Skip to main content
SpringerLink
Log in

Understanding the Efficiency in Generating Human Development in Sub-Saharan Africa: A Two-Stage Network DEA Approach

  • Original Research
  • Published:
Social Indicators Research Aims and scope Submit manuscript

Abstract

One of the primary goals of any nation is to improve the level of human development, which entails higher levels of education, health, and income. However, considering the holistic human development system, previous studies in Africa have neglected to assess the system’s performance while considering the inefficiency within internal structures (i.e., economic growth, health promotion, and education promotion). Accordingly, this study proposes a new methodological framework consisting of a new two-stage network DEA model, combined with rank-sum tests and the concept of efficiency Theil coefficient and its corresponding decomposition method to address this research gap. The proposed framework can obtain multi-dimensional efficiency scores of the human development system, examine heterogeneity between research groups, measure efficiency inequality across countries, and identify impediments to technology diffusion. Empirically, this study focuses on 26 sub-Saharan African countries from 2014 to 2018 due to the numerous development challenges of the region. Our results show that, first, sub-Saharan Africa failed to improve the overall performance of the human development system during the study period. However, two divisions (i.e., economic growth and education promotion divisions) improved efficiency during the study period, while the health promotion division showed a decreasing trend. Second, the education promotion division appears as the primary source of the system's inefficiency, while its positive growth rate indicates that efforts have been made to promote education. However, the low-efficiency level across three divisions suggests that all divisions should be prioritized to improve the system's overall performance. Finally, there is heterogeneity across countries and research groups regarding efficiency measures, and cross-group inequity is the main factor producing technology inequality.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. The query is accessible at https://www.webofscience.com/wos/woscc/summary/a1d34c6f-84e6-4589-a88c-ed1b5db296a7-9daf816a/relevance/1

  2. The query is accessible at https://www.webofscience.com/wos/woscc/summary/dca9881e-d1c2-40e1-99c4-56d703004db9-9db052bf/relevance/1

  3. The Web of Science Core Collection database was accessed on 20 November 2022.

  4. We have extended the keywords due to the very limited number of studies on human development performance in Africa adopting DEA as a methodology.

  5. In the context of Hitomi (1979), the term "assembly conversion" refers to the process of transforming or converting the components of a product or system from individual parts into a complete assembly. It involves combining the separate parts or modules together in a coordinated manner to form the final product or system.

  6. PWT: https://www.rug.nl/ggdc/productivity/pwt/pwt-releases/pwt100

  7. WDI: https://databank.worldbank.org/source/world-development-indicators

  8. UNDP: https://hdr.undp.org/data-center

  9. EIA: https://www.eia.gov/international/data/world

  10. WHO: https://www.who.int/data

  11. The average inefficiency shares of each country are obtained as a share of division-based inefficiency scores in terms of the total division inefficiency scores (stage 1) and add up to 100%.

References

  • Aggelopoulos, E., & Georgopoulos, A. (2017). Bank branch efficiency under environmental change: A bootstrap DEA on monthly profit and loss accounting statements of Greek retail branches. European Journal of Operational Research, 261(3), 1170–1188.

    Article  Google Scholar 

  • Asongu, S. A. (2013). Fighting corruption in Africa: Do existing corruption-control levels matter? International Journal of Development Issues, 12(1), 36–52.

    Article  Google Scholar 

  • AUC/OECD. (2018). Africa’s development dynamics 2018: Growth, jobs and inequalities. OECD Publishing. https://doi.org/10.1787/9789264302501-en

    Book  Google Scholar 

  • Bollou, F., Ngwenyama, O., & Morawczynski, O. (2006). The impact of investments in ICT, health and education on development: A DEA analysis of five African countries from 1993–1999. ECIS 2006 Proceedings, 35. https://aisel.aisnet.org/ecis2006/35.

  • Chakamera, C., & Alagidede, P. (2018). Electricity crisis and the effect of CO2 emissions on infrastructure-growth nexus in Sub-Saharan Africa. Renewable and Sustainable Energy Reviews, 94, 945–958.

    Article  Google Scholar 

  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.

