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SİGORTA ŞİRKETLERİNİN STOKASTİK SINIR ANALİZİ İLE ETKİNLİĞİ: BİR META ANALİZ

Year 2025, Issue: 50, 806 - 829, 31.08.2025
https://doi.org/10.14520/adyusbd.1542107

Abstract

Çalışmanın amacı, Stokastik Sınır Analizi (SSA) ile sigorta şirketlerinin maliyet etkinliğini hesaplayan çalışmaları meta analiz ile değerlendirmektir. Meta analiz, PRISMA yönergeleri doğrultusunda gerçekleştirilmiştir. 01.06.2024 tarihinde Web of Science, Scopus ve Google Scholar kullanılarak tarama yapılmıştır. Meta analiz için Jamovi istatistik yazılımı kullanılmıştır. Bu çalışmada incelenen çalışmalar arasında yüksek heterojenlik ortaya çıkmıştır. Yüksek heterojenlik farklı çalışmaların örneklemleri, örneklem büyüklükleri, değişkenleri, dağılımları ve sonuçları arasında önemli farklılıklar olduğunun göstergesidir. Örneklemi yüksek gelir grubunda olan ülkelerde maliyet etkinliği yüksek olma eğilimindedir. Yazında sigorta şirketlerinin maliyet etkinliğini ölçen çalışma sayısı azdır. Konu ile ilgili çalışma sayısının artması çalışmalar arasında karşılaştırma yapmayı kolaylaştıracaktır. Yöneticiler ve politika yapıcılar şirketlerin maliyet etkinliğinin artması için ülke politikalarını ve yasal düzenlemeleri gözden geçirmelidir.

