@TechReport{iza:izadps:dp18814,
            	author={Taghizadeh, Rahim and Behestani, Salar Babazadeh and Arabsheibani, Reza},
            	title={The Impact of Technological Change on Employment: A Composite Indicator Approach},
            	year={2026},
	month={Jul},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={18814},
            	url={https://www.iza.org/index.php/publications/dp18814},
	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},
            }