Inequality thresholds, governance and gender economic inclusion in sub-Saharan Africa

ABSTRACT

Inequality and gender economic exclusion are major policy concerns facing sub-Saharan Africa in the post-2015 development agenda. This paper identifies ‘thresholds’ of inequality that should not be exceeded if governance is to promote gender economic participation. The research focuses on 42 countries in sub-Saharan Africa using annual data from 2004 to 2014. The empirical work utilises the Generalized Method of Moments. The following findings are established. First, inequality (i.e. the Gini coefficient) levels that completely nullify the positive effect of governance on female labour force participation are 0.708 for political stability, 0.601 for voice & accountability, 0.588 for government effectiveness, 0.631 for regulatory quality, 0.612 for the rule of law, and 0.550 for corruption-control. Second, inequality thresholds at which female unemployment can no longer be mitigated by governance channels include: 0.561 for political stability and 0.465 for the rule of law. Third, inequality levels that completely dampen the positive impact of governance on female employment are 0.608 for political stability, 0.580 for voice & accountability, 0.581 for government effectiveness, and 0.557 for the rule of law. As the main policy implication, for good governance to promote gender economic inclusion, inequality levels should not exceed such thresholds.

KEYWORDS:

• Africa
• gender
• inequality
• inclusive development

JEL CLASSIFICATION:

• G20
• I10
• I32
• O40
• O55

Acknowledgements

The authors are indebted to the editor and reviewers for constructive comments.

Notes

1. The terms ‘gender inclusion’, ‘gender economic participation’, ‘female labour force participation’, ‘female employment’, ‘female economic participation’ and ‘gender economic inclusion’ are used interchangeably throughout the study.

2. It is important to note that the conclusions of Fosu are consistent with the finding that government actions to promote inclusive development are hampared by existing levels of inequality.

3. The 42 countries are Angola, Benin, Botswana, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo Democratic Republic, Congo Republic, Côte d’Ivoire, Djibouti, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritius, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome & Principe, Senegal, Seychelles, Sierra Leone, South Africa, Sudan, Swaziland, Tanzania, Togo, Uganda and Zambia.

4. Hence, the procedure for treating ivstyle (years) is ‘iv (years, eq(diff))’ whereas the gmmstyle is employed for predetermined variables.

5. ‘First, the null hypothesis of the second-order Arellano and Bond autocorrelation test (AR (2)) in difference for the absence of autocorrelation in the residuals should not be rejected. Second the Sargan and Hansen over-identification restrictions (OIR) tests should not be significant because their null hypotheses are the positions that instruments are valid or not correlated with the error terms. In essence, while the Sargan OIR test is not robust but not weakened by instruments, the Hansen OIR is robust but weakened by instruments. In order to restrict identification or limit the proliferation of instruments, we have ensured that instruments are lower than the number of cross-sections in most specifications. Third, the Difference in Hansen Test (DHT) for exogeneity of instruments is also employed to assess the validity of results from the Hansen OIR test. Fourth, a Fisher test for the joint validity of estimated coefficients is also provided’ (Asongu and De Moor 2017, 200).