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dc.contributor.authorMcFadden, Jonathan R.eng
dc.contributor.authorMiranowski, John A.eng
dc.date.issued2016eng
dc.description.abstractAlthough prior research has identified the effects of climate change on crop yields, there has been little consideration of outliers, structural change, information decay, and model complexity. To incorporate these features and regional productivity heterogeneity, we estimate Bayesian dynamic regressions of corn and soybean yields for Iowa, Illinois, and Nebraska. Corn yield growth of 7-26% and soybean yield growth of up to 32% over 2011 averages are forecasted by 2031. We find asymmetries in the evolution of weather effects across states and crops. Current impacts of monthly growing-season temperature and precipitation differ greatly from impacts during 1970-1999. We also observe a shift in importance from July temperatures to August temperatures, as well as a shift from average precipitation to intense precipitation. The changing time paths of weather impacts and associated yield forecasts have key adaptation implications. In turn, these could affect the long-run sustainability of the Midwestern bioeconomy.eng
dc.identifier.urihttps://hdl.handle.net/10355/59575
dc.languageEnglisheng
dc.publisherUniversity of Missourieng
dc.relation.ispartofcollectionAgBioForum, vol. 19, no. 2 (2016)eng
dc.relation.ispartofcommunityUniversity of Missouri-Columbia. College of Food, Agriculture and Natural Resources. Division of Applied Social Sciences. Department of Agricultural Economics. Economics and Management of Agrobiotechnology Center. AgBioForum.eng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.subjectagricultural yieldseng
dc.subjectBayesian dynamic modelseng
dc.subjectbioeconomyeng
dc.subjectclimate changeeng
dc.titleClimate change : challenge and opportunity to maintain sustainable productivity growth and environment in a corn-soybean bioeconomyeng
dc.typeArticleeng


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