A Bayesian Approach to the Determinants of Structural Transformation in Sub‐Saharan Africa

ABSTRACT The literature on structural transformation reveals a large number of variables, models and a wide range of recommendations (sometimes divergent or conflicting). This creates a certain amount of confusion as to the best‐suited model to analyse this phenomenon and as to variables that are the main determinants of its process. This paper aims to dispel that confusion in sub‐Saharan Africa by attempting to identify (i) the best‐suited model to analyse the structural transformation of the region, and (ii) the variables that are its main determinants. From a panel of 43 countries over the period of 1991–2019, a two‐step methodological approach is used. First, shift‐share decomposition, to assess the annual performances of countries in structural transformation, and then, Bayesian approaches, to select the ‘best‐suited model’ and the ‘main determinants’ of the process from a list of 58 variables that run through the literature. The results show that none of the models significantly dominates the models' space. However, they ranked 12 variables as key determinants of structural transformation in the region. Findings suggest three key policy axes for stimulating structural transformation in sub‐Saharan Africa: (i) the improvement of governance, the eradication of corruption and respect for the fundamental rights and freedoms of individuals; (ii) the increase in human capital, mainly through secondary education; and (iii) subregional and regional integration of African countries. The value of this paper lies in its success in identifying the main determinants of structural transformation in sub‐Saharan Africa, by introducing Bayesian approaches to this field of study.

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Publication Details

Journal
South African Journal of Economics
Published
2025-04-01
DOI
https://doi.org/10.1111/saje.12404
Citations
2
Primary Topic
Global Financial Crisis and Policies
Type
article
Field-Weighted Citation Impact
4.42
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article

A Bayesian Approach to the Determinants of Structural Transformation in Sub‐Saharan Africa

Aronda Tchamsé
2 citations
South African Journal of Economics
Global Financial Crisis and Policies
4.42
article

A Bayesian Approach to the Determinants of Structural Transformation in Sub‐Saharan Africa

Aronda Tchamsé
article en
2 citations

Abstract

ABSTRACT The literature on structural transformation reveals a large number of variables, models and a wide range of recommendations (sometimes divergent or conflicting). This creates a certain amount of confusion as to the best‐suited model to analyse this phenomenon and as to variables that are the main determinants of its process. This paper aims to dispel that confusion in sub‐Saharan Africa by attempting to identify (i) the best‐suited model to analyse the structural transformation of the region, and (ii) the variables that are its main determinants. From a panel of 43 countries over the period of 1991–2019, a two‐step methodological approach is used. First, shift‐share decomposition, to assess the annual performances of countries in structural transformation, and then, Bayesian approaches, to select the ‘best‐suited model’ and the ‘main determinants’ of the process from a list of 58 variables that run through the literature. The results show that none of the models significantly dominates the models' space. However, they ranked 12 variables as key determinants of structural transformation in the region. Findings suggest three key policy axes for stimulating structural transformation in sub‐Saharan Africa: (i) the improvement of governance, the eradication of corruption and respect for the fundamental rights and freedoms of individuals; (ii) the increase in human capital, mainly through secondary education; and (iii) subregional and regional integration of African countries. The value of this paper lies in its success in identifying the main determinants of structural transformation in sub‐Saharan Africa, by introducing Bayesian approaches to this field of study.

South African Journal of EconomicsVol. 93(3)
University of Kara (TG)
Openalex Percentile: Top 7%
Global Financial Crisis and Policies
4.42
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