IDEAS home Printed from https://ideas.repec.org/a/sav/journl/v70y2022i1p3-21.html
   My bibliography  Save this article

Early Warning System for the European Insurance Sector

Author

Listed:
  • Lorenzo Danieli

    (European Securities and Markets Authority)

  • Petr Jakubik

    (European Insurance and Occupational Pensions Authority)

Abstract

This study proposes an Early Warning System model composed of macro-financial and company-specific indicators that could help to anticipate a potential market distress in the European insurance sector. A distress is defined as periods in which insurance companies’ equity prices crash and CDS spreads spike simultaneously. The model is estimated using a sample of 36 insurance companies that are listed. Based on a fixed-effects panel binomial logit specification, empirical evidence shows that economic overheating that could be manifested by high economic growth, inflation and interest rates have negative impact on insurance sector stability. At the company level, a drop in return on assets and price-to-book value or raising operating expenses increase the likelihood of distress occurrence.

Suggested Citation

  • Lorenzo Danieli & Petr Jakubik, 2022. "Early Warning System for the European Insurance Sector," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(1), pages 3-21, January.
    • Handle: RePEc:sav:journl:v:70:y:2022:i:1:p:3-21
    as

    Download full text from publisher

    File URL: https://www.sav.sk/journals/uploads/0310180501%2022%20Danieli-Jakubik%20+%20SR.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Fabio Comelli, 2014. "Comparing Parametric and Non-parametric Early Warning Systems for Currency Crises in Emerging Market Economies," Review of International Economics, Wiley Blackwell, vol. 22(4), pages 700-721, September.
    2. Girardi, Giulio & Hanley, Kathleen W. & Nikolova, Stanislava & Pelizzon, Loriana & Sherman, Mila Getmansky, 2021. "Portfolio similarity and asset liquidation in the insurance industry," Journal of Financial Economics, Elsevier, vol. 142(1), pages 69-96.
    3. Alessi, Lucia & Detken, Carsten, 2011. "Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity," European Journal of Political Economy, Elsevier, vol. 27(3), pages 520-533, September.
    4. Òscar Jordà & Moritz Schularick & Alan M Taylor, 2011. "Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 59(2), pages 340-378, June.
    5. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    6. Sevim, Cuneyt & Oztekin, Asil & Bali, Ozkan & Gumus, Serkan & Guresen, Erkam, 2014. "Developing an early warning system to predict currency crises," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1095-1104.
    7. André K. Anundsen & Karsten Gerdrup & Frank Hansen & Kasper Kragh‐Sørensen, 2016. "Bubbles and Crises: The Role of House Prices and Credit," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1291-1311, November.
    8. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    9. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    10. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    11. Drehmann, Mathias & Juselius, Mikael, 2014. "Evaluating early warning indicators of banking crises: Satisfying policy requirements," International Journal of Forecasting, Elsevier, vol. 30(3), pages 759-780.
    12. Cristina Dorofti & Petr Jakubik, 2015. "Insurance Sector Profitability and the Macroeconomic Environment," EIOPA Financial Stability Report - Thematic Articles 4, EIOPA, Risks and Financial Stability Department.
    13. Candelon, B. & Dumitrescu, E-I. & Hurlin, C., 2010. "How to evaluate an early warning system? Towards a united statistical framework for assessing financial crises forecasting methods," Research Memorandum 046, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    14. Claudio Borio & Mathias Drehmann, 2009. "Assessing the risk of banking crises - revisited," BIS Quarterly Review, Bank for International Settlements, March.
    15. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    16. Hua Chen & J. David Cummins & Krupa S. Viswanathan & Mary A. Weiss, 2014. "Systemic Risk and the Interconnectedness Between Banks and Insurers: An Econometric Analysis," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(3), pages 623-652, September.
    17. Bertrand Candelon & Elena-Ivona Dumitrescu & Christophe Hurlin, 2012. "How to Evaluate an Early-Warning System: Toward a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 60(1), pages 75-113, April.
    18. Mr. Fabio Comelli, 2014. "Comparing the Performance of Logit and Probit Early Warning Systems for Currency Crises in Emerging Market Economies," IMF Working Papers 2014/065, International Monetary Fund.
