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Supervisory power and insurer financial stability: the role of institutional quality

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Abstract

This is the first study to investigate whether country institutional quality influences the impact of supervisory power on insurer soundness. It tests the hypothesis arguing that institutional quality enhances the implementation capacity of supervisors versus the one that maintains that institutional quality mitigates the impact of supervisory power on insurer soundness, particularly when this effect is negative. An analysis is carried out on firms operating in the insurance markets of 12 Muslim-populous countries over the eight-year sample period 2009–2016. As a proxy of insurers’ financial stability, we use the Z-score and conduct the study by employing the two-step system generalised method of moments. We find a negative impact of supervisory power on insurer soundness—exercised by increasing portfolio risk—that is mitigated by national institutional quality, in particular by government effectiveness, regulatory quality and control of corruption. The findings emphasise the view that national institutional quality avoids private use of supervision.

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Notes

  1. In this study, national institutional quality refers to country governance, which consists of ‘traditions and institutions by which authority in a country is exercised. This includes the process by which governments are selected, monitored and replaced; the capacity of the government to effectively formulate and implement sound policies; and the respect of citizens and the state for the institutions that govern economy and social interactions among them’ (taken from the Worldwide Governance Indicators, available at https://info.worldbank.org/governance/wgi/).

  2. The regulatory response to the global financial crisis pushed towards the adoption of transnational principles and rules in the field of insurance by encouraging the convergence of national regulation to a common regulatory framework. However, important national differences in terms of insurance regulation and supervision continue to exist. See e.g. Marano (2021) and Rego and Sixas (2021) for analyses on European jurisdictions, and Biener et al. (2014) and Noussia (2021) for analyses on non-European jurisdictions.

  3. Countries included in the analysis are selected for the fact that they are Muslim-majority but also that the information needed to construct the supervisory power index is available and that there are enough observations to conduct a reliable analysis.

  4. The low level of insurance penetration shown by most analysed countries is due to their low level of life insurance penetration, which is explained by cultural limitations and by unequal income distribution (see Swiss Re 2015).

  5. Nevertheless, there is an important strand of literature on the effect of regulation and supervision on other economic aspects of the insurance industry. For instance, Grace and Phillips (2008), after controlling for the professional background of insurance commissioners, found evidence that automobile insurance prices in regulated U.S. states can differ significantly from what one would otherwise expect to see in a similarly situated state where competition is the primary determinant of prices. Gaganis et al. (2016) showed that supervisory power constrains income smoothing in a sample of insurers operating in 87 countries over the period 2000–2009. Gaganis et al. (2020) found that overall supervisory power does not matter in insurance development for an unbalanced dataset of 44 countries over the 2000–2008 period.

  6. There are several studies supporting the general argument that institutional quality enhances the efficient functioning of insurance markets. For instance, Fields et al. (2012) found that a greater operating setting decreased risk-taking in a cross-country analysis of listed insurers. Lee and Lin (2016) provided evidence that insurers showed better performance in countries with a stable political institution. Cummins and Rubio-Misas (2021) showed that national institutional quality enhanced the cost performance and integration of European life insurance markets.

  7. The sample includes Takaful operators (they work with the conformity of Islamic principles and participants in each Takaful risk pool share risks (see e.g. Archer et al. 2009; Alokla et al. 2022)) and conventional insurers. Nevertheless, not all the countries in the sample have this dual system. This is the case for Saudi Arabia, whose legislation allows only Islamic insurance business. Furthermore, some countries of the sample have a separate act governing Takaful operations (for instance, law 87.18 on Takaful insurance in Morocco or Oman’s Takaful insurance legislation approved by Royal Decree 11/2016). However, in other countries, legislation on Takaful operators appears along with legislation on conventional insurers. This is the case of insurance regulatory law no. 12 of 2021 in Jordan.

  8. We notice that the impact of supervisory power on insurers’ soundness has not been previously studied in most countries of the present analysis since only five (Bahrain, Jordan, Pakistan, Saudi Arabia and Turkey) out of the 12 analysed countries were studied in the paper by Pasiouras and Gaganis (2013).

