Hostname: page-component-7479d7b7d-qs9v7 Total loading time: 0 Render date: 2024-07-08T16:30:42.119Z Has data issue: false hasContentIssue false
  • English
  • Français

Testing Nonlinear Logit Models of Performance Effectiveness Ratings: Cooperative Extension and Organic Farmers

Published online by Cambridge University Press:  26 January 2015

Luanne Lohr  and
Timothy A. Park
Luanne Lohr
Affiliation:
Department of Agricultural and Applied Economics at the University of Georgia
Timothy A. Park
Affiliation:
Department of Agricultural and Applied Economics at the University of Georgia
Get access Rights & Permissions [Opens in a new window]

Abstract

Survey evidence from U.S. organic farmers is evaluated to identify the factors influencing effectiveness ratings of cooperative extension advisors by organic farmers. A nonlinear logit model is specified for the ratings provided by organic producers, and critical demographic and management factors that influence the ratings are identified. The impact of the organic farmers' status in transitioning to organic production is highlighted. The results indicate that part-time, newer adopters of organic farming methods are more likely to rate extension service providers as effective providers of information. Scenarios to predict extension effectiveness when interacting with specific groups of organic farmers are developed.

Keywords

cooperative extensionnonlinear logit modelorganic farmingperformance ratingsC25Q16Q01
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 40 , Issue 2 , August 2008 , pp. 667 - 679
Copyright
Copyright © Southern Agricultural Economics Association 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allison, P.D. “Comparing Logit and Probit Coefficients across Groups.” Sociological Methods and Research 28(1999):186–208.Google Scholar
Bhattacharyya, A., Harris, T.R., Kvasnicka, W.G., and Veserat, G.M.. “Factors Influencing Rates of Adoption of Trichomoniasis Vaccine by Nevada Range Cattle Producers.” Journal of Agricultural and Resource Economics 22(1997):174–90.Google Scholar
Estrella, A. “A New Measure of Fit for Equations with Dichotomous Dependent Variables.” Journal of Business and Economics Statistics 16(1998):198–205.Google Scholar
Frisvold, G.B., Fernicola, K., and Langworthy, M.. “Market Returns, Infrastructure and the Supply and Demand for Extension Services.” American Journal of Agricultural Economics 83(2001):758–763.Google Scholar
Greene, W.H. Econometric Analysis, 5th ed. Upper Saddle River, NJ: Prentice Hall, 2003.Google Scholar
Hanson, J.C. “Opportunities and Challenges in Cooperative Extension for Agricultural Economists.” Agricultural and Resource Economics Review 26(1997):143–152.CrossRefGoogle Scholar
Hanson, J.C., and Just, R.E.. “The Potential for Transition to Paid Extension.” American Journal of Agricultural Economics 83(2001):777–784.Google Scholar
Keele, L.J., and Park, D.K.. “Ambivalent about Ambivalence: A Re-examination of Heteroske-dastic Probit Models.” Working Paper, Department of Political Science. Ohio State University, December 2006.Google Scholar
Kotcon, J., and Thilmany, D.. CSREES Organic Opportunities White Paper. Washington, DC: U.S. Department of Agriculture, Cooperative State Research, Education, and Extension Service, Internet site: www.ofrf.org/policy/usda_organic/csrees/organic_opportunities.pdf (Accessed October 10, 2006).Google Scholar
Levitt, S.D. “Optimal Incentive Schemes When Only the Agents' ‘Best’ Output Matters to the Principal.” RAND Journal of Economics 26(1995):744–760.Google Scholar
Liao, T.F. Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models. Thousand Oaks, CA: Sage, 1994.Google Scholar
Lohr, L., and Park, T.A.. “Choice of Insect Management Portfolios by Organic Farmers: Lessons and Comparative Analysis” Ecological Economics 43(2002):87–99.Google Scholar
McDowell, G.R. Land-Grant Universities and Extension into the Twenty-First Century: Renegotiating or Abandoning a Social Contract. Ames, IA: Iowa State University Press, 2001.Google Scholar
National Research Council. Publicly Funded Agricultural Research and the Changing Structure of U.S. Agriculture. Washington, DC: National Academy Press, 2002.Google Scholar
Postlewait, A., Parker, D., and Zilberman, D.. “The Advent of Biotechnology and Technology Transfer in Agriculture.” Technological Forecasting and Social Change 43(1993):271–87.CrossRefGoogle Scholar
Smith, P.C., and Goddard, M.. “Performance Management and Operational Research: A Marriage Made in Heaven?” Journal of Operational Research Society 53(2002):247–255.CrossRefGoogle Scholar
Walz, E. Final Results of the Third Biennial National Organic Farmers' Survey. Santa Cruz, CA: Organic Farming Research Foundation, 1999.Google Scholar
Walz, E. Final Results of the Fourth Biennial National Organic Farmers' Survey. Santa Cruz, CA: Organic Farming Research Foundation, 2001.Google Scholar