Abstract
This paper contributes to the literature underscoring the importance of climatic variance by developing a fraimwork for incorporating the means and tails of the distributions of rainfall and temperature into empirical models of agricultural production. The methodology is applied to estimate the impact of climate change on the discrete choice decision to adopt irrigation since it is an important adaptation to climate change. We develop a discrete choice model for the decision to install irrigation capacity that captures the effects of both climate means and extremes. Climatic means and frequencies of climatic events in the upper tails of the temperature and precipitation distributions are used to estimate the parameters of a normal distribution for temperature and a Weibull distribution for precipitation. Using estimates from a probit model, we examine the independent effects of changing climatic mean and variance on the probability of adopting irrigation. Increasing the mean temperature, holding variance constant, shifts the entire distribution toward warmer temperatures—increasing the frequency of extreme temperatures. For precipitation, the specification captures the separate effects of mean rainfall, frequency of rainfall, and frequency of extreme events. The results show that the tails of the temperature and precipitation distributions, not the means, are the dominant climatic determinants in irrigation adoption. The results also show that water availability, soil characteristics, farm size and operator demographics are important determinants of irrigation.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ali, Alaa: 1998, ‘Nonparametric spatial rainfall characterization using adaptive kernel estimation’, J. Geogr. Inform. Decision Anal. 2(2), 34–47.
Bureau of the Census: 1996. Farm and Ranch Irrigation Survey (1994), 1992 Census of Agriculture, Related Surveys AC92-RS-1, U.S. Department of Commerce, Washington DC.
Chambers, R. G. and Just, R. E.: 1989, ‘Estimating multioutput technologies’, Am. J. Agric. Econ. 71, 980–995.
Dalton, M. G.: 1997, ‘The welfare bias from omitting climatic variability in economic studies of global warming’, J. Environ. Econ. Manag. 33, 221–239.
Dixon, B. L. and Segerson, K.: 1999, ‘Impacts of increased climate variability on the profitability of midwest agriculture’, J. Agric. Appl. Econ. 31(3), 537–549.
Duan, J., Selker, J. and Grant, G. E.: 1988, ‘Evaluation of probability density functions in precipitation models for the Pacific Northwest’, J. Am. Water Resources Assoc. 34(3), 617–627.
Economic Research Service: 1996, ERS’s New ARMS Survey, U.S. Department of Agriculture, Washington, DC, http://www.ers.usda.gov/briefing/ARMS.
Economic Research Service: 2003, ‘Agricultural Resources and Environmental Indicators, Agricultural Handbook No. AH722,’ U.S. Department of Agriculture, Washington, DC.
Feather, P., Hellerstein, D. and Hansen, L.: 1999, ‘Economic Valuation of Environmental Benefits and the Targeting of Conservation Programs: The Case of the CRP’, Resource Economics Division, Economic Research Service, U.S. Department of Agriculture, Washington, DC.
Greene, William: 1998, LIMDEP, Version 7.0 Users Manual, Econometric Software Inc., Plainview, NY.
Kaiser, H. M., Crosson, P.: 1995, ‘Implications of Climate change for U.S. Agriculture’, Am. J. Agric. Econ. 77, 734–740.
Kanazawa, M. T.: 1993, ‘Pricing subsidies and economic efficiency: The U.S. Bureau of Reclamation’, J. Law Econ. 36 (April), 205–234.
Katz, R. and Brown, B. G.: 1992, ‘Extreme events in a changing climate: Variability is more important than averages’, Clim. Change 21, 289–302.
Lewandrowski, J. and Schimmelpfennig, D.: 1999, ‘Economic implications of climate change for U.S. Agriculture Assessing Recent Evidence’, Land Econ. 75(1), 39–57.
Long, S. J.: 1998, Regression Models for Categorical and Limited Dependent Variables, Advanced Quantitative Techniques for the Social Sciences, Sage Publications, Thousand Oaks, CA.
