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

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Author Info
Bezemer, Dirk
Balcombe, Kelvin
Davis, Junior
Fraser, Iain

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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.

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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

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Keywords: livelihoods analysis survey data incomes efficiency Bayesian stochastic frontier approach

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  1. Gary Koop & M. F. J. Steel, 2004. "Bayesian Analysis of Stochastic Frontier Models," ESE Discussion Papers 19, Edinburgh School of Economics, University of Edinburgh.
  2. 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. [Downloadable!] (restricted)
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  3. 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. [Downloadable!] (restricted)
  4. 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. [Downloadable!] (restricted)
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  5. 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. [Downloadable!] (restricted)
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