Understanding Temperature and Moisture Interactions in the Economics of Climate Change Impacts and Adaptation on Agriculture
AbstractGrowing econometric and statistical evidence points to high temperature as the main driver of large negative effects of climate change on US agriculture. This literature also suggests a limited role for precipitation in overall impacts. This paper shows this finding stems from the widespread use of calendar precipitation variables, which poorly represent water availability for rainfed crops. I rely on a state-of-the art dataset with very high spatial (14km) and temporal (1h) resolution to develop a statistical model and unpack the effects of temperature and drought stress and analyze their interactions. Using a 31-year panel of corn yields covering 70% of US production, I account for nonlinear effects of soil moisture with varying effects throughout the growing season, in addition to nonlinear temperature effects. I show that yield is highly sensitive to soil moisture toward the middle of the season around flowering time. Results show that omission of soil moisture leads to overestimation of the detrimental effects of temperature by 30%. Because climate change affects intra-seasonal soil moisture and temperature patterns differently, this omission also leads to very different impacts on US corn yields, with a much greater role for water resources in overall impacts. Under the medium warming scenario (RCP6), models omitting soil moisture overestimate yield impacts by almost 100%. The approach shows a more complete understanding that climate change impacts on agriculture are likely to be driven by both heat and drought stresses, and that their relative role can vary depending on the climate change scenario and farmer ability to adapt.
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Bibliographic InfoPaper provided by Agricultural and Applied Economics Association in its series 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. with number 150435.
Date of creation: 03 Jun 2013
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climate change; agriculture; impacts; adaptation; drought; temperature stress; nonlinear effects; omitted variable bias; spatial error panel model; Agricultural and Food Policy; Environmental Economics and Policy; Research and Development/Tech Change/Emerging Technologies; Research Methods/ Statistical Methods; Q54; Q15; Q51; R15;
Find related papers by JEL classification:
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters
- Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
- Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
- R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
This paper has been announced in the following NEP Reports:
- NEP-AGR-2013-06-24 (Agricultural Economics)
- NEP-ALL-2013-06-24 (All new papers)
- NEP-ENV-2013-06-24 (Environmental Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- 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.
- Chen, Shuai & Chen, Xiaoguang & Xu, Jintao, 2014. "Impacts of Climate Change on Agriculture: Evidence from China," Discussion Papers dp-14-07-efd, Resources For the Future.
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