The Impact of Technological Change on Employment: A Composite Indicator Approach

Rahim Taghizadeh (), Salar Babazadeh Behestani () and Reza Arabsheibani ()
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Rahim Taghizadeh: Department of Industrial Engineering, Urmia University of Technology, West Azerbaijan, Urmia, Iran.
Salar Babazadeh Behestani: Allameh Tabatabaei University, Tehran, Iran.
Reza Arabsheibani: London School of Economics

No 18814, IZA Discussion Papers from IZA Network @ LISER

Abstract: generally a consensus remains elusive regarding the optimal method for measuring the effects of technological change and innovation on employment. This study introduces a Technological Change Composite Indicator (TCI), constructed using Principal Component Analysis (PCA) to synthesize seven firm-level innovation metrics. This methodology mitigates issues associated with multicollinearity in regression analyses involving correlated variables. The proposed TCI serves as a proxy for technological change to examine its association with employment in manufacturing sectors across 10 European Union countries and 17 seventeen manufacturing sectors with country fixed effects and a one‑year time lag. We find that a one‑unit increase in the TCI corresponds to a 0.58% higher employment level. The association is positive and statistically significant, indicating that a multidimensional measure of technological change outperforms traditional single proxies such as R&D expenditure or patent counts. By moving beyond narrow indicators, our approach offers a more reliable empirical basis for understanding the employment implications of technological change, including emerging technologies such as AI.

Keywords: composite indicator; latent approach; technological change; employment; manufacturing industry; PCA analysis; regression method (search for similar items in EconPapers)
JEL-codes: C38 J23 O14 O33 (search for similar items in EconPapers)
Date: 2026-07
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