IDEAS home Printed from https://ideas.repec.org/a/ags/aareaj/176899.html
   My bibliography  Save this article

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

Author

Listed:
  • Rahman, Sanzidur

Abstract

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
    as

    Download full text from publisher

    File URL: http://ageconsearch.umn.edu/record/176899/files/j.1467-8489.2011.00537.x.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aareaj:176899. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aaresea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.