Estimating the Effects of Weather Variations on Corn Yields using Geographically Weighted Panel Regression
AbstractThrough 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.
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Bibliographic InfoPaper provided by Agricultural and Applied Economics Association in its series 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington with number 124627.
Date of creation: 2012
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Geographically weighted panel regression; Climate change; Corn yields; Crop Production/Industries; Research Methods/ Statistical Methods; Resource /Energy Economics and Policy;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-06-25 (All new papers)
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- 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.
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