Evaluating the β-Convergence of Labour Productivity under Varying Political Regimes
Evaluating the β-Convergence of Labour Productivity under Varying Political Regimes
Author(s): Weerasak SAWANGLOKE, Aphichat WIYO, Mana LUKSAMEE-ARUNOTHAI, Suteera CHANTHES, Phubet SENBUT, Nut THANCHAROEN, Supattra NUTTEESubject(s): Politics / Political Sciences, Politics, Economy, Supranational / Global Economy, Labor relations, Economic policy
Published by: RITHA Publishing
Keywords: labour productivity; β-convergence; political regimes; political stability; economic growth; dynamic panel data;
Summary/Abstract: This paper evaluates the β-convergence of labour productivity across the political regimes. The analysis provides insight into the extent and pattern of labour productivity convergence differentiated by political system, controlling for economic and political stability variables. Data were collected from 129 countries, which were grouped by four political regime types and using fixed effects and Generalized Method of Moments (GMM) estimations on dynamic panel data, we examine the unconditional and conditional convergence of three separate periods. The control variables include gross fixed capital formation, life expectancy, foreign direct investment, trade openness, and political stability. The results show a significant relationship between labour productivity growth rates and the initial levels of productivity across all regime types, with full democracies exhibiting the most rapid β-convergence relative to the other system types. The analysis reveals that the impact of political stability on convergence rates is profound; specifically, more politically stable regimes tend to converge at higher rates of labour productivity. This explains considerable variance in labour productivity convergence paths across political contexts. The paper provides new evidence on the relevance of the political regimes for β-convergence of labour productivity, while employing political regime typologies rather than traditional geographic or sector classifications.
Journal: Journal of Applied Economic Sciences (JAES)
- Issue Year: XX/2025
- Issue No: 4(90)
- Page Range: 913-939
- Page Count: 28
- Language: English
