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A Binary Logit Estimation of Factors Affecting Adoption of GPS Guidance Systems by Cotton Producers

Published online by Cambridge University Press:  26 January 2015

Swagata “Ban” Banerjee
Affiliation:
Delta Research and Extension Center, Mississippi State University, Stoneville, MS
Steven W. Martin
Affiliation:
Delta Research and Extension Center, Mississippi State University, Stoneville, MS
Roland K. Roberts
Affiliation:
Department of Agricultural Economics, University of Tennessee, Knoxville, TN
Sherry L. Larkin
Affiliation:
Food and Resource Economics Department, University of Florida, Gainesville, FL
James A. Larson
Affiliation:
Department of Agricultural Economics, University of Tennessee, Knoxville, TN
Kenneth W. Paxton
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana State University, Baton Rouge, LA
Burton C. English
Affiliation:
Department of Agricultural Economics, University of Tennessee, Knoxville, TN
Michele C. Marra
Affiliation:
Department of Agricultural and Resource Economics, North Carolina State University, Raleigh, NC
Jeanne M. Reeves
Affiliation:
Cotton Incorporated, Cary, NC
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Abstract

Binary logit analysis was used to identify the factors influencing adoption of Global Positioning System (GPS) guidance systems by cotton farmers in 11 Mid-south and Southeastern states. Results indicate that adoption was more likely by those who had already adopted other precision-farming practices and had used computers for farm management. In addition, younger and more affluent farmers were more likely to adopt. Farmers with larger farms and with relatively high yields were also more likely to adopt. Education was not a significant factor in a farmer's decision to adopt GPS guidance systems.

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Articles
Copyright
Copyright © Southern Agricultural Economics Association 2008

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References

Amemiya, T.Selection of Regressors.” International Economic Review 24(1980):331–54.CrossRefGoogle Scholar
Anderson, S., and Newell, R.G.Simplified Marginal Effects in Discrete Choice Models.” Economics Letters 81,3(December 2003):321–26.CrossRefGoogle Scholar
Baerenklau, K.A., and Knapp, K.C.A Stochastic-Dynamic Model of Costly Reversible Technology Adoption.” Selected paper presented at the annual meeting of American Agricultural Economics Association, Providence, RI, July 24–27, 2005.Google Scholar
Barham, B.L., Jackson-Smith, D., and Moon, S.The Dynamics of Agricultural Biotechnology Adoption: Lessons from rBST Use in Wisconsin, 1994–2001.” Paper submitted for the AAEA-WAEA Annual Meeting, Long Beach, CA, 2002.Google Scholar
Batte, M.T., and Ehsani, M.R.The Economics of Precision Guidance with Auto-Boom Control for Farmer-Owned Agricultural Sprayers.” Computers and Electronics in Agriculture 53,1 (August 2006):2844.CrossRefGoogle Scholar
Bell, C.D., Roberts, R.K., English, B.C., and Park, W.M.A Logit Analysis of Participation in Tennessee’s Forestry Stewardship Program.” Journal of Agricultural and Applied Economics 26(1994):463–72.CrossRefGoogle Scholar
Ben-Akiva, M.E., and Lerman, S.R. Discrete Choice Analysis: Theory and Application to Travel Demand. Cambridge, MA: MIT Press, 1985.Google Scholar
Buick, R., and White, E.Comparing GPS Guidance with Foam Marker Guidance.” Proceedings of the 4th International Conference on Precision Agriculture. Rust, R.H. and Larson, W.E. eds. Madison, WI: ASA/CSSA/SSSA, 1999.Google Scholar
