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Three essays on weather and crop yield

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  • Yu, Tian

Abstract

The general theme of this dissertation is the study of impacts of weather variability on crop yields, with each chapter addressing a specific topic related to this theme. Chapter 2 tests the hypothesis that corn and soybeans have become more drought tolerant by regressing county yields on a drought index and time. Results indicate that corn yield losses from drought of a given severity, whether measured in quantity terms or as a percentage of mean yields, have decreased over time. Soybean percentage yield losses have also declined but absolute losses have remained largely constant. The potential impact of increased drought tolerance on U.S. crop insurance rates is illustrated by comparing Group Risk Plan (GRP) premium rates assuming time-invariant susceptibility to drought with rates generated from regression results in this dissertation. Chapter 3 develops a linear spline model with endogenous knots to capture the non-linear impacts of rainfall and temperature on corn yields. A hierarchical structure is applied to capture the county-specific factors determining corn yields. Using Bayesian techniques, the thresholds and other model parameters are simultaneously estimated. Gibbs sampling and the Metropolis - Hastings algorithm are applied to estimate the posterior distributions. Corn yield decreases significantly above the upper temperature threshold and below the lower rainfall threshold. Results indicate a geographically clustering pattern of how corn yields respond to changes in temperature and rainfall. Chapter 4 applies the linear spline yield model developed in chapter 3 to examine weather impacts on yield trend, yield risk, and the distribution of corn yield. The climate trend from 1980 to 2009 explains up to 20% of observed yield trend. Not controlling for temporal weather patters leads to biased trend estimates, especially for short times series. Isolating changes in weather variability in the sample period, the hypothesis of constant coefficient of variation is rejected in most states in the Corn Belt. Decreasing marginal benefit of weather partly explains why corn yield is negatively skewed. Conditional on weather, the distribution of unexplained residuals from our yield model is symmetric in general.

Suggested Citation

  • Yu, Tian, 2011. "Three essays on weather and crop yield," ISU General Staff Papers 201101010800002976, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genstf:201101010800002976
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    1. Hennessy, David A., 2009. "Crop Yield Skewness and the Normal Distribution," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), pages 1-19, April.
    2. Xiaodong Du & David A. Hennessy & Cindy L. Yu, 2012. "Testing Day's Conjecture that More Nitrogen Decreases Crop Yield Skewness," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(1), pages 225-237.
    3. Olivier Deschênes & Michael Greenstone, 2007. "The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather," American Economic Review, American Economic Association, vol. 97(1), pages 354-385, March.
    4. Charles B. Moss & J. S. Shonkwiler, 1993. "Estimating Yield Distributions with a Stochastic Trend and Nonnormal Errors," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(4), pages 1056-1062.
    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. Jerry R. Skees & J. Roy Black & Barry J. Barnett, 1997. "Designing and Rating an Area Yield Crop Insurance Contract," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 430-438.
    7. 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.
    8. Carl H. Nelson & Paul V. Preckel, 1989. "The Conditional Beta Distribution as a Stochastic Production Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 370-378.
    9. David A. Hennessy, 2009. "Crop Yield Skewness Under Law of the Minimum Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 197-208.
    10. Wolfram Schlenker & Michael J. Roberts, 2006. "Nonlinear Effects of Weather on Corn Yields," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 28(3), pages 391-398.
    11. Arellano, M, 1987. "Computing Robust Standard Errors for Within-Groups Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 431-434, November.
    12. Paul Gallagher, 1987. "U.S. Soybean Yields: Estimation and Forecasting with Nonsymmetric Disturbances," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(4), pages 796-803.
    13. Daniel O'Brien & Marvin Hayenga & Bruce Babcock, 1996. "Deriving Forecast Probability Distributions of Harvest-Time Corn Futures Prices," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 18(2), pages 167-180.
    14. Gallagher, Paul W., 1987. "U.S. Soybean Yields: Estimation and Forecasting with Non-Symmetric Disturbances," Staff General Research Papers Archive 10779, Iowa State University, Department of Economics.
    15. Joshua D. Woodard & Gary D. Schnitkey & Bruce J. Sherrick & Nancy Lozano‐Gracia & Luc Anselin, 2012. "A Spatial Econometric Analysis of Loss Experience in the U.S. Crop Insurance Program," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 79(1), pages 261-286, March.
    16. Wolfram Schlenker & W. Michael Hanemann & Anthony C. Fisher, 2006. "The Impact of Global Warming on U.S. Agriculture: An Econometric Analysis of Optimal Growing Conditions," The Review of Economics and Statistics, MIT Press, vol. 88(1), pages 113-125, February.
    17. 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.
    18. Tian Yu & Bruce A. Babcock, 2010. "Are U.S. Corn and Soybeans Becoming More Drought Tolerant?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1310-1323.
    19. 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.
    20. Bruce A. McCarl & Xavier Villavicencio & Ximing Wu, 2008. "Climate Change and Future Analysis: Is Stationarity Dying?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(5), pages 1241-1247.
    21. -, 2009. "The economics of climate change," Sede Subregional de la CEPAL para el Caribe (Estudios e Investigaciones) 38679, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    22. Schnitkey, Gary, 2011. "Crop Insurance in 2011," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 1, March.
    23. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
    24. Neville Nicholls, 1997. "Increased Australian wheat yield due to recent climate trends," Nature, Nature, vol. 387(6632), pages 484-485, May.
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