    Article  Google Scholar 

  • Chen, S., Zhang, R., Li, P., & Li, A. (2023). How to improve the performance of China’s energy-transport-economy-environment system: An analysis based on new strategy parallel-series input-output data envelopment analysis models. Energy, 281, 128235.

    Article  Google Scholar 

  • Despotis, D. K. (2005). Measuring human development via data envelopment analysis: The case of Asia and the Pacific. Omega, 33(5), 385–390.

    Article  Google Scholar 

  • Eren, M., Eren, M., & Başar, S. (2017). Measuring of human development through the output-oriented super efficiency VRS DEA model without inputs. Serbian Journal of Management, 12(2), 255–270.

    Article  Google Scholar 

  • Feng, C., & Wang, M. (2018). Analysis of energy efficiency in China’s transportation sector. Renewable and Sustainable Energy Reviews, 94, 565–575.

    Article  Google Scholar 

  • Ferraz, D., Mariano, E. B., Rebelatto, D., & Hartmann, D. (2020). Linking human development and the financial responsibility of regions: Combined index proposals using methods from data envelopment analysis. Social Indicators Research, 150(2), 439–478.

    Article  Google Scholar 

  • Ferraz, D., Moralles, H. F., da Costa, N. S., & Rebelatto, D. A. N. (2022). Economic complexity and human development: Comparison of standard and slack-based data envelopment analysis models. CEPAL Review, 137, 61–85.

    Google Scholar 

  • Ferraz, D., Moralles, H. F., Campoli, J. S., Oliveira, F. C. R., & Rebelatto, D. A. N. (2018). Economic complexity and human development: DEA performance measurement in Asia and Latin America. Gestão and Produção, 25(4), 839–853.

    Article  Google Scholar 

  • Furlan, M., & Mariano, E. (2021). Guiding the nations through fair low-carbon economy cycles: A climate justice index proposal. Ecological Indicators, 125, 107615.

    Article  Google Scholar 

  • Giménez, V., Ayvar-Campos, F. J., & Navarro-Chávez, J. C. L. (2017). Efficiency in the generation of social welfare in Mexico: A proposal in the presence of bad outputs. Omega, 69, 43–52.

    Article  Google Scholar 

  • Gossel, S. J. (2018). FDI, democracy and corruption in Sub-Saharan Africa. Journal of Policy Modeling, 40(4), 647–662.

    Article  Google Scholar 

  • Hatefi, S. M., & Torabi, S. A. (2018). A slack analysis framework for improving composite indicators with applications to human development and sustainable energy indices. Econometric Reviews, 37(3), 247–259.

    Article  Google Scholar 

  • Hitomi, K. (1979). Manufacturing systems engineering. Taylor & Francis.

    Google Scholar 

  • Ivanova, I., Arcelus, F. J., & Srinivasan, G. (1999). An assessment of the measurement properties of the human development index. Social Indicators Research, 46(2), 157–179.

    Article  Google Scholar 

  • Kao, C. (2009). Efficiency decomposition in network data envelopment analysis: A relational model. European Journal of Operational Research, 192(3), 949–962.

    Article  Google Scholar 

  • Kao, C. (2018). A classification of slacks-based efficiency measures in network data envelopment analysis with an analysis of the properties possessed. European Journal of Operational Research, 270(3), 1109–1121.

    Article  Google Scholar 

  • Lambert, P. J., & Aronson, J. R. (1993). Inequality decomposition analysis and the Gini coefficient revisited. The Economic Journal, 103(420), 1221–1227.

    Article  Google Scholar 

  • Li, Y., Wu, S., & Yan, B. (2022). Spatial characteristics and influential mechanism of the coupling coordination degree of urban accessibility and human development index in China. Environmental Science and Pollution Research, 29(20), 29793–29807.

    Article  Google Scholar 

  • Lima, P. A. B., Paião Júnior, G. D., Santos, T. L., Furlan, M., Battistelle, R. A. G., Silva, G. H. R., Ferraz, D., & Mariano, E. B. (2022). Sustainable human development at the municipal level: A data envelopment analysis index. Infrastructures, 7(2), 12.

