Automating Labor: Evidence from Firm-Level Patent Data

98 Pages Posted: 14 Jan 2020

See all articles by Antoine Dechezleprêtre

Antoine Dechezleprêtre

London School of Economics & Political Science (LSE)

David Hémous

University of Zürich

Morten Olsen

University of Copenhagen

Carlo Zanella

University of Zurich - Department of Economics

Multiple version iconThere are 2 versions of this paper

Date Written: December 2019

Abstract

Do higher wages lead to more automation innovation? To answer this question, we first introduce a new measure of automation by using the frequency of certain keywords in patent text to identify automation innovations in machinery. We validate our measure by showing that it is correlated with a reduction in routine tasks in a cross-sectoral analysis in the US. Then we build a firm-level panel dataset on automation patents. We combine macroeconomic data from 41 countries and information on geographical patent history to build firm-specific measures of low-skill and high-skill wages. We find that an increase in low-skill wages leads to more automation innovation with an elasticity between 2 and 4. An increase in high-skill wages tends to reduce automation innovation. Placebo regressions show that the effect is specific to automation innovations. Finally, we use the Hartz labor market reforms in Germany for an event study and find that they are associated with a relative reduction in automation innovations.

Keywords: automation, Income inequality, Innovation, patents

JEL Classification: J20, O31, O33

Suggested Citation

Dechezleprêtre, Antoine and Hemous, David and Olsen, Morten and Zanella, Carlo, Automating Labor: Evidence from Firm-Level Patent Data (December 2019). CEPR Discussion Paper No. DP14249, Available at SSRN: https://ssrn.com/abstract=3518588

Antoine Dechezleprêtre (Contact Author)

London School of Economics & Political Science (LSE) ( email )

Houghton Street
London, WC2A 2AE
United Kingdom

David Hemous

University of Zürich ( email )

Zürich
Switzerland

Morten Olsen

University of Copenhagen ( email )

Copenhagen
Copenhagen
Denmark

Carlo Zanella

University of Zurich - Department of Economics ( email )

Zürich
Switzerland

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
0
Abstract Views
148
PlumX Metrics