Improving the accuracy of efficiency estimation in insurance companies using the three-stage data envelopment model Ananalytical study using the bootstrap method
Keywords:
bootstrap method, Sudanese insurance companies, Three-Stage DEA model, Stochastic Frontier Analysis (SFA)
Abstract
This study aims to evaluate the operational efficiency of Sudanese insurance companies using the Three-Stage Data Envelopment Analysis (DEA) model supported by the Bootstrap technique, to provide more accurate estimates by eliminating the effects of environmental and random factors, based on data from 2012 to 2020. The first stage results showed that Al baraka company maintained full efficiency over several years, while other companies recorded varying efficiency levels. Notably, Islamic Insurance and The United Insurance consistently exhibited low efficiency scores, indicating persistent operational weaknesses. Additionally, Middle East Insurance demonstrated relative inefficiency even after environmental adjustments, suggesting internal challenges affecting its performance. Applying the bootstrap method led to a slight decrease in efficiency scores due to bias correction. The second stage, using Stochastic Frontier Analysis (SFA), revealed an inverse relationship between efficiency and inefficiency, confirming Al baraka’s strong internal performance and highlighting the operational difficulties of the aforementioned companies. In the third stage, after adjusting for external factors, most companies showed improved efficiency, indicating that environmental and random factors negatively impacted observed performance. Bootstrap results further enhanced estimation accuracy and reduced variance, with convergence of efficiency values across stages. The study validates its hypotheses regarding the superiority of the Three-Stage DEA model and the Bootstrap approach for efficiency assessment. It recommends integrating environmental factors into efficiency models, adopting bootstrap techniques to reduce bias, reviewing internal policies of underperforming companies, conducting regular multi-stage efficiency assessments by regulators, and encouraging future research to include broader environmental and economic variables for more comprehensive evaluations.References
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- Alhassan, A. L., & Biekpe, N. (2016). Competition and efficiency in the non-life insurance market in South Africa. Research in International Business and Finance, 38, 69–83.
- Batal, H., et al. (2017). Al-Kafa’a Al-Hajmiya wa Ta’theeruha ‘ala Al-Ada’ Al-Mali [Scale efficiency and its effect on financial performance]. Majallat Al-Dirasat Al-Idariya, 15(2), 121–138. [In Arabic]
- Battese, G. E., & Coelli, T. J. (1992). Frontier production functions, technical efficiency and panel data. Journal of Productivity Analysis, 3(1), 153–169.
- Chen, Y., & Chen, Y. (2024). Changes in technological innovation efficiency... Sustainability, 16(2), 1251.
- Fried, H. O., Lovell, C. A. K., & Schmidt, S. S. (2008). The measurement of productive efficiency and productivity growth. Oxford: Oxford University Press.
- Han, Y., & Gu, W. (2022). Innovation efficiency... Journal of Business Research, 139, 1234–1246.
- Hafez, M. M. E., & Aboubakr, E. A. (2020, July). Using a Bootstrap method and two-stage Data Envelopment Analysis models in estimating the relative efficiency of life insurance companies in the Egyptian market. Journal of the Faculty of Commerce – Beni Suef University, 21(3).
- Kaya, E. (2015). The effects of risk management... Risk Management Journal, 14(3), 215–228.
- Kerstens, K., & Van de Woestyne, I. (2014). Evaluating radial and non-radial DEA models... Omega, 46, 1–9.
- Kumbhakar, S. C., & Lovell, C. A. K. (2000). Stochastic frontier analysis. Cambridge: Cambridge University Press.
- Lee, H., & Ulgado, F. M. (2019). Financial risk behavior... Journal of Risk and Insurance, 86(4), 1156–1178.
- Lin, R., & Tseng, C. (2005). Application of the three-stage DEA model... Tourism Management, 26(4), 511–517.
- Loethgren, M., & Tambour, M. (1999). Testing the significance... Applied Economics Letters, 6(8), 547–549.
- Lu, W., & Meng, Q. (2024). Research on total factor energy efficiency... Energy Reports, 10, 112–124.
- Nguyen, N., Pham, H., & Nguyen, T. (2018). Political uncertainty... Emerging Markets Finance and Trade, 54(12), 2812–2825.
- Simar, L. (1992). Estimating efficiencies from frontier models... Journal of Productivity Analysis, 3(1–2), 171–203.
- Simar, L., & Wilson, P. W. (1998). Sensitivity analysis of efficiency scores... Management Science, 44(1), 49–61.
- Simar, L., & Wilson, P. W. (2007). Estimation and inference in two-stage... Journal of Econometrics, 136(1), 31–64.
- Su, J., Zhang, C., & Yu, H. (2021). Convergence of technological innovation efficiency... Technological Forecasting and Social Change, 164, 120–137.
- Sun, L., & Luo, X. (2017). Efficiency analysis of Chinese commercial banks... China Finance Review International, 7(1), 20–43.
- Tone, K., & Tsutsui, M. (2010). Dynamic network DEA with bootstrap... European Journal of Operational Research, 207(3), 1584–1594.
- Zhang, Y., & Chen, X. (2022). Applying the three-stage SBM-DEA model... Energy Economics, 105, 105754.
- Zhou, P., Ang, B. W., & Poh, K. L. (2008). A survey of DEA in energy and environmental studies. European Journal of Operational Research, 189(1), 1–18.
Published
2025-09-21
How to Cite
Fadwa Abd Allah Ibrahem Ahmed, & Khalid Rahmatullah Khidr Qanawi. (2025). Improving the accuracy of efficiency estimation in insurance companies using the three-stage data envelopment model Ananalytical study using the bootstrap method. Journal of The Faculty of Science and Technology, 10(10), 85 - 119. https://doi.org/10.52981/jfst.v10i10.3406
Section
Articles
