The nexus between female unemployment and labor supply: evidence from Arab countries

Abstract

With an emphasis on groups like women who have an elastic labour supply, this study examines the link between unemployment and labour market participation in Arab countries from 1991 to 2021. The bootstrap panel Granger causality method is used to determine the causal direction, considering cross-sectional dependency, slope heterogeneity, and structural breaks. The results provide mixed evidence for the invariance, discouraged worker, and additional worker hypotheses, which qualify earlier findings. Of the 17 countries, only 4 are in favour of the unemployment invariance theory. Policies that raise the growth path of capital, productivity, and increase the effective working-age population may influence the unemployment rate.

Keywords:

• Unemployment invariance hypothesis
• discouraged worker effect
• female labour force participation rates
• female unemployment rates
• causality

JEL CLASSIFICATION:

• E24
• J60

Acknowledgements

The author is truly indebted to the Editor and two anonymous referees for their invaluable comments and suggestions. The usual disclaimers apply.

Ethical statement

I declare that this submission follows the policies as outlined in the Guide for Authors and in the Ethical Statement.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data used in this study is publicly available online. The information on the sources of data is provided in the text and references.

Notes

1 This methodology has also been used, for example, in Irandoust (2022). The relationship between the variables is in line with the empirical literature (Emerson, 2011; Liu, 2014; Lee & Parasnis, 2014; Apergis & Arisoy, 2017).

2 The robustness of the results was checked by using the procedure proposed by Toda and Yamamoto (1995) and Yamada and Toda (1998) to ensure that the usual test statistics for Granger causality have standard asymptotic distributions. It has been established that the limiting behavior of the Wald statistic with stochastic trends and cointegration is non-trivial (Toda & Phillips, 1993). Without well-behaved asymptotic distribution of the test statistic, bootstrap is likely to be inconsistent if the test statistic’s asymptotic distribution is not continuous with respects to perturbations in the data generating process (Horowitz, 2001). If the asymptotic distribution of the test statistic depends on the parameters of the data generating process, the bootstrap distribution can deviate a great deal from the true asymptotic distribution of the test statistic. Toda and Yamamoto (1995) and Yamada and Toda (1998) utilize a modified Wald test (MWald) for restrictions on the parameters of a VAR (k), where k is the lag length in the system. This test has an asymptotic chi-square distribution when a VAR (k + dmax) is estimated (where dmax is the maximal order of integration suspected to occur in the system). The results, however, support our findings regarding the direction of causality.