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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.

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Paper provided by European Association of Agricultural Economists in its series 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland with number 116088.

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Date of creation: 2011
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Handle: RePEc:ags:eaae11:116088

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Keywords: Bayesian Inference; Stochastic Production Frontier; Time Varying Technical Inefficiency; Total Factor Productivity Growth; Tropical Agricultural Systems; Farm Management; Productivity Analysis; C15; D24; O47;

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  1. Jim Griffin & Mark Steel, 2005. "Bayesian Stochastic Frontier Analysis Using WinBUGS," Econometrics 0509004, EconWPA.
  2. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
  3. 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.
  4. Tim J. Coelli & D. S. Prasada Rao, 2005. "Total factor productivity growth in agriculture: a Malmquist index analysis of 93 countries, 1980-2000," Agricultural Economics, International Association of Agricultural Economists, vol. 32(s1), pages 115-134, 01.
  5. 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.
  6. J. Griffin & M. Steel, 2008. "Flexible mixture modelling of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 29(1), pages 33-50, February.
  7. 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.
  8. 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.
  9. 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.
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