It’s not just the statistical model. A comment on Seo (2013)
A recent paper in this journal argues that the choice of statistical model is responsible for the divergence in damage estimates of climate change on US agriculture. We provide five arguments why we believe this assertion is misguided. Copyright Springer Science+Business Media Dordrecht 2013
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Volume (Year): 121 (2013)
Issue (Month): 2 (November)
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References listed on IDEAS
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.:
- Marshall Burke & John Dykema & David Lobell & Edward Miguel & Shanker Satyanath, 2011. "Incorporating Climate Uncertainty into Estimates of Climate Change Impacts, with Applications to U.S. and African Agriculture," NBER Working Papers 17092, National Bureau of Economic Research, Inc.
- S. Seo, 2013. "An essay on the impact of climate change on US agriculture: weather fluctuations, climatic shifts, and adaptation strategies," Climatic Change, Springer, vol. 121(2), pages 115-124, November.
- Anthony C. Fisher & W. Michael Hanemann & Michael J. Roberts & Wolfram Schlenker, 2012. "The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather: Comment," American Economic Review, American Economic Association, vol. 102(7), pages 3749-60, December.
- Wolfram Schlenker & W. Michael Hanemann & Anthony C. Fisher, 2006.
"The Impact of Global Warming on U.S. Agriculture: An Econometric Analysis of Optimal Growing Conditions,"
The Review of Economics and Statistics,
MIT Press, vol. 88(1), pages 113-125, February.
- Schlenker, Wolfram & Hanemann, W. Michael & Fisher, Anthony C., 2004. "The Impact of Global Warming on U.S. Agriculture: An Econometric Analysis of Optimal Growing Conditions," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt0801j7s0, Department of Agricultural & Resource Economics, UC Berkeley.
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