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Spatially Smoothed Kernel Densities with Application to Crop Yield Distributions

Author

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  • Kuangyu Wen

    (Huazhong University of Science and Technology)

  • Ximing Wu

    (Texas A&M University)

  • David J. Leatham

    (Texas A&M University)

Abstract

This study is motivated by the estimation of many crop yield densities, each with a small number of observations. These densities tend to resemble one another if they are spatially proximate. To gain flexibility and improve efficiency, we propose kernel-based estimators refined by empirical likelihood probability weights derived under spatially smoothed moment conditions. We construct spatially smoothed moments based on spline functions, which are robust to outliers and readily customizable. We use these methods to estimate the corn yield distributions of Iowa counties and to predict the premiums of crop insurance programs. Monte Carlo simulations and an empirical application demonstrate the good performance and usefulness of the proposed methods.

Suggested Citation

  • Kuangyu Wen & Ximing Wu & David J. Leatham, 2021. "Spatially Smoothed Kernel Densities with Application to Crop Yield Distributions," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 349-366, September.
    • Handle: RePEc:spr:jagbes:v:26:y:2021:i:3:d:10.1007_s13253-021-00442-6
    DOI: 10.1007/s13253-021-00442-6
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    1. Biao Zhang, 1997. "Quantile Processes in the Presence of Auxiliary Information," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 49(1), pages 35-55, March.
    2. Peter Robinson, 2011. "Asymptotic theory for nonparametric regression with spatial data," CeMMAP working papers CWP11/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Carbon, Michel & Tran, Lanh Tat & Wu, Berlin, 1997. "Kernel density estimation for random fields (density estimation for random fields)," Statistics & Probability Letters, Elsevier, vol. 36(2), pages 115-125, December.
    4. Iversen, Edwin S, Jr, 2001. "Spatially Disaggregated Real Estate Indices," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 341-357, July.
    5. Peter C. B. Phillips, 2001. "Descriptive econometrics for non-stationary time series with empirical illustrations," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 389-413.
    6. Badi H. Baltagi & Georges Bresson & Jean‐Michel Etienne, 2015. "Hedonic Housing Prices in Paris: An Unbalanced Spatial Lag Pseudo‐Panel Model with Nested Random Effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 509-528, April.
    7. Lu, Zudi & Chen, Xing, 2004. "Spatial kernel regression estimation: weak consistency," Statistics & Probability Letters, Elsevier, vol. 68(2), pages 125-136, June.
    8. Ani Eloyan & Sujit Ghosh, 2011. "Smooth density estimation with moment constraints using mixture distributions," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 513-531.
    9. Ardian Harri & Keith H. Coble & Alan P. Ker & Barry J. Goodwin, 2011. "Relaxing Heteroscedasticity Assumptions in Area-Yield Crop Insurance Rating," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(3), pages 703-713.
    10. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
    11. Lee, Y. K. & Choi, H. & Park, B. U. & Yu, K. S., 2004. "Local likelihood density estimation on random fields," Statistics & Probability Letters, Elsevier, vol. 68(4), pages 347-357, July.
    12. Hallin, Marc & Lu, Zudi & Tran, Lanh T., 2004. "Kernel density estimation for spatial processes: the L1 theory," Journal of Multivariate Analysis, Elsevier, vol. 88(1), pages 61-75, January.
    13. Jesús Crespo Cuaresma & Martin Feldkircher, 2013. "Spatial Filtering, Model Uncertainty And The Speed Of Income Convergence In Europe," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 720-741, June.
    14. Robinson, P.M., 2011. "Asymptotic theory for nonparametric regression with spatial data," Journal of Econometrics, Elsevier, vol. 165(1), pages 5-19.
    15. Ryan R. Brady, 2011. "Measuring the diffusion of housing prices across space and over time," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(2), pages 213-231, March.
    16. Alan P. Ker & Tor N. Tolhurst & Yong Liu, 2016. "Bayesian Estimation of Possibly Similar Yield Densities: Implications for Rating Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(2), pages 360-382.
    17. Badi H. Baltagi & Jing Li, 2014. "Further Evidence On The Spatio‐Temporal Model Of House Prices In The United States," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(3), pages 515-522, April.
    18. Marc Hallin & Zudi Lu & Lanh T. Tran, 2001. "Density estimation for spatial linear processes," ULB Institutional Repository 2013/2109, ULB -- Universite Libre de Bruxelles.
    19. Tran, Lanh Tat, 1990. "Kernel density estimation on random fields," Journal of Multivariate Analysis, Elsevier, vol. 34(1), pages 37-53, July.
    20. Banerjee S. & Gelfand A.E. & Knight J.R. & Sirmans C.F., 2004. "Spatial Modeling of House Prices Using Normalized Distance-Weighted Sums," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 206-213, April.
    21. Eunchun Park & B Wade Brorsen & Ardian Harri, 2019. "Using Bayesian Kriging for Spatial Smoothing in Crop Insurance Rating," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(1), pages 330-351.
    22. Marc Hallin & Zudi Lu & Lanh T. Tran, 2004. "Local linear spatial regression," ULB Institutional Repository 2013/2131, ULB -- Universite Libre de Bruxelles.
    23. Majumdar, Anandamayee & Munneke, Henry J. & Gelfand, Alan E. & Banerjee, Sudipto & Sirmans, C.F., 2006. "Gradients in Spatial Response Surfaces With Application to Urban Land Values," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 77-90, January.
    24. Zhengyan Lin & Degui Li & Jiti Gao, 2009. "Local Linear M‐estimation in non‐parametric spatial regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 286-314, May.
    25. 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.
    26. Vitor Ozaki & Ralph Silva, 2009. "Bayesian ratemaking procedure of crop insurance contracts with skewed distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(4), pages 443-452.
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    1. repec:ags:aaea22:335759 is not listed on IDEAS
    2. Kuangyu Wen, 2023. "A semiparametric spatio‐temporal model of crop yield trend and its implication to insurance rating," Agricultural Economics, International Association of Agricultural Economists, vol. 54(5), pages 662-673, September.

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