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The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data

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  • DePaula, Guilherme

Abstract

The economic impact of global warming likely varies across farms because of differences in climate, technology, and adaptive capacity. Therefore, aggregate estimates of the average effect of warming may be insufficient to model climate change vulnerability. In this study, I propose a quantile model for the distributional effect of climate change. I estimate interquantile regressions of land value on climate using agricultural census data for 464,277 commercial farms in Brazil. I find that the effects of climate change in Brazilian agriculture vary significantly by climate, land quality, and irrigation choice. A 1 °C of warming is more detrimental to farms in warm climates, those with high-quality land, and those using irrigation. A 100-mm decrease in annual precipitation is more damaging to farms in dry climates, those with low-quality land, and those using irrigation. The heterogeneity in climate change effects is particularly large within the subset of farms in the warmest or the driest climates, as the most vulnerable farms appear to be those that have reached their limits for climate adaptation.

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  • 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).
  • Handle: RePEc:eee:jeeman:v:104:y:2020:i:c:s0095069620301017
    DOI: 10.1016/j.jeem.2020.102378
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    as
    1. Andrew Chesher, 2003. "Identification in Nonseparable Models," Econometrica, Econometric Society, vol. 71(5), pages 1405-1441, September.
    2. Richard Hornbeck, 2012. "The Enduring Impact of the American Dust Bowl: Short- and Long-Run Adjustments to Environmental Catastrophe," American Economic Review, American Economic Association, vol. 102(4), pages 1477-1507, June.
    3. 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.
    4. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    5. Guido W. Imbens & Whitney K. Newey, 2009. "Identification and Estimation of Triangular Simultaneous Equations Models Without Additivity," Econometrica, Econometric Society, vol. 77(5), pages 1481-1512, September.
    6. Emanuele Massetti & Robert Mendelsohn, 2011. "Estimating Ricardian Models With Panel Data," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 301-319.
    7. 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.
    8. Francis Annan & Wolfram Schlenker, 2015. "Federal Crop Insurance and the Disincentive to Adapt to Extreme Heat," American Economic Review, American Economic Association, vol. 105(5), pages 262-266, May.
    9. Buchinsky, Moshe, 1994. "Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression," Econometrica, Econometric Society, vol. 62(2), pages 405-458, March.
    10. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 487-535.
    11. Ortiz-­Bobea, Ariel, 2013. "Understanding Temperature and Moisture Interactions in the Economics of Climate Change Impacts and Adaptation on Agriculture," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150435, Agricultural and Applied Economics Association.
    12. Nathan P. Hendricks, 2018. "Potential Benefits from Innovations to Reduce Heat and Water Stress in Agriculture," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 5(3), pages 545-576.
    13. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    14. Parente Paulo M.D.C. & Santos Silva João M.C., 2016. "Quantile Regression with Clustered Data," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 1-15, January.
    15. Richard Hornbeck & Pinar Keskin, 2014. "The Historically Evolving Impact of the Ogallala Aquifer: Agricultural Adaptation to Groundwater and Drought," American Economic Journal: Applied Economics, American Economic Association, vol. 6(1), pages 190-219, January.
    16. Carlo Fezzi & Ian Bateman, 2015. "The Impact of Climate Change on Agriculture: Nonlinear Effects and Aggregation Bias in Ricardian Models of Farmland Values," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 2(1), pages 57-92.
    17. 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.
    18. Solomon Hsiang & Paulina Oliva & Reed Walker, 2019. "The Distribution of Environmental Damages," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 13(1), pages 83-103.
    19. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    20. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    21. 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.
    22. Victor Chernozhukov & Christian Hansen, 2004. "The Effects of 401(K) Participation on the Wealth Distribution: An Instrumental Quantile Regression Analysis," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 735-751, August.
    23. Mendelsohn, Robert & Nordhaus, William D & Shaw, Daigee, 1994. "The Impact of Global Warming on Agriculture: A Ricardian Analysis," American Economic Review, American Economic Association, vol. 84(4), pages 753-771, September.
    24. Wolfram Schlenker & W. Michael Hanemann & Anthony C. Fisher, 2005. "Will U.S. Agriculture Really Benefit from Global Warming? Accounting for Irrigation in the Hedonic Approach," American Economic Review, American Economic Association, vol. 95(1), pages 395-406, March.
    25. Ortiz-Bobea, Ariel, 2016. "The Economic Impacts of Climate Change on Agriculture: Accounting for Time-invariant Unobservables in the Hedonic Approach," Working Papers 250035, Cornell University, Department of Applied Economics and Management.
    26. 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.
    27. Margriet F. Caswell & David Zilberman, 1986. "The Effects of Well Depth and Land Quality on the Choice of Irrigation Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(4), pages 798-811.
    28. Mendelsohn, Robert & Dinar, Ariel & Williams, Larry, 2006. "The distributional impact of climate change on rich and poor countries," Environment and Development Economics, Cambridge University Press, vol. 11(2), pages 159-178, April.
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    2. Xun Su & Minpeng Chen, 2022. "Econometric Approaches That Consider Farmers’ Adaptation in Estimating the Impacts of Climate Change on Agriculture: A Review," Sustainability, MDPI, vol. 14(21), pages 1-23, October.
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    4. Litao Feng & Wei Liu & Zhihui Zhao & Yining Wang, 2023. "Rainfall fluctuations and rural poverty: Evidence from Chinese county‐level data," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 31(3), pages 633-656, July.
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    6. Litao Feng & Zhuo Li & Zhihui Zhao, 2021. "Extreme Climate Shocks and Green Agricultural Development: Evidence from the 2008 Snow Disaster in China," IJERPH, MDPI, vol. 18(22), pages 1-22, November.
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    8. Xu, Haitao & Pan, Xiongfeng & Guo, Shucen & Lu, Yuduo, 2021. "Forecasting Chinese CO2 emission using a non-linear multi-agent intertemporal optimization model and scenario analysis," Energy, Elsevier, vol. 228(C).
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    More about this item

    Keywords

    Climate change; Distributional effects; Agriculture; Quantile regression; Census data; Brazil;
    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
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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