IDEAS home Printed from https://ideas.repec.org/a/oup/revage/v31y2009i1p163-182.html
   My bibliography  Save this article

Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality

Author

Listed:
  • Ardian Harri
  • Cumhur Erdem
  • Keith H. Coble
  • Thomas O. Knight

Abstract

This study revisits the large but inconclusive body of research on crop yield distributions. Using competing techniques across 3,852 crop/county combinations we can reconcile some inconsistencies in previous studies. We examine linear, polynomial, and ARIMA trend models. Normality tests are undertaken, with an implementable R-test and multivariate testing to account for spatial correlation. Empirical results show limited support for stochastic trends in yields. Results also show that normality rejection rates depend on the trend specification. Corn Belt corn and soybeans yields are negatively skewed while they tend to become more normal as one moves away from the Corn Belt. Copyright 2009, Oxford University Press.

Suggested Citation

  • Ardian Harri & Cumhur Erdem & Keith H. Coble & Thomas O. Knight, 2009. "Crop Yield Distributions: A Reconciliation of Previous Research and Statistical Tests for Normality," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(1), pages 163-182.
    • Handle: RePEc:oup:revage:v:31:y:2009:i:1:p:163-182
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1467-9353.2008.01431.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. C. Robert Taylor, 1990. "Two Practical Procedures for Estimating Multivariate Nonnormal Probability Density Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(1), pages 210-217.
    2. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    3. Octavio A. Ramírez, 1997. "Estimation and Use of a Multivariate Parametric Model for Simulating Heteroskedastic, Correlated, Nonnormal Random Variables: The Case of Corn Belt Corn, Soybean, and Wheat Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 191-205.
    4. Bailey Norwood & Matthew C. Roberts & Jayson L. Lusk, 2004. "Ranking Crop Yield Models Using Out-of-Sample Likelihood Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1032-1043.
    5. 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.
    6. Bessler, David A., 1982. "Adaptive Expectations, the Exponentially Weighted Forecast, and Optimal Statistical Predictors: A Revisit," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 34(2), pages 1-8, April.
    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. Lu, Yue & Ramirez, Octavio A. & Rejesus, Roderick M. & Knight, Thomas O. & Sherrick, Bruce J., 2008. "Empirically Evaluating the Flexibility of the Johnson Family of Distributions: A Crop Insurance Application," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 37(1), pages 1-13, April.
    2. Zheng, Qiujie & Wang, H. Holly & Shi, Qinghua, 2008. "Estimating Farm Level Multivariate Yield Distribution Using Nonparametric Methods," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6509, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Ramirez, Octavio & Shonkwiler, J. Scott, 2016. "Some Comparative Statics for Evaluating the Performance of the US Crop Insurance Program," SCC-76 Meeting, 2016, March 17-19, Pensacola, Florida 233761, SCC-76: Economics and Management of Risk in Agriculture and Natural Resources.
    4. Kapiamba, Luabeya F., 2005. "Modeling Heteroskedasticity of Crop Yield Distributions: Implications for Normality," 2005 Annual meeting, July 24-27, Providence, RI 19475, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Park, Eunchun & Brorsen, B. Wade & Harri, Ardian, 2016. "Using Bayesian Spatial Smoothing and Extreme Value Theory to Develop Area-Yield Crop Insurance Rating," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235754, Agricultural and Applied Economics Association.
    6. Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2008. "Shape Persistence in Elicited Subjective Crop Yield Probability Density Functions," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44128, European Association of Agricultural Economists.
    7. Ramirez, Octavio A. & Shonkwiler, J. Scott, 2017. "A Probabilistic Model of Crop Insurance Purchase Decision," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(1), pages 1-17, January.
    8. 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.
    9. Tor N. Tolhurst & Alan P. Ker, 2015. "On Technological Change in Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(1), pages 137-158.
    10. Ramirez, Octavio A. & McDonald, Tanya U., 2006. "The Expanded Johnson System: A Highly Flexible Crop Yield Distribution Model," 2006 Annual meeting, July 23-26, Long Beach, CA 21455, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. 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.
    12. Clop-Gallart, M. Merce & Juarez-Rubio, Francisco, 2005. "Elicitation of Subjective Crop Yield PDF for DSS Implementation," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24561, European Association of Agricultural Economists.
    13. Zanini, Fabio C. & Irwin, Scott H. & Schnitkey, Gary D. & Sherrick, Bruce J., 2000. "Estimating Farm-Level Yield Distributions For Corn And Soybeans In Illinois," 2000 Annual meeting, July 30-August 2, Tampa, FL 21720, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    14. Chen, Shu-Ling & Miranda, Mario J., 2006. "Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton," 2006 Annual meeting, July 23-26, Long Beach, CA 21392, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    15. Arora, Gaurav & Agarwal, Sandip K., 2020. "Agricultural input use and index insurance adoption: Concept and evidence," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304508, Agricultural and Applied Economics Association.
    16. Ramirez, Octavio A. & Carpio, Carlos E. & Rejesus, Roderick M., 2011. "Can Crop Insurance Premiums Be Reliably Estimated?," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 40(1), pages 1-14, April.
    17. Yong Liu & Alan P. Ker, 2021. "Simultaneous borrowing of information across space and time for pricing insurance contracts: An application to rating crop insurance policies," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 231-257, March.
    18. Liu, Y. & Ker, A., 2018. "Is There Too Much History in Historical Yield Data," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277293, International Association of Agricultural Economists.
    19. Du, Xiaodong & Dong, Fengxia, 2024. "Climate Change and Dynamics of Crop Yield Distribution," 2024 Annual Meeting, July 28-30, New Orleans, LA 343786, Agricultural and Applied Economics Association.
    20. Octavio A. Ramirez & Carlos A. Carpio, 2012. "Premium estimation inaccuracy and the actuarial performance of the US crop insurance program," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 72(1), pages 117-133, May.

    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:oup:revage:v:31:y:2009:i:1:p:163-182. 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: Oxford University Press or Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    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.