Are South African Medical Schemes Efficient? A Longitudinal Analysis

Ndlovu, Thabang (2022): Are South African Medical Schemes Efficient? A Longitudinal Analysis.

Abstract

This study assessed the efficiencies of South African private medical schemes for the period 2011 to 2017. There are two types of medical schemes in the private medical scheme sector. First, there are open medical schemes which are legally required to accept any individual who would want to join. Second, there are restricted medical schemes which are attached to a specific group such as an employer, industry or union and these schemes are open only to the members of the association. The study estimated efficiency scores using first, the Data Envelope Analysis (DEA) technique which is a non-parametric procedure that uses linear programming in order to formulate efficient frontiers which envelop all input-output combinations of firms within a sample. Second, the study employed the Stochastic Frontier Analysis (SFA) technique which is an econometric technique which postulates a functional relationship amongst outputs and inputs and thus employs statistical procedures in order to determine parameters for the function. The empirical findings of both the DEA and SFA approaches suggest that open medical schemes tend to be more efficient than restricted medical schemes in terms of technical, scale and pure technical efficiency over the sample period.

• Item Type: MPRA Paper
• Language: English
• Keywords: Healthcare Insurance, DEA, SFA, Efficiency, Technical Efficiency, Pure Technical Efficiency, Scale Efficiency, South Africa
• Subjects: L - Industrial Organization > L0 - General > L00 - General; L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L11 - Production, Pricing, and Market Structure ; Size Distribution of Firms; L - Industrial Organization > L2 - Firm Objectives, Organization, and Behavior > L22 - Firm Organization and Market Structure

