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Crop Insurance, Disaster Payments, and Land Use Change: The Effect of Sodsaver on Incentives for Grassland Conversion

Published online by Cambridge University Press:  26 January 2015

Roger Claassen ,
Joseph C. Cooper  and
Fernando Carriazo
Roger Claassen
Affiliation:
Economic Research Service, U.S. Department of Agriculture, Washington, DC
Joseph C. Cooper
Affiliation:
Economic Research Service, U.S. Department of Agriculture, Washington, DC
Fernando Carriazo
Affiliation:
Universidad de Los Andes, Bogota, Columbia
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Abstract

Subsidized crop insurance may encourage conversion of native grassland to cropland. The Sodsaver provision of the 2008 farm bill could deny crop insurance on converted land in the Prairie Pothole states for 5 years. Supplemental Revenue Assistance payments, which are linked to crop insurance purchases, could also be withheld. Using representative farms, we estimate that Sodsaver would reduce expected crop revenue by up to 8% and expected net return by up to 20%, while increasing the standard deviation of revenue by as much as 6% of market revenue. Analysis based on elasticities from the literature suggests that Sodsaver would reduce grassland conversion by 9% or less.

Keywords

bootstrapcrop insurancegrasslandjoint densitiesSodsaverSupplemental Revenue AssistanceQ2
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 43 , Issue 2 , May 2011 , pp. 195 - 211
Copyright
Copyright © Southern Agricultural Economics Association 2011