    Article  Google Scholar 

  • Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. The Annals of Mathematical Statistics, 18(1), 50–60.

    Article  Google Scholar 

  • Mariano, E. B., & Rebelatto, D. A. N. (2014). Transformation of wealth produced into quality of life: Analysis of the social efficiency of nation-states with the DEA’s triple index approach. Journal of the Operational Research Society, 65(11), 1664–1681.

    Article  Google Scholar 

  • Mariano, E. B., Ferraz, D., & de Oliveira Gobbo, S. C. (2021). The human development index with multiple data envelopment analysis approaches: A comparative evaluation using social network analysis. Social Indicators Research, 157(2), 443–500.

    Article  Google Scholar 

  • Mariano, E. B., Sobreiro, V. A., & do Rebelatto, D. A. N. (2015). Human development and data envelopment analysis: A structured literature review. Omega, 54, 33–49.

    Article  Google Scholar 

  • Martínez-Murcia, F. J., Górriz, J. M., Ramírez, J., Puntonet, C. G., & Salas-González, D. (2012). Computer aided diagnosis tool for Alzheimer’s disease based on Mann–Whitney–Wilcoxon U-Test. Expert Systems with Applications, 39(10), 9676–9685.

    Article  Google Scholar 

  • Navas, L. P., Montes, F., Abolghasem, S., Salas, R. J., Toloo, M., & Zarama, R. (2020). Colombian higher education institutions evaluation. Socio-Economic Planning Sciences, 71, 100801.

    Article  Google Scholar 

  • Prasetyo, A. D., & Zuhdi, U. (2013). The government expenditure efficiency towards the human development. Procedia Economics and Finance, 5, 615–622.

    Article  Google Scholar 

  • Ramanathan, R. (2006). Evaluating the comparative performance of countries of the Middle East and North Africa: A DEA application. Socio-Economic Planning Sciences, 40(2), 156–167.

    Article  Google Scholar 

  • Reig-Martínez, E. (2013). Social and economic wellbeing in Europe and the Mediterranean basin: Building an enlarged human development indicator. Social Indicators Research, 111(2), 527–547.

    Article  Google Scholar 

  • Roy, A., Dutta, T., Li, Y., & Dong, X. (2022). Human development at the cost of the environment? An application of planetary pressures–adjusted human development index in the lens of planetary boundaries. Environmental Science and Pollution Research, 30, 32383–32405.

    Article  Google Scholar 

  • Salman, M., Wang, G., & Zha, D. (2022). Modeling the convergence analysis of sustainable production and consumption in terms of ecological footprints and human development index in Belt and Road Initiative countries. Sustainable Production and Consumption, 30, 233–254.

    Article  Google Scholar 

  • Shen, Y., Yue, S., Pu, Z., Lai, X., & Guo, M. (2020). Sustainable total-factor ecology efficiency of regions in China. Science of the Total Environment, 734, 139241.

    Article  Google Scholar 

  • Sikayena, I., Bentum-Ennin, I., Andoh, F. K., & Asravor, R. (2022). Efficiency of public spending on human capital in Africa. Cogent Economics and Finance, 10(1), 2140905.

    Article  Google Scholar 

  • Singh, B. P., & Yadava, A. K. (2022). Technical efficiency of financial inclusion and human development: Insights from the Indian states. Economic Notes, 51(2), e12199.

    Article  Google Scholar 

  • Sueyoshi, T., & Goto, M. (2018). Environmental assessment on energy and sustainability by data envelopment analysis. Wiley.

    Book  Google Scholar 

  • Sueyoshi, T., Qu, J., Li, A., & Liu, X. (2021). A new approach for evaluating technology inequality and diffusion barriers: The concept of efficiency Gini coefficient and its application in Chinese provinces. Energy, 235, 121256.

    Article  Google Scholar 

  • Theil, H. (1967). Economics and information theory. North-Holland.

    Google Scholar 

  • Tone, K., & Tsutsui, M. (2009). Network DEA: A slacks-based measure approach. European Journal of Operational Research, 197(1), 243–252.

