Abstract

The thesis investigates the effects of industrial automation on post-secondary education enrollment. To assess the effects, we build linear regression models to estimate the impact of the surge in the stock of industrial robots on post-secondary enrollment across 50 U.S. states and 41 countries. Drawing upon these estimates and the literature documenting the structural shift in the labor market, we find that recent developments in the fields of automation and robotics have contributed to a shift in demand for post-secondary education, with panel data models that control for both country and time fixed unobservables indicating a significant decline in enrollment for 4-year degree programs internationally.

Thesis Completion

2020

Semester

Fall

Thesis Chair/Advisor

Scrogin, David

Co-Chair

Guldi, Melanie

Degree

Bachelor of Science (B.S.)

College

College of Business Administration

Department

Economics

Degree Program

Economics

Language

English

Access Status

Open Access

Release Date

12-1-2020

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