References

AKHTAR, M. H. (2018). Performance analysis of takaful and conventional insurance companies in Saudi Arabia. Benchmarking: An International Journal, 25(2), 677-695. BAI-QING, SUN, XIA YI-XING, and CAO WEN-TAO. “The Efficiency Evaluation of Property Insurance Companies based on Two-Stage Correlative DEA Models”. 2012 International Conference on Management Science & Engineering 19th Annual Conference Proceedings: 699-712. BARROS, C. P., BARROSO, N. and BORGES, M. R. (2005). Evaluating the efficiency and productivity of insurance companies with a malmquist index: A case study for Portugal. The Geneva Papers on Risk and Insurance – Issues and Practice, 30(2), 244-267. BARROS, C. P. and DUMBO, S. W. P. (2014). Efficiency determinants and capacity issues in Angolan insurance companies. South African Journal of Economics, 82(3), 455-467. BARROS, C. P., NEKTARIOS, M. and ASSAF, A. (2010). Efficiency in the Greek insurance industry. European Journal of Operational Research, 205(2), 431-436. BARROS, C. P. and WANKE, P. (2017). Technology gaps and capacity issues in African insurance companies: Selected country evidence. Journal of International Development, 29(1), 117-133. BATTESE, G. and COELLI, T. (1995). A model for technical ineffiicency effects in a stochastic frontier production function for panel data. Empirical Economics, 20(2), 325-332. BHISHMA RAO, G. and VENKATESWARLU, R. (2014). Efficiency of Indian private non-life insurance firms using stochastic frontier analysis. Journal of Economics and Finance, 4(1), 42-46. BIENER, C. and ELING, M. (2012). Organization and efficiency in the international insurance industry: A cross-frontier analysis. European Journal of Operational Research, 221(2), 454-468. BIENER, C. and ELING, M. (2011). The performance of microinsurance programs: A data envelopment analysis. The Journal of Risk Insurance, 78(1), 83-115. BIENER, C., ELING, M. and WIRFS, J. H. (2016). The determinants of efficiency and productivity in the Swiss insurance industry. European Journal of Operational Research, 248(2), 703-714. BORU, T. and KUHIL, A. M. (2018). The structure conduct performance model and competing hypothesis – A review of literature. Research Journal of Finance and Accounting, 9(1), 76-89. BROCKETT, P. L., CHANG, R. E., ROUSSEAU, J. J., SEMPLE, J. H. and YANG, C. (2004). A comparison of HMO efficiencies as a function of provider autonomy. The Journal of Risk and Insurance, 71(1), 1-19. CHARNES, A., COPPER, W. and RHODES, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operations Research, 2(6), 429-444. CHEN, M. S. and CHANG, P. L. (2010). Distribution channel strategy and efficiency performance of the life insurance industry in Taiwan. Journal of Financial Services Marketing, 15(1), 62-75. COELLI, T., PERELMAN, S. and ROMANO, E. (1999). Accounting for environmental influences in stochastic frontier models: With application to international airlines. Journal of Productivity Analysis, 3(11), 251-273. CUMMINS, D. J., WEISS, M. A., XIE, X. and ZI, H. (2010). Economies of scope in financial services: A DEA efficiency analysis of the US insurance industry. Journal of Banking & Finance, 34(7), 1525-1539. CUMMINS, J. D. and XIE, X. (2013). Efficiency, productivity and scale economies in the US property-liability insurance industry. Journal of Productivity Analysis, 39(2), 141-164. DEMSETZ, H. (1973). Industry structure, market rivary and public policy. Journal of Lae and Economics, 16(1), 1-9. DEPOTIS, D. K., KORONAKOS, G. and SOTIROS, D. (2016). Composition versus decomposition in two-stage network DEA: A reverse approach. Journal of Productivity Analysis, 45(1), 71-87. DIACON, K. and O'BRIEN, S. C. (2002). Size and efficiency in european long-term insurance companies: An international comparison. The Geneva Papers on Risk and Insurance, 27(3), 444-466. DYSON, R. and SHALE, E. A. (2010). Data envelopment analysis, operational research and uncertainty. The Journal of the Operational Research Society , 61(1), 25-34. FARRELL, M. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A(General), 120(3), 253-290. GREENE, W. (2005). Reconsidering heterogeneity in panel data estimators fo the stochastic frontier model. Journal of Econometrics, 126(2), 269-303. HAUSMAN, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251-1271. HICKS, J. (1935). Annual survey of economic theory: the theory of monopoly. Econometrica, 3(1), 1-20. KAFFASH, S., AZIZI, R., HUANG, Y. and ZHU, J. (2020). A survey of data envelopment analysis applications in the insurance industry 1993–2018. European Journal of Operational Research, 284(3), 801-813. KAO, C. and HWANG, S.-N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operations Research, 185(1), 418-429. KASMAN, A. and TURGUTLU, E. (2007, January). A comparison of chance-constrained DEA and stochastic frontier analysis: An application to the Turkish life insurance industry. In 8 Congreso Turco de Econometr Ekonomertía y Estadística, 1-8. LEVERTY, T., LIN, Y. and ZHOU, H. (2004). Firm performance in the Chinese insurance industry. [Online] Available: http://rmictr.gsu.edu/Papers/WP04_10.pdf. LUHNEN, M. (2009). Determinants of efficiency and productivity in German property-liability insurance: Evidence for 1995–2006. Geneva Papers on Risk and Insurance: Issues and Practice., 34(3), 483-505. OGLOBLIN, C. (2011). Healthcare efficiency across countries: A Stochastic frontier analysis. Applied Econometics and International Development, 11(1), 5-14. SHEPHARD, R. W. (1953). Cost and production functions. Princeton, NJ: Princeton University Press. SIMAR, L. and WILSON, P. W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136(1), 31-64. SMIRLOCK, M. (1985). Evidence on the (non) relationship between concentration and profitbability in banking. Journal of Money, Credit and Banking, 1(17), 69-83. WATKINS, K. B., HRISTOVSKA, T., MAZZANTI, R., WILSON, Jr., C. E. and SCHMIDT, L. (2014). Measurement of technical, allocative, economic, and scale efficienct of rice production in Arkansas using data envelopment analysis. Journal of Agricultural and Applied Economics, 46(1), 89-106. WORLD HEALTH ORGANIZATION (WHO). (2007), Everybody's Business: Strengthening Health Systems to Improve Health Outcomes – Who's Framework for Action. [Online] Available: https://www.who.int/healthsystems/strategy/everybodys_business.pdf