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Risk, Schooling and the Choice of Seed Technology in Developing Countries: A Meta-Profit Function Approach

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  • Pitt, Mark M
  • Sumodiningrat, Gunawan

Abstract

The determinants of rice seed variety choice are studied in a framework in which cultivator's variety-specific profit, risk preferences, uncertainty, and schooling affect variety choice. The econometric model takes the form of a simultaneous equation switching regimes model with random profit functions (the metaprofit functions). Adoption of high-yielding varieties in Indonesia is found to be positively associated with profitability, likelihood of flooding, quality of irrigation conditional on relative profit, and availability of credit, and negatively associated with likelihood of drought and land wealth. Schooling significantly affects variety-specific profit and input demand, but not variety choice. Copyright 1991 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Suggested Citation

  • Pitt, Mark M & Sumodiningrat, Gunawan, 1991. "Risk, Schooling and the Choice of Seed Technology in Developing Countries: A Meta-Profit Function Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(2), pages 457-473, May.
    • Handle: RePEc:ier:iecrev:v:32:y:1991:i:2:p:457-73
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    1. Blackman, Allen & Bannister, Geoffrey, 1997. "Community Pressure and Clean Technologies in the Informal Sector: An Econometric Analysis of the Adoption of Propane by Traditional Brickmakers in Ciudad Juarez, Mexico," RFF Working Paper Series dp-97-16-rev, Resources for the Future.
    2. Tao Yang, Dennis, 2004. "Education and allocative efficiency: household income growth during rural reforms in China," Journal of Development Economics, Elsevier, vol. 74(1), pages 137-162, June.
    3. Gregory Amacher & Jeffrey Alwang, 2004. "Productivity and Land Enhancing Technologies in Northern Ethiopia: Health, Public Investments, and Sequential Adoption," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 321-331.
    4. Blackman, Allen & Bannister, Geoffrey J., 1998. "Community Pressure and Clean Technology in the Informal Sector: An Econometric Analysis of the Adoption of Propane by Traditional Mexican Brickmakers," Journal of Environmental Economics and Management, Elsevier, vol. 35(1), pages 1-21, January.
    5. Rahman, S., 2003. "Resource Use Efficiency with Self-Selectivity: An Application of a Switching Regression Framework to Stochastic Frontier Models," Economics Discussion Paper Series 0301, Economics, The University of Manchester.
    6. Hussain, S. Sajidin & Byerlee, Derek R., 1995. "Education and Farm Productivity in Post- 'green revolution' Agriculture in Asia," 1994 Conference, August 22-29, 1994, Harare, Zimbabwe 183412, International Association of Agricultural Economists.
    7. Ibanez, Marcela, 2010. "Adoption of certified organic technologies: the case of coffee farming in Colombia," Proceedings of the German Development Economics Conference, Hannover 2010 58, Verein für Socialpolitik, Research Committee Development Economics.
    8. Yang, Dennis Tao & An, Mark Yuying, 2002. "Human capital, entrepreneurship, and farm household earnings," Journal of Development Economics, Elsevier, vol. 68(1), pages 65-88, June.
    9. Masakazu Hojo, 2004. "Measuring Education Levels of Farmers: Evidence from Innovation Adoption in Bangladesh," Discussion Papers in Economics and Business 04-06, Osaka University, Graduate School of Economics.
    10. Blackman, Allen, 1999. "The Economics of Technology Diffusion: Implications for Climate Policy in Developing Countries," Discussion Papers 10574, Resources for the Future.
    11. Bharadwaj, Prashant & Ali Mirza, Rinchan, 2019. "Displacement and development: Long term impacts of population transfer in India," Explorations in Economic History, Elsevier, vol. 73(C), pages 1-1.
    12. Ngugi, Daniel & Mukundu, Denford & Epperson, James E. & Acheampong, Yvonne J., 2003. "Determinants of Household Participation in Rural Development Projects," 2003 Annual Meeting, February 1-5, 2003, Mobile, Alabama 35251, Southern Agricultural Economics Association.
    13. Deribe, Yared & Tesfaye, Agajie, 2017. "Simultaneous estimation of multiple dairy technologies uptake," MPRA Paper 98921, University Library of Munich, Germany, revised 10 May 2017.
    14. Larson, Donald F. & Gurara, Daniel Zerfu, 2013. "A conceptual model of incomplete markets and the consequences for technology adoption policies in Ethiopia," Policy Research Working Paper Series 6681, The World Bank.
    15. Karanja, D. D. & Renkow, M. & Crawford, E. W., 2003. "Welfare effects of maize technologies in marginal and high potential regions of Kenya," Agricultural Economics, Blackwell, vol. 29(3), pages 331-341, December.
    16. Lybbert, Travis J., 2005. "Indian Farmers' Valuation of Crop Yield Distributions: Will poor farmers value 'pro-poor' seeds?," 2005 Annual meeting, July 24-27, Providence, RI 19160, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    17. Van Dusen, M. Eric, 2000. "In Situ Conservation Of Crop Genetic Resources In The Mexican Milpa System," Dissertations 11941, University of California, Davis, Department of Agricultural and Resource Economics.
    18. Lybbert, Travis J., 2006. "Indian farmers' valuation of yield distributions: Will poor farmers value `pro-poor' seeds?," Food Policy, Elsevier, vol. 31(5), pages 415-441, October.
    19. Holloway, Garth & Shankar, Bhavani & Rahman, Sanzidur, 2002. "Bayesian spatial probit estimation: a primer and an application to HYV rice adoption," Agricultural Economics, Blackwell, vol. 27(3), pages 383-402, November.
    20. Lapar, Ma. Lucila A. & Ehui, Simeon K., 2004. "Factors affecting adoption of dual-purpose forages in the Philippine uplands," Agricultural Systems, Elsevier, vol. 81(2), pages 95-114, August.

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