    19. Davis, E. Philip & Karim, Dilruba, 2008. "Comparing early warning systems for banking crises," Journal of Financial Stability, Elsevier, vol. 4(2), pages 89-120, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Antunes, António & Bonfim, Diana & Monteiro, Nuno & Rodrigues, Paulo M.M., 2018. "Forecasting banking crises with dynamic panel probit models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 249-275.
    2. Xianglong Liu, 2023. "Towards Better Banking Crisis Prediction: Could an Automatic Variable Selection Process Improve the Performance?," The Economic Record, The Economic Society of Australia, vol. 99(325), pages 288-312, June.
    3. Tihana Skrinjaric, 2023. "Leading indicators of financial stress in Croatia: a regime switching approach," Public Sector Economics, Institute of Public Finance, vol. 47(2), pages 205-232.
    4. Wang, Peiwan & Zong, Lu, 2023. "Does machine learning help private sectors to alarm crises? Evidence from China’s currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    5. Zsuzsanna Hosszu & Gergely Lakos, 2022. "Early Warning Performance of Univariate Credit-to-GDP Gaps," MNB Occasional Papers 2022/142, Magyar Nemzeti Bank (Central Bank of Hungary).
    6. Kalatie, Simo & Laakkonen, Helinä & Tölö, Eero, 2015. "Indicators used in setting the countercyclical capital buffer," Bank of Finland Research Discussion Papers 8/2015, Bank of Finland.
    7. Carsten Detken & Olaf Weeken & Lucia Alessi & Diana Bonfim & Miguel M. Boucinha & Christian Castro & Sebastian Frontczak & Gaston Giordana & Julia Giese & Nadya Jahn & Jan Kakes & Benjamin Klaus & Jan, 2014. "Operationalising the countercyclical capital buffer: indicator selection, threshold identification and calibration options," ESRB Occasional Paper Series 05, European Systemic Risk Board.
    8. Tihana Škrinjarić, 2023. "Credit-to-GDP Gap Estimates in Real Time: A Stable Indicator for Macroprudential Policy Making in Croatia," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 65(3), pages 582-614, September.
    9. Helene Olsen & Harald Wieslander, 2020. "The Impact of Monetary Policy on Leading Variables for Financial Stability in Norway," Working Papers No 02/2020, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    10. Kalatie, Simo & Laakkonen, Helinä & Tölö, Eero, 2015. "Indicators used in setting the countercyclical capital buffer," Research Discussion Papers 8/2015, Bank of Finland.
    11. repec:zbw:bofrdp:2015_008 is not listed on IDEAS
    12. Sarah Vella, 2025. "Constructing a country-specific indicator for cyclical systemic risk," Economic Change and Restructuring, Springer, vol. 58(3), pages 1-63, June.
    13. Bespalova, Olga, 2018. "Forecast Evaluation in Macroeconomics and International Finance. Ph.D. thesis, George Washington University, Washington, DC, USA," MPRA Paper 117706, University Library of Munich, Germany.
    14. repec:zbw:bofrdp:2019_014 is not listed on IDEAS
    15. Savas Papadopoulos & Pantelis Stavroulias & Thomas Sager & Etti Baranoff, 2017. "A ternary-state early warning system for the European Union," Working Papers 222, Bank of Greece.
    16. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    17. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    18. Lang, Jan Hannes & Izzo, Cosimo & Fahr, Stephan & Ruzicka, Josef, 2019. "Anticipating the bust: a new cyclical systemic risk indicator to assess the likelihood and severity of financial crises," Occasional Paper Series 219, European Central Bank.
    19. Lo Duca, Marco & Koban, Anne & Basten, Marisa & Bengtsson, Elias & Klaus, Benjamin & Kusmierczyk, Piotr & Lang, Jan Hannes & Detken, Carsten & Peltonen, Tuomas, 2017. "A new database for financial crises in European countries," ESRB Occasional Paper Series 13, European Systemic Risk Board.
    20. Tölö, Eero, 2019. "Predicting systemic financial crises with recurrent neural networks," Research Discussion Papers 14/2019, Bank of Finland.
    21. Mahir Binici & Aytül Ganioglu, 2021. "Net external position, financial development, and banking crisis," Empirical Economics, Springer, vol. 61(3), pages 1225-1251, September.
    22. Geršl, Adam & Jašová, Martina, 2018. "Credit-based early warning indicators of banking crises in emerging markets," Economic Systems, Elsevier, vol. 42(1), pages 18-31.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sav:journl:v:70:y:2022:i:1:p:3-21. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Renac (email available below). General contact details of provider: https://edirc.repec.org/data/eusavsk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.