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Estimating the Spatially Varying Responses of Corn Yields toWeather Variations using GeographicallyWeighted Panel Regression

Researchers have extensively studied crop yield response to weather variations, while only a limited number of studies have attempted to identify spatial heterogeneity in this relationship. We explore spatial heterogeneity in corn yield response to weather by combining geographically weighted regression and panel regression. We find that temperature tends to have negative effects on U.S. corn yields in warmer regions and positive effects in cooler regions, with spatial heterogeneity at a fine scale. The spatial pattern of precipitation effects is more complicated. A further analysis shows that precipitation effects are sensitive to the existence of irrigation systems.
- Environmental Defense Fund United States
- Environmental Defense Fund United States
- Minjiang University China (People's Republic of)
- Montclair State University United States
- Minjiang University China (People's Republic of)
S, corn yields, spatial heterogeneity, crop yields, geographically weighted panel regressions, Agriculture, Crop Production/Industries, climate change, Environmental Economics and Policy, climate change, corn yields, geographically weighted panel regression, spatial heterogeneity, Crop Production/Industries, Environmental Economics and Policy,, geographically weighted panel regression
S, corn yields, spatial heterogeneity, crop yields, geographically weighted panel regressions, Agriculture, Crop Production/Industries, climate change, Environmental Economics and Policy, climate change, corn yields, geographically weighted panel regression, spatial heterogeneity, Crop Production/Industries, Environmental Economics and Policy,, geographically weighted panel regression
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).21 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
