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Efficiency Determinants and Capacity Issues in Angolan Insurance Companies

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  • Carlos Pestana Barros
  • Silvestre Dumbo
  • Peter Wanke

Abstract

This paper describes a variety of approaches used to assess the efficiency of a sample of major insurance companies in Angola between 2003 and 2012. Starting out with the bootstrapping technique, several data envelopment analysis (DEA) estimates were generated, allowing the use of confidence intervals and bias correction in central estimates to test for significant differences in efficiency levels and input-decreasing/output-increasing potentials. Previous studies have focused on the measurement and explanation of the factors affecting the performance rather than the prediction. The use of neural networks combined with DEA results as part of an attempt to produce a model for insurance companies’ performance with effective predictive ability is investigated. The findings indicate that older insurance companies with Portuguese origin tend to be more efficient. Results also suggest that opportunities for accommodating future demand appear to be scarce.

Suggested Citation

  • Carlos Pestana Barros & Silvestre Dumbo & Peter Wanke, 2014. "Efficiency Determinants and Capacity Issues in Angolan Insurance Companies," South African Journal of Economics, Economic Society of South Africa, vol. 82(3), pages 455-467, September.
  • Handle: RePEc:bla:sajeco:v:82:y:2014:i:3:p:455-467
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    File URL: http://hdl.handle.net/10.1111/saje.12056
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    References listed on IDEAS

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    Cited by:

    1. Francesco Longo & Luigi Siciliani & Andrew Street, 2019. "Are cost differences between specialist and general hospitals compensated by the prospective payment system?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(1), pages 7-26, February.
    2. Yauheniya Varabyova & Carl Rudolf Blankart & Aleksandra Torbica & Jonas Schreyögg, 2017. "Comparing the Efficiency of Hospitals in Italy and Germany: Nonparametric Conditional Approach Based on Partial Frontier," Health Care Management Science, Springer, vol. 20(3), pages 379-394, September.
    3. Wanke, Peter & Barros, Carlos Pestana, 2016. "Efficiency drivers in Brazilian insurance: A two-stage DEA meta frontier-data mining approach," Economic Modelling, Elsevier, vol. 53(C), pages 8-22.
    4. Laura Botega & Mônica Viegas Andrade & Gilvan Ramalho Guedes, 2020. "Brazilian hospitals’ performance: an assessment of the unified health system (SUS)," Health Care Management Science, Springer, vol. 23(3), pages 443-452, September.
    5. Carlos Pestana Barros & Zorro Mendes, 2016. "Assessing the competition in Angola’s banking industry," Applied Economics, Taylor & Francis Journals, vol. 48(30), pages 2785-2791, June.
    6. Sepideh Kaffash & Marianna Marra, 2017. "Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds," Annals of Operations Research, Springer, vol. 253(1), pages 307-344, June.
    7. Singh, Sanjeet, 2016. "Evaluation of world’s largest social welfare scheme: An assessment using non-parametric approach," Evaluation and Program Planning, Elsevier, vol. 57(C), pages 16-29.
    8. Kwaku Ohene-Asare & Jones Kofi Anyimadu Asare & Charles Turkson, 2019. "Dynamic cost productivity and economies of scale of Ghanaian insurers," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 44(1), pages 148-177, January.
    9. Irinela Constantina Badea, 2017. "Literature Review On The Determinants Of Insurers’ Financial Performance," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 206-212, December.
    10. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.

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