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Identifying climatic constraints of US agriculture

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  • Ortiz-Bobea, Ariel
  • Kim, Do-Hyung
  • Chen, Yanyou

Abstract

The paper estimates the countervailing climatic factors driving the timing of US corn planting decisions. We combine very diverse sources of data, including daily fine-scale satellite-derived information, to infer the timing of planting decisions over the past 30 years at the county-level. We match this information with daily data on temperature and soil moisture conditions to assess their contributions to the planting decision. Using a panel logit model we find that warmer spring temperatures increase the probability of planting, while extremely low or high levels of moisture reduce it. We find that the levels of moisture necessary to fully offset the season-expanding effect of a temperature rise of 3ºC would need to be very extreme, suggesting that the growing season for corn is likely to expand with climate change.

Suggested Citation

  • Ortiz-Bobea, Ariel & Kim, Do-Hyung & Chen, Yanyou, "undated". "Identifying climatic constraints of US agriculture," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170674, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea14:170674
    DOI: 10.22004/ag.econ.170674
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    References listed on IDEAS

    as
    1. Stehfest, Elke & Heistermann, Maik & Priess, Joerg A. & Ojima, Dennis S. & Alcamo, Joseph, 2007. "Simulation of global crop production with the ecosystem model DayCent," Ecological Modelling, Elsevier, vol. 209(2), pages 203-219.
    2. Ariel Ortiz-Bobea & Richard E. Just, 2013. "Modeling the Structure of Adaptation in Climate Change Impact Assessment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 244-251.
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    Keywords

    Crop Production/Industries; Environmental Economics and Policy;

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