Impacts from Automation Diffuse Locally: A Novel Approach to Estimate Jobs Risk in US Cities

Teresa Farinha*

*Corresponding author for this work

Research output: Working paper / PreprintWorking paper

Abstract

Workers that become automated may transfer productivity gains to their co-workers or make it easier to automate their jobs too. In this paper, I empirically investigate how automatable jobs have diffused impacts to neighbouring jobs in North American cities between 2007 and 2016. Results indicate that jobs that share similarities with neighbouring high-risk jobs grew less, even when controlling for their own technical risk of automation. Conversely, jobs that share complementarities with neighbouring high-risk jobs grew faster, possibly indicating productivity gains from working with recently automated jobs. In addition to the analysis in this paper, I provide an adjusted index of job automation risk that accounts for local diffusion of impacts (negative and positive) in US cities.
Original languageEnglish
PublisherUtrecht University
Publication statusPublished - 1 Jul 2020

JEL classifications

  • e24 - "Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital"
  • o15 - "Economic Development: Human Resources; Human Development; Income Distribution; Migration"
  • o32 - Management of Technological Innovation and R&D

Fingerprint

Dive into the research topics of 'Impacts from Automation Diffuse Locally: A Novel Approach to Estimate Jobs Risk in US Cities'. Together they form a unique fingerprint.

Cite this