    Article  Google Scholar 

  • Top, M., Konca, M., & Sapaz, B. (2020). Technical efficiency of healthcare systems in African countries: An application based on data envelopment analysis. Health Policy and Technology, 9(1), 62–68.

    Article  Google Scholar 

  • Turshen, M., & Sen, A. (2001). Development as freedom. Journal of Public Health Policy, 22(4), 484–486. https://doi.org/10.2307/3343168

    Article  Google Scholar 

  • UNDP. (2022). Human Development Report 2021/2022. Uncertain times, unsettled lives: Shaping our future in a transforming world. https://hdr.undp.org/system/files/documents/global-report-document/hdr2021-22pdf_1.pdf

  • Van Puyenbroeck, T. (2018). On the output orientation of the benefit-of-the-doubt-model. Social Indicators Research, 139(2), 415–431.

    Article  Google Scholar 

  • Van Puyenbroeck, T., & Rogge, N. (2020). Comparing regional human development using global frontier difference indices. Socio-Economic Planning Sciences, 70, 100663.

    Article  Google Scholar 

  • World Bank. (2020). Monitoring global poverty. In Poverty and shared prosperity 2020: Reversals of forsstune (pp. 27–80). The World Bank. https://doi.org/10.1596/978-1-4648-1602-4_ch1

  • Yue, S., Shen, Y., & Yuan, J. (2019). Sustainable total factor productivity growth for 55 states: An application of the new Malmquist index considering ecological footprint and human development index. Resources, Conservation and Recycling, 146, 475–483.

    Article  Google Scholar 

  • Zhang, R., Lin, X., & Li, A. (2023). Understanding the role of the government in promoting various sustainability sub-systems: an analysis based on new parallel-series network data envelopment analysis models. Journal of Cleaner Production, 398, 136593.

    Article  Google Scholar 

  • Zhang, R., Wei, Q., Li, A., & Ren, L. (2022a). Measuring efficiency and technology inequality of China’s electricity generation and transmission system: A new approach of network Data Envelopment Analysis prospect cross-efficiency models. Energy, 246, 123274.

    Article  Google Scholar 

  • Zhou, L., Zhang, R., & Li, A. (2022b). New concepts for bootstrap-based cross-efficiency and relative weight analysis and an application to China’s governance-finance-innovation-sustainability system. Journal of Cleaner Production, 379, 134549.

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the anonymous referees for their valuable suggestions. This paper is supported by Taishan Scholars, the National Natural Foundation of China (Grant No. 71873078&71603148&71974085), Young Scholars of Ideology and Culture Propaganda of Publicity Department, CCCPC, Humanities and Social Sciences Research Major Project of Shandong University (Grant No. 21RWZD16) and SDU Outstanding Scholar.

Author information

Authors and Affiliations

  1. The Center for Economic Research, Shandong School of Development, Shandong University, Jinan, 250100, People’s Republic of China

    Shanshan Chen, Aijun Li & Liqi Hu

  2. Institute of Blue and Green Development, Shandong University, Weihai, 264209, People’s Republic of China

    Morié Guy-Roland N’Drin

  3. Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, 01 BP 1303, Abidjan 01, Côte d’Ivoire

    Morié Guy-Roland N’Drin

Authors
  1. Shanshan Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aijun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Liqi Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Morié Guy-Roland N’Drin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Morié Guy-Roland N’Drin.

Ethics declarations

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (XLS 72 kb)

Appendix

Appendix

See Tables 10, 11 and 12.

Table 10 Keywords used in literature review research
Full size table
Table 11 Group-based decomposition of overall efficiency Theil coefficient
Full size table
Table 12 List of countries based on income groups. Source: World Bank (2022) available from https://blogs.worldbank.org/opendata/new-world-bank-country-classifications-income-level-2021-2022
Full size table

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, S., Li, A., Hu, L. et al. Understanding the Efficiency in Generating Human Development in Sub-Saharan Africa: A Two-Stage Network DEA Approach. Soc Indic Res 171, 295–324 (2024). https://doi.org/10.1007/s11205-023-03255-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11205-023-03255-x

Keywords

Search

Navigation