Sectoral value-added and employment shifts as drivers of inclusive growth in sub-Saharan Africa: evidence from structural transformation dynamics

Purpose This study investigates the linkage between structural transformation and inclusive growth in sub-Saharan Africa (SSA) by decoupling productive transformation, reflected in sectoral value-added and social transformation, reflected in cross-sector employment shifts. It asks whether changes in agriculture, manufacturing, industry and services value-added and employment shares transmit differently into inclusive growth. Design/methodology/approach The study constructs composite indices for inclusive growth and structural transformation to capture the multidimensional nature of these concepts. It uses annual unbalanced panel data for 32 SSA countries over the period 2000–2024. The empirical strategy applies the Bias-Corrected Method of Moments estimator as the main technique, supported by pooled ordinary least squares, between-country regression, common correlated effects, median quantile regression with year fixed effects and one-year lagged regressor model with year fixed effects estimation for robustness, with specifications adjusted to limit multicollinearity among sectoral shares. Findings The results establish a positive relationship between structural transformation and inclusive growth in SSA, suggesting that broad-based sectoral reallocation supports shared prosperity. The twin-channel evidence indicates that employment movement into services is the most consistent driver of inclusiveness, whereas manufacturing value-added has no statistically significant independent effect. The findings imply that the quality and employment-absorbing capacity of transformation matter more than the expansion of sectoral output shares alone. Research limitations/implications In the process, one potential limitation is that of availability and quality of sectoral employment data and data on value added across SSA countries at high frequency with consistent classification in terms of the sectors which might affect how granularly the analysis can be carried out. Furthermore, although the composite indices of inclusive growth and structural transformation were developed using state-of-the-art techniques, they might not record all the dimensions and complexities of these multifaceted phenomena. Next steps could involve studying alternative methods of analysis (e.g. panel threshold models or quantile regressions) in order to draw further conclusions with respect to the non-linear relationship between the process of structural change and inclusive growth. Second, taking a finer disaggregated perspective of the services sector in terms of high-productivity modern and low-productivity traditional services could offer a richer insight into inclusivity determinants. Future research might also replicate this dual-channel conceptualisation over more developing countries or on specific sub-regions in Africa to ascertain the generalisability of the results and compare contextual differences in the Structural Transformation-Inclusive Growth (ST-IG) relationship. Practical implications Policymakers should prioritise structural transformation strategies that emphasise employment creation rather than output expansion alone. Strengthening high-absorbing service sectors, improving service trade integration and enhancing productivity in agriculture are critical for inclusive outcomes. Industrial policies should focus on employment intensity and linkages rather than manufacturing expansion per se. Coordinated labour market, trade and human capital policies are essential to ensure transformation translates into shared prosperity. Social implications The findings highlight the importance of labour-absorbing structural change for reducing poverty and inequality in SSA. Shifting workers from low-productivity agriculture into productive service activities can improve livelihoods and social inclusion. Failure to align transformation with employment generation risks reinforcing exclusion. Inclusive structural change is therefore central to achieving decent work, social mobility and equitable development outcomes in the region. Originality/value This study contributes by jointly modelling sectoral value-added and employment shifts within a single SSA-focused inclusive-growth framework. By distinguishing the productive and social dimensions of structural transformation, it clarifies why sectoral upgrading may be inclusive only when output gains are matched by productive employment opportunities. The findings offer sector-specific policy guidance for structural transformation strategies aligned with Africa’s Agenda 2063.

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Journal
Journal of Economic Studies
Published
2026-08-21
DOI
https://doi.org/10.1108/jes-01-2026-0078
Primary Topic
Economic Growth and Development
Type
article
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article

Sectoral value-added and employment shifts as drivers of inclusive growth in sub-Saharan Africa: evidence from structural transformation dynamics

Christelle Meniago, Nkanyiso K. Ndlovu, Salom Kuume Katoole
Journal of Economic Studies
Economic Growth and Development
article

Sectoral value-added and employment shifts as drivers of inclusive growth in sub-Saharan Africa: evidence from structural transformation dynamics

Christelle Meniago, Nkanyiso K. Ndlovu, Salom Kuume Katoole
article en

Abstract

Purpose This study investigates the linkage between structural transformation and inclusive growth in sub-Saharan Africa (SSA) by decoupling productive transformation, reflected in sectoral value-added and social transformation, reflected in cross-sector employment shifts. It asks whether changes in agriculture, manufacturing, industry and services value-added and employment shares transmit differently into inclusive growth. Design/methodology/approach The study constructs composite indices for inclusive growth and structural transformation to capture the multidimensional nature of these concepts. It uses annual unbalanced panel data for 32 SSA countries over the period 2000–2024. The empirical strategy applies the Bias-Corrected Method of Moments estimator as the main technique, supported by pooled ordinary least squares, between-country regression, common correlated effects, median quantile regression with year fixed effects and one-year lagged regressor model with year fixed effects estimation for robustness, with specifications adjusted to limit multicollinearity among sectoral shares. Findings The results establish a positive relationship between structural transformation and inclusive growth in SSA, suggesting that broad-based sectoral reallocation supports shared prosperity. The twin-channel evidence indicates that employment movement into services is the most consistent driver of inclusiveness, whereas manufacturing value-added has no statistically significant independent effect. The findings imply that the quality and employment-absorbing capacity of transformation matter more than the expansion of sectoral output shares alone. Research limitations/implications In the process, one potential limitation is that of availability and quality of sectoral employment data and data on value added across SSA countries at high frequency with consistent classification in terms of the sectors which might affect how granularly the analysis can be carried out. Furthermore, although the composite indices of inclusive growth and structural transformation were developed using state-of-the-art techniques, they might not record all the dimensions and complexities of these multifaceted phenomena. Next steps could involve studying alternative methods of analysis (e.g. panel threshold models or quantile regressions) in order to draw further conclusions with respect to the non-linear relationship between the process of structural change and inclusive growth. Second, taking a finer disaggregated perspective of the services sector in terms of high-productivity modern and low-productivity traditional services could offer a richer insight into inclusivity determinants. Future research might also replicate this dual-channel conceptualisation over more developing countries or on specific sub-regions in Africa to ascertain the generalisability of the results and compare contextual differences in the Structural Transformation-Inclusive Growth (ST-IG) relationship. Practical implications Policymakers should prioritise structural transformation strategies that emphasise employment creation rather than output expansion alone. Strengthening high-absorbing service sectors, improving service trade integration and enhancing productivity in agriculture are critical for inclusive outcomes. Industrial policies should focus on employment intensity and linkages rather than manufacturing expansion per se. Coordinated labour market, trade and human capital policies are essential to ensure transformation translates into shared prosperity. Social implications The findings highlight the importance of labour-absorbing structural change for reducing poverty and inequality in SSA. Shifting workers from low-productivity agriculture into productive service activities can improve livelihoods and social inclusion. Failure to align transformation with employment generation risks reinforcing exclusion. Inclusive structural change is therefore central to achieving decent work, social mobility and equitable development outcomes in the region. Originality/value This study contributes by jointly modelling sectoral value-added and employment shifts within a single SSA-focused inclusive-growth framework. By distinguishing the productive and social dimensions of structural transformation, it clarifies why sectoral upgrading may be inclusive only when output gains are matched by productive employment opportunities. The findings offer sector-specific policy guidance for structural transformation strategies aligned with Africa’s Agenda 2063.

Journal of Economic StudiesVol. 53(9)
Sol Plaatje University (ZA), North West Agriculture and Forestry University (CN)
Openalex Percentile: Top 90%
Economic Growth and Development
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