1970s), also found in the literature, can be explained by the growing influence of omitted factors extraneous to the agricultural sector. I propose and evaluate a simple strategy to circumvent such nonfarm influences in the form of a Ricardian model based on cash rents (2009–2016), which better reflect agricultural profitability and do not capitalize expected land use changes. The new damage estimates on nonirrigated cropland and pasture rents are more optimistic and cannot be distinguished from zero. However, estimates remain imprecise under extreme climate change scenarios pointing to a cautionary long‐term outlook for United States agriculture. The findings are robust to multiple checks and alternative explanations."> 1970s), also found in the literature, can be explained by the growing influence of omitted factors extraneous to the agricultural sector. I propose and evaluate a simple strategy to circumvent such nonfarm influences in the form of a Ricardian model based on cash rents (2009–2016), which better reflect agricultural profitability and do not capitalize expected land use changes. The new damage estimates on nonirrigated cropland and pasture rents are more optimistic and cannot be distinguished from zero. However, estimates remain imprecise under extreme climate change scenarios pointing to a cautionary long‐term outlook for United States agriculture. The findings are robust to multiple checks and alternative explanations.">
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The Role of Nonfarm Influences in Ricardian Estimates of Climate Change Impacts on US Agriculture

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  • Ariel Ortiz‐Bobea
Abstract
The Ricardian approach is a popular hedonic method for analyzing climate change impacts on agriculture. The approach typically relies on a cross‐sectional regression of farmland asset prices on fixed climate variables, making it particularly vulnerable to omitted variables. I conduct a long‐spanning Ricardian analysis of farmland prices in the eastern United States (1950–2012) and find a convergence of evidence indicating that large estimates of climate change damages for recent cross‐sections (>1970s), also found in the literature, can be explained by the growing influence of omitted factors extraneous to the agricultural sector. I propose and evaluate a simple strategy to circumvent such nonfarm influences in the form of a Ricardian model based on cash rents (2009–2016), which better reflect agricultural profitability and do not capitalize expected land use changes. The new damage estimates on nonirrigated cropland and pasture rents are more optimistic and cannot be distinguished from zero. However, estimates remain imprecise under extreme climate change scenarios pointing to a cautionary long‐term outlook for United States agriculture. The findings are robust to multiple checks and alternative explanations.

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  • 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.
    • Handle: RePEc:wly:ajagec:v:102:y:2020:i:3:p:934-959
    DOI: 10.1093/ajae/aaz047
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    15. Wimmer, Stefan & Stetter, Christian & Schmitt, Jonas & Ringer, Robert, 2022. "Farm-level responses to weather trends," 96th Annual Conference, April 4-6, 2022, K U Leuven, Belgium 321221, Agricultural Economics Society - AES.
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    21. B. James Deaton & Chad Lawley, 2022. "A survey of literature examining farmland prices: A Canadian focus," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 70(2), pages 95-121, June.
    22. Seungki Lee & Yongjie Ji & GianCarlo Moschini, 2021. "Agricultural Innovation and Adaptation to Climate Change: Insights from Genetically Engineered Maize," Center for Agricultural and Rural Development (CARD) Publications 21-wp616, Center for Agricultural and Rural Development (CARD) at Iowa State University.
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