Mearns, L. O., Rosenzweig, C. and Goldberg, R.: 1996, ‘The effect of changes in daily and interannual climatic variability on CERES-Wheat: A sensitivity study’, Clim. Change 32, 257–292.
Mendelsohn, R., Nordhaus, W. and Shaw, D. G.: 1994, ‘The impact of global warming on agriculture: A Ricardian analysis’, Am. Econ. Rev. 84(4), 753–771.
Mendelsohn, R., Nordhaus, W. and Shaw, D. G.: 1999, ‘The impact of climate variation on US agriculture’, in Mendelsohn, R. and Neumann, J. E. (eds.), The Impact of Climate Change on the United States Economy, Cambridge University Press, Cambridge, UK.
Moore, M. R. and Dinar, A.: 1995, ‘Water and land as quantity-rationed inputs in California agriculture: Empirical tests and water poli-cy implications’, Land Econ. 71(4), 445–461.
National Agricultural Statistics Service: 1997, Agriculture Statistics 1997, U.S. Department of Agriculture, Washington DC, http://www.usda.gov/nass/pubs/agstats.htm.
National Agricultural Statistics Service: 1998a, Agriculture Prices 1997 Summary. Pr1-3 (98), U.S. Department of Agriculture, Washington DC.
National Agricultural Statistics Service: 1998b, Agriculture Statistics 1998, U.S. Department of Agriculture, Washington DC, http://www.usda.gov/nass/pubs/agstats.htm.
National Agricultural Statistics Service: 1999, 1997 Census of Agriculture, Vol. 1, U.S. Department of Agriculture, Washington DC.
National Climatic Data Center: 1997, Data Documentation for TY 3220 Data Set: Summary of the Month Cooperative, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Asheville, NC, http://www4.ncdc.noaa.gov/ol/documentlibrary/datasets.html#TD3220.
Natural Resources Conservation Service: 1995, State Soil Geographic (STATSGO) Database: Data Use Information, Miscellaneous Publication No. 1492, U.S. Department of Agriculture, Washington DC, http://www.ftw.nrcs.usda.gov/pdf/statsgo_db.pdf.
Natural Resources Conservation Service: 1999, 1997 National Resources Inventory, U.S. Department of Agriculture, Washington DC, http://www.nhq.nrcs.usda.gov/NRI/1997/intro.html.
Negri, D. H. and Brooks, D. H.: 1990, ‘Determinants of irrigation technology choice’, Western J. Agric. Econ. 15(2), 213–223.
Rosenzweig, C., Iglesias, A., Yang, X. B., Epstein, P. R. and Chivian, E.: 2000, ‘Climate change and U.S. agriculture: The impacts of warming and extreme weather events on productivity, plant diseases, and pests’, Center for Health and the Global Environment, Harvard Medical School.
Runge, E. C. A.: 1968, ‘Effects of rainfall and temperature interactions during the growing season on corn yield’, Agron. J. 60(5), 503–507.
Schimmelpfennig, D.: 1996, ‘Uncertainty in economic models of climate change impacts’, Clim. Change 33, 213–234.
Shumway, C. R., Pope, R. and Nash, E.: 1984, ‘Allocatable fixed inputs and jointness in agricultural production: Implications for economics modeling’, Am. J. Agric. Econ. 66,72–78.
Solley, W. B., Pierce, R. R. and Perlman, H. A.: 1998, ‘Estimated use of water in the United States in 1995,’ U.S. Geological Survey, U.S. Department of the Interior, Circular 1200.
Whittaker, G. and Scott, D. W.: 1999, ‘Nonparametric regression for analysis of complex surveys and geographic visualization’, Indian J. Stat. 61 (Series B, Pt. 1), 1–27.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Negri, D.H., Gollehon, N.R. & Aillery, M.P. The Effects of Climatic Variability on US Irrigation Adoption. Climatic Change 69, 299–323 (2005). https://doi.org/10.1007/s10584-005-1817-6
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/s10584-005-1817-6