Unemployment in the WAEMU Countries: A Cross-Sectional Data Approach
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Abstract
The aim of this article is to conduct an empirical evaluation of the microeconomic determinants of unemployment in the West African Economic and Monetary Union (WAEMU), controlling for inactivity. A multinomial logistic analysis has been conducted by using the Harmonized Survey of Household Living Conditions (2019) survey. Our results show that being female, single, young, disabled, and living in urban increases the risk of unemployment and inactivity. Furthermore, despite a higher incidence of unemployment among educated individuals, they are less likely to be inactive compared to those with no education. We also note that women with a university education are less affected by inactivity than men with the same level of education but remain more exposed to unemployment. In addition, age has a very limited influence on unemployment among men, unlike women, where it has a very significant amplifying effect. In addition, the negative effect of university education on unemployment is more pronounced in rural areas than in big cities. Finally, disability does not determine rural unemployment, unlike in urban areas, where it exacerbates it.
JEL codes: D63, J16, J64
Keywords: Unemployment, WAEMU, Cross-sectional data, Employment survey, Inactivity
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How to Cite
Niaré, M. and Mariko, O. (2023) “Unemployment in the WAEMU Countries: A Cross-Sectional Data Approach”, World Journal of Applied Economics, 9(2), pp. 113-124. doi: 10.22440/wjae.9.2.1.
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Research Articles
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References
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Anyanwu, J. C. (2013). Characteristics and Macroeconomic Determinants of Youth Employment in Africa. African Development Review, 25, 107–129. doi:10.1111/j.1467-8268.2013.12019.x
Baah-Boateng, W. (2013). Determinants of Unemployment in Ghana. African Development Review, 25, 385-399. doi:10.1111/1467-8268.12037
Becker, G. (1964). Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. Columbia University Press, New York. doi:10.7208/chicago/9780226041223.001.0001
Ben, B., & Coretta, P. (2007). Disproportionate and Discriminatory: Reviewing the Evidence on Police Stop and Search. Modern Law Review, 70, 936–961. doi:10.1111/j.1468-2230.2007.00671.x
Benhabib, L. (2017). Youth unemployment and insertion inequalities in the Algerian labour market: multidimensional analysis and experimentation. PhD thesis, Economic sciences, Université Paris-Est.
Boateng, K. (1994). Measuring Cost of Unemployment: The Case of Ghana. Measuring Cost of Unemployment: The Case of Ghana.
Buchel, F., & van Ham, M. (2003). Overeducation, Regional Labour Markets and Spatial Flexibility. Journal of Urban Economics, 53, 482-493. doi:10.1016/S0094-1190(03)00008-1
Calves, A.-E., & Kobiane, J.-F. (2014). Genre et nouvelles dynamiques d’insertion professionnelle chez les jeunes a Ouagadougou. Autrepart, 71, 33-56. doi:10.3917/autr.071.0033
Doumbia Gakou, A., & Kuépié, M. (2008). Niveau et déterminants de l’insertion des femmes sur le marché du travail au Mali. Working Paper, IRD.
Gad, A. Y. (2021). The impact of education to the transition from unemployment to employment in Egypt. Review of Economics and Political Science, 1-17. doi:10.1108/REPS-07-2020-0093
Groce, E. N., & Kett, M. (2014). Youth with disabilities. Working Paper, Leonard Cheshire Disability.
ILO. (2018). Qu’est-ce qui penalise les femmes face a l’emploi? Qu’est-ce qui penalise les femmes face a l’emploi?
ILO. (2020). Meeting the challenge of youth employment. Meeting the challenge of youth employment.
Isengard, B. (2003). Youth unemployment: Individual risk factors and institutional determinants. A case study of Germany and the United Kingdom. Journal of Youth Studies, 6, 357-376. doi:10.1080/1367626032000162096
Jarousse, J.-P., Bhuwanee, T., & Huot-Marchand, H. (2008). Elements de Diagnostic et de developpement de l’acces a l’emploi des sortants des systemes educatifs en Afrique. Report, UNESCO/BREDA.
Kett, M. (2012). Skills development for youth living with disabilities in four developing countries. Background paper prepared for the Education for all Global Monitoring Report, UNESCO.
Kiiru, J., Onsumu, E., & Wamalwa, F. (2013). Does training matter for youth employment? Lessons from Kenya. Journal of Emerging Issues Economics, Finance and Banking, 2, 128-149.
Mahmoudi, A. (2021). Discrimination dans l’acces a l’emploi due au handicap moteur, en Ile de France. Revue Française d’economie, 36, 141-184. doi:10.3917/rfe.211.0141
Mbebi, O. E. (2018). Les determinants du travail des enfants au Cameroun: le role du milieu de residence et du genre. Revue d'economie du developpement, 26, 5-52. doi:10.3917/edd.321.0005
Msigwa, R., & Kipesha, E. F. (2013). Determinants of youth unemployment in developing countries: Evidence from Tanzania. Journal of Economics and Sustainable Development, 4, 67-76.
National Statistics Bureau of Bhutan. (2020). Determinants of youth unemployment in Bhutan. Thematic Research Report Series, National Statistics Bureau of Bhutan.
Njifen, I. (2015). Caracteristiques et determinants du chomage des jeunes au Cameroun: le role preponderant du diplome et du sexe. African Development Review, 27, 443-455. doi:10.1111/1467-8268.12159
Oancea, B. (2016). A logit model for the estimation of the educational level influence on unemployment in Romania. MPRA Working Paper, Munich Archive.
OECD. (2016). Cote d'Ivoire Multidimensional Country Review: Investing in the workforce through quality education and appropriate skills. Report, Organisation for Economic Co-operation and Development. doi:10.1787/9789264258501-8-en.
O'Higgins, N. (2003). Trends in the Youth Labour Market in Developing and Transition Countries. Social Protection Discussion Paper Series, World Bank.
Sackey, H. A., & Osei, B. (2006). Human Resource Underutilization in an Era of Poverty Reduction: An Analysis of Unemployment and Underemployment in Ghana. African Development Review, 18, 221–247. doi:10.1111/j.1467-8268.2006.00140.x
Schultz, T. W. (1961). Investment in Human Capital. American Economic Review, 51, 1-17.
WAEMU. (2019). Integrated Regional Survey on Employment and the Informal Sector - IRS-EIS. Integrated Regional Survey on Employment and the Informal Sector - IRS-EIS.
World Bank. (2019). World Development Indicators. World Development Indicators.