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Risk allocation in energy infrastructure PPPs projects in selected African countries: does institutional quality, PPPs experience and income level make a difference?

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Abstract

This study aims to investigate the extent to which institutional quality influences risk allocation in energy infrastructure public–private partnerships (PPPs) projects in Africa. The analysis covers 396 energy infrastructure PPP projects in 35 African countries over the period 1990–2019 based on the World Bank Private Participation in Infrastructure database and the Worldwide Governance Indicators. Risk is measured through contract classification and relates to the increasing participation of the private sector in more structured forms of PPPs, that is, the private sector supports higher risks as it participates in more structured forms of PPPs. For that purpose, four types of PPPs contracts are considered: management and leases, brownfields, greenfields, and divestitures. The results show that control of corruption, sound government effectiveness, political stability and absence of violence, and strong rule of law significantly and positively influence the risk allocation between the private and public sectors toward the private entity. Conversely, regulatory quality and voice and accountability do not significantly affect risk allocation between the two parties. The estimated effects are much stronger in countries with greater experience in energy infrastructure PPPs projects, suggesting that in addition to institutional quality, private investors are more likely to be interested in taking more risks in energy PPPs projects in experienced countries. While distinguishing between African low-income and middle-income countries, the findings suggest that with the same level of institutional quality, there is a high probability that more risks are allocated to the private sector in middle-income countries compared to low-income countries. Policy recommendations are presented and discussed accordingly.

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Fig. 1

Source: Authors using the 2019 World Bank Private Participation in Infrastructure (PPI) database

Fig. 2

Source: Authors using the 2019 World Bank PPI database

Fig. 3

Source: Authors using the 2019 World Bank PPI database

Fig. 4

Source: Authors using the 2019 World Bank PPI database

Fig. 5

Source: Authors using the 2019 World Bank PPI database

Fig. 6

Source: Authors using the 2019 World Bank PPI database

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Notes

  1. Africa’s pulse, April 2019.

  2. 2018 Infrastructure Financing Trends Report (Infrastructure Consortium for Africa 2018).

  3. Private Participation in Infrastructure (PPI) database, World Bank.

  4. https://ppi.worldbank.org/en/methodology/glossary.

  5. https://ppi.worldbank.org/en/methodology/glossary.

  6. https://ppi.worldbank.org/en/methodology/glossary.

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Acknowledgements

We are grateful to Rafiou Raphaël Bétila (ENSEA Abidjan) who provided constructive criticism of the paper. Special thanks are extended to Tomoki Fukunaga (African Development Bank) for providing useful feedbacks from his review of an initial draft of the manuscript. We also thank anonymous referees for their helpful comments and suggestions that contributed to significantly enhancing the final version of the paper. The usual disclaimer applies and any errors remain the authors’ sole responsibility.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Correspondence to Jeffrey Kouton.

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Appendices

Appendix 1: Results of the estimations on the sample of 20 countries with greater PPP experience

See Tables 8, 9, 10.

Table 8 Baseline results of the estimations on the sample of 20 countries with greater PPP experience
Table 9 Results of the estimations on the sample of 20 countries with greater PPP experience (with robust standard errors estimates)
Table 10 Results of the estimations on the sample of 20 countries with greater PPP experience (with Jackknife replications)

Appendix 2: Results of the estimations for African low-income countries

See Tables 11, 12, 13.

Table 11 Baseline results of the estimations for African low−income countries
Table 12 Results of the estimations for African low−income countries (with robust standard errors estimates)
Table 13 Results of the estimations for African low-income countries (with Jackknife replications)

Appendix 3: Results of the estimations for African middle-income countries

See Tables 14, 15, 16.

Table 14 Baseline results of the estimations for African middle-income countries
Table 15 Results of the estimations for African middle−income countries (with robust standard errors estimates)
Table 16 Results of the estimations for African middle−income countries (with Jackknife replications)

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Kouton, J., Sanogo, W. & Djomgoue, N. Risk allocation in energy infrastructure PPPs projects in selected African countries: does institutional quality, PPPs experience and income level make a difference?. Econ Change Restruct 56, 537–580 (2023). https://doi.org/10.1007/s10644-022-09433-0

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