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A Bayesian Total Factor Productivity Analysis of Tropical Agricultural Systems in Central-Western Africa And South-East Asia

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  • Tonini, Axel
  • Matus, Silvia Saravia
  • Gomez y Paloma, Sergio

Abstract

This paper computes and analyses total factor productivity (TFP) growth rates for tropical agricultural systems in Central-Western Africa and South-East Asia. Two regions that despite sharing common agro-ecological conditions, have pursued different adoption rates of green revolution technology and have reported dissimilar yields per hectare. A panel data set is constructed for the period 1987-2007 from the FAOSTAT database. A Bayesian stochastic frontier model with country specific temporal variation in technical efficiency is estimated. Technical efficiency estimates reveal that there is substantial room for improvement in both continental sub-sets and that TFP estimates show on average larger rates of growth for South-East Asian countries as compared to Central-Western African countries. Results indicate that TFP is mostly driven by technical change and countries such as Benin, and Gambia display catch-up.

Suggested Citation

  • Tonini, Axel & Matus, Silvia Saravia & Gomez y Paloma, Sergio, 2011. "A Bayesian Total Factor Productivity Analysis of Tropical Agricultural Systems in Central-Western Africa And South-East Asia," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 116088, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae11:116088
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    File URL: http://ageconsearch.umn.edu/record/116088/files/Tonini_Axel_280.pdf
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    References listed on IDEAS

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    1. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    2. Vernon W. Ruttan, 2002. "Productivity Growth in World Agriculture: Sources and Constraints," Journal of Economic Perspectives, American Economic Association, vol. 16(4), pages 161-184, Fall.
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    5. David E. Bloom & Jeffrey D. Sachs, 1998. "Geography, Demography, and Economic Growth in Africa," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 29(2), pages 207-296.
    6. Pingali, P. L. & Traxler, G., 2002. "Changing locus of agricultural research: will the poor benefit from biotechnology and privatization trends?," Food Policy, Elsevier, vol. 27(3), pages 223-238, June.
    7. Jim Griffin & Mark Steel, 2007. "Bayesian stochastic frontier analysis using WinBUGS," Journal of Productivity Analysis, Springer, vol. 27(3), pages 163-176, June.
    8. J. Griffin & M. Steel, 2008. "Flexible mixture modelling of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 29(1), pages 33-50, February.
    9. Adlas, J. & Achoth, Lalith, 2006. "Is the Green Revolution Vanishing? Empirical Evidence from TFP Analysis for Rice," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25561, International Association of Agricultural Economists.
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    Keywords

    Farm Management; Productivity Analysis;

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