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The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Bias in Ricardian Models of Farm Land Values

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  • Carlo Fezzi

    (Department of Economics, University of California and CSERGE (School of Environmental Sciences), University of East Anglia)

  • Ian Bateman

    (CSERGE (School of Environmental Sciences), University of East Anglia)

Abstract

Ricardian (hedonic) analyses of the impact of climate change on farmland values typically assume additively separable effects of temperature and precipitation. Model estimation is implemented on data aggregated across counties or large regions. We investigate the potential bias induced by such approaches by using a large panel of farm-level data. Consistent with the literature on plant physiology, we observe significant non-linear interaction effects, with more abundant precipitation acting as a mitigating factor for increased heat stress. This interaction disappears when the same data is aggregated in the conventional manner, leading to predictions of climate change impacts which are significantly distorted.

Suggested Citation

  • Carlo Fezzi & Ian Bateman, 2013. "The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Bias in Ricardian Models of Farm Land Values," Working Papers 2013.94, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2013.94
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    Cited by:

    1. Ingmar Schumacher, 2018. "The Aggregation Dilemma In Climate Change Policy Evaluation," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-20, August.
    2. Mérel, Pierre & Gammans, Matthew, 2018. "Climate econometrics: Can the panel approach account for long-run adaptation?," 2018 Annual Meeting, August 5-7, Washington, D.C. 274399, Agricultural and Applied Economics Association.
    3. Hsing-Hsiang Huang & Michael R. Moore, 2018. "Farming under Weather Risk: Adaptation, Moral Hazard, and Selection on Moral Hazard," NBER Chapters, in: Agricultural Productivity and Producer Behavior, pages 77-124, National Bureau of Economic Research, Inc.
    4. Ji, Xinde & Cobourn, Kelly M. & Weng, Weizhe, 2018. "The Effect of Climate Change on Irrigated Agriculture: Water-Temperature Interactions and Adaptation in the Western U.S," 2018 Annual Meeting, August 5-7, Washington, D.C. 274306, Agricultural and Applied Economics Association.
    5. Prince Etwire & David Fielding & Victoria Kahui, 2017. "The impact of climate change on crop production in Ghana: A Structural Ricardian analysis," Working Papers 1706, University of Otago, Department of Economics, revised Apr 2017.
    6. Lungarska, Anna & Chakir, Raja, 2018. "Climate-induced Land Use Change in France: Impacts of Agricultural Adaptation and Climate Change Mitigation," Ecological Economics, Elsevier, vol. 147(C), pages 134-154.
    7. Mu, Jianhong E. & Mihiar, Christopher & Lewis, David J. & Sleeter, Benjamin & Abatzoglou, John T., 2016. "An Empirical Analysis of Climate Uncertainty and Land-use Transitions in the U.S. Pacific and Mountain Regions," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236643, Agricultural and Applied Economics Association.
    8. Steven Passel & Emanuele Massetti & Robert Mendelsohn, 2017. "A Ricardian Analysis of the Impact of Climate Change on European Agriculture," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(4), pages 725-760, August.
    9. Zhang, Hongliang & Antle, John, 2016. "Assessing Climate Vulnerability of Agricultural Systems Using High-order moments: A Case Study in the U.S. Pacific Northwest," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236233, Agricultural and Applied Economics Association.
    10. Xinde Ji & Kelly M. Cobourn, 2021. "Weather Fluctuations, Expectation Formation, and Short-Run Behavioral Responses to Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 78(1), pages 77-119, January.
    11. Basurto, Saul, 2016. "A Mexican Ricardian analysis: land rental prices or net revenues?," 90th Annual Conference, April 4-6, 2016, Warwick University, Coventry, UK 236362, Agricultural Economics Society.
    12. Jianhong E. Mu & Benjamin M. Sleeter & John T. Abatzoglou & John M. Antle, 2017. "Climate impacts on agricultural land use in the USA: the role of socio-economic scenarios," Climatic Change, Springer, vol. 144(2), pages 329-345, September.
    13. Basurto-Hernandez, S. & Maddison, D. & Banerjee, A., 2018. "The effects of climate change on crop and livestock choices," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277517, International Association of Agricultural Economists.
    14. Lucas Bretschger & Karen Pittel, 2020. "Twenty Key Challenges in Environmental and Resource Economics," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(4), pages 725-750, December.
    15. Hongliang Zhang & John M. Antle, 2018. "Weather, Climate and Production Risk," IRENE Working Papers 18-01, IRENE Institute of Economic Research.
    16. Martina Bozzola & Emanuele Massetti & Robert Mendelsohn & Fabian Capitanio, 2018. "A Ricardian analysis of the impact of climate change on Italian agriculture," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 45(1), pages 57-79.
    17. DePaula, Guilherme, 2020. "The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data," Journal of Environmental Economics and Management, Elsevier, vol. 104(C).
    18. Geoffrey Norman Tumwine & Razack B Lokina & John Mary Matovu, 2019. "The Effect of Climate Change on Agricultural Crop Returns in Uganda," Journal of Economics and Behavioral Studies, AMH International, vol. 11(4), pages 71-87.
    19. Lucas Bretschger & Karen Pittel, 2019. "Twenty Key Questions in Environmental and Resource Economics," CER-ETH Economics working paper series 19/328, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    20. Etwire, Prince Maxwell, 2020. "The impact of climate change on farming system selection in Ghana," Agricultural Systems, Elsevier, vol. 179(C).
    21. Prince M. Etwire & David Fielding & Viktoria Kahui, 2019. "Climate Change, Crop Selection and Agricultural Revenue in Ghana: A Structural Ricardian Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 70(2), pages 488-506, June.
    22. Guilherme DePaula, 2018. "The Distributional Impact of Climate Change in Brazilian Agriculture: A Ricardian Quantile Analysis with Census Data," Center for Agricultural and Rural Development (CARD) Publications 18-wp583, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    23. Ariel Ortiz‐Bobea, 2020. "The Role of Nonfarm Influences in Ricardian Estimates of Climate Change Impacts on US Agriculture," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 934-959, May.
    24. John M. Antle & Claudio O. Stöckle, 2017. "Climate Impacts on Agriculture: Insights from Agronomic-Economic Analysis," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 11(2), pages 299-318.
    25. Emanuele Massetti & Steven Van Passel & Camila Apablaza, 2018. "Is Western European Agriculture Resilient to High Temperatures?," CESifo Working Paper Series 7286, CESifo.

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    More about this item

    Keywords

    Climate Change; Agriculture; Ricardian Analysis; Aggregation Bias; Semi-Parametric Models;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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