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Estimating the Effects of Weather Variations on Corn Yields using Geographically Weighted Panel Regression

Author

Listed:
  • Cai, Ruohong
  • Yu, Danlin
  • Oppenheimer, Michael

Abstract

Through a geographically weighted panel regression analysis, we demonstrate the spatially varying relationship between weather and corn yields. A balanced panel data of 958 U.S. corn production counties for the period 2002-2006 is used. The results indicate that the relationship between weather and corn yield has large spatial variability. In specific, temperature tends to have negative marginal effects on corn yield in warmer regions, and positive effects in cooler regions. The spatial pattern of precipitation effects is more complicated since it is expected to be largely affected by local irrigation systems.

Suggested Citation

  • Cai, Ruohong & Yu, Danlin & Oppenheimer, Michael, 2012. "Estimating the Effects of Weather Variations on Corn Yields using Geographically Weighted Panel Regression," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124627, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea12:124627
    DOI: 10.22004/ag.econ.124627
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    File URL: https://ageconsearch.umn.edu/record/124627/files/Estimating%20the%20Effects%20of%20Weather%20Variations%20on%20Corn%20Yields%20using%20Geographically%20Weighted%20Panel%20Regression.pdf
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    Cited by:

    1. Xiaoping Zhou & Zhenyang Qin & Yingjie Zhang & Linyi Zhao & Yan Song, 2019. "Quantitative Estimation and Spatiotemporal Characteristic Analysis of Price Deviation in China's Housing Market," Sustainability, MDPI, vol. 11(24), pages 1-28, December.
    2. Wrenn, Douglas H. & Sam, Abdoul G., 2014. "Geographically and temporally weighted likelihood regression: Exploring the spatiotemporal determinants of land use change," Regional Science and Urban Economics, Elsevier, vol. 44(C), pages 60-74.
    3. O’Donoghue, Cathal & McKinstry, Alistair & Green, Stuart & Fealy, Reamonn & Heanue, Kevin & Ryan, Mary & Connolly, Kevin & Desplat, J.C. & Horan, Brendan, 2016. "A Blueprint for a Big Data Analytical Solution to Low Farmer Engagement with Financial Management," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(A), pages 1-24, June.

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