Fertility and Female Labor Force Participation in Asian Countries; Panel ARDL Approach

Abstract

Fertility has a close relationship with female labor force participation and is predicted to be the prominent factor affecting female labor force participation in rich and emerging countries. The decline in fertility worldwide, accompanied by increased female education, is assumed to increase female labor force participation. The increase in the female labor force participation rate can improve economic incentives for the country. Therefore, this study estimates the effect of fertility and female education on female labor force participation in cross-country panel datasets from 39 Asian countries, using panel ARDL analysis from 1990-2018. This study also examines the panel causality between the variables employing Dumitrescu and Hurlin’s (2012) Granger non-causality test. According to the Hausman test, among the three models in panel ARDL, DFE is the preferred model compared to the PMG and MG. The results revealed that fertility was negatively significant on female labor participation in the short run but not in the long run. In contrast, female education was positively significant on female labor participation in the long run but not in the short run. Meanwhile, the panel causality showed a bidirectional relationship between female labor participation and fertility, female labor participation and education, and fertility and female education.

Foreign direct investment (FDI) and environmental quality: Is greenfield FDI greener than mergers and acquisitions FDI?

“…In our study, we applied the approach of imposing a common lag structure across countries, particularly because data limitations and insufficient time dimensions prohibited us from extending the lags further (Table 3). This approach aligns with similar studies in the literature (Demetriades & Hook Law, 2006;Loayza & Ranciere, 2006;Nazah et al, 2021;Pesaran et al, 1999).…”

The impact of education and digitalization on female labour force participation in BRICS: an advanced panel data analysis

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The determinants of poverty in the West Papua province

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