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Impacts From Automation Diffuse Locally €“ A Novel Approach To Estimate Jobs Risk In Us Cities

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  • Teresa Farinha

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.

Suggested Citation

  • Teresa Farinha, 2020. "Impacts From Automation Diffuse Locally €“ A Novel Approach To Estimate Jobs Risk In Us Cities," Papers in Evolutionary Economic Geography (PEEG) 2029, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jul 2020.
    • Handle: RePEc:egu:wpaper:2029
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    File URL: http://econ.geo.uu.nl/peeg/peeg2029.pdf
    File Function: Version July 2020
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    More about this item

    Keywords

    automation; Cities; complementarity; diffusion; jobs; similarity;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • O20 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - General
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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