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The Unholy Trinity: Fat Tails, Tail Dependence, and Micro-Correlations

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  • Kousky, Carolyn

    (Resources for the Future)

  • Cooke, Roger M.

    (Resources for the Future)

Abstract

Recent events in the financial and insurance markets, as well as the looming challenges of a globally changing climate point to the need to re-think the ways in which we measure and manage catastrophic and dependent risks. Management can only be as good as our measurement tools. To that end, this paper outlines detection, measurement, and analysis strategies for fat-tailed risks, tail dependent risks, and risks characterized by micro-correlations. A simple model of insurance demand and supply is used to illustrate the difficulties in insuring risks characterized by these phenomena. Policy implications are discussed.

Suggested Citation

  • Kousky, Carolyn & Cooke, Roger M., 2009. "The Unholy Trinity: Fat Tails, Tail Dependence, and Micro-Correlations," RFF Working Paper Series dp-09-36-rev.pdf, Resources for the Future.
    • Handle: RePEc:rff:dpaper:dp-09-36-rev.pdf
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    References listed on IDEAS

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    1. MOSSIN, Jan, 1968. "Aspects of rational insurance purchasing," LIDAM Reprints CORE 23, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Neil A. Doherty & Harris Schlesinger, 2001. "Insurance Contracts and Securitization," CESifo Working Paper Series 559, CESifo.
    3. Carolyn Kousky & Erzo Luttmer & Richard Zeckhauser, 2006. "Private investment and government protection," Journal of Risk and Uncertainty, Springer, vol. 33(1), pages 73-100, September.
    4. Kousky, Carolyn & Cooke, Roger, 2009. "Climate Change and Risk Management: Challenges for Insurance, Adaptation, and Loss Estimation," RFF Working Paper Series dp-09-03-rev, Resources for the Future.
    5. Erwann Michel-Kerjan & Frederic Morlaye, 2008. "Extreme Events, Global Warming, and Insurance-Linked Securities: How to Trigger the “Tipping Point”," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 33(1), pages 153-176, January.
    6. Kenneth A. Froot, 1999. "The Financing of Catastrophe Risk," NBER Books, National Bureau of Economic Research, Inc, number froo99-1.
    7. Ladoucette, Sophie A. & Teugels, Jef L., 2006. "Analysis of risk measures for reinsurance layers," Insurance: Mathematics and Economics, Elsevier, vol. 38(3), pages 630-639, June.
    8. Milidonis, Andreas & Grace, Martin F., 2008. "Tax-Deductible Pre-Event Catastrophe Loss Reserves: The Case of Florida1," ASTIN Bulletin, Cambridge University Press, vol. 38(1), pages 13-51, May.
    9. Colin F. Camerer & Howard Kunreuther, 1989. "Decision processes for low probability events: Policy implications," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 8(4), pages 565-592.
    10. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    11. Christopher Lewis & Kevin C. Murdock, 1999. "Alternative Means of Redistributing Catastrophic Risk in a National Risk-Management System," NBER Chapters, in: The Financing of Catastrophe Risk, pages 51-92, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Clovis Freire, 2011. "Social and Economic Impact of Disasters: Estimating the Threshold between Low and High Levels of Risk," MPDD Working Paper Series WP/11/15, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP).
    2. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    3. Tianyang Wang & James S. Dyer, 2012. "A Copulas-Based Approach to Modeling Dependence in Decision Trees," Operations Research, INFORMS, vol. 60(1), pages 225-242, February.
    4. Benjamin Jones & Michael Keen & Jon Strand, 2013. "Fiscal implications of climate change," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 20(1), pages 29-70, February.
    5. Tianyang Wang & James S. Dyer & Warren J. Hahn, 2017. "Sensitivity analysis of decision making under dependent uncertainties using copulas," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 117-139, November.
    6. Christoph Werner & Tim Bedford & John Quigley, 2018. "Sequential Refined Partitioning for Probabilistic Dependence Assessment," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2683-2702, December.
    7. Gernot Wagner & Richard Zeckhauser, 2012. "Climate policy: hard problem, soft thinking," Climatic Change, Springer, vol. 110(3), pages 507-521, February.
    8. Alexander Vinel & Pavlo A. Krokhmal, 2017. "Certainty equivalent measures of risk," Annals of Operations Research, Springer, vol. 249(1), pages 75-95, February.
    9. Ceballos, Francisco, 2016. "Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay," IFPRI discussion papers 1595, International Food Policy Research Institute (IFPRI).
    10. Michael Hanemann, 2010. "The Impact of Climate Change: An Economic Perspective," Chapters, in: Emilio Cerdá Tena & Xavier Labandeira (ed.), Climate Change Policies, chapter 2, Edward Elgar Publishing.
    11. Furman, Edward & Kuznetsov, Alexey & Su, Jianxi & Zitikis, Ričardas, 2016. "Tail dependence of the Gaussian copula revisited," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 97-103.
    12. Masih-Tehrani, Behdad & Xu, Susan H. & Kumara, Soundar & Li, Haijun, 2011. "A single-period analysis of a two-echelon inventory system with dependent supply uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1128-1151, September.
    13. Bozic, Marin & Newton, John & Thraen, Cameron S. & Gould, Brian W., 2012. "Livestock Gross Margin Insurance for Dairy: Designing Margin Insurance Contracts to Account for Tail Dependence Risk," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124718, Agricultural and Applied Economics Association.
    14. Marc N. Conte & David L. Kelly, 2016. "An Imperfect Storm: Fat-Tailed Hurricane Damages, Insurance and Climate Policy," Working Papers 2016-01, University of Miami, Department of Economics.
    15. Cossette, Hélène & Marceau, Etienne & Mtalai, Itre, 2019. "Collective risk models with dependence," Insurance: Mathematics and Economics, Elsevier, vol. 87(C), pages 153-168.
    16. Tang, Qihe & Tong, Zhiwei & Xun, Li, 2022. "Portfolio risk analysis of excess of loss reinsurance," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 91-110.
    17. Conte, Marc N. & Kelly, David L., 2018. "An imperfect storm: Fat-tailed tropical cyclone damages, insurance, and climate policy," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 677-706.

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    More about this item

    Keywords

    risk; fat tails; tail dependence; micro-correlations; insurance; natural disasters;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics

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