Daberkow, S.G., Fernandez-Cornejo, J., and Padgitt, M.Precision Agriculture Adoption Continues to Grow.” Agricultural Outlook, pp. 3538. Washington, DC: U.S. Department of Agriculture/Economic Research Service, November 2002.Google Scholar
Daberkow, S.G., and McBride, W.D.Adoption of Precision Agriculture Technologies by U.S. Farmers.” Proceedings of the 5th International Conference on Precision Agriculture, Robert, P.C., Rust, R.H. and Larson, W.E. eds. Madison, WI: ASA/CSSA/SSSA, 2000.Google Scholar
Dillman, D.A. Mail and Telephone Surveys: The Total Design Method. New York: John Wiley & Sons, 1978.Google Scholar
Ehsani, M.R., Sullivan, M., Walker, J.T., and Zimmerman, T.L.A Method of Evaluating Different Guidance Systems.” 2002 ASAE annual meeting, paper no. 021155, 2002.Google Scholar
Ehsani, M.R., Sullivan, M., and Zimmerman, T.L.Field Evaluation of the Percentage of Overlap for Crop Protection Inputs with a Foam Marker System Using Real-Time Kinematic (RTK) GPS.” Integrated Pest Management Program, Ohio State University. Internet site: http://ipm.osu.edu/mini/03m-4.htm (Accessed November 29, 2007).Google Scholar
El-Osta, H.S., and Mishra, A.K.Adoption and Economic Impact of Site-Specific Technologies in U.S. Agriculture.” Selected paper presented at the annual meeting of the American Agricultural Economics Association, Chicago, IL, August 5–8, 2001.Google Scholar
Fernandez-Cornejo, J., Daberkow, S.G., and McBride, W.D.Decomposing the Size Effect on the Adoption of Innovations: Agrobiotechnology and Precision Farming.” Selected paper presented at the annual meeting of the American Agricultural Economics Association, Chicago, IL, August 5–8, 2001.Google Scholar
Florkowski, W.J., and Bilgic, A.Planning an Expansion of Blueberry Production by Southern Growers.” Selected paper presented at the annual meeting of the Southern Agricultural Economics Association, Orlando, FL, February 5–8, 2006.Google Scholar
Foster, A.D., and Rosenzweig, M.R.Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture.” Journal of Political Economy 103(1995):1176–209.CrossRefGoogle Scholar
Govindasamy, R., Italia, J., and Adelaja, A.Predicting Willingness-to-Pay a Premium for Integrated Pest Management Produce: A Logistic Approach.” Agricultural and Resource Economics Review 30,2(October 1991):151–59.CrossRefGoogle Scholar
Greene, W.H. Econometric Analysis, 3rd ed. Upper Saddle River, NJ: Prentice Hall, 1997.Google Scholar
Griffin, T.W., Lowenberg-DeBoer, J., Lambert, D.M., Peone, J., Payne, T., and Daberkow, S.G.Adoption, Profitability, and Making Better Use of Precision Farming Data.” Staff paper no. 04-06, Department of Agricultural Economics, Purdue University, West Lafayette, IN, June 2004.Google Scholar
Grisso, R., and Alley, M. “Precision Farming Tools—Light Bar Navigation.” Virginia Cooperative Extension Publication no. 442-501, January 2002. Internet site: www.ext.vt.edu/pubs/bse/442-501/442-501.html (Accessed November 29, 2007).Google Scholar
Hausman, J.A.Specification Tests in Econometrics.” Econometrica 46,6(November 1978):1251–71.CrossRefGoogle Scholar
Hensher, D.A., and Johnson, L.W. Applied Discrete Choice Modelling. London, UK: Croom Helm, 1981.Google Scholar
Isik, M., and Khanna, M.Stochastic Technology, Risk Preferences and Adoption of Site-Specific Technologies.” Selected paper submitted for presentation at the annual meeting of the American Agricultural Economics Association, Long Beach, CA, July 28–31, 2002.Google Scholar
Jarvis, A.M.Computer Adoption Decisions—Implications for Research and Extension: The Case of Texas Rice Producers.” American Journal of Agricultural Economics 72(1990):1388–94.CrossRefGoogle Scholar
