What are the local spillover effects of innovation?

I investigate the spillover effects of labor displacement from technological innovation in local U.S. labor markets. Previous work on the direct effect uses textual matching of patents to occupations and finds that occupations more exposed to innovation face a decline in employment and wages. I document the indirect effect of how the displacement lowers aggregate demand and therefore hurts industries who fully rely on local demand. In addition, I show how the labor displacement from technology as well as the lower local aggregate demand alters the local supply/demand of labor. The existence of local spillovers ties the discussion of innovation’s welfare consequences to location. Even if a worker is not directly displaced, they may still be affected by technological advancement. While there are many possible local spillovers, this paper focuses on the aggregate demand channel. I first document the direct effect of labor displacement at the commuting zone level and find that occupations in the 75th percentile of innovation exposure vs. occupations in the 25th percentile experience a decline in within-industry employment of 3.5% (though not statistically significant) and a decline in wages of 4%. I then create a shift-share instrument of local innovation exposure using local occupation shares and the national measure of occupation exposure. To isolate the effect of lower local aggregate demand, I focus on low-exposure occupations in non-tradeable industries, as they are not impacted by labor displacement but are impacted by lower local aggregate demand. I find that these workers in the 75th percentile of local area exposure vs. the 25th percentile face a 6% decline in employment and no meaningful change in wages. Lastly, I find that the higher quantiles of wages are more impacted by both the direct and indirect effect. And though wage inequality decreases in more impacted areas, it is driven by a decrease in wages for both tails so is not welfare improving.

Name thesis:degree_name

Master

Department dc:contributor.department

Sloan School of Management

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Bidanda, Maya

Advisor dc:contributor.advisor

• Verdelhan, Adrien

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/139244

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/139244