References

  • Al‐Amri, K., Gattoufi, S., & Al‐Muharrami, S. (2012). Analyzing the technical efficiency of insurance companies in GCC. The Journal of Risk Finance, 13(4), 362-380.
  • Alhassan, A. L., & Biekpe, N. (2016). Competition and efficiency in the non-life insurance market in South Africa. Journal of Economic Studies, 43(6), 882-909.
  • Alshammari, A. A., Alhabshi, S. M. B. S. J., & Saiti, B. (2019). The impact of competition on cost efficiency of insurance and takaful sectors: Evidence from GCC markets based on the Stochastic Frontier Analysis. Research in International Business and Finance, 47, 410-427.
  • Baujat, B., Mahé, C., Pignon, J. P., & Hill, C. (2002). A graphical method for exploring heterogeneity in meta‐analyses: application to a meta‐analysis of 65 trials. Statistics in medicine, 21(18), 2641-2652. https://doi.org/10.1002/sim.1221
  • Bian, W., & Wang, X. (2019). The openness of China’s insurance industry and the efficiency of domestic vs. foreign life insurers , Asia-Pacific Journal of Accounting & Economics, 26:6, 731-746, DOI: 10.1080/16081625.2017.1404919
  • Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2021). Introduction to meta-analysis. John wiley & sons.
  • Chuang, C. C., & Tang, Y. C. (2015). Asymmetric Dependence between Efficiency and Market Power in the Taiwanese Life Insurance Industry [Review]. Panoeconomicus, 62(4), 511-525. https://doi.org/10.2298/pan1504511c
  • Cochran, W. G. (1954). The combination of estimates from different experiments. Biometrics, 10(1), 101-129.
  • Cooper, H. M. (2010). Research synthesis and meta-analysis: A step-by-step approach (4th ed.). Sage.
  • Cooper, H., Hedges, L. V., & Valentine, J. C. (Eds.). (2019). The handbook of research synthesis and meta-analysis. Russell Sage Foundation.
  • Cummins, J. D., & Zi, H. M. (1998). Comparison of frontier efficiency methods: An application to the US life insurance industry [Article]. Journal of Productivity Analysis, 10(2), 131-152. https://doi.org/10.1023/a:1026402922367
  • Danquah, M., Otoo, D. M., & Baah-Nuakoh, A. (2018). Cost efficiency of insurance firms in Ghana [Article]. Managerial and Decision Economics, 39(2), 213-225. https://doi.org/10.1002/mde.2897
  • Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. bmj, 315(7109), 629-634. https://doi.org/10.1136/bmj.315.7109.629
  • Eling, M., & Luhnen, M. (2010). Efficiency in the international insurance industry: A cross-country comparison [Article; Proceedings Paper]. Journal of Banking & Finance, 34(7), 1497-1509. https://doi.org/10.1016/j.jbankfin.2009.08.026
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society Series A: Statistics in Society, 120(3), 253-281. https://doi.org/10.2307/2343100
  • Fenn, P., Vencappa, D., Diacon, S., Klumpes, P., & O’Brien, C. (2008). Market structure and the efficiency of European insurance companies: A stochastic frontier analysis. Journal of Banking & Finance, 32(1), 86-100.
  • Ferro, G., & León, S. (2018). A stochastic frontier analysis of efficiency in Argentina’s non-life insurance market. The Geneva Papers on Risk and Insurance-Issues and Practice, 43, 158-174.
  • Fiordelisi, F., & Ricci, O. (2011). Bancassurance efficiency gains: evidence from the Italian banking and insurance industries. European Journal of Finance, 17(9-10), 789-810. https://doi.org/10.1080/1351847x.2010.538519
  • Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3–8. https://doi.org/10.3102/0013189X005010003
  • Greene, W. H., & Segal, D. (2004). Profitability and efficiency in the US life insurance industry. Journal of Productivity Analysis, 21(3), 229-247. https://doi.org/10.1023/B:PROD.0000022092.70204.fa
  • Haghdoost, A. A., & Moosazadeh, M. (2013). The prevalence of cigarette smoking among students of Iran's universities: A systematic review and meta-analysis. Journal of research in medical sciences: the official journal of Isfahan University of Medical Sciences, 18(8), 717-725.
  • https://www.ncbi.nlm.nih.gov/pubmed/24379851
  • Higgins, J. P. T., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta‐analysis. Statistics in Medicine, 21(11), 1539–1558. https://doi.org/10.1002/sim.1186
