IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v36y2016i1p57-73.html
   My bibliography  Save this article

An Empirical, Nonparametric Simulator for Multivariate Random Variables with Differing Marginal Densities and Nonlinear Dependence with Hydroclimatic Applications

Author

Listed:
  • Upmanu Lall
  • Naresh Devineni
  • Yasir Kaheil

Abstract

Multivariate simulations of a set of random variables are often needed for risk analysis. Given a historical data set, the goal is to develop simulations that reproduce the dependence structure in that data set so that the risk of potentially correlated factors can be evaluated. A nonparametric, copula‐based simulation approach is developed and exemplified. It can be applied to multiple variables or to spatial fields with arbitrary dependence structures and marginal densities. The nonparametric simulator uses logspline density estimation in the univariate setting, together with a sampling strategy to reproduce dependence across variables or spatial instances, through a nonparametric numerical approximation of the underlying copula function. The multivariate data vectors are assumed to be independent and identically distributed. A synthetic example is provided to illustrate the method, followed by an application to the risk of livestock losses in Mongolia.

Suggested Citation

  • Upmanu Lall & Naresh Devineni & Yasir Kaheil, 2016. "An Empirical, Nonparametric Simulator for Multivariate Random Variables with Differing Marginal Densities and Nonlinear Dependence with Hydroclimatic Applications," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 57-73, January.
    • Handle: RePEc:wly:riskan:v:36:y:2016:i:1:p:57-73
    DOI: 10.1111/risa.12432
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/risa.12432
    Download Restriction: no
    File URL: https://libkey.io/10.1111/risa.12432?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, October.
    2. Turvey, Calum G. & Zhao, Jinhua, 1999. "Parametric And Non-Parametric Crop Yield Distributions And Their Effects On All-Risk Crop Insurance Premiums," Working Papers 34129, University of Guelph, Department of Food, Agricultural and Resource Economics.
    3. Kooperberg, Charles & Stone, Charles J., 1991. "A study of logspline density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 12(3), pages 327-347, November.
    4. Mahul, Olivier & Skees, Jerry, 2007. "Managing agricultural risk at the country level : the case of index-based livestock insurance in Mongolia," Policy Research Working Paper Series 4325, The World Bank.
    5. Vitor Ozaki & Barry Goodwin & Ricardo Shirota, 2008. "Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts," Applied Economics, Taylor & Francis Journals, vol. 40(9), pages 1151-1164.
    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. Dias, Ronaldo & Garcia, Nancy L., 2007. "Consistent estimator for basis selection based on a proxy of the Kullback-Leibler distance," Journal of Econometrics, Elsevier, vol. 141(1), pages 167-178, November.
    2. Ozaki, Vitor & Campos, Rogério, 2017. "Reduzindo a Incerteza no Mercado de Seguros: Uma Abordagem via Informações de Sensoriamento Remoto e Atuária," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 71(4), December.
    3. Ghahremanzadeh, Mohammad & Mohammadrezaei, Rassul & Dashti, Ghader & Ainollahi, Moharram, 2018. "Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 17(02), January.
    4. Li, Hong & Porth, Lysa & Tan, Ken Seng & Zhu, Wenjun, 2021. "Improved index insurance design and yield estimation using a dynamic factor forecasting approach," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 208-221.
    5. Qiujie Zheng & H. Holly Wang & Qing Hua Shi, 2014. "Estimating bivariate yield distributions and crop insurance premiums using nonparametric methods," Applied Economics, Taylor & Francis Journals, vol. 46(18), pages 2108-2118, June.
    6. repec:spo:wpmain:info:hdl:2441/7182 is not listed on IDEAS
    7. Sebastian Weber, 2009. "European Financial Market Integration: A Closer Look at Government Bonds in Eurozone Countries," Working Paper / FINESS 1.1b, DIW Berlin, German Institute for Economic Research.
    8. Harding, Don & Pagan, Adrian, 2011. "An Econometric Analysis of Some Models for Constructed Binary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 86-95.
    9. Menzel, Konrad, 2014. "Consistent estimation with many moment inequalities," Journal of Econometrics, Elsevier, vol. 182(2), pages 329-350.
    10. Ural Marchand, Beyza, 2012. "Tariff pass-through and the distributional effects of trade liberalization," Journal of Development Economics, Elsevier, vol. 99(2), pages 265-281.
    11. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    12. Daniel Buncic, 2012. "Understanding forecast failure of ESTAR models of real exchange rates," Empirical Economics, Springer, vol. 43(1), pages 399-426, August.
    13. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    14. David Fairris & Gurleen Popli & Eduardo Zepeda, 2008. "Minimum Wages and the Wage Structure in Mexico," Review of Social Economy, Taylor & Francis Journals, vol. 66(2), pages 181-208.
    15. Javier Parada Gómez Urquiza & Alejandro López-Feldman, 2013. "Poverty dynamics in rural Mexico: What does the future hold?," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 55-74, November.
    16. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    17. Joseph G. Altonji & Rosa L. Matzkin, 2001. "Panel Data Estimators for Nonseparable Models with Endogenous Regressors," NBER Technical Working Papers 0267, National Bureau of Economic Research, Inc.
    18. Inanoglu, Hulusi & Jacobs, Michael, Jr. & Liu, Junrong & Sickles, Robin, 2015. "Analyzing Bank Efficiency: Are "Too-Big-to-Fail" Banks Efficient?," Working Papers 15-016, Rice University, Department of Economics.
    19. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Robert Breunig & Alison Stegman, 2005. "Testing For Regime Switching In Singaporean Business Cycles," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 50(01), pages 25-34.
    21. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.

    More about this item

    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:wly:riskan:v:36:y:2016:i:1:p:57-73. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    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.