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Efficiency, Productivity and Returns to Scale Economies in the Non-Life Insurance Market in South Africa

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Abstract

This paper undertakes a comprehensive analysis of efficiency, productivity and returns to scale economies in the non-life insurance market in South Africa from 2007 to 2012. The data envelopment analysis technique is employed to estimate efficiency and returns to scale while productivity growth is analysed with the Malmquist index. Truncated bootstrapped regression and logistic regression techniques are used to identify the determinants of efficiency and the probability of operating under constant returns to scale. The results indicate that non-life insurers operate with about 50 per cent inefficiencies, while about 20 per cent of insurers operate at an optimal scale. We also observe productivity improvements attributable to technological changes. The results of the regression analysis reveal a non-linear effect of size on efficiency and constant returns to scale. Product line diversification, reinsurance and leverage also have a significant relationship with efficiency and constant returns to scale. A major contribution of this paper is the analysis of efficiency convergence using the growth convergence theory. Implications for management and industry regulation are drawn from the findings.

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Notes

  1. Sarker and Sarker (2000).

  2. Freeman and Kunreuther (2002).

  3. Sinha (2004).

  4.  4 Swiss Re (2011).

  5.  5 See Eling and Luhnen (2010b) for a comprehensive review of the insurance efficiency literature.

  6.  6 Eling and Luhnen (2010b).

  7.  7 Both were working papers. Since then, Ansah-Adu et al. (2012) have examined the cost-efficiency of Ghanaian insurance companies.

  8.  8 Cummins and Xie (2013) note that few studies have specifically set out to examine economies of scale characteristics in insurance markets.

  9.  9 Fecher et al. (1993).

  10. Cummins et al. (1996).

  11. Noulas et al. (2001).

  12. Worthington and Hurley (2002).

  13. Yao et al. (2007).

  14. Luhnen (2009).

  15. Brazil, Russia, India and China.

  16. Huang and Eling (2013).

  17. Simar and Wilson (2007).

  18. Cummins and Xie (2013).

  19. Barro and Sala-i-Martin (1991).

  20. Weill (2009).

  21. Casu and Girardone (2010).

  22. Zhang and Matthews (2012).

  23. Eling and Luhnen (2010a).

  24. SAM seeks to establish a framework that protects both policyholders and insurers and enhance the stability of the insurance industry.

  25. Hanweck and Hogan (1996) and Cummins and Xie (2013) are among the very few studies that have specifically focused on returns to scale economies in insurance markets.

  26. Property, transportation, motor, accident and health, guarantee, liability, engineering and miscellaneous.

  27. Charnes et al. (1978). This gives the estimates of technical efficiency.

  28. Banker et al. (1984). This gives the estimates of pure technical efficiency.

  29. Refer to Cummins and Weiss (2000) for a detailed discussion on the merits and demerits of non-parametric efficiency estimations.

  30. Farrel (1957).

  31. Charnes et al. (1978).

  32. Aly et al. (1990).

  33. Simar and Wilson (1998, 2000).

  34. Simar and Wilson (1998).

  35. Wilson (2008).

  36. Mahlberg and Url (2003).

  37. Fischer (1922).

  38. Tornqvist (1936).

  39. Färe et al. (1994).

  40. Grifell-Tatjé and Lovell (1995).

  41. Coelli et al. (1999).

  42. Noulas et al. (2001); Worthington and Hurley (2002); Mahlberg and Url (2003); Cummins and Rubio-Misas (2006); Yao et al. (2007); Barros et al. (2010).

  43. Arrow (1962).

  44. Jovanovic (1982).

  45. Barron et al. (1994).

  46. Jensen (1986).

  47. Jensen and Meckling (1976).

  48. The HHI is computed as the square of the sum of the market share of premium from each business line to gross premiums for all business lines for each insurer.

  49. Simar and Wilson (2011).

  50. Refer to Simar and Wilson (2007) for a detailed procedure of the truncated bootstrapped regression.

  51. Refer to Simar and Wilson (2007) for a detailed description of the seven-step bootstrapping procedure.

  52. Sala-i-Martin (1996).

  53. Arellano and Bover (1995).

  54. This period is partly influenced by data availability.

  55. They are insurers in run-off who are winding up their businesses and no longer receiving any more premiums, but continue paying out for their existing policies.

  56. Cummins and Weiss (2000) argue that the importance of debt and equity capital are important inputs for which adequate cost measures have to be found.

  57. Cummins and Rubio-Misas (2006), we do not include deposits from reinsurers due data limitations.

  58. Rai (1996).

  59. Diacon et al. (2002).

  60. Cooper et al. (2000).

  61. Kader et al. (2010).

  62. Yuengert (1993).

  63. Leverty and Grace (2010).

  64. Diacon (2001).

  65. Klumpes (2007).

  66. For scale efficiency, medium and big insurers have higher efficiency scores compared with small and large insurers.

  67. This also indicates that 44.3 per cent of insurance premiums generated are ceded to reinsurers. This proxies for risk diversification.

  68. Kennedy (2008).

  69. The convex relationship arises because the quadratic term of size is positive. The relationship is concave if the linear term is positive and the quadratic term is negative as found in Model 2 with TE.

  70. Shui (2009).

  71. Choi (2010).

  72. Cummins and Nini (2002).

  73. The results presented are marginal effects of the independent variables which measure the probability of an insurer operating under a returns to scale category arising from deviations in the sample mean of an independent variable.

  74. The assumptions of no second-order autocorrelation and over-identifying restriction were met in all the estimations.

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Acknowledgements

We thank two anonymous reviewers and the guest editor for their helpful comments. We also acknowledge the assistance of the Insurance department of the FSB in providing the data for this study and Africagrowth Institute for sponsoring the research. All normal caveats apply.

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  1. Graduate School of Business, University of Cape Town, Private Bag X3, Rondebosch, Cape Town, 7701, South Africa

    Abdul Latif Alhassan & Nicholas Biekpe

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Alhassan, A., Biekpe, N. Efficiency, Productivity and Returns to Scale Economies in the Non-Life Insurance Market in South Africa. Geneva Pap Risk Insur Issues Pract 40, 493–515 (2015). https://doi.org/10.1057/gpp.2014.37

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