Judge, G.G., Griffiths, W.E., Hill, R.C., and Lee, T.C. The Theory and Practice of Econometrics. New York: John Wiley & Sons Inc., 1980.Google Scholar
Khanna, M.Sequential Adoption of Site-Specific Technologies and Its Implications for Nitrogen Productivity: A Double Selectivity Model.” American Journal of Agricultural Economics 83(2001):3551.CrossRefGoogle Scholar
Kim, S.-A., Westra, J.V., and Gillespie, J.M.Factors Influencing the Russian Varroa-Resis-tant Honey Bees.” Selected paper presented at the annual meeting of the Southern Agricultural Economics Association, Orlando, FL, February 5–8, 2006.Google Scholar
Kurkalova, L., Kling, C., and Zhao, J.Green Subsidies in Agriculture: Estimating the Adoption Costs of Conservation Tillage from Observed Behavior.” Working paper no. 01-WP 286, Center for Agricultural and Rural Development, Iowa State University, Ames, April 2003.Google Scholar
Langemeier, M.Impact of the Adoption of Less Tillage Practices on Overall Efficiency.” Selected paper presented at the annual meeting of the Southern Agricultural Economics Association, Little Rock, AR, February 6–9, 2005.Google Scholar
Larson, J.A., and Roberts, R.K.Farmers’ Perceptions of Spatial Yield Variability as Influenced by Precision Farming Information Gathering Technologies.” Selected paper presented at the annual meeting of the Southern Agricultural Economics Association, Tulsa, OK, February 14–18, 2004.Google Scholar
Liao, T.F. Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models. Thousand Oaks, CA: Sage Publications, 1994.CrossRefGoogle Scholar
Long, J.S. Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA: Sage Publications, 1997.Google Scholar
Louviere, J.J., Hensher, D.A., and Swait, J.D. Stated Choice Methods: Analysis and Application. Cambridge, UK: Cambridge University Press, 2000.CrossRefGoogle Scholar
Lowenberg-DeBoer, J.Risk Management Potential of Precision Farming Technologies.” Journal of Agricultural and Applied Economics 31(1999):275–85.CrossRefGoogle Scholar
Lowenberg-DeBoer, J. “Purdue Study Drives Home Benefits of GPS Auto Guidance.” Purdue News. April 13 2004. Internet site: http://news.uns.purdue.edu/UNS/html4ever/2004/040413.Lowenberg.gps.html (Accessed November 29, 2007).Google Scholar
Lowenberg-DeBoer, J., and Boehlje, M.Revolution, Evaluation, or Deadend: Economic Perspectives on Precision Agriculture.” Proceedings of the 3rd International Conference on Precision Agriculture, Robert, P.C., Rust, R.H. and Larson, W.E. eds. Madison, WI: SSSA, 1997.Google Scholar
Lusk, J.L., Roosen, J., and Fox, J.A.Demand for Beef from Cattle Administered Growth Hormones or Fed Genetically Modified Corn: A Comparison of Consumers in France, Germany, the United Kingdom, and the United States.” American Journal of Agricultural Economics 85(2003):1629.CrossRefGoogle Scholar
Maddala, G.S. Limited-Dependent and Qualitative Variables in Econometrics. New York, NY: Cambridge University Press, 1983.CrossRefGoogle Scholar
Marra, M.C., and Carlson, G.A.The Role of Farm Size and Resource Constraints in the Choice between Risky Technologies.” Western Journal of Agricultural Economics 12(1987):109–18.Google Scholar
Martin, S.W., Hanks, J., Harris, A., Wills, G., and Banerjee, S.Estimating Total Costs and Possible Returns from Precision Farming Practices.” Crop Management. Research article doi:10.1094/CM-2005-1018-01-RS, October 18, 2005. Internet site: www.plantmanagementnetwork.org/cm/element/cmsum2.asp?id=5108 (Accessed November 29, 2007).Google Scholar
