IDEAS home Printed from https://ideas.repec.org/p/fpr/ifprid/1595.html
   My bibliography  Save this paper

Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay

Author

Listed:
  • Ceballos, Francisco

Abstract

This paper develops a novel methodology to estimate the degree of spatial basis risk for an arbitrary rainfall index insurance instrument. It relies on a widelyused stochastic rainfall generator, extendedto accommodate nontraditional dependence patterns—in particular spatial upper-tail dependence in rainfall—through a copula function. The methodology is applied to a recentlylaunched index product insuring against excess rainfall in Uruguay. The model is first calibrated using historical daily rainfall data from the national network of weather stations, complemented with a unique,high-resolution dataset from a dense network of 34 automatic weather stations around the study area. The degree of downside spatial basis risk is then estimated by Monte Carlo simulations and the results are linked to both a theoretical model of the demand for index insurance and to farmers’ perceptions about the product.

Suggested Citation

  • 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).
  • Handle: RePEc:fpr:ifprid:1595
    as

    Download full text from publisher

    File URL: http://cdm15738.contentdm.oclc.org/utils/getfile/collection/p15738coll2/id/131033/filename/131244.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ostap Okhrin & Martin Odening & Wei Xu, 2013. "Systemic Weather Risk and Crop Insurance: The Case of China," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(2), pages 351-372, June.
    2. Daniel J. Clarke, 2016. "A Theory of Rational Demand for Index Insurance," American Economic Journal: Microeconomics, American Economic Association, vol. 8(1), pages 283-306, February.
    3. Shawn Cole & Xavier Gine & Jeremy Tobacman & Petia Topalova & Robert Townsend & James Vickery, 2013. "Barriers to Household Risk Management: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 5(1), pages 104-135, January.
    4. Kellner, Ralf & Gatzert, Nadine, 2013. "Estimating the basis risk of index-linked hedging strategies using multivariate extreme value theory," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4353-4367.
    5. Jensen, Nathaniel D. & Mude, Andrew G. & Barrett, Christopher B., 2018. "How basis risk and spatiotemporal adverse selection influence demand for index insurance: Evidence from northern Kenya," Food Policy, Elsevier, vol. 74(C), pages 172-198.
    6. M. Ritter & O. Mußhoff & M. Odening, 2014. "Minimizing Geographical Basis Risk of Weather Derivatives Using A Multi-Site Rainfall Model," Computational Economics, Springer;Society for Computational Economics, vol. 44(1), pages 67-86, June.
    7. Ruth Vargas Hill & John Hoddinott & Neha Kumar, 2013. "Adoption of weather-index insurance: learning from willingness to pay among a panel of households in rural Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 44(4-5), pages 385-398, July.
    8. H. Holly Wang & Hao Zhang, 2003. "On the Possibility of a Private Crop Insurance Market: A Spatial Statistics Approach," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 70(1), pages 111-124, March.
    9. Jing Cai, 2016. "The Impact of Insurance Provision on Household Production and Financial Decisions," American Economic Journal: Economic Policy, American Economic Association, vol. 8(2), pages 44-88, May.
    10. Dercon, Stefan & Hill, Ruth Vargas & Clarke, Daniel & Outes-Leon, Ingo & Seyoum Taffesse, Alemayehu, 2014. "Offering rainfall insurance to informal insurance groups: Evidence from a field experiment in Ethiopia," Journal of Development Economics, Elsevier, vol. 106(C), pages 132-143.
    11. Kousky, Carolyn & Cooke, Roger M., 2009. "The Unholy Trinity: Fat Tails, Tail Dependence, and Micro-Correlations," Discussion Papers dp-09-36-rev.pdf, Resources For the Future.
    12. Mobarak, A. Mushfiq & Rosenzweig, Mark, 2012. "Selling Formal Insurance to the Informally Insured," Working Papers 97, Yale University, Department of Economics.
    13. López Cabrera, Brenda & Odening, Martin & Ritter, Matthias, 2013. "Pricing rainfall futures at the CME," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4286-4298.
    14. Shawn Cole & Xavier Giné & James Vickery, 2017. "How Does Risk Management Influence Production Decisions? Evidence from a Field Experiment," Review of Financial Studies, Society for Financial Studies, vol. 30(6), pages 1935-1970.
    15. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    16. Hill, Ruth Vargas & Robles, Miguel & Ceballos, Francisco, 2013. "Demand for weather hedges in India: An empirical exploration of theoretical predictions:," IFPRI discussion papers 1280, International Food Policy Research Institute (IFPRI).
    17. Peter J. Danaher & Michael S. Smith, 2011. "Modeling Multivariate Distributions Using Copulas: Applications in Marketing," Marketing Science, INFORMS, vol. 30(1), pages 4-21, 01-02.
    18. Martin Odening & Oliver Musshoff & Wei Xu, 2007. "Analysis of rainfall derivatives using daily precipitation models: opportunities and pitfalls," Agricultural Finance Review, Emerald Group Publishing, vol. 67(1), pages 135-156, May.
    19. Barry K. Goodwin & Ashley Hungerford, 2015. "Copula-Based Models of Systemic Risk in U.S. Agriculture: Implications for Crop Insurance and Reinsurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(3), pages 879-896.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ceballos, Francisco & Robles, Miguel, 2020. "Demand heterogeneity for index-based insurance: The case for flexible products," Journal of Development Economics, Elsevier, vol. 146(C).

