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Resource use efficiency under self-selectivity: the case of Bangladeshi rice producers


  • Rahman, Sanzidur


The paper jointly evaluates the determinants of switching to modern rice and its productivity while allowing for production inefficiency at the level of individual producers. Model diagnostics reveal that serious selection bias exists, justifying the use of a sample selection framework in stochastic frontier models. Results revealed that modern variety selection decisions are influenced positively by the availability of irrigation and gross return from rice and negatively by a rise in the relative wage of labour. Adoption of modern rice is higher in underdeveloped regions. Seasonality and geography/ location does matter in adoption decisions. Stochastic production frontier results reveal that land, labour and irrigation are the significant determinants of modern rice productivity. Decreasing returns to scale prevail in modern rice production. The mean level of technical efficiency (MTE) is estimated at 0.82. Results also demonstrate that the conventional stochastic frontier model significantly overestimates inefficiency by three points (MTE = 0.79). Policy implications include measures to increase access to irrigation, tenurial reform and keeping rice prices high to boost farm returns and offset the impact of a rise in the labour wage which will synergistically increase the adoption of modern rice as well as farm productivity.

Suggested Citation

  • Rahman, Sanzidur, 2011. "Resource use efficiency under self-selectivity: the case of Bangladeshi rice producers," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(2), pages 1-18.
  • Handle: RePEc:ags:aareaj:176899
    DOI: 10.22004/ag.econ.176899

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    References listed on IDEAS

    1. William Greene, 2010. "A stochastic frontier model with correction for sample selection," Journal of Productivity Analysis, Springer, vol. 34(1), pages 15-24, August.
    2. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    3. 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.
    4. Shiyani, R. L. & Joshi, P. K. & Asokan, M. & Bantilan, M. C. S., 2002. "Adoption of improved chickpea varieties: KRIBHCO experience in tribal region of Gujarat, India," Agricultural Economics, Blackwell, vol. 27(1), pages 33-39, May.
    5. 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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    Cited by:

    1. Abdul-Rahaman, Awal & Abdulai, Awudu, 2018. "Do farmer groups impact on farm yield and efficiency of smallholder farmers? Evidence from rice farmers in northern Ghana," Food Policy, Elsevier, vol. 81(C), pages 95-105.
    2. ODOZI, JOHN CHIWUZULUM & Adeniyi, Oluwaosin & Yusuf, Sulaiman A., 2018. "Production Efficiency in Small Agriculture: Do Migrant Remittances Matter?Evidence from Rural Nigeria," AgriXiv jfvzn, Center for Open Science.
    3. Sanzidur Rahman & Md. Abdul Matin & Md. Kamrul Hasan, 2018. "Joint Determination of Improved Variety Adoption, Productivity and Efficiency of Pulse Production in Bangladesh: A Sample-Selection Stochastic Frontier Approach," Agriculture, MDPI, Open Access Journal, vol. 8(7), pages 1-16, July.
    4. Rahman, Sanzidur & Daniel Chima, Chidiebere, 2015. "Determinants of modern technology adoption in multiple food crops in Nigeria: a multivariate probit approach," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 4(3), April.
    5. Satya Laksana & Arie Damayanti, 2013. "Determinants of the Adoption of System of Rice Intesification in Tasikmalaya District, West Java Indonesia," Working Papers in Economics and Development Studies (WoPEDS) 201306, Department of Economics, Padjadjaran University, revised Mar 2013.
    6. Lachaud, Michee Arnold & Bravo-Ureta, Boris E. & Ludena, Carlos E., 2015. "Agricultural productivity growth in Latin America and the Caribbean and other world regions: An analysis of climatic effects, convergence and catch-up," Working Papers 40, University of Connecticut, Department of Agricultural and Resource Economics, Charles J. Zwick Center for Food and Resource Policy.
    7. Uttam Khanal & Clevo Wilson & Boon Lee & Viet-Ngu Hoang, 2018. "Do climate change adaptation practices improve technical efficiency of smallholder farmers? Evidence from Nepal," Climatic Change, Springer, vol. 147(3), pages 507-521, April.
    8. Lachaud, Michee & Bravo-Ureta, Boris & Ludena, Carlos, 2015. "Agricultural Productivity Growth in Latin America and the Caribbean (LAC): An analysis of Climatic Effects, Convergence, and Catch-up," 2015 Conference, August 9-14, 2015, Milan, Italy 211721, International Association of Agricultural Economists.


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