McBride, W.D., and Daberkow, S.G.Information and the Adoption of Precision Farming Technologies.” Journal of Agribusiness 21,1(Spring 2003):2138.Google Scholar
McBride, W.D., and El, H.S.-Osta. “Impacts of the Adoption of Genetically Engineered Crops on Farm Financial Performance.” Journal of Agricultural and Applied Economics 34,1(April 2002):175-91.CrossRefGoogle Scholar
McFadden, D.Conditional Logit Analysis of Qualitative Choice Behavior.” Frontiers in Econometrics, Zarembka, P. ed. New York, NY: Academic Press, 1974.Google Scholar
Medlin, C., and Lowenberg, J.-DeBoer. “Increasing Cost Effectiveness of Weed Control.” Precision Farming Profitability, SSM-3, Erickson, K. ed., p. 4451. West Lafayette, IN: Purdue University, 2000.Google Scholar
Neter, J., Wasserman, W., and Kutner, M.H. Applied Linear Regression Models. Homewood, IL: Richard D. Irwin Inc., 1983.Google Scholar
Obubuafo, J., Gillespie, J., Paudel, K., and Kim, S.A.Knowledge, Application and Adoption of Best Management Practices by Cattle Farmers under the Environmental Quality Incentives Program—A Sequential Analysis.” Selected paper presented at the annual meeting of the Southern Agricultural Economics Association, Orlando, FL, February 5–8, 2006.Google Scholar
Pindyck, R.S., and Rubinfeld, D.L. Econometric Models and Economic Forecasts. New York, NY: McGraw-Hill, 1976.Google Scholar
Rahm, M.R., and Huffman, W.E.The Adoption of Reduced Tillage: The Role of Human Capital and Other Variables.” American Journal of Agricultural Economics 6(1984):405–13.CrossRefGoogle Scholar
Rivers, D., and Vuong, Q.H.Limited Information Estimators and Exogeneity Tests for Simultaneous Probit Models.” Journal of Econometrics 39(1988):347–66.CrossRefGoogle Scholar
Roberts, R.K., English, B.C., Larson, J.A., Cochran, R.L., Goodman, W.R., Larkin, S.L., Marra, M.C., Martin, S.W., Shurley, W.D., and Reeves, J.M.Adoption of Site-Specific Information and Variable-Rate Technologies in Cotton Precision Farming.” Journal of Agricultural and Applied Economics 36(2004):143–58.CrossRefGoogle Scholar
Roberts, R.K., English, B.C., Larson, J.A., Cochran, R.L., Larkin, S.L., Marra, M.C., Martin, S.W., Paxton, K.W., Shurley, W.D., Goodman, W.R., and Reeves, J.M.Use of Precision Farming Technologies by Cotton Farmers in Eleven States: Results from the 2005 Southern Precision Farming Survey.” Proceedings of the 2006 Beltwide Cotton Conferences, San Antonio, TX, January 3–6, 2006, pp. 288–94. Memphis, TN: National Cotton Council.Google Scholar
Rogers, E.M. Diffusion of Innovations. Glencoe, IL: Free Press, 1962.Google ScholarPubMed
Russell, M.Auto-Steer: Does It Pay?Corn and Soybean Digest 66,4(March 2006):42.Google Scholar
Smith, A., Goe, W.R., Kenney, M., and Paul, C.J.M.Computer and Internet Use by Great Plains Farmers.” Journal of Agricultural and Resource Economics 29,3(December 2004):481500.Google Scholar
Stalcup, L.Affordable Auto-Steer.” The Corn and Soybean Digest 66,3(Mid-February 2006):18.Google Scholar
U.S. Department of Agriculture–Economic Research Service. Internet site: www.ers.usda.gov/Briefing/AgChemicals/Table1.htm (Accessed June 21, 2007).Google Scholar
Wooldridge, J.M. Economic Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press, 2002.Google Scholar
Zepeda, L.Predicting Bovine Somatotropin Use by California Dairy Farmers.” Western Journal of Agricultural Economics 15(1990):5562.Google Scholar
Zepeda, L.Simultaneity of Technology Adoption and Productivity.” Journal of Agricultural and Resource Economics 19,1(1994):4657.Google Scholar
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