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Business failure, efficiency, and volatility: Evidence from the European insurance industry

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  • Eling, Martin
  • Jia, Ruo

Abstract

We analyze the operations and performance of insurance companies that left the insurance market from 2006 to 2013. Using a large European sample (2060 insurers from 16 countries and 250 failure events), we find that technical efficiency negatively and business volatility positively correlate with the probability of failure. Moreover, we document that firm growth has a U-shaped, nonlinear impact on failure probability. The research is original, in that we demonstrate the persistency of technical efficiency and business volatility in terms of early surveillance, extending valuable response time and thus broadening the available measures to prevent failures. We also demonstrate our identified failure indicators' applicability across financial crises and different regulatory philosophies. We apply the state-of-the-art data envelopment analysis, rare event logistic regression, hazard model of time to failure, and supporting vector machine approaches to the business failure prediction.

Suggested Citation

  • Eling, Martin & Jia, Ruo, 2018. "Business failure, efficiency, and volatility: Evidence from the European insurance industry," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 58-76.
  • Handle: RePEc:eee:finana:v:59:y:2018:i:c:p:58-76
    DOI: 10.1016/j.irfa.2018.07.007
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    Cited by:

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    3. Fernando Zambrano Farias & María del Carmen Valls Martínez & Pedro Antonio Martín-Cervantes, 2021. "Explanatory Factors of Business Failure: Literature Review and Global Trends," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    4. Carmona, Pedro & Dwekat, Aladdin & Mardawi, Zeena, 2022. "No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure," Research in International Business and Finance, Elsevier, vol. 61(C).
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    7. Shoaib Alam Siddiqui, 2022. "How efficient is Indian health insurance sector: An SBM‐DEA study," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(4), pages 950-962, June.
    8. Bilel Jarraya & Hatem Afi & Anis Omri, 2023. "Analyzing the Profitability and Efficiency in European Non-Life Insurance Industry," Methodology and Computing in Applied Probability, Springer, vol. 25(2), pages 1-25, June.
    9. Ali Shaddady, 2022. "Business environment, political risk, governance, Shariah compliance and efficiency in insurance companies in the MENA region," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(4), pages 861-904, October.
    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.
    11. Mohammad Nourani & Qian Long Kweh & Irene Wei Kiong Ting & Wen-Min Lu & Anna Strutt, 2022. "Evaluating traditional, dynamic and network business models: an efficiency-based study of Chinese insurance companies," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(4), pages 905-943, October.
    12. A.V. Larionov, 2020. "Assessing the Financial Stability of Insurance Companies by Analyzing the Dynamics of Cash Flows," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 19(2), pages 208-224.
    13. Liu, Shuyan & Jia, Ruo & Zhao, Yulong & Sun, Qixiang, 2019. "Global consistent or market-oriented? A quantitative assessment of RBC standards, solvency II, and C-ROSS," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    14. Zhiyong Li & Chen Feng & Ying Tang, 2022. "Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis," Annals of Operations Research, Springer, vol. 315(1), pages 279-315, August.
    15. Olivier de Bandt & George Overton, 2022. "Why do insurers fail? A comparison of life and nonlife insurance companies from an international database," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(4), pages 871-905, December.
    16. Draženović Bojana Olgić & Hodžić Sabina & Maradin Dario, 2019. "The Efficiency of Mandatory Pension Funds: Case of Croatia," South East European Journal of Economics and Business, Sciendo, vol. 14(2), pages 82-94, December.
    17. Yang Liu & Qingguo Zeng & Bobo Li & Lili Ma & Joaquín Ordieres‐Meré, 2022. "Anticipating financial distress of high‐tech startups in the European Union: A machine learning approach for imbalanced samples," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1131-1155, September.
    18. Apostolos Kiohos, 2020. "Risk Affection and Transmission of News of Conditional Volatility from the Non-Life to Life Insurance Sector," Bulletin of Applied Economics, Risk Market Journals, vol. 7(2), pages 77-86.

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    More about this item

    Keywords

    Insurance; Data envelopment analysis; Business failure model; Insolvency; Early surveillance;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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