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Direct Payments, Cash Rents, Land Values, and the Effects of Imputation in U.S. Farm-level Data

Published online by Cambridge University Press:  15 September 2016

Michael W. Robbins
Affiliation:
RAND Corporation in Pittsburgh, Pennsylvania
T. Kirk White*
Affiliation:
U.S. Census Bureau's Center for Economic Studies
*
Correspondence: T. Kirk WhiteCenter for Economic Studies4600 Silver Hill RoadWashington, DC 20233Phone 301.763.1879Email[email protected].
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Abstract

Research using the Agricultural Resource Management Survey (ARMS) and other data shows that direct government payments to farmers increase rents and the price of land. However, some ARMS data is imputed and does not account for relationships between payments and other variables. We investigate various imputation methods and benefits gained from a method with a wide scope rather than a parsimonious range of variables. Using our method, we estimate that an additional dollar of direct payment increases land value about $2.69 more per acre than ARMS imputation methods and that our imputations (using an exhaustive iterative sequential regression) outperform other methods and/or smaller models.

Type
Research Article
Copyright
Copyright © 2014 Northeastern Agricultural and Resource Economics Association 

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References

Banker, D. 2007. “ARMS Phase III: Data Processing and Analysis.” Working paper, Economic Research Service, USDA.Google Scholar
Barnard, C., Nehring, R., Ryan, J., and Collender, R. 2001. “Higher Cropland Value from Farm Program Payments: Who Gains?Agricultural Outlook 2001(Nov): 2630.Google Scholar
Floyd, J. 1965. “The Effects of Farm Price Supports on the Returns to Land and Labor in Agriculture.Journal of Political Economy 73(2): 148158.Google Scholar
Gardner, B. 1992. “Changing Economic Perspectives on the Farm Problem.Journal of Economic Literature 30(1): 62101.Google Scholar
Goodwin, B.K., Mishra, A.K., and Ortalo-Magné, F. 2011. “The Buck Stops Where? The Distribution of Agricultural Subsidies.” NBER Working Paper 16693, National Bureau of Economic Research, Cambridge, MA.CrossRefGoogle Scholar
Habiger, J., Robbins, M., and Ghosh, S. 2010. “An Assessment of Imputation Methods for the USDA's Agricultural Resource Management Survey.JSM Proceedings: Section on Survey Research Methods. Alexandria, VA: American Statistical Association.Google Scholar
Huber, P.J., and Ronchetti, E.M. 2009. Robust Statistics (2nd edition). Hoboken, NJ: John Wiley & Sons. CrossRefGoogle Scholar
Ifft, J., Kuethe, T., and Morehart, M. 2013. “The Impact of Decoupled Payments on U.S. Cropland Values.” Working Paper, Economic Research Service, USDA, Washington, DC.Google Scholar
Ifft, J., Nickerson, C., Kuethe, T., and You, C. 2012. “Potential Farm-level Effects of Eliminating Direct Payments.” Economic Information Brief 103, Economic Research Service, USDA, Washington, DC.CrossRefGoogle Scholar
Kirwan, B.E. 2009. “The Incidence of U.S. Agricultural Subsidies on Farmland Rental Rates.Journal of Political Economy 117(1): 138164.Google Scholar
Kott, P.S. 1995. “A Paradox of Multiple Imputation.” Working paper, National Agricultural Statistics Service, USDA, Fairfax, VA.Google Scholar
Kuchler, F., and Tegene, A. 1993. “Asset Fixity and the Distribution of Rents from Agricultural Policies.Land Economics 69(4): 428437.Google Scholar
Little, R.J.A., and Rubin, D.B. 2002. Statistical Analysis with Missing Data (2nd edition). Hoboken, NJ: John Wiley & Sons. CrossRefGoogle Scholar
Miller, D., Robbins, M., and Habiger, J. 2010. “Examining the Challenges of Missing Data Analysis in Phase Three of the Agricultural Resource Management Survey.JSM Proceedings: Section on Survey Research Methods. Alexandria, VA: American Statistical Association.Google Scholar
Robbins, M.W., Ghosh, S., Goodwin, B., Habiger, J., Miller, D., and White, T.K. 2011a. “Multivariate Imputation Methods for Addressing Missing Data in the Agricultural Resource Management Survey.” Working paper, National Institute of Statistical Sciences, Research Triangle Park, NC.Google Scholar
Robbins, M.W., Ghosh, S., Goodwin, B., Habiger, J., Miller, D., and White, T.K. 2011b. “Multivariate Imputation Methods for Addressing Missing Data in the Agricultural Resource Management Survey.NISS/NASS collaborative research project, National Agricultural Statistics Service/National Institute of Statistical Sciences, Research Triangle Park, NC.Google Scholar
Robbins, M.W., Ghosh, S.K., and Habiger, J.D. 2013. “Imputation in High-dimensional Economic Data as Applied to the Agricultural Resource Management Survey.Journal of the American Statistical Association 108(501): 8195.Google Scholar
Robbins, M.W., and White, T.K. 2011. “Farm Commodity Payments and Imputation in the Agricultural Resource Management Survey.American Journal of Agricultural Economics 93(2): 606612.Google Scholar
Roberts, M.J., Kirwan, B., and Hopkins, J. 2003. “The Incidence of Government Program Payments on Agricultural Land Rents: The Challenges of Identification.American Journal of Agricultural Economics 85(3): 762769.Google Scholar
Rubin, D.B. 1987. Multiple Imputation for Nonresponse in Surveys. New York, NY: John Wiley & Sons.CrossRefGoogle Scholar
Rubin, D.B., and Schenker, N. 1986. “Multiple Imputation for Interval Estimation from Simple Random Samples with Ignorable Nonresponse.Journal of the American Statistical Association 81(394): 366374.Google Scholar
Schafer, J.L. 1997. Analysis of Incomplete Multivariate Data. New York, NY: Chapman and Hall/CRC.CrossRefGoogle Scholar
Schafer, J.L., and Graham, J.W. 2002. “Missing Data: Our View of the State of the Art.Psychological Methods 7(2): 147177.Google ScholarPubMed
Schenker, N., Raghunathan, T.E., Chiu, P.L., Makuc, D.M., Zhang, G., and Cohen, A.J. 2006. “Multiple Imputation of Missing Income Data in the National Health Interview Survey.Journal of the American Statistical Association 101(475): 924933.Google Scholar
Tanner, M.A., and Wong, W.H. 1987. “The Calculation of Posterior Distributions by Data Augmentation (With Discussion).Journal of the American Statistical Association 82(398): 528550.Google Scholar
U.S. Department of Agriculture. 2008. “Land Values and Cash Rents 2008 Summary.” Summary Report, National Agricultural Statistics Service, USDA, Washington, DC.Google Scholar
White, T.K., and Hoppe, R. 2012. “Changing Farm Structure and the Distribution of Farm Payments and Federal Crop Insurance.” Economic Information Brief 91, Economic Research Service, USDA, Washington, DC.Google Scholar