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Risk-taking and systemic banking crisis in Africa: do regulatory policy framework provide new insight in threshold models?

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Abstract

This study examines how regulatory policy impacts the complex relationship between bank risk-taking and the predicted probability of a systemic banking crisis in 54 African countries for the period, 2004–2020. The empirical evidence is based on the instrumental variable probit panel regressions. The study found a non-linear U-shaped relationship between bank risk-taking and the probability of a systemic banking crisis. The study shows that a systemic banking crisis is likely to occur when the monotonically increasing levels of risk-taking of banks exceed thresholds of 0.015 and 0.79. The study also found that the thresholds of risk-taking in countries with stringent regulatory policies are relatively greater in countries operating in low regulatory policy regimes. In light of the conditional marginal effects, the study provides evidence to support that regulatory policy amplifies and augments the negative linear impact of risk-taking on the predicted probability of a systemic banking crisis. This is relevant to policymakers because the established conditional effects imply that regulatory policy is a sufficient complementary condition for shaping the negative effect of bank risk-taking and systemic banking crises.

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Data availability

The datasets used and/or analyzed during the current study are available (with the corresponding author) upon reasonable request.

Notes

  1. For instance, it is shown that out of 101 worldwide banking crisis, 60 occurred in rich countries, 20 happened in developing countries, while 21 of banking crises were reported in Africa. This indicates that compared to developing nations, the frequency of banking crises is rising in Africa (see Appendix 2).

  2. See Appendix 2.

  3. In building the instrumental variable, we consider changes in risk-taking that took place in the subsequent 6 to 10 years before an election event and the occurrence of a banking crisis (i.e., the lead values of changes in risk-taking is constructed at least six years before an election year and a crisis year). This allows us to limit the direct effect of risk-taking behavior and subsequent crises. The instrumental variable is arguably exogenous; it deals with reverse causality and it satisfies the relevance and exclusion restriction assumptions (Lousdal, 2018)—because the event that corresponds to possible structural changes in risk-taking occurs after a bank provides financing.

  4. See Appendix 3.

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Acknowledgements

The authors are grateful to participants of the University of Ghana Business School PhD seminar series for their criticism and comments which helped improve the quality of this paper. We are grateful to the Carnegie Corporation of New York (CCNY) BANGA Project to the University of Ghana and the University of Ghana Business School for funding this project. All errors and omissions remain ours.

Funding

This work was supported by the Carnegie Corporation of New York (CCNY) BANGA Project to the University of Ghana and University of Ghana Business School.

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Authors and Affiliations

  1. Department of Finance, University of Ghana Business School, P.O Box LG 78, Legon-Accra, Ghana

    Daniel Ofori-Sasu, Emmanuel Sarpong-Kumankoma, Saint Kuttu, Elikplimi Komla Agbloyor & Joshua Yindenaba Abor

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  1. Daniel Ofori-Sasu
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Contributions

Daniel Ofori-Sasu conceptualized the idea and wrote the paper. Emmanuel Sarpong-Kumankoma, Saint Kuttu, Elikplimi Komla Agbloyor, and Joshua Yindenaba Abor provided supervision, guidance, and direction for this paper. All authors have read and approved the final manuscript.

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Appendices

Appendix 1

See Tables 

Table 1 Descriptive statistics
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Table 2 Pairwise correlations
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Table 3 Non-linear relationship between bank risk-taking and systemic banking crisis: instrumental variable probit regression
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Table 4 Threshold impacts of risk-taking on systemic banking crisis across different regulatory environment
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Table 5 Interactive effect of bank risk-taking and regulatory policies on systemic banking crisis
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Appendix 2

See Figs. 

Fig. 1
figure 1

Banking crisis. Note Data were obtained from the Global Financial Development Database and Laeven and Valencia (2018) database over the period, 2006–2018

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Fig. 2
figure 2

Monetary policy and macro-prudential policy. Authors’ construction and data analysis based on data from the World Bank, IMF, and Alam et al. (2019)

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Fig. 3
figure 3

Micro-prudential regulations: Regulatory capital and capital buffer. Authors’ construction and data analysis based on data from the World Bank (WDI), IMF, Alam et al. (2019), and Garriga (2020) databases

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3.

Appendix 3

See Table 

Table 6 Description of variables
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6.

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Ofori-Sasu, D., Sarpong-Kumankoma, E., Kuttu, S. et al. Risk-taking and systemic banking crisis in Africa: do regulatory policy framework provide new insight in threshold models?. Risk Manag 26, 10 (2024). https://doi.org/10.1057/s41283-023-00137-x

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