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References

Ahmed, S.A., Hertel, T.W., and Lubowski, R. “Calibration of a Land Cover Supply Function Using Transition Probabilities.” GTAP Research Memorandum No. 14, Global Trade Analysis Project, Perdue University, October 2008.Google Scholar
Barr, K.J., Babcock, B.A., Carriquiry, M., Nasser, A., and Harfuch, L. “Agricultural Land Elasticities in the United States and Brazil.” Working Paper 10-WP 505, Center for Agricultural and Rural Development, Iowa State University, 2010.Google Scholar
Chavas, J.-P., and Holt, M.T. “Acreage Decisions under Risk: The Case of Corn and Soybeans.” American Journal of Agricultural Economics 72(1990):529–38.10.2307/1243021Google Scholar
Coble, K., Dismukes, R., and Thomas, S. “Policy Implications of Crop Yield and Revenue Variability at Differing Levels of Disaggregation.” Paper presented at the American Agricultural Economics Association Annual Meeting, Portland, Oregon, July 29-August 1, 2007.Google Scholar
Conner, R., Seidl, A., VanTassell, L., and Wilkins, N. “United States Grasslands and Related Resources: An Economic and Biological Trends Assessment.” Internet site: irnr.tamu.edu/pdf/grasslands_high.pdf (Accessed July 15, 2010).Google Scholar
Cooper, J. “The Empirical Distribution of the Costs of Revenue-Based Commodity Support Programs – Estimates and Policy Implications.” Review of Agricultural Economics 31(2009): 206–21.10.1111/j.1467-9353.2009.01433.xGoogle Scholar
Cooper, J. “Average Crop Revenue Election: A Revenue-Base Alternative to Price-Based Commodity Payments Programs.” American Journal of Agricultural Economics 92(2010): 1214–28.10.1093/ajae/aaq048Google Scholar
Dobos, R., Sinclair, H., and Hippie, K. User Guide National Commodity Crop Productivity Index (NCCPI) Version 1.0. Lincoln, NE: U.S. Department of Agriculture, Natural Resource Conservation Service, National Soil Survey Center, 2008.Google Scholar
Eve, M.D., Sperrow, M., Howerton, K., Paulson, K., and Follet, R.F. “Predicted Impact of Changes on Soil Carbon Storage for Each Cropland Region of the Conterminous United States.” Journal of Soil and Water Conservation 57(2002): 196–204.Google Scholar
Featherstone, A., and Kastens, T. “Non-Parametric and Semi-Parametric Techniques for Modeling and Simulating Correlated, Non-Normal Price and Yield Distributions: Applications to Risk Analysis in Kansas Agriculture.” Journal of Agricultural and Applied Economics 32(2000): 267–81.S1074070800020356Google Scholar
Glauber, J. “Crop Insurance Reconsidered.” American Journal of Agricultural Economics 86(2003): 1179–95.Google Scholar
Goodwin, B.K., Vandeveer, M.L., and Deal, J. “An Empirical Analysis of Acreage Effects of Participation in the Federal Crop Insurance Program.” American Journal of Agricultural Economics 86(2004): 1058–77.10.1111/j.0002-9092.2004.00653.xGoogle Scholar
Goodwin, B., and Rejesus, R. “Safety Nets or Trampolines? Federal Crop Insurance, Disaster Assistance, and the Farm Bill.” Journal of Agricultural and Applied Economics 40(2008):415–29.S1074070800023713Google Scholar
Gray, A., Boehlje, M., Gloy, B., and Slinsky, S. “How U.S. Farm Programs and Crop Revenue Insurance Affect Returns to Farm Land.” Review of Agricultural Economics 26(2004):238–53.10.1111/j.1467-9353.2004.00173.xGoogle Scholar
Harwood, J., Heifner, R., Coble, K., Perry, J., and Somwaru, A. “Managing Risk in Farming: Concepts, Research, and Analysis.” Agricultural Economics Report 774, U.S. Department of Agriculture, Economic Research Service, March 1999.Google Scholar
Johnson, D. “Management of Northern Prairies and Wetlands for the Conservation of Neotropical Migratory Birds.” Management of Midwestern Landscapes for the Conservation of Neotropical Migratory Birds. Thompson, F.R. III, ed. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North-central Experiment Station, General Technical Report NC-187, November 2000.Google Scholar
Just, R.E. “Risk Research in Agricultural Economics: Opportunities and Challenges for the Next Twenty-Five Years.” Agricultural Systems 75(2003): 123–59.10.1016/S0308-521X(02)00063-XGoogle Scholar
Just, R.E., Calvin, L., and Quiggen, J. “Adverse Selection in Crop Insurance: Actuarial and Asymmetric Information Incentives.” American Journal of Agricultural Economics 81(1999):834–49.10.2307/1244328Google Scholar
Just, D., and Peterson, H. “Diminishing Marginal Utility of Wealth and Calibration of Risk in Agriculture.” American Journal of Agricultural Economics 85(2003): 1234–41.10.1111/j.0092-5853.2003.00536.xGoogle Scholar
Lahiri, S. “Theoretical Comparison of Block Bootstrap Methods.” Annals of Statistics 27(1999):386–404.10.1214/aos/1018031117Google Scholar
Lence, S. “Using Consumption and Asset Return Data to Estimate Farmers' Time Preferences and Risk Attitudes.” American Journal of Agricultural Economics 82(2000):934–47.10.1111/0002-9092.00092Google Scholar
Lubowski, R., Bucholtz, S., Claassen, R., Roberts, M., Cooper, J., Gueorguieva, A., and Johansson, R. “Environmental Effects of Agricultural Land-Use Change: The Role of Economics and Policy.” Economic Research Report 25. U.S. Department of Agriculture, Economic Research Service, August 2006.Google Scholar
Lubowski, R., Plantinga, A., and Stavins, R. “What Drives Land-Use Change in the United States? A National Analysis of Landowner Decisions.” Land Economics 84(2008):529–50.Google Scholar
Makki, S., and Somwaru, A. “Evidence of Adverse Selection in Crop Insurance Markets.” The Journal of Risk and Insurance 68(2001):685–708.10.2307/2691544Google Scholar
Metz, L. Montana Grazing Animal Unit Month (AUM) Estimator. Bozeman, MT: U.S. Department of Agriculture, Natural Resources Conservation Service, Range Technical Note MT-32, (Rev. 1), February 2007.Google Scholar
Morgan, D. “Subsidies Spur Crops on Fragile Habitat.” Washington Post, Page A3, December 2, 2008.Google Scholar
Sana, A., Shumway, C.R., and Talpaz, H. “Joint Estimation of Risk Preference Structure and Technology Using Expo-Power Utility.” American Journal of Agricultural Economics 76(1994): 173–84.10.2307/1243619Google Scholar
Skees, J., and Reed, M. “Rate Making for Farm-Level Crop Insurance: Implications for Adverse Selection.” American Journal of Agricultural Economics 68(1986):653–59.10.2307/1241549Google Scholar
Smith, V., and Watts, M. “The New Standing Disaster Program: A SURE Invitation to Moral Hazard Behavior.” Applied Economic Perspectives and Policy 32(2010): 154–69.10.1093/aepp/ppp003Google Scholar
Stephens, S., Walker, J., Blunck, D., Jayaraman, A., and Naugle, D. “Grassland Conversion in the Missouri Coteau of North and South Dakota 1984-2003,” Unpublished manuscript, Ducks Unlimited, September 2006.Google Scholar
U.S. Department of Agriculture Natural Resources Conservation Service. Summary Report: 2007 National Resources Inventory. Washington D.C.: U.S. Department of Agriculture, Natural Resources Conservation Service, 2009. Internet site: http://www.nrcs.usda.gov/technical/NRI/ (Accessed April 25, 2010).Google Scholar
U.S. Department of Agriculture Risk Management Agency. Premium Rate Calculations for the Continuous Rating Model. Internet site: http://www.rma.usda.gov/ftp/Continuous_Rating/cr_instr.pdf (Accessed July 5, 2007).Google Scholar
U.S. Department of Commerce, National Oceanic and Atmospheric Administration, U.S. Department of the Interior, Fish and Wildlife Service, Bureau of Land Management, and National Park Service, U.S. Department of Agriculture, Forest Service, U.S. Environmental Protection Agency, and National Aeronautics and Space Administration. Ecoregion: Prairie Grasslands. June 2009. Internet site: www. globalchange.gov/climate-toolkit (Accessed July 20, 2010).Google Scholar
U.S. Government Accountability Office. Agricultural Conservation: Farm Program Payments Are an Important Factor in Landowners' Decisions to Convert Grassland to Cropland. Washington, D.C.: U.S. Government Accountability Office, Report 07-1054, September 2007.Google Scholar
Vedenov, D., and Powers, G. “Risk Reducing Effectiveness of Revenue versus Yield Insurance in the Presence of Government Payments.” Journal of Agricultural and Applied Economics 40(2008):443–59.Google Scholar
Yatchew, A. “Nonparametric Regression Techniques in Economics.” Journal of Economic Literature 36(1998):669–721.Google Scholar