  • Kaya, N. (2024). Bank technical efficiency of country groups:A meta regression analysis. Journal of Business Economics and Finance, 13(1), 13-23.
  • Kaya, N., & Algın, A. (2022). Kamu Hastanelerinde Teknik Etkinlik: Bir Meta-Regresyon Analizi, Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 17(3), 810-821. DOI: 10.17153/oguiibf.1094736
  • Kendall, M. G. (1938). A New Measure of Rank Correlation. Biometrika, 30(1-2), 81–93. https://doi.org/10.1093/biomet/30.1-2.81
  • Kholis, N., & Afifah, Y. N. (2022). Measuring Financial Efficiency of Insurance Companies in Indonesia Using Stochastic Frontier Analysis Approach: A Comparison Between Islamic and Conventional Insurances. Journal of Islamic Economics Lariba, 196-212.
  • Kounetas, K., & Papathanassopoulos, F. (2013). How efficient are Greek hospitals? A case study using a double bootstrap DEA approach. The European Journal of Health Economics, 14, 979-994.
  • Mamatzakis, E., Staikouras, C., Triantopoulos, C., & Wang, Z. C. (2023). Measuring the efficiency and productivity of UK insurance market [Article; Early Access]. International Journal of Finance & Economics, 18. https://doi.org/10.1002/ijfe.2723
  • Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group*, T. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine, 151(4), 264-269. https://doi.org/10.7326/0003-4819-151-4-200908180-00135
  • Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Prisma Group. (2010). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. International journal of surgery, 8(5), 336-341. https://doi.org/10.1016/j.ijsu.2010.02.007
  • Moosazadeh, M., Nekoei‐moghadam, M., Emrani, Z., & Amiresmaili, M. (2014). Prevalence of unwanted pregnancy in Iran: a systematic review and meta‐analysis. The International Journal of Health Planning and Management, 29(3), e277-e290. https://doi.org/10.1002/hpm.2184
  • Nasiripour, A. A., Reza Maleki, M., & Mehrolhassani, M. H. (2012). Technical Efficiency of Iranian Medical-services Insurance Organization using data envelopment analysis approach. HealthMED, 603.
  • Rezaei, S., Hajizadeh, M., Nouri, B., Ahmadi, S., Rezaeian, S., Salimi, Y., & Karyani, A. K. (2019). Iranian hospital efficiency: a systematic review and meta-analysis. International Journal of Health Care Quality Assurance, 32(2), 385-397. https://doi.org/10.1108/IJHCQA-03-2018-0067
  • Rezaei, S., Hajizadeh, M., Zandian, H., Fathi, A., & Nouri, B. (2017). Period Prevalence and Reporting Rate of Needlestick Injuries to Nurses in Iran: A Systematic Review and Meta-Analysis. Research in Nursing & Health, 40(4), 311-322. https://doi.org/10.1002/nur.21801
  • Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological bulletin, 86(3), 638. https://psycnet.apa.org/doi/10.1037/0033-2909.86.3.638
  • Shi, P., & Zhang, W. (2011). A copula regression model for estimating firm efficiency in the insurance industry. Journal of Applied Statistics, 38(10), 2271-2287.
  • Shi, P., & Zhang, W. (2011). Time-varying X-efficiency: evidence from US property casualty insurers, Applied Economics Letters, 18:3, 217-221, DOI:10.1080/13504850903559559
  • Sinha, R. P. (2021). Two-stage data envelopment analysis efficiency of Indian general insurance companies. Global Business Review, 09721509211047645.
  • Smętek, K., Zawadzka, D., & Strzelecka, A. (2022). Examples of the use of Data Envelopment Analysis (DEA) to assess the financial effectiveness of insurance companies. Procedia Computer Science, 207, 3924-3930.
  • Thanassoulis, E. (2001). Introduction to the theory and application of data envelopment analysis. Dordrecht: Kluwer Academic Publishers.
  • The jamovi project (2022). Jamovi. (Version 2.3) [Computer Software]. Retrieved from https://www.jamovi.org.
  • Vadlamannati, K. C. (2008). Do insurance sector growth and reforms affect economic development? Empirical evidence from India. Margin: The Journal of Applied Economic Research, 2(1), 43–86. https://doi.org/10.1177/097380100700200102
  • Yaisawarng, S., Asavadachanukorn, P., & Yaisawarng, S. (2014). Efficiency and productivity in the Thai non-life insurance industry [Article; Proceedings Paper]. Journal of Productivity Analysis, 41(2), 291-306. https://doi.org/10.1007/s11123-012-0317-8

