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Impact of farmer education on farm productivity under varying technologies: case of paddy growers in India

Author

Listed:
  • Kirtti Ranjan Paltasingh

    (SMVD University)

  • Phanindra Goyari

    (University of Hyderabad)

Abstract

This paper analyzes the effects of education on farm productivity in the case of growers of modern and traditional varieties of paddy in Odisha, Eastern India. Using an endogenous switching regression model, the study has found that a minimum threshold level of education is significantly influencing the adoption of modern varieties of paddy and thereby the farm productivity of adopters only. So, the study finds the evidence in support of Schultz hypothesis that says education enhances farm productivity in the case of adopters of modern technology. The study suggests that farmers’ field school program must be implemented along with a strong extension network in the study region for a wider dissemination modern technology.

Suggested Citation

  • Kirtti Ranjan Paltasingh & Phanindra Goyari, 2018. "Impact of farmer education on farm productivity under varying technologies: case of paddy growers in India," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 6(1), pages 1-19, December.
    • Handle: RePEc:spr:agfoec:v:6:y:2018:i:1:d:10.1186_s40100-018-0101-9
    DOI: 10.1186/s40100-018-0101-9
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    References listed on IDEAS

    as
    1. Lockheed, Marlaine E & Jamison, Dean T & Lau, Lawrence J, 1980. "Farmer Education and Farm Efficiency: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 29(1), pages 37-76, October.
    2. Tilak, Jandhyala B.G., 1993. "Education and Agricultural Productivity in Asia: A Review," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 48(2).
    3. Som P. Pudasaini, 1983. "The Effects of Education in Agriculture: Evidence from Nepal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(3), pages 509-515.
    4. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    5. Salvatore Di Falco & Marcella Veronesi & Mahmud Yesuf, 2011. "Does Adaptation to Climate Change Provide Food Security? A Micro-Perspective from Ethiopia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(3), pages 825-842.
    6. Malte Reimers & Stephan Klasen, 2013. "Revisiting the Role of Education for Agricultural Productivity," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(1), pages 131-152.
    7. Richard V. Llewelyn & Jeffery R. Williams, 1996. "Nonparametric analysis of technical, pure technical, and scale efficiencies for food crop production in East Java, Indonesia," Agricultural Economics, International Association of Agricultural Economists, vol. 15(2), pages 113-126, November.
    8. Khonje, Makaiko & Manda, Julius & Alene, Arega D. & Kassie, Menale, 2015. "Analysis of Adoption and Impacts of Improved Maize Varieties in Eastern Zambia," World Development, Elsevier, vol. 66(C), pages 695-706.
    9. Moock, Peter R, 1981. "Education and Technical Efficiency in Small-Farm Production," Economic Development and Cultural Change, University of Chicago Press, vol. 29(4), pages 723-739, July.
    10. Simon Appleton & Arsene Balihuta, 1996. "Education and agricultural productivity: Evidence from Uganda," Journal of International Development, John Wiley & Sons, Ltd., vol. 8(3), pages 415-444.
    11. Tim Coelli & Sanzidur Rahman & Colin Thirtle, 2002. "Technical, Allocative, Cost and Scale Efficiencies in Bangladesh Rice Cultivation: A Non‐parametric Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 53(3), pages 607-626, November.
    12. Hausman, Jerry A., 1983. "Specification and estimation of simultaneous equation models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 7, pages 391-448, Elsevier.
    13. Arega Alene & V. Manyong, 2007. "The effects of education on agricultural productivity under traditional and improved technology in northern Nigeria: an endogenous switching regression analysis," Empirical Economics, Springer, vol. 32(1), pages 141-159, April.
    14. Narayanamoorthy, A., 2000. "Farmers' Education and Productivity of Crops: A New Approach," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 55(3), September.
    15. Abdul Wadud & Ben White, 2000. "Farm household efficiency in Bangladesh: a comparison of stochastic frontier and DEA methods," Applied Economics, Taylor & Francis Journals, vol. 32(13), pages 1665-1673.
    16. Azhar, Rauf A, 1991. "Education and Technical Efficiency during the Green Revolution in Pakistan," Economic Development and Cultural Change, University of Chicago Press, vol. 39(3), pages 651-665, April.
    17. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    18. 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.
    19. Keith O. Fuglie & Darrell J. Bosch, 1995. "Economic and Environmental Implications of Soil Nitrogen Testing: A Switching-Regression Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(4), pages 891-900.
    20. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    21. Awudu Abdulai & Wallace Huffman, 2014. "The Adoption and Impact of Soil and Water Conservation Technology: An Endogenous Switching Regression Application," Land Economics, University of Wisconsin Press, vol. 90(1), pages 26-43.
    22. Hasnah & Fleming, Euan & Coelli, Tim, 2004. "Assessing the performance of a nucleus estate and smallholder scheme for oil palm production in West Sumatra: a stochastic frontier analysis," Agricultural Systems, Elsevier, vol. 79(1), pages 17-30, January.
    23. Michael Lokshin & Zurab Sajaia, 2004. "Maximum likelihood estimation of endogenous switching regression models," Stata Journal, StataCorp LP, vol. 4(3), pages 282-289, September.
    24. Asfaw, Solomon & Shiferaw, Bekele & Simtowe, Franklin & Lipper, Leslie, 2012. "Impact of modern agricultural technologies on smallholder welfare: Evidence from Tanzania and Ethiopia," Food Policy, Elsevier, vol. 37(3), pages 283-295.
    25. Huang, Fung-Mey & Luh, Yir-Hueih, 2009. "The Economic Value of Education in Agricultural Production: A Switching Regression Analysis of Selected East Asian Countries," 2009 Conference, August 16-22, 2009, Beijing, China 50928, International Association of Agricultural Economists.
    26. M. N. Asadullah & S. Rahman, 2009. "Farm productivity and efficiency in rural Bangladesh: the role of education revisited," Applied Economics, Taylor & Francis Journals, vol. 41(1), pages 17-33.
    27. Lee, Lung-Fei & Trost, Robert P., 1978. "Estimation of some limited dependent variable models with application to housing demand," Journal of Econometrics, Elsevier, vol. 8(3), pages 357-382, December.
    28. Asfaw, Abay & Admassie, Assefa, 2004. "The role of education on the adoption of chemical fertiliser under different socioeconomic environments in Ethiopia," Agricultural Economics, Blackwell, vol. 30(3), pages 215-228, May.
    29. Richard Mussa, 2015. "The Effects of Educational Externalities on Maize Production in Rural Malawi," Oxford Development Studies, Taylor & Francis Journals, vol. 43(4), pages 508-532, December.
    30. Akhter Ali & Awudu Abdulai, 2010. "The Adoption of Genetically Modified Cotton and Poverty Reduction in Pakistan," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(1), pages 175-192, February.
    31. Schultz, Theodore W, 1975. "The Value of the Ability to Deal with Disequilibria," Journal of Economic Literature, American Economic Association, vol. 13(3), pages 827-846, September.
    32. Simon Appleton & Arsene Balihuta, 1996. "Education and agricultural productivity: Evidence from Uganda," Journal of International Development, John Wiley & Sons, Ltd., vol. 8(3), pages 415-444.
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    More about this item

    Keywords

    Education; Technology adoption; Farm productivity; Endogenous switching regression;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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