Macro-econometric analysis of unemployment in WAEMU countries

Analyse macro-économétrique du chômage dans les pays de l’UEMOA

Ousmane Mariko () and Mohamed Niaré ()
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Ousmane Mariko: USSGB - Université des sciences sociales et de gestion de Bamako, CREG - Centre de recherche en économie de Grenoble - UGA - Université Grenoble Alpes
Mohamed Niaré: USSGB - Université des sciences sociales et de gestion de Bamako

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Abstract: Purpose : This paper aims to assess the macroeconomic determinants of unemployment in WAEMU countries, with a particular focus on rainfall shocks. Design/methodology/approach : The use of sub-regional data requires checking that time series are not simultaneously correlated. With this in mind, we used the Breusch-Pagan (1980) test to detect possible error correlation. Based on this result, we respectively used Pesaran ' s (2007) second-generation unit root test and Westerlund ' s (2007) cointegration test, which are robust to individual interdependence. Finally, we estimated the long-term unemployment equation using the DOLS technique to correct for any endogeneity problems. The data used in this study cover the period 1991–2020 and come from various sources : World Development Indicators, Worldwide Governance Indicators, and Global Climate Data-University of Delaware covering. Findings : Empirical analysis shows that rainfall shocks, trade openness and corruption control exacerbate unemployment, while GDP growth helps to reduce it. Inflation, ICT, and financial development, on the other hand, proved insignificant. Originality/value : This article assesses the impact of rainfall anomalies on unemployment, a first in the empirical literature.

Keywords: déterminants macroéconomiques; chômage; UEMOA; DOLS; macroeconomic determinants; unemployment; WAEMU (search for similar items in EconPapers)
Date: 2024-08-02
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Published in Revue internationale des économistes de langue française, 2024, 9 (1), pp.154-173. ⟨10.18559/RIELF.2024.1.1639⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-04734883

DOI: 10.18559/RIELF.2024.1.1639

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