EFFICIENCY OF INSURANCE COMPANIES WITH STOCHASTIC FRONTIER ANALYSIS: A META ANALYSIS

Year 2025, Issue: 50, 806 - 829, 31.08.2025
https://doi.org/10.14520/adyusbd.1542107

Abstract

This study aims to evaluate the studies calculating the cost effectiveness of insurance companies using Stochastic Frontier Analysis (SFA) through a meta-analysis. The meta-analysis was conducted in accordance with PRISMA guidelines. The search was performed on 01.06.2024, using Web of Science, Scopus and Google Scholar. Jamovi statistical software was employed for meta-analysis. High heterogeneity was identified among the examined studies, indicating significant differences in samples, sample sizes, variables, distributions and results. Cost effectiveness tends to be higher in countries with high-income sample groups. There is a dearth of studies measuring the cost effectiveness of insurance companies in the relevant literature. Increasing the number of studies on this subject will facilitate comparison between studies. Managers and policy makers should review country policies and legal regulations to enhance the cost effectiveness of companies.

References

  • Al‐Amri, K., Gattoufi, S., & Al‐Muharrami, S. (2012). Analyzing the technical efficiency of insurance companies in GCC. The Journal of Risk Finance, 13(4), 362-380.
  • Alhassan, A. L., & Biekpe, N. (2016). Competition and efficiency in the non-life insurance market in South Africa. Journal of Economic Studies, 43(6), 882-909.
  • Alshammari, A. A., Alhabshi, S. M. B. S. J., & Saiti, B. (2019). The impact of competition on cost efficiency of insurance and takaful sectors: Evidence from GCC markets based on the Stochastic Frontier Analysis. Research in International Business and Finance, 47, 410-427.
  • Baujat, B., Mahé, C., Pignon, J. P., & Hill, C. (2002). A graphical method for exploring heterogeneity in meta‐analyses: application to a meta‐analysis of 65 trials. Statistics in medicine, 21(18), 2641-2652. https://doi.org/10.1002/sim.1221
  • Bian, W., & Wang, X. (2019). The openness of China’s insurance industry and the efficiency of domestic vs. foreign life insurers , Asia-Pacific Journal of Accounting & Economics, 26:6, 731-746, DOI: 10.1080/16081625.2017.1404919
  • Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2021). Introduction to meta-analysis. John wiley & sons.
  • Chuang, C. C., & Tang, Y. C. (2015). Asymmetric Dependence between Efficiency and Market Power in the Taiwanese Life Insurance Industry [Review]. Panoeconomicus, 62(4), 511-525. https://doi.org/10.2298/pan1504511c
  • Cochran, W. G. (1954). The combination of estimates from different experiments. Biometrics, 10(1), 101-129.
  • Cooper, H. M. (2010). Research synthesis and meta-analysis: A step-by-step approach (4th ed.). Sage.
  • Cooper, H., Hedges, L. V., & Valentine, J. C. (Eds.). (2019). The handbook of research synthesis and meta-analysis. Russell Sage Foundation.
  • Cummins, J. D., & Zi, H. M. (1998). Comparison of frontier efficiency methods: An application to the US life insurance industry [Article]. Journal of Productivity Analysis, 10(2), 131-152. https://doi.org/10.1023/a:1026402922367
  • Danquah, M., Otoo, D. M., & Baah-Nuakoh, A. (2018). Cost efficiency of insurance firms in Ghana [Article]. Managerial and Decision Economics, 39(2), 213-225. https://doi.org/10.1002/mde.2897
  • Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). Bias in meta-analysis detected by a simple, graphical test. bmj, 315(7109), 629-634. https://doi.org/10.1136/bmj.315.7109.629
  • Eling, M., & Luhnen, M. (2010). Efficiency in the international insurance industry: A cross-country comparison [Article; Proceedings Paper]. Journal of Banking & Finance, 34(7), 1497-1509. https://doi.org/10.1016/j.jbankfin.2009.08.026
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society Series A: Statistics in Society, 120(3), 253-281. https://doi.org/10.2307/2343100
  • Fenn, P., Vencappa, D., Diacon, S., Klumpes, P., & O’Brien, C. (2008). Market structure and the efficiency of European insurance companies: A stochastic frontier analysis. Journal of Banking & Finance, 32(1), 86-100.
  • Ferro, G., & León, S. (2018). A stochastic frontier analysis of efficiency in Argentina’s non-life insurance market. The Geneva Papers on Risk and Insurance-Issues and Practice, 43, 158-174.
  • Fiordelisi, F., & Ricci, O. (2011). Bancassurance efficiency gains: evidence from the Italian banking and insurance industries. European Journal of Finance, 17(9-10), 789-810. https://doi.org/10.1080/1351847x.2010.538519
  • Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3–8. https://doi.org/10.3102/0013189X005010003
  • Greene, W. H., & Segal, D. (2004). Profitability and efficiency in the US life insurance industry. Journal of Productivity Analysis, 21(3), 229-247. https://doi.org/10.1023/B:PROD.0000022092.70204.fa
  • Haghdoost, A. A., & Moosazadeh, M. (2013). The prevalence of cigarette smoking among students of Iran's universities: A systematic review and meta-analysis. Journal of research in medical sciences: the official journal of Isfahan University of Medical Sciences, 18(8), 717-725.
