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Recalibrating the Reported Returns to Agricultural R&D: What if We All Heeded Griliches?

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  • Rao, Xudong
  • Hurley, Terrance M.
  • Pardey, Philip G.

Abstract

Zvi Griliches’ seminal analysis of hybrid corn spawned a large literature seeking to quantify and demonstrate the value of agricultural research and development (R&D) investments. The most important metric for quantifying the rate of return to R&D emerging from this literature is the internal rate of return (IRR), even though Griliches was skeptical of its usefulness as a metric in this context. An alternative metric, also reported by Griliches but not as commonly used in the subsequent returns-to-research literature, is the benefit-cost ratio (BCR). We assess how the implications of the returns to agricultural R&D literature may have differed if the BCR had become the standard rather than the IRR. We reveal that the IRR and BCR produce substantially different rankings of agricultural R&D projects; differences that persist even under substantial commodity and geographical aggregations of the BCR and IRR estimates. The median across 2,627 reported IRRs is 37.5 percent per year. Using data gleaned from 492 research evaluation studies, we developed and deployed a methodology to impute 2,126 BCRs (median of 5.4) and modified internal rates of returns, MIRRs (16.4 percent per year) assuming a uniform 10 percent per year discount rate and a 30-year research timeline.

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  • Rao, Xudong & Hurley, Terrance M. & Pardey, Philip G., 2019. "Recalibrating the Reported Returns to Agricultural R&D: What if We All Heeded Griliches?," Staff Papers 298430, University of Minnesota, Department of Applied Economics.
  • Handle: RePEc:ags:umaesp:298430
    DOI: 10.22004/ag.econ.298430
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    References listed on IDEAS

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    1. Hall, Bronwyn H. & Mairesse, Jacques & Mohnen, Pierre, 2010. "Measuring the Returns to R&D," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 1033-1082, Elsevier.
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    7. Rao, Xudong & Hurley, Terrance M. & Pardey, Philip G., 2019. "Are agricultural R&D returns declining and development dependent?," World Development, Elsevier, vol. 122(C), pages 27-37.
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    Cited by:

    1. Minot, Nicholas & Balie, Jean & Valera, Harold Glenn A., 2021. "Prioritizing yield-increasing crop research for poverty impact: An application of microsimulation in the Philippines," 2021 Annual Meeting, August 1-3, Austin, Texas 313976, Agricultural and Applied Economics Association.
    2. Julian M. Alston & Philip G. Pardey, 2020. "Innovation, Growth, and Structural Change in American Agriculture," NBER Chapters, in: The Role of Innovation and Entrepreneurship in Economic Growth, pages 123-165, National Bureau of Economic Research, Inc.
    3. Pemsl, Diemuth E. & Staver, Charles & Hareau, Guy & Alene, Arega D. & Abdoulaye, Tahirou & Kleinwechter, Ulrich & Labarta, Ricardo & Thiele, Graham, 2022. "Prioritizing international agricultural research investments: lessons from a global multi-crop assessment," Research Policy, Elsevier, vol. 51(4).
    4. Kym Anderson, 2022. "Loss of preferential access to the protected EU sugar market: Fiji's response," Departmental Working Papers 2022-11, The Australian National University, Arndt-Corden Department of Economics.
    5. Kym Anderson, 2018. "From taxing to subsidizing farmers in China post-1978," China Agricultural Economic Review, Emerald Group Publishing, vol. 10(1), pages 36-47, February.
    6. Julian M. Alston & Philip G. Pardey & Xudong Rao, 2022. "Payoffs to a half century of CGIAR research," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(2), pages 502-529, March.
    7. Thornton, Philip & Dijkman, Jeroen & Herrero, Mario & Szilagyi, Lili & Cramer, Laura, 2022. "Viewpoint: Aligning vision and reality in publicly funded agricultural research for development: A case study of CGIAR," Food Policy, Elsevier, vol. 107(C).

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    Keywords

    Agricultural and Food Policy; Agricultural Finance; Research Methods/ Statistical Methods;
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