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The Impact of Climate Change on U.S. Agriculture: The Roles of Adaptation Techniques and Emissions Reductions

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  • Timothy Neal

    (UNSW School of Economics)

  • Michael Keane

    (UNSW School of Economics)

Abstract

We investigate the impact of climate change on U.S. agricultural productivity using county-level yield and weather data from 1950 to 2015. We present two new methods of modelling how producers adapt agricultural techniques to harsh temperatures, including a new panel data estimator that allows for two-dimensional fixed-effects in slopes. We find evidence of adaptation to geographic and temporal variation in climate, but it has stalled since 1989. We show that adaptation implies fixed-effects slope heterogeneity in the relationship between crop yield and temperature, and ignoring this leads to biased estimates of temperature sensitivity. We use our estimates to project corn yields to 2100 using a variety of climate models and emission scenarios, and find that unmitigated climate change will have severe effects on yields. Our models indicate that adaptation techniques can mitigate 10 to 45% of the damage, but significant emissions reductions can mitigate far more (i.e., 42 to 91%).

Suggested Citation

  • Timothy Neal & Michael Keane, 2018. "The Impact of Climate Change on U.S. Agriculture: The Roles of Adaptation Techniques and Emissions Reductions," Discussion Papers 2018-08, School of Economics, The University of New South Wales.
    • Handle: RePEc:swe:wpaper:2018-08
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2018-08.pdf
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    References listed on IDEAS

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    1. Olivier Deschênes & Michael Greenstone, 2011. "Climate Change, Mortality, and Adaptation: Evidence from Annual Fluctuations in Weather in the US," American Economic Journal: Applied Economics, American Economic Association, vol. 3(4), pages 152-185, October.
    2. Timothy Neal, 2016. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15, School of Economics, The University of New South Wales.
    3. Marshall Burke & Kyle Emerick, 2016. "Adaptation to Climate Change: Evidence from US Agriculture," American Economic Journal: Economic Policy, American Economic Association, vol. 8(3), pages 106-140, August.
    4. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
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    6. David B. Lobell & Graeme L. Hammer & Greg McLean & Carlos Messina & Michael J. Roberts & Wolfram Schlenker, 2013. "The critical role of extreme heat for maize production in the United States," Nature Climate Change, Nature, vol. 3(5), pages 497-501, May.
    7. Maximilian Auffhammer & Solomon M. Hsiang & Wolfram Schlenker & Adam Sobel, 2013. "Using Weather Data and Climate Model Output in Economic Analyses of Climate Change," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 7(2), pages 181-198, July.
    8. Kentaro Kawasaki & Shinsuke Uchida, 2016. "Quality Matters More Than Quantity: Asymmetric Temperature Effects on Crop Yield and Quality Grade," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 1195-1209.
    9. Olivier Deschênes & Michael Greenstone, 2007. "The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather," American Economic Review, American Economic Association, vol. 97(1), pages 354-385, March.
    10. Michael J. Roberts & Wolfram Schlenker, 2011. "Is Agricultural Production Becoming More or Less Sensitive to Extreme Heat? Evidence from U.S. Corn and Soybean Yields," NBER Chapters, in: The Design and Implementation of US Climate Policy, pages 271-282, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Timothy Neal, 2016. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15, School of Economics, The University of New South Wales.

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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • 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
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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