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Quantifying Structural Change in U.S. Agriculture: The Case of Research and Productivity

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  • James Oehmke
  • David Schimmelpfennig

Abstract

Previous work on structural change in agriculture has failed to distinguish long-run trends from structural breaks leading to new trends. We measure structural changes as statistically significant breaks in either stochastic or deterministic time trends, and apply these measures to agricultural productivity and research. Productivity has a break in 1925 accompanying agriculture's early experience with the Great Depression. Research trends shifted in 1930 as the Depression and new technology began to strongly influence efficient farm size and capitalization. After modeling lags between research and productivity impacts in a vector autoregression (VAR), we compare our results to earlier work by developing a procedure to estimate the rate of return to research from the impulse response function of the VAR. Copyright Kluwer Academic Publishers 2004

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  • James Oehmke & David Schimmelpfennig, 2004. "Quantifying Structural Change in U.S. Agriculture: The Case of Research and Productivity," Journal of Productivity Analysis, Springer, vol. 21(3), pages 297-315, May.
    • Handle: RePEc:kap:jproda:v:21:y:2004:i:3:p:297-315
    DOI: 10.1023/B:PROD.0000022095.97676.42
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    Cited by:

    1. Baek, Jungho & Koo, Won W., 2006. "Price Dynamics in the North American Wheat Market," Agricultural and Resource Economics Review, Cambridge University Press, vol. 35(2), pages 265-275, October.
    2. Jungho Baek & Won W. Koo, 2010. "Analyzing Factors Affecting U.S. Food Price Inflation," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 58(3), pages 303-320, September.
    3. Vítor João Pereira Domingues Martinho, 2019. "Testing for Structural Changes in the European Union’s Agricultural Sector," Agriculture, MDPI, vol. 9(5), pages 1-21, May.
    4. Toole, Andrew A. & King, John L., 2011. "Industry-science connections in agriculture: Do public science collaborations and knowledge flows contribute to firm-level agricultural research productivity?," ZEW Discussion Papers 11-064, ZEW - Leibniz Centre for European Economic Research.
    5. Darragh Clancy & A. Kazukauskas & C. Newman & Fiona Thorne, 2009. "An investigation of the level of structural change in the agrifood sector of Ireland, Denmark and the Netherlands," Working Papers 0915, Rural Economy and Development Programme,Teagasc.
    6. Rada, Nicholas E. & Schimmelpfennig, David E., 2015. "Propellers of Agricultural Productivity in India," Economic Research Report 262202, United States Department of Agriculture, Economic Research Service.
    7. J. Zwolak, 2008. "The impact of fixed assets on Polish agricultural production," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 54(1), pages 20-25.
    8. Paul Heisey & Sarah Adelman, 2011. "Research expenditures, technology transfer activity, and university licensing revenue," The Journal of Technology Transfer, Springer, vol. 36(1), pages 38-60, February.
    9. Zimmermann, Andrea & Heckelei, Thomas & Adenauer, Marcel, 2007. "Report and Code to Simulate Structural Change," Reports 57468, Wageningen University, SEAMLESS: System for Environmental and Agricultural Modelling; Linking European Science and Society.
    10. Andersen, Matthew A., 2019. "Knowledge productivity and the returns to agricultural research: a review," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(2), April.

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