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Uncertainty and learning in a technologically dynamic industry: Seed density in U.S. maize

Author

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  • Edward D. Perry
  • David A. Hennessy
  • GianCarlo Moschini
Abstract
The large and sustained yield gains achieved since the introduction of maize hybrids in the 1930s (about 1.8 bushels per acre per year) have been accompanied by a remarkably parallel and steady increase in seeding density. This increase occurred in an environment characterized by rapid technological innovation, including genetic engineering, and commercial hybrid varieties with short life cycles. An important question, then, is whether and how breeders and farmers have learned about the optimal planting density. In this paper, we use unique and detailed U.S. farm‐level data, consisting of more than 400,000 planting choices from 1995–2016, to assess the nature of learning about seeding density. Importantly, we control for unobserved confounders through both hybrid and farm‐level fixed effects. We find that the variance in planting rates for a given hybrid has decreased over time, and that farmers tend to plant a given variety at higher rates over time. This is consistent with Bayesian learning in which risk‐neutral farmers possess priors consistently below the true optimal rate. We cast doubt on risk aversion as a credible explanation for this finding by analyzing the contrasting evolution of soybean planting rates (a crop with exogenously different agronomic determinants of seed density). We interpret our results as evidence of inertia: the initial bias in maize farmers' priors is tilted towards the optimal planting rates of varieties planted in the past. One implication of the finding that farmers historically underinvested in seeding rates is that eliminating this tendency could result in productivity gains.

Suggested Citation

  • Edward D. Perry & David A. Hennessy & GianCarlo Moschini, 2022. "Uncertainty and learning in a technologically dynamic industry: Seed density in U.S. maize," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(4), pages 1388-1410, August.
  • Handle: RePEc:wly:ajagec:v:104:y:2022:i:4:p:1388-1410
    DOI: 10.1111/ajae.12276
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    References listed on IDEAS

    as
    1. Joshua Schwartzstein, 2014. "Selective Attention And Learning," Journal of the European Economic Association, European Economic Association, vol. 12(6), pages 1423-1452, December.
    2. Esther Duflo & Michael Kremer & Jonathan Robinson, 2008. "How High Are Rates of Return to Fertilizer? Evidence from Field Experiments in Kenya," American Economic Review, American Economic Association, vol. 98(2), pages 482-488, May.
    3. Edward D. Perry & GianCarlo Moschini & David A. Hennessy, 2016. "Testing for Complementarity: Glyphosate Tolerant Soybeans and Conservation Tillage," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(3), pages 765-784.
    4. Michael S. Haigh & John A. List, 2005. "Do Professional Traders Exhibit Myopic Loss Aversion? An Experimental Analysis," Journal of Finance, American Finance Association, vol. 60(1), pages 523-534, February.
    5. Chad Syverson, 2011. "What Determines Productivity?," Journal of Economic Literature, American Economic Association, vol. 49(2), pages 326-365, June.
    6. Peter Thompson, 2001. "How Much Did the Liberty Shipbuilders Learn? New Evidence for an Old Case Study," Journal of Political Economy, University of Chicago Press, vol. 109(1), pages 103-137, February.
    7. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
    8. Moschini, Giancarlo & Hennessy, David A., 2001. "Uncertainty, risk aversion, and risk management for agricultural producers," Handbook of Agricultural Economics, in: B. L. Gardner & G. C. Rausser (ed.), Handbook of Agricultural Economics, edition 1, volume 1, chapter 2, pages 88-153, Elsevier.
    9. Steven D. Levitt & John A. List & Chad Syverson, 2013. "Toward an Understanding of Learning by Doing: Evidence from an Automobile Assembly Plant," Journal of Political Economy, University of Chicago Press, vol. 121(4), pages 643-681.
    10. Benjamin Handel & Joshua Schwartzstein, 2018. "Frictions or Mental Gaps: What's Behind the Information We (Don't) Use and When Do We Care?," Journal of Economic Perspectives, American Economic Association, vol. 32(1), pages 155-178, Winter.
    11. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    12. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    13. C. Lanier Benkard, 2000. "Learning and Forgetting: The Dynamics of Aircraft Production," American Economic Review, American Economic Association, vol. 90(4), pages 1034-1054, September.
    14. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    15. Esther Duflo & Michael Kremer & Jonathan Robinson, 2011. "Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya," American Economic Review, American Economic Association, vol. 101(6), pages 2350-2390, October.
    16. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    17. Boyan Jovanovic & Yaw Nyarko, 1995. "A Bayesian Learning Model Fitted to a Variety of Empirical Learning Curves," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 26(1995 Micr), pages 247-305.
    18. Seungki Lee & Yongjie Ji & GianCarlo Moschini, 2021. "Agricultural Innovation and Adaptation to Climate Change: Insights from Genetically Engineered Maize," Center for Agricultural and Rural Development (CARD) Publications 21-wp616, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    19. Matthew S. Clancy & GianCarlo Moschini, 2017. "Intellectual Property Rights and the Ascent of Proprietary Innovation in Agriculture," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 53-74, October.
    20. Tavneet Suri, 2011. "Selection and Comparative Advantage in Technology Adoption," Econometrica, Econometric Society, vol. 79(1), pages 159-209, January.
    21. Ortiz-Bobea, Ariel & Tack, Jesse B., 2018. "Another genetic yield revolution is needed to offset climate change effects on U.S. maize," 2018 Annual Meeting, August 5-7, Washington, D.C. 274380, Agricultural and Applied Economics Association.
    22. Tessa Bold & Kayuki C. Kaizzi & Jakob Svensson & David Yanagizawa-Drott, 2017. "Lemon Technologies and Adoption: Measurement, Theory and Evidence from Agricultural Markets in Uganda," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(3), pages 1055-1100.
    23. Federico Ciliberto & GianCarlo Moschini & Edward D. Perry, 2019. "Valuing product innovation: genetically engineered varieties in US corn and soybeans," RAND Journal of Economics, RAND Corporation, vol. 50(3), pages 615-644, September.
    24. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    25. George W. Norton & Jeffrey Alwang, 2020. "Changes in Agricultural Extension and Implications for Farmer Adoption of New Practices," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 8-20, March.
    26. Rema Hanna & Sendhil Mullainathan & Joshua Schwartzstein, 2014. "Learning Through Noticing: Theory and Evidence from a Field Experiment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(3), pages 1311-1353.
    27. Kyle Emerick & Manzoor H. Dar, 2021. "Farmer Field Days and Demonstrator Selection for Increasing Technology Adoption," The Review of Economics and Statistics, MIT Press, vol. 103(4), pages 680-693, October.
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    Cited by:

    1. Luo, Jinjing & Moschini, GianCarlo & Perry, Edward D., 2023. "Switching costs in the US seed industry: Technology adoption and welfare impacts," International Journal of Industrial Organization, Elsevier, vol. 89(C).

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