Date of Award

Spring 4-1-2021

Document Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Arkolaks, Costas


This dissertation studies a range of topics in automation and globalization. Chapter 1 studies the role of industrial robots in the US in expanding the occupational wage polarization. Chapter 2 explores the effect of industrial robots in Japan on employment and wages in each industry and region. Chapter 3 investigates the impact of recent growth in multinational enterprises on headquarter country's labor demand and labor share. Chapter 1 studies the distributional and aggregate effects of the rising use of industrial robots across occupations. I construct a novel dataset that tracks the cost of robots from Japan by occupations. The dataset reveals a relative one-standard deviation drop of Japan's robot cost induces a 0.2-0.3¥% drop in the US occupational wages. I develop a general equilibrium model where robots are internationally traded durable goods that may substitute for labor differently across occupations. The elasticities of substitution between robots and labor within an occupation drive the occupation-specific real-wage effects of robotization. I estimate the model using the robot cost shock from my dataset and the optimal instrumental variable implied by the model. I find that the elasticities of substitution between robots and labor are heterogeneous across occupations, and higher than those between general capital goods and labor in production occupations such as welding. The estimated model implies that the industrial robots explain a 0.9 percentage point increase in the 90-50th percentile ratio of US occupational wages, and a 0.2 percentage point increase of the US real income from 1990 to 2007. Chapter 2 explores the impacts of industrial robots on employment in Japan, the country with the longest tradition of robot adoption. We employ a novel data set of robot shipments by destination industry and robot application (specified task) in quantity and unit values. These features allow us to use an identification strategy leveraging the heterogeneous application of robots across industries and heterogeneous price changes across applications. For example, the price drop of welding robots relative to assembling robots induced faster adoption of robots in the automobile industry, which intensively uses welding processes, than in the electric machine industry, which intensively uses assembling process. Our industrial-level and commuting zone-level analyses both indicate that the decline of robot prices increased the number of robots as well as employment, suggesting that robots and labor are grossly complementary in the production process. We compare our estimates with the ones reported by existing studies and propose a mechanism that explains apparent differences between the results. Chapter 3 investigates the impact of multinational enterprises (MNEs) on the source-country labor share. Our model shows that source-country factor demand elasticities with respect to foreign factor prices affect aggregate labor share. To identify these elasticities, we develop an estimator that leverages a foreign factor-productivity shock. We apply this estimator to a unique natural experiment: the 2011 Thailand Floods, which negatively impacted the foreign operation of Japanese MNEs. We employ a uniquely combined Japanese firm- and plant-level microdata and find that the Floods decreased fixed assets in Japan more than employment, suggesting that foreign factor productivity growth reduces Japan's labor share.