a general equilibrium framework that endogenizes the choice of workers to switch occupations. Using the general equilibrium model, I estimate that industrial robots have increased average real wages by 0.8 percent but with substantial distributional consequences. Production workers employed in manufacturing have lost 6 percent from the arrival of robots.

In Chapter 2, I provide causal evidence on the individual and market level impacts of retraining subsidies. I study a reform that unexpectedly and temporarily eliminated all subsidies for 40 percent of the retraining courses available for unemployed workers in Denmark. I find that training activity reacts strongly to subsidies, and that retraining courses are effective in helping workers find jobs.

In Chapter 3, co-authored with Bjørn Bjørnsson Meyer, we first rank college majors according to whether their graduates work in Artificial Intelligence (AI) firms. We then use a regression discontinuity design to estimate the causal effects of admitting students to more AI relevant college majors. We find substantial labor market returns to college degrees that are relevant to firms that produce AI.