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

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

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.

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File URL: http://econstor.eu/bitstream/10419/19797/1/Bezemer.pdf
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Paper provided by Verein für Socialpolitik, Research Committee Development Economics in its series Proceedings of the German Development Economics Conference, Kiel 2005 with number 4.

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Date of creation: 2005
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Handle: RePEc:zbw:gdec05:3477
Contact details of provider: Web page: http://www.ael.ethz.ch/

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  1. 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.
  2. Tim J. Coelli & Chris O'Donnell, 2003. "A Bayesian Approach To Imposing Curvature On Distance Functions," CEPA Working Papers Series WP032003, School of Economics, University of Queensland, Australia.
  3. 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.
  4. Koop, G. & Osiewalski, J. & Steel, M. F. J., . "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," CORE Discussion Papers RP 1245, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  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. 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.
  7. World Bank, 2002. "Georgia : Poverty Update," World Bank Other Operational Studies 15447, The World Bank.
  8. 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.
  9. 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.
  10. 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.
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