Sampling Interview Team Biofuels and Climate Change: Farmers' Land Use Decisions Research Symposium University of Kansas, Lawrence, KS August 25, 2011
Sampling Methods Sample based on Farmers who indicated on the survey they were willing to be contacted again 650 survey respondents Compared the characteristics of these 650 respondents to the entire pool of survey respondents Farm size, Irrigation, Region, Age, etc..
Sampling Methods Drew a random sample of 200 and repeated the validity checks, comparing them to the survey respondents Second week of June, we started calling Started in the South and moved North to avoid wheat harvest As much as possible, we wanted to avoid any response bias Using survey techniques, we tried to give each of these farmers an equal chance of being interviewed
Survey Methods In late July, we added 100 additional names to the original pool of 200. Used about 50% of these new names. Ended with 151 respondents
Interview Sample Tentative Final Interview Sample by Region, Compared to Survey Sample Distribution 8/24/11 NW NC NE SW SC SE Totals Survey Count 332 378 429 483 376 239 2237 % of total 15% 17% 19% 22% 17% 11% 101% Interview Count 23 22 24 35 30 14 148 % of total 16% 15% 16% 24% 20% 9% 100% Final Goal 22.5 25.5 28.5 34.5 25.5 16.5 150
Research Activities Sarah Beach, Chris Jahns and I developed a poster for EPSCOR meeting. The research question focuses on whether crop insurance influences farmers land use practices? Do they take more risks with their cropping practices if they have crop insurance and their level of coverage is substantial?
Socio-economic Implications of the U.S. Crop Insurance Program Sarah Beach 1, Joseph Aistrup 2, and Chris Jahns 2 1 Department of Sociology, Anthropology, and Social Work, 2 Department of Political Science, Kansas State University Introduction There are several approaches farmers utilize to manage risks, including enterprise diversification, financial leverage, vertical integration, contracting, hedging, liquidity, crop yield insurance, crop revenue insurance, and household off-farm employment or investment (Harwood et al. 1999). Federally subsidized crop insurance, including both crop yield and crop revenue insurance, is available across the United States for key crops (Harwood et al. 1999). Crop insurance policies are obtainable for more than one hundred commodities, but only four crops, including corn, soybeans, wheat, and cotton account for nearly 80 percent of the crops covered (World Bank 2005). Now over 80 percent of eligible crop acres are covered by insurance (Babcock 2010). Research suggests that crop insurance may be being used by farmers to mitigate risk and loss from climate change (Mendelsohn 2006 and Antle 2010). The research questions are 1) how ubiquitous is crop insurance, and 2) does it impact farmers land use practices, such that they take more risks with their cropping practices if they have 1) crop insurance and 2) their level of coverage is substantial (beyond hail insurance). Preliminary Results (n=16) As part of the EPSCoR team, we have interviewed sixteen farmers who returned our statewide survey and indicated they were willing to be contacted further regarding the project. Kansas farmers surveyed: Types of insurance held..% have APH,..% have RA and/or CRC,..% have ACRE, and..% have others. The same Kansas farmers were interviewed, and one of the questions they were asked is if the rules of crop insurance influence their farming decisions: 1 does not have insurance; the farmer said they could absorb loss 14 answered negatively (e.g., no, not really) 1 answered in a neutral to negative manner and said only mostly after loss occurs 14 of 15 = 93% of interviewees do not believe crop insurance impacts their farming decisions Discussion The Federal Crop Insurance Corporation (FCIC), created in 1938, manages the Federal crop insurance program which is a joint effort with private-sector insurance companies. As of 1996, the Risk Management Agency (RMA) oversees the administration of FCIC programs in conjunction with seventeen private insurance companies (RMA 2010b). Various policies, as of 2010, including Actual Production History (APH), Revenue Assurance and/or Crop Revenue Coverage (RA and/or CRC), Group Risk Plan (GRP), Acreage Crop Revenue Election (ACRE), and Supplemental Revenue Assistance Program (SURE). 4 main crops insured: corn, soy, wheat, and cotton (World Bank 2005; EWG n.d.). In 2010, 256 million acres were insured with the crops valued at $77.9 billion (RMA 2010b). Projections by Young et al. (2001) and estimates by Goodwin et al. (2004) suggest that there is little impact on the number of acres planted when farmers have or do not have crop insurance. The results from this EPSCoR study are not final. Preliminary results from a small sample of Kansas farmers suggests crop insurance may not be impacting their farming decisions. The map shows indemnities (i.e., payments) to farmers based on their crop insurance coverage. The government pays about 60 percent of farmers crop insurance premium costs (Dismukes and Young 2008). As crop prices rise, the amount of subsidies paid for by the government toward farmers crop insurance premiums and insurance companies administrative and operating costs increases (Dismukes and Young 2008). Babcock (2010) argues that while program reforms in 2000 helped initiate the spread of crop insurance coverage, so that over 80 percent of eligible acres are now insured, that it has incurred high costs to taxpayers. 