The impact of technological change on employment: a composite indicator approach

Rahim Taghizadeh, Salar Babazadeh Behestani and G. Reza Arabsheibani

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Despite extensive research, 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 European Union countries. Applying the TCI to a pooled cross‑section of ten European countries and seventeen manufacturing sectors (170 observations) 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. The TCI provides policymakers and industry stakeholders with a novel framework for assessing how a broad portfolio of innovation activities—including machinery acquisitions, external knowledge, intellectual property rights, and both product‑ and process‑oriented efforts—relates to manufacturing employment. 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: J23 O14 O33 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2026-07-24
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Published in Journal of Industrial and Business Economics, 24, July, 2026. ISSN: 0391-2078

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