Empowering economic growth through female labor force participation in central Asia: Evidence from regression and dynamic analyses

Abstract

Female labor force participation plays a significant role in driving the economic development of a country across various sectors. The previous literature suggests that increasing female labor force participation contributes to economic growth, the sector-specific impact remains unclear. The current study addresses this gap by analyzing female employment at both aggregate and sectoral levels, focusing on agriculture, industry, and services—on the economic growth of Central Asian economies from 1995 to 2022. Using a combination of regression techniques—including pooled OLS, fixed effects, and random effects models—and dynamic analytical approaches, the study addresses key issues of reverse causality and endogeneity through the adoption of the system GMM model. In addition, this study uses stationarity tests, including the Breitung and Das, IPS, and Pesaran tests, which reveal a mixed order of integration. The results of regression analysis show that total female labor force participation positively contributes to economic growth, while corruption negatively affects it. Sector-specific analysis result reveals that female participation in agriculture and services significantly enhances economic growth, whereas participation in the industrial sector has a detrimental impact. These results highlight the essential need for targeted policies to improve female labor force participation in high-growth sectors, mitigate the negative effects in the industrial sector, and address corruption. The study offers valuable insights into the role of female labor force participation in shaping economic growth in Central Asia.