Theoretical and Applied Economics
No. 2 / 2026 (647), Summer
Can monetary policy drive inclusive social development in Africa? Instrumental variables quantile regression approach
Thomas SANKARA University, Burkina Faso
Pousbila DIANDA
Thomas SANKARA University, Burkina Faso / Pan-African Institute for Development in West Africa and the Sahel (IPD-AOS), Burkina Faso
Abstract. This paper examines whether, beyond its conventional aims of price stability, monetary policy is a determinant of inclusive social development in Africa. The analysis is based on a panel of African countries covering the period 2010–2022. The empirical strategy employs three complementary econometric models: a fixed-effects model to capture country-specific variations, a two-stage least squares (2SLS) regression to address endogeneity, and an instrumental-variable quantile regression (IV-QR) to study the heterogeneity impact according to levels of inclusive development. The empirical results provide robust evidence that monetary policy has positive and causal effects on inclusive human development in Africa. Bank liquidity, monetary depth, and real interest rate stability significantly improve the inequality-adjusted human development index (IHDI). Instrumental variable quantile regressions reveal remarkably stable coefficients across the conditional distribution of inclusive development, indicating the absence of strong heterogeneity across countries. Furthermore, alternative estimations show that monetary policy reduces social and income inequalities while enhancing human development. These findings suggest that monetary policy operates as a macrostructural lever for inclusive development rather than a purely distributive instrument. These findings call for monetary authorities to strengthen macroeconomic stability, enhance liquidity management, and foster financial deepening as strategic tools to promote inclusive human development in African economies.
Contents
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Can monetary policy drive inclusive social development in Africa? Instrumental variables quantile regression approach
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