  • https://www.ncbi.nlm.nih.gov/pubmed/24379851
  • Higgins, J. P. T., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta‐analysis. Statistics in Medicine, 21(11), 1539–1558. https://doi.org/10.1002/sim.1186
  • Kaya, N. (2024). Bank technical efficiency of country groups:A meta regression analysis. Journal of Business Economics and Finance, 13(1), 13-23.
  • Kaya, N., & Algın, A. (2022). Kamu Hastanelerinde Teknik Etkinlik: Bir Meta-Regresyon Analizi, Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 17(3), 810-821. DOI: 10.17153/oguiibf.1094736
  • Kendall, M. G. (1938). A New Measure of Rank Correlation. Biometrika, 30(1-2), 81–93. https://doi.org/10.1093/biomet/30.1-2.81
  • Kholis, N., & Afifah, Y. N. (2022). Measuring Financial Efficiency of Insurance Companies in Indonesia Using Stochastic Frontier Analysis Approach: A Comparison Between Islamic and Conventional Insurances. Journal of Islamic Economics Lariba, 196-212.
  • Kounetas, K., & Papathanassopoulos, F. (2013). How efficient are Greek hospitals? A case study using a double bootstrap DEA approach. The European Journal of Health Economics, 14, 979-994.
  • Mamatzakis, E., Staikouras, C., Triantopoulos, C., & Wang, Z. C. (2023). Measuring the efficiency and productivity of UK insurance market [Article; Early Access]. International Journal of Finance & Economics, 18. https://doi.org/10.1002/ijfe.2723
  • Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group*, T. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine, 151(4), 264-269. https://doi.org/10.7326/0003-4819-151-4-200908180-00135
  • Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Prisma Group. (2010). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. International journal of surgery, 8(5), 336-341. https://doi.org/10.1016/j.ijsu.2010.02.007
  • Moosazadeh, M., Nekoei‐moghadam, M., Emrani, Z., & Amiresmaili, M. (2014). Prevalence of unwanted pregnancy in Iran: a systematic review and meta‐analysis. The International Journal of Health Planning and Management, 29(3), e277-e290. https://doi.org/10.1002/hpm.2184
  • Nasiripour, A. A., Reza Maleki, M., & Mehrolhassani, M. H. (2012). Technical Efficiency of Iranian Medical-services Insurance Organization using data envelopment analysis approach. HealthMED, 603.
  • Rezaei, S., Hajizadeh, M., Nouri, B., Ahmadi, S., Rezaeian, S., Salimi, Y., & Karyani, A. K. (2019). Iranian hospital efficiency: a systematic review and meta-analysis. International Journal of Health Care Quality Assurance, 32(2), 385-397. https://doi.org/10.1108/IJHCQA-03-2018-0067
  • Rezaei, S., Hajizadeh, M., Zandian, H., Fathi, A., & Nouri, B. (2017). Period Prevalence and Reporting Rate of Needlestick Injuries to Nurses in Iran: A Systematic Review and Meta-Analysis. Research in Nursing & Health, 40(4), 311-322. https://doi.org/10.1002/nur.21801
  • Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological bulletin, 86(3), 638. https://psycnet.apa.org/doi/10.1037/0033-2909.86.3.638
  • Shi, P., & Zhang, W. (2011). A copula regression model for estimating firm efficiency in the insurance industry. Journal of Applied Statistics, 38(10), 2271-2287.
  • Shi, P., & Zhang, W. (2011). Time-varying X-efficiency: evidence from US property casualty insurers, Applied Economics Letters, 18:3, 217-221, DOI:10.1080/13504850903559559
  • Sinha, R. P. (2021). Two-stage data envelopment analysis efficiency of Indian general insurance companies. Global Business Review, 09721509211047645.
  • Smętek, K., Zawadzka, D., & Strzelecka, A. (2022). Examples of the use of Data Envelopment Analysis (DEA) to assess the financial effectiveness of insurance companies. Procedia Computer Science, 207, 3924-3930.
  • Thanassoulis, E. (2001). Introduction to the theory and application of data envelopment analysis. Dordrecht: Kluwer Academic Publishers.
  • The jamovi project (2022). Jamovi. (Version 2.3) [Computer Software]. Retrieved from https://www.jamovi.org.
  • Vadlamannati, K. C. (2008). Do insurance sector growth and reforms affect economic development? Empirical evidence from India. Margin: The Journal of Applied Economic Research, 2(1), 43–86. https://doi.org/10.1177/097380100700200102
  • Yaisawarng, S., Asavadachanukorn, P., & Yaisawarng, S. (2014). Efficiency and productivity in the Thai non-life insurance industry [Article; Proceedings Paper]. Journal of Productivity Analysis, 41(2), 291-306. https://doi.org/10.1007/s11123-012-0317-8
There are 44 citations in total.

Details

Primary Language Turkish
Subjects Econometrics (Other)
Journal Section Articles
Authors

Neylan Kaya 0000-0003-2645-3246

Publication Date August 31, 2025
Submission Date September 2, 2024
Acceptance Date August 19, 2025
Published in Issue Year 2025 Issue: 50

Cite

APA Kaya, N. (2025). SİGORTA ŞİRKETLERİNİN STOKASTİK SINIR ANALİZİ İLE ETKİNLİĞİ: BİR META ANALİZ. Adıyaman Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(50), 806-829. https://doi.org/10.14520/adyusbd.1542107