The impact of public employment on labour market performance: evidence from African countries

ABSTRACT

Using census data for Ghana, Mali and Mozambique, we study the long-term impact of public sector employment on local labour markets. We find that the public sector crowds out private employment and induces skilled workers to queue for a public job, thus increasing their unemployment rate. In addition, a growing public sector fosters employment in the tradable and nontradable sectors, remarkably for the unskilled, and the reallocation of unskilled workers away from agriculture.

KEYWORDS:

• Public employment
• local labour markets
• skills
• sub-Saharan Africa

JEL CLASSIFICATION:

• J21
• J45
• O55
• R11

Acknowledgements

The article’s findings, interpretations and conclusions are entirely those of the authors, and do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors or the governments they represent. We thank Pierella Paci for helpful discussions. We acknowledge the Minnesota Population Center and the statistical offices that provided the underlying data making this research possible: Ghana Statistical Services, Ghana; National Directorate of Statistics and Informatics, Mali; National Institute of Statistics, Mozambique.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Even cross-country studies such as Algan, Cahuc, and Zylberberg (2002) do not take into consideration developing countries.

² For 17 out of the 20 countries in sub-Saharan Africa available in the Integrated Public Use Microdata Series, International, it was not possible to perform the present analysis, due to a lack of a sufficient number of years, administrative units comparable over time and/or industrial classification. Minnesota Population Center. Integrated Public Use Microdata Series, International: Version 6.4 [Machine-readable database]. Minneapolis: University of Minnesota, 2015.

³ The first-stage F-statistic is above 10 and the impact of our instrumental variable is statistically significant and positive.

⁴ As agricultural workers are mostly unskilled, we do not distinguish the effect by skill level, and we refer to Table 1 for the overall results.

⁵ Results available upon request.