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Determinants of Kansas Farmers' Participation in On-Farm Research

Published online by Cambridge University Press:  28 April 2015

B. K. Goodwin ,
B. W. Schurle ,
D. W. Norman ,
S. G. Freyenberger ,
L. E. Bloomquist  and
D. L. Regehr
B. K. Goodwin
Affiliation:
Department of Agricultural Economics, North Carolina State University, Raleigh
B. W. Schurle
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan
D. W. Norman
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan
S. G. Freyenberger
Affiliation:
Department of Agricultural Economics, Kansas State University, Manhattan
L. E. Bloomquist
Affiliation:
Department of Sociology, Anthropology, and Social Work, Kansas State University, Manhattan
D. L. Regehr
Affiliation:
Department of Agronomy, Kansas State University, Manhattan
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Abstract

On-farm research (OFR) has increased in popularity in the U.S. in recent years due to heightened interest in sustainability issues, the likely decline in resources available for agricultural research, and increasing pressures for accountability and responsiveness to state and local needs. Information relating to OFR was obtained from 431 commercial Kansas farmers. Data were analyzed to determine the degree of OFR being implemented, and three models were estimated to identify which farmer/farm characteristics influenced its implementation. The results indicate that OFR is commonly implemented, and that several farm/farmer characteristics are related to the degree of OFR initiated. It is proposed that to maximize the return from externally initiated OFR, there would be merit in focusing attention on farms/farmers with those characteristics.

Keywords

farmer attitudesfarmer participationfarming systems researchon-farm researchsustainable agriculture
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 29 , Issue 2 , December 1997 , pp. 385 - 396
Copyright
Copyright © Southern Agricultural Economics Association 1998

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References

Belsley, D.A., Kuh, E., and Welsch, R.E.. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. New York: John Wiley and Sons, 1980.Google Scholar
Cameron, A., and Trivedi, P.. “Regression-Based Tests for Overdispersion in the Poisson Model.” J. Econometrics 46(1990):347-64.CrossRefGoogle Scholar
Creel, M.E., and Loomis, J.B.. “Theoretical and Empirical Advantages of Truncated Count Data Estimators for Analysis of Deer Hunting in California.” Amer. J. Agr. Econ. 72(1990):434-41.CrossRefGoogle Scholar
DeLano, F.D. Annual Report 1993: Management Information, Kansas Farm Management Associations. Coop. Ext. Ser., Dept. of Agr. Econ., Kansas State University, Manhattan, 1993.Google Scholar
Dobson, W.D. “Strategies for Declining Academic Enterprises.” Choices (3rd Quarter 1995):29–33.Google Scholar
Featherstone, A.M., Griebel, J.C., and Langemeier, L.N.. “A Comparison of the Farm Management Association Data to the USDA Cost and Return Data.” In Farm Management Newsletter, Dept. of Agr. Econ., Kansas State University, Manhattan, April 1992.Google Scholar
Freyenberger, S., Bloomquist, L., Norman, D., Regehr, D., and Schurle, B.. “On-Farm Research in Kansas, 1993: A Survey of Farmers' Opinions.” Report of Progress No. 720, Agr. Exp. Sta., Kansas State University, Manhattan, 1994.Google Scholar
Goodwin, B.K., and Kastens, T.L.. “Adverse Selection, Disaster Relief, and the Demand for Multiple-Peril Crop Insurance.” A research report prepared for the Federal Crop Insurance Corporation (Proj. No. 92-EXCA-3-020), Dept. of Agr. Econ., Kansas State University, Manhattan, 1993.Google Scholar
Hausman, J.A., Hall, B.H., and Griliches, Z.. “Econometric Models for Count Data with an Application to the Parents—R&D Relationship.” Econometrica 52(1984):909-38.CrossRefGoogle Scholar
Hesterman, O.B., and Thorburn, T.L.. “A Comprehensive Approach to Sustainable Agriculture: W.K. Kellogg's Integrated Farming Systems Initiative.” J. Prod. Agr. 7(1994):132-34.Google Scholar
Hildebrand, P.E., and Russell, J.T.. Adaptability Analysis. Ames IA: Iowa State University Press, 1996.Google Scholar
Kelly, W.A. Jr. “A Generalized Interpretation of the Herfindahl Index.” S. Econ. J. 47(1981):50–57.Google Scholar
Lockeretz, W., and Anderson, M.. Agricultural Research Initiatives. Lincoln NE: University of Nebraska Press, 1993.Google Scholar
Michelini, C., and Pickford, M.. “Estimating the Herfindahl Index from Concentration Ratio Data.” J. Amer. Statis. Assoc. 80(June 1985):301-05.Google Scholar
Norman, D., Bloomquist, L., Freyenberger, S., Regehr, D., Schurle, B., and Janke, J.. “Kansas Farmers' Attitudes to On-Farm Research: Results of a Survey.” Dept. of Agr. Econ., Kansas State University, Manhattan, 1997.Google Scholar
Norman, D., Frankenberger, T., and Hildebrand, P.. “Agricultural Research in Developing Countries: Past, Present, and Future of Farming Systems Research and Extension.” J. Prod. Agr. 7(1994):124-31.CrossRefGoogle Scholar
Norman, D., Mollel, N., Mangheni, M., and Par, P.-adza. “The Future of Agricultural Extension in South Africa: Lessons from Within and Outside die African Continent.” S. African J. Agr. Ext. 23(1994):1–20.Google Scholar
Norman, D., Worman, F., Siebert, J., and Modiak, E.-gotla. The Farming Systems Approach to Development and Appropriate Technology Generation. FAO Farm Systems Management Series No. 10. Rome, Italy: Food and Agriculture Organization of the United Nations, Agricultural Services Division, 1995.Google Scholar
Rzewnicki, P. “An Assessment of On-Farm Experiment Design and Implications for Involving Farmers and Extension Agents in Applied Agronomy Research.” Unpub. Ph.D. dissertation, Department of Agronomy, University of Nebraska, Lincoln, 1991.Google Scholar
Rzewnicki, P.E., Thompson, R., Lesoing, G.W., Elmore, R.W., Francis, C.A., Parkhurst, A.M., and Moomaw, R.S.. “On-Farm Experiment Designs and Implications for Locating Research Sites.” Amer. J. Alternative Agr. 3(1988):168-73.Google Scholar
Shapiro, C.A., Parkhurst, A.M., and Krantz, W.L.. “Update on the Statistical Implications of Experimental Units for On-Farm Trials.” In Agronomy Abstracts, 1991.Google Scholar
Stewart, M. “On Least Squares Estimation When the Dependent Variable Is Grouped.” Rev. Econ. Stud. L(4), no. 163(1983):737-53.Google Scholar
U.S. Department of Agriculture. Economic Indicators of the Farm Sector: State Financial Summary, 1991. Pub. No. EC1FS11-2, p. 254. USDA/Economic Research Service, Agriculture and Rural Economy Div., Washington DC, March 1993.Google Scholar
U.S. Department of Commerce. 1992 Census of Agriculture, Vol. 1, Part 16: “Kansas State and County Data.” Pub. No. AC92-A-16, Bureau of the Census, Economic and Statistics Administration, Washington DC, September 1994.Google Scholar