2001-2007 over $22 billion taxpayer dollars toward crop insurance program with roughly $11 billion received by farmers and the other $11 billion toward, for example, administrative and operating costs (Babcock 2010). Crop insurance agents work on commission (Babcock 2010). Conclusion, Considerations, and Future Research The U.S. crop insurance program brings together the private sector and the public sector to administer and operate the program for the benefit of farmers and arguably U.S. society. Mendelsohn (2006) and Antle (2010) caution against using Federally subsidized crop insurance as a long-term mitigation tool for climate change, because it may reduce farmers willingness to adapt to climate change. In addition, of the sixteen farmers mentioned here, some do not believe climate change is occurring, and it can be inferred they are not thinking of how to adapt to the projected climate changes. Future research: we need to 1) move to use the survey data collected this spring, 2) supplement this analysis with all the interviews to see if patterns hold and validate the generalizeability of these findings with survey data, and 3) distinguish between dry land acres and irrigated acres, because, dry land acres are the most exposed to risk. Our main question is: Do dry land fields covered by crop insurance, have crops that are more prone to failure due to weather conditions than acres without insurance, controlling for region of Kansas and its climate and type of insurance coverage? References Antle, John M. 2010. Adaptation of Agricultural and the Food System to Climate Changes: Policy Issues. Issue Brief 10-03, Resources for the Future. Babcock, Bruce A. 2010. The Political Economy of the US Crop Insurance Program. In V. Eldon Ball, Roberto Fanfani, and Luciano Gutierrez (eds.), The Economic Impact of Public Support to Agriculture, Series: Studies in Productivity and Efficiency Vol. 7, The Netherlands: Springer. Pp. 293-308. Dismukes, Robert and Edwin Young. 2008. New Market Realities Affect Crop Program Choices. Amber Waves 6(5):18-25. Retrieved January 21, 2011 (http://www.ers.usda.gov/amberwaves/). EWG. n.d. Total Costs (see methodology) by Crop in the United States. 2011 Farm Subsidy Database. Environmental Working Group. Retrieved August 10, 2011 (http://farm.ewg.org/cropinsurance.php?fips=00000&summpage=tc_by_crop&statename=). Goodwin, Barry K. Monte L. Vandeveer, and John L. Deal. 2004. An Empirical Analysis of Acreage Effects of Participation in the Federal Crop Insurance Program. American Journal of Agricultural Economics 86(4):1058 1077. Harwood, Joy, Richard Heifner, Keith Coble, Janet Perry, and Agapi Somwaru. 1999. Managing Risk in Farming Concepts, Research, and Analysis. Economic Research Service, U.S. Department of Agriculture. Agricultural Economic Report No. 774. Retrieved February 24, 2011 (http://www.ers.usda.gov/publications/aer774/aer774.pdf). Mendelsohn, Robert. 2006. The Role of Markets and Governments in Helping Society Adapt to a Changing Climate. Climatic Change 78: 203 215. RMA. 2010. Crop Indemnity Map March 1, 2010. U.S. Department of Agriculture, Risk Management Agency. Retrieved August 10, 2011 (http://www.rma.usda.gov/data/indemnity/2010/30110map.pdf). -----. 2010b. A Risk Management Agency Factsheet: About the Risk Management Agency. U.S. Department of Agriculture, Risk Management Agency November 2010. Retrieved August 11, 2011 (http://www.rma.gov/pubs/rme/aboutrma.pdf). Young, C. Edwin, Monte L. Vandeveer, and Randall D. Schnepf. 2001. Production and Price Impacts of U.S. Crop Insurance Programs. American Journal of Agricultural Economics 83(5):1196 1203. World Bank. 2005. Managing agricultural production risk. Report no. 32727-GLB, Agriculture and Rural Development Department, The International Bank for Reconstruction and Development/ The World Bank. Kansas NSF EPSCoR Biofuels and Climate Change: Farmers' Land Use Decisions For Further Information Contact: Sarah Beach, srhbeach@ksu.edu Support provided by: Kansas NSF EPSCoR Biofuels and Climate Change: Farmers Land Use Decisions via Kansas State University Acknowledgements: Dr. László J. Kulcsár and the rest of the EPSCoR team
Future Research Plans Develop article from EPSCOR Poster, using both interview and survey data
Research Activities Laszlo J. Kulcsar, Sarah Beach, Jacob Muslein and I presented Hyper-Extractive Economies and Sustainability at Rural Sociological Society conference in Boise, ID on July 28-31, 2011
Cluster analysis #3 -Employment structure, population change 1990-2000, %65+, immigration, crime race/ethnicity (% Black and % Hispanic), and irrigation, distance to metro
Future Research Activities Develop existing article from hyper-extractive economies presentation and develop new paper using more explicit indicators farmers land-use patterns in the model