- Apply for Authority
- P-ISSN1738-3110
- E-ISSN2093-7717
- SCOPUS
ISSN : 1738-3110
Explaining Share of Farm Loss Systemic with County Loss in the United States?
Lim, Jin-Soon
Zulauf, Carl
- Downloaded
- Viewed
Abstract
Purpose - Relationship between farm and county losses determines whether the county program provides too little, too much, or similar amount of assistance relative to the loss on an individual farm. A review of the literature finds limited analysis of the determinants of this relationship. This paper conducts such an analysis using farm-level yield data. Research design, data, and methodology - Farm-level yield data from Illinois and Kansas farm business management associations are used for to calculate the correlation between farm and county loss and the share of farm loss systemic with county loss, and also for the regression analysis. Results - Average share of farm loss systemic with the county loss lies between 42% and 68%. The correlation between farm and county yield/revenue deviation from expected value is statistically significant in all four models. The coefficient is positive, implying the higher the correlation, the larger the share of farm loss that is systemic with the county loss. Conclusions - The findings of this study are consistent with the existing literature which argues that county variability may not be closely associated with farm variability. The findings of this study thus raise questions about the efficacy of area yield and revenue insurance products in helping farmers manage their risk.
- keywords
- Agricultural Risk Coverage, Agribusiness, Agricultural Marketing, County Loss, Systemic Loss
Reference
Barnett, B. J., Black, J. R., Hu, Y., & Skees, J. R. (2005). Is area yield insurance competitive with farm yield insurance?. Journal of Agricultural and Resource Economics, 30(2), 285-301.
Bourgeon, J. M., & Chambers, R. G. (2003). Optimal Area-Yield Crop Insurance Reconsidered. American Journal of Agricultural Economics, 85(3), 590-604.
Cherubini, U., Luciano, E., & Vecchiato, W. (2004). Copula Methods in Finance. New York: John Wiley & Sons.
Claassen, R., & Just, R. E. (2011). Heterogeneity and distributional form of farm-level yields. American Journal of Agricultural Economics, 93(1), 144-160.
Cooper, J., Zulauf, C., Langemeier, M., & Schnitkey, G. (2012). Implications of Within County Yield Heterogeneity for Modeling Crop Insurance Premiums. Agricultural Finance Review, 72(1), 134-155.
Congressional Research Service. (2014). The 2014 Farm Bill (P.L. 113-79): Summary and Side-by-Side Comparison. Report R43076. Coordinated by R. M. Chite.
Erum, N., Hussain, S., & Yousaf, A. (2016). Foreign Direct Investment and Economic Growth in SAARC Countries. Journal of Asian Finance, Economics and Business, 3(4), 57-66.
Gerlt, S., Thompson, W., & Miller, D. J. (2014). Exploiting the Relationship between Farm-Level Yields and County-Level Yields for Applied Analysis. Journal of Agricultural and Resource Economics, 39(2), 253-270.
Halcrow, H. G. (1949). Actuarial Structures for Crop Insurance. Journal of Farm Economics, 31(August), 418-443.
Hill, R. V., Robles, M., & Ceballos, F. (2016). Demand for a Simple Weather Insurance Product in India:Theory and Evidence. American Journal of Agricultural Economics, 98(4), 1250-1270.
Joe, H. (1997). Multivariate Models and Dependence Concepts. Monographs in Statistics and Probability 73. London, UK: Chapman and Hall.
Ker, A. P., & Coble, K. (2003). Modeling conditional yield densities. American Journal of Agricultural Economics, 85(2), 291-304.
Kim, J. J., & Youn, M. K. (2015). Correlation Analysis of Self-employment of Retirees Using Demographic Characteristics of the Retail Establishment. International Journal of Industrial Distribution &Business, 6(4), 17-22.
Langemeier, M. (2005). Comparison of 2002 Census and KFMA Farms. Staff Paper No. 06-01, Department of Agricultural Economics, Kansas State University.
Lee, D. H., & Lee, S. K. (2017). The China’s Exchange Rate Policy to Export Competition. International Journal of Industrial Distribution and Business, 8(2), 5-10.
Marra, M. C., & Schurle, B. W. (1994). Kansas Wheat Yield Risk Measures and Aggregation: A Meta-Analysis Approach. Journal of Agricultural and Resource Economics, 19(1), 69-77.
Miranda, M. J. (1991). Area-yield crop insurance reconsidered. American Journal of Agricultural Economics, 73(2), 233-242.
Miranda, M. J,., & Glauber, J. W. (1997). Systemic Risk, Reinsurance and the Failure of Crop Insurance Markets. American Journal of Agricultural Economics, 79(1), 206-215.
National Association of Counties (2015). Counties: Find a County. Retrieved September 5, 2017 from http://explorer.naco.org/
Nelsen, R. B. (2006). An Introduction to Copulas. New York: Springer.
Patton, A. J. (2009). Copula-Based Models for Financial Time Series. In T. G. Anderson, R. A. Davis, J. P. Kreiss, & T. Mikosch(eds.), Handbook of Financial Time Series, New York: Springer-Verlag.
U.S. Department of Agriculture, Economic Research Service (2008). Food, Conservation, and Energy Act of 2008. H.R. 2419. Retrieved September 5, 2017from http://www.ers.usda.gov/farm-bill-resources.aspx
U.S. Department of Agriculture, National Agricultural Statistics Service (2013). Data and Statistics: Quick Stats. Retrieved September 5, 2017 from http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/index.asp
U.S. Department of Agriculture, Risk Management Agency (2016). Summary of Business. http://www.rma.usda.gov/
- Downloaded
- Viewed
- 0KCI Citations
- 0WOS Citations