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Estimating Non-linear Weather Impacts on Corn Yield—A Bayesian Approach

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  • Yu, Tian
  • Babcock, Bruce A.

Abstract

We estimate impacts of rainfall and temperature on corn yields by fitting a linear spline model with endogenous thresholds. Using Gibbs sampling and the Metropolis - Hastings algorithm, we simultaneously estimate the thresholds and other model parameters. A hierarchical structure is applied to capture county-specific factors determining corn yields. Results indicate that impacts of both rainfall and temperature are nonlinear and asymmetric in most states. Yield is concave in both weather variables. Corn yield decreases significantly when temperature increases beyond a certain threshold, and when the amount of rainfall decreases below a certain threshold. Flooding is another source of yield loss in some states. A moderate amount of heat is beneficial to corn yield in northern states, but not in other states. Both the levels of the thresholds and the magnitudes of the weather effects are estimated to be different across states in the Corn Belt.

Suggested Citation

  • Yu, Tian & Babcock, Bruce A., 2011. "Estimating Non-linear Weather Impacts on Corn Yield—A Bayesian Approach," Hebrew University of Jerusalem Archive 103915, Hebrew University of Jerusalem.
    • Handle: RePEc:ags:hebarc:103915
    DOI: 10.22004/ag.econ.103915
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    1. 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.
    2. 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.
    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. 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.
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    More about this item

    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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