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Research and productivity in Thai agriculture

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  • Waleerat Suphannachart
  • Peter Warr

Abstract

This paper examines the impact that publicly funded agricultural research has on productivity in crop production within Thailand. It tests empirically the two hypotheses that, first, publicly funded research and development (R&D) in crop production is a significant determinant of total factor productivity (TFP) in the crop sector and, second, that its social rate of return is high. The statistical analysis applies error correction methods to national level time series data for Thailand, covering the period 1970–2006. Emphasis is given to public research in crop production, where most publicly funded agricultural R&D has occurred. The role of international research spillovers and other possible determinants of TFP are also taken into account. The results demonstrate that public investment in research has a positive and significant impact on TFP. International research spillovers have also contributed to TFP. The results support the finding of earlier studies that returns on public research investment have been high. This result holds even after controlling for possible sources of upward biases present in most such studies, due to the omission of alternative determinants of measured TFP. The findings raise a concern over declining public expenditure on crop research, in Thailand and many other developing countries.
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Suggested Citation

  • Waleerat Suphannachart & Peter Warr, 2011. "Research and productivity in Thai agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(1), pages 35-52, January.
  • Handle: RePEc:bla:ajarec:v:55:y:2011:i:1:p:35-52
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    References listed on IDEAS

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    7. Evenson, Robert E., 2001. "Economic impacts of agricultural research and extension," Handbook of Agricultural Economics,in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 11, pages 573-628 Elsevier.
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    Citations

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    Cited by:

    1. Waleerat Suphannachart & Peter Warr, 2011. "Research and productivity in Thai agriculture," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(1), pages 35-52, January.
    2. Mogues, Tewodaj & Yu, Bingxin & Fan, Shenggen & Mcbride, Linden, 2012. "The impacts of public investment in and for agriculture: Synthesis of the existing evidence," IFPRI discussion papers 1217, International Food Policy Research Institute (IFPRI).
    3. Warr, Peter G., 2012. "Research and agricultural productivity in Indonesia," 2012 Conference (56th), February 7-10, 2012, Freemantle, Australia 124475, Australian Agricultural and Resource Economics Society.
    4. Waleerat Suphannachart, 2013. "Total Factor Productivity of Main and Second Rice Production in Thailand," Applied Economics Journal, Kasetsart University, Faculty of Economics, Center for Applied Economic Research, vol. 20(1), pages 1-22, June.
    5. repec:unt:jnapdj:v:24:y:2017:i:2:p:1-22 is not listed on IDEAS
    6. Waleerat Suphannachart, 2017. "What Drives Labour Productivity in the Ageing Agriculture of Thailand?," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 7(1), pages 1-6.
    7. Zuzana Smeets Kristkova & Michiel van Dijk & Hans van Meijl, 2015. "Long-term projections of global food security with R&D-driven technological progress," EcoMod2015 8601, EcoMod.

    More about this item

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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