IDEAS home Printed from https://ideas.repec.org/p/zbw/gdec05/3477.html
   My bibliography  Save this paper

Is Rural Income Diversity Pro-Growth? Is It Pro-Poor? Evidence from Georgia

Author

Listed:
  • Fraser, Iain
  • Davis, Junior
  • Balcombe, Kelvin
  • Bezemer, Dirk

Abstract

This paper contributes to the literature on the role of on rural livelihood strategies in rural growth and poverty reduction. It distinguishes between livelihood diversity strategies that contribute to sustainable growth in household incomes, and those that mainly have a 'coping' function. It suggests that typically, the contribution of livelihood diversity to growing household income is through relaxing dependence on credit for access to capital. In this scenario, livelihood diversity would lead to higher technical efficiency in agriculture via investment and thereby to higher household incomes. Survey data from Georgia are introduced and used to test these hypotheses using a Bayesian stochastic frontier approach. The findings are relevant to defining more clearly the scope and aims of policies to stimulate the rural non-farm economy in developing and transition countries.

Suggested Citation

  • Fraser, Iain & Davis, Junior & Balcombe, Kelvin & Bezemer, Dirk, 2005. "Is Rural Income Diversity Pro-Growth? Is It Pro-Poor? Evidence from Georgia," Proceedings of the German Development Economics Conference, Kiel 2005 4, Verein für Socialpolitik, Research Committee Development Economics.
  • Handle: RePEc:zbw:gdec05:3477
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/19797/1/Bezemer.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    2. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    3. World Bank, 2002. "Georgia : Poverty Update," World Bank Other Operational Studies 15447, The World Bank.
    4. Barrett, C. B. & Reardon, T. & Webb, P., 2001. "Nonfarm income diversification and household livelihood strategies in rural Africa: concepts, dynamics, and policy implications," Food Policy, Elsevier, vol. 26(4), pages 315-331, August.
    5. Dashti, Imad, 2003. "Inference from concave stochastic frontiers and the covariance of firm efficiency measures across firms," Energy Economics, Elsevier, vol. 25(6), pages 585-601, November.
    6. Andrew N. Kleit & Dek Terrell, 2001. "Measuring Potential Efficiency Gains From Deregulation Of Electricity Generation: A Bayesian Approach," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 523-530, August.
    7. Erik Mathijs & Johan F. M. Swinnen, 2001. "Production Organization And Efficiency During Transition: An Empirical Analysis Of East German Agriculture," The Review of Economics and Statistics, MIT Press, vol. 83(1), pages 100-107, February.
    8. 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.
    9. L. Kurkalova & A. Carriquiry, 2003. "Input- and Output-Oriented Technical Efficiency of Ukrainian Collective Farms, 1989–1992: Bayesian Analysis of a Stochastic Production Frontier Model," Journal of Productivity Analysis, Springer, vol. 20(2), pages 191-211, September.
    10. Piesse, Jenifer & Thirtle, Colin, 2000. "A Stochastic Frontier Approach to Firm Level Efficiency, Technological Change, and Productivity during the Early Transition in Hungary," Journal of Comparative Economics, Elsevier, vol. 28(3), pages 473-501, September.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    livelihoods analysis; survey data; incomes; efficiency; Bayesian stochastic frontier approach;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:zbw:gdec05:3477. 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: (ZBW - German National Library of Economics). General contact details of provider: http://edirc.repec.org/data/vfselea.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.