The Impact of Global Automation Pressure and Technological Advancement on Unemployment in Developing Economies: Evidence from Panel Data (2012–2023)

Abstract

Global automation and rapid technological progress have emerged as major forces driving economic transformation, stimulating extensive discussion about their consequences for employment, particularly in developing economies. Although technological innovation has the potential to improve productivity and foster economic growth, concerns persist regarding its impact on labour-market dynamics. This study examines the relationship between global automation pressure, technological advancement, and unemployment in a panel of ten developing countries during the period 2012–2023.

The analysis employs annual panel data collected from the World Bank, the International Labour Organization (ILO), the International Federation of Robotics (IFR), and the UNESCO Institute for Statistics. Global automation pressure is measured by the annual number of industrial robot installations worldwide, as reported by the IFR, while technological advancement is represented by high-technology exports. The empirical analysis is conducted using a Fixed Effects model with Driscoll–Kraay robust standard errors to address potential econometric issues. In addition, several diagnostic procedures—including the Im–Pesaran–Shin (IPS) and Levin–Lin–Chu (LLC) panel unit-root tests, the Variance Inflation Factor (VIF), the Hausman specification test, and the Pesaran cross-sectional dependence test—are performed to ensure the reliability and robustness of the estimated results.

The empirical findings reveal that global automation pressure exerts a positive and statistically significant effect on unemployment, indicating that global technological substitution may intensify labour-market adjustment challenges in developing economies. Nevertheless, the negative coefficient associated with the nonlinear term of global automation pressure suggests that these adverse effects gradually weaken over time as economies adapt through technological diffusion, labour reallocation, and improvements in workforce skills. Economic growth is found to significantly reduce unemployment, providing empirical support for Okun’s Law. Likewise, education contributes to lower unemployment by enhancing workers’ adaptability and employability within technology-intensive labour markets. Furthermore, high-technology exports are associated with declining unemployment rates, implying that technological advancement can create employment opportunities when accompanied by structural economic transformation and investment in human capital. Overall, the estimated model accounts for approximately 73.7% of the variation in unemployment across the selected developing economies.

This study contributes to the existing body of literature by providing updated empirical evidence on the labour-market implications of global automation pressure and technological transformation in developing countries. The findings emphasize the need to strengthen education systems, expand digital and technical skills, promote workforce reskilling initiatives, and support innovation-driven growth policies to ensure that technological progress fosters sustainable employment and inclusive economic development.

Keywords: Global Automation Pressure; Technological Advancement; Unemployment; Industrial Robots; Economic Growth; Education; Developing Economies; Panel Data Analysis.

DOI: 10.7176/JLPG/155-06

Publication date: September 28th 2026