  9. Capital adequacy is viewed as a key indicator for assessing the financial stability of insurers. Nevertheless, both quantitative and qualitative indicators are required to provide a comprehensive analysis of an insurer’s financial soundness. There are three broad categories of quantitative information: financial soundness indicators, stress test/risk model information and additional (most off-balance sheet) information. With regard to financial soundness indicators, the International Monetary Fund has suggested a number of indicators that adjoins the ‘Actuarial and Reinsurance issues’ to the CAMELS methodology commonly utilised for banks. The elected indicators are shown within the CARAMELS framework and include capital adequacy, asset quality, reinsurance and actuarial issues, management soundness, earnings and profitability, liquidity and sensitivity to market risk (see Das et al. 2003). This kind of analysis exceeds the aim of this paper but offers areas for future research.

  10. To the best of our knowledge, Gaganis et al. (2020) is the only cross-country study that reports a supervisory power index in the insurance industry per country. However, they only report values for three countries (Jordan, Pakistan and Turkey) out of the 12 analysed in this paper. Although our values are not directly comparable with the ones in Gaganis et al. (2020) because, among other reasons, they consider a different number of actions, we may conclude that they are in line with the ones reported for these three countries.

  11. Regarding interaction terms, we follow previous works (e.g. Agoraki et al. 2011) and address multicollinearity concerns by ‘centering’ the variables. We do this by subtracting the mean from each observation.

  12. The variable for 2009 is omitted to prevent singularity.

  13. This discussion is also valid for the model fitness results presented in Tables 4, 5 and 6.

  14. We conducted additional regressions to provide robustness checks for this relationship. In this regard, the fact that the coefficient of the supervisory power index is negative and statistically significant holds in regressions where a) we omit the interaction term; b) we omit the interaction term and the institutional quality indicator; c) we include insurance density (calculated as premiums per inhabitant) as a control variable of market development in the analysis. Results from these regressions are not reported to save space but they are available upon request.

  15. As the supervisory power index is a time-invariant variable, we are not able to consider its lags in two-step system GMM. Nevertheless, we formally address the issue of potential endogeneity of supervisory power by employing panel data two-stage instrumental variable regressions. In doing so, we select instrumental variables that have previously been used for supervisory power. More precisely, we follow Barth et al. (2004) and—as instruments for the supervisory power variable—use a country latitudinal distance from the equator and a country fractionalisation measure of ethnicity (see Alesina et al. 2003). The results (available upon request) confirm that the coefficient of the supervisory power index is negative and statistically significant in the second-stage instrumental variable regression, pointing towards a negative causal effect of supervisory power on insurers’ financial stability.

  16. We do not show separate analyses on the following aspects (variables) of institutional quality: voice and accountability, political stability and absence of violence and rule of law. Their coefficients are not statistically significant.

  17. Our data (see Table 1) in general confirm this point. We observe that Bahrain, Oman, Saudi Arabia and the UAE (the countries of our sample belonging to the high-income group) spent on average 540.6, 223.2, 281.3 and 1,291.3 thousand USD per inhabitant, respectively, in 2020. However, Indonesia, Jordan, Malaysia, Morocco, Nigeria, Pakistan, Tunisia and Turkey (the countries of our sample belonging to the non-high-income group) spend on average 75, 81.6, 568.4, 137.6, 5.9, 9.5, 76 and 128 thousand USD per inhabitant, respectively.

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Acknowledgements

I would like to thank anonymous reviewers for valuable comments and suggestions. The author gratefully acknowledges financial support from the Spanish Ministry of Science and Innovation (Project PID2021-127736NB-I00).

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Funding was provided by Ministerio de Ciencia e Innovación (PID2021-127736NB-I00).

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  1. Finance and Accounting Department, Campus El Ejido, Universidad de Málaga, 29071, Malaga, Spain

    María Rubio-Misas

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Appendix

Appendix

See Tables 7 and 8.

Table 7 Supervisory power index and observation distribution
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Table 8 Definition of key explanatory variables
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Rubio-Misas, M. Supervisory power and insurer financial stability: the role of institutional quality. Geneva Pap Risk Insur Issues Pract (2023). https://doi.org/10.1057/s41288-023-00309-6

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