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The Real Output Costs of Financial Crisis: A Loss Distribution Approach

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  • Kapp, Daniel

    (University of Paris)

  • Vega, Marco

    (Banco Central de Reserva del Perú
    Universidad Católica del Perú)

Abstract

We study cross-country GDP losses due to financial crises in terms of frequency (number of loss events per period) and severity (loss per occurrence). We perform the Loss Distribution Approach (LDA) to estimate a multi-country aggregate GDP loss probability density function and the percentiles associated to extreme events due to financial crises. We find that output losses arising from financial crises are strongly heterogeneous and that currency crises lead to smaller output losses than debt and banking crises. Extreme global financial crises episodes, occurring with a one percent probability every five years, lead to losses between 2.95% and 4.54% of world GDP.

Suggested Citation

  • Kapp, Daniel & Vega, Marco, 2012. "The Real Output Costs of Financial Crisis: A Loss Distribution Approach," Working Papers 2012-013, Banco Central de Reserva del Perú.
    • Handle: RePEc:rbp:wpaper:2012-013
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    1. Annabelle Mourougane, 2017. "Crisis, potential output and hysteresis," International Economics, CEPII research center, issue 149, pages 1-14.
    2. Devereux, John & Dwyer, Gerald P., 2016. "What determines output losses after banking crises?," Journal of International Money and Finance, Elsevier, vol. 69(C), pages 69-94.
    3. repec:dgr:rugsom:13010-eef is not listed on IDEAS
    4. Boris Vujcic & Mirna Dumicic, 2016. "Managing systemic risks in the Croatian economy," BIS Papers chapters, in: Bank for International Settlements (ed.), Macroprudential policy, volume 86, pages 75-84, Bank for International Settlements.
    5. Emilia-Ancuta Corovei, 2015. "Real Output Costs of Financial Crisis on CEE Countries," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 7(1), pages 80-84, March.
    6. Steiner, Andreas, 2014. "Reserve accumulation and financial crises: From individual protection to systemic risk," European Economic Review, Elsevier, vol. 70(C), pages 126-144.
    7. Raputsoane, Leroi, 2018. "Quantifying economic recovery from the recent global financial crisis," MPRA Paper 87410, University Library of Munich, Germany.
    8. Tolga Umut Kuzubas & Burak Saltoglu & Can Sever, 2014. "Systemic Risk and Heterogeneous Leverage in Banking Network: Implications for Banking Regulation," Working Papers 2014/01, Bogazici University, Department of Economics.
    9. Aizenman, Joshua & Ito, Hiro, 2014. "Living with the trilemma constraint: Relative trilemma policy divergence, crises, and output losses for developing countries," Journal of International Money and Finance, Elsevier, vol. 49(PA), pages 28-51.
    10. Mahdi Yazdani & Mohammad Nikzad, 2021. "Output Losses from Currency Crises and the Role of Central Bank," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(3), pages 79-97.
    11. Iustina Alina Boitan, 2015. "Output Loss Severity across EU Countries. Evidence for the 2008 Financial Crisis," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 11(4), pages 117-126, August.
    12. Carbajal-De-Nova, Carolina & Venegas-Martínez, Francisco, 2019. "On the paradigm shift of asset pricing models, before and after the global financial crisis: a literature review," Panorama Económico, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 15(29), pages 7-38, Primer se.
    13. Sever, Can, 2014. "Systemic Liquidity Crisis with Dynamic Haircuts," MPRA Paper 55602, University Library of Munich, Germany.
    14. Boonman, Tjeerd M., 2013. "Sovereign defaults, business cycles and economic growth in Latin America, 1870-2012," Research Report 13010-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).

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    More about this item

    Keywords

    Financial Crisis; Severity; Frequency; Loss Distribution Approach;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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