    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. Takahashi, Kazushi & Noritomo, Yuma & Ikegami, Munenobu & Jensen, Nathaniel D., 2020. "Understanding pastoralists’ dynamic insurance uptake decisions: Evidence from four-year panel data in Ethiopia," Food Policy, Elsevier, vol. 95(C).
    2. Hill, Ruth Vargas & Kumar, Neha & Magnan, Nicholas & Makhija, Simrin & de Nicola, Francesca & Spielman, David J. & Ward, Patrick S., 2019. "Ex ante and ex post effects of hybrid index insurance in Bangladesh," Journal of Development Economics, Elsevier, vol. 136(C), pages 1-17.
    3. Hill, Ruth Vargas & Kumar, Neha & Magnan, Nicholas & Makhija, Simrin & de Nicola, Francesca & Spielman, David J. & Ward, Patrick S., 2017. "Insuring against droughts: Evidence on agricultural intensification and index insurance demand from a randomized evaluation in rural Bangladesh," IFPRI discussion papers 1630, International Food Policy Research Institute (IFPRI).
    4. Glenn W. Harrison & Jia Min Ng, 2019. "Behavioral insurance and economic theory: A literature review," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 22(2), pages 133-182, July.
    5. Platteau, Jean-Philippe & De Bock, Ombeline & Gelade, Wouter, 2017. "The Demand for Microinsurance: A Literature Review," World Development, Elsevier, vol. 94(C), pages 139-156.
    6. Shukri Ahmed & Craig McIntosh & Alexandros Sarris, 2020. "The Impact of Commercial Rainfall Index Insurance: Experimental Evidence from Ethiopia," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1154-1176, August.
    7. Haile, Kaleab K. & Nillesen, Eleonora & Tirivayi, Nyasha, 2020. "Impact of formal climate risk transfer mechanisms on risk-aversion: Empirical evidence from rural Ethiopia," World Development, Elsevier, vol. 130(C).
    8. Petraud, Jean & Boucher, Stephen & Carter, Michael, 2015. "Competing theories of risk preferences and the demand for crop insurance: Experimental evidence from Peru," 2015 Conference, August 9-14, 2015, Milan, Italy 211383, International Association of Agricultural Economists.
    9. Ward, Patrick S. & Kumar, Neha & De Nicola, Francesca & Hill, Ruth & Makhija, Simrin & Spielman, David J. & Magnan, Nicholas, 2017. "Insuring Against Drought: Evidence on Agricultural Intensification and Demand for Index Insurance from a Randomized Evaluation in Rural Bangladesh," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258090, Agricultural and Applied Economics Association.
    10. Negi, Digvijay S., 2018. "Tail-dependent Rainfall Risk and Demand for Index based Crop Insurance," 2018 Annual Meeting, August 5-7, Washington, D.C. 274481, Agricultural and Applied Economics Association.
    11. Sibiko, Kenneth W. & Veettil, Prakashan C. & Qaim, Matin, 2016. "Small Farmers’ Preferences for Weather Index Insurance: Insights from Kenya," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246399, African Association of Agricultural Economists (AAAE).
    12. Jensen, Nathaniel D. & Barrett, Christopher B. & Mude, Andrew G., 2014. "Basis Risk and the Welfare Gains from Index Insurance: Evidence from Northern Kenya," MPRA Paper 59153, University Library of Munich, Germany.
    13. Jensen, Nathaniel D. & Mude, Andrew G. & Barrett, Christopher B., 2018. "How basis risk and spatiotemporal adverse selection influence demand for index insurance: Evidence from northern Kenya," Food Policy, Elsevier, vol. 74(C), pages 172-198.
    14. Ceballos, Francisco & Robles, Miguel, 2020. "Demand heterogeneity for index-based insurance: The case for flexible products," Journal of Development Economics, Elsevier, vol. 146(C).
    15. Gunnsteinsson, Snaebjorn, 2020. "Experimental identification of asymmetric information: Evidence on crop insurance in the Philippines," Journal of Development Economics, Elsevier, vol. 144(C).
    16. Yanyan Liu & Kevin Chen & Ruth V. Hill, 2020. "Delayed Premium Payment, Insurance Adoption, and Household Investment in Rural China," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1177-1197, August.
    17. Lampe, Immanuel & Würtenberger, Daniel, 2020. "Loss aversion and the demand for index insurance," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 678-693.
    18. King, Michael & Singh, Anuj Pratap, 2020. "Understanding farmers’ valuation of agricultural insurance: Evidence from Vietnam," Food Policy, Elsevier, vol. 94(C).
    19. Ayako Matsuda & Takashi Kurosaki, 2017. "Temperature and Rainfall Index Insurance in India," OSIPP Discussion Paper 17E002, Osaka School of International Public Policy, Osaka University.
    20. Dougherty, John P. & Flatnes, Jon Einar & Gallenstein, Richard A. & Miranda, Mario J. & Sam, Abdoul G., 2020. "Climate change and index insurance demand: Evidence from a framed field experiment in Tanzania," Journal of Economic Behavior & Organization, Elsevier, vol. 175(C), pages 155-184.

    More about this item

    Keywords

    rain; rainfall patterns; insurance; weather; precipitation; risk management;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:fpr:ifprid:1595. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/ifprius.html .

    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: (email available below). General contact details of provider: https://edirc.repec.org/data/ifprius.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.