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Estimating Yield Gaps With Limited Data: An Application to United States Wheat

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  • Jesse Tack
  • Andrew Barkley
  • Lawton Lanier Nalley

Abstract

The objective of this research is to estimate and analyze the gap between in-trial yield potential, on-farm yield potential, and actual on-farm wheat yields. Yield gaps are quantified by measuring how varietal mean yields have changed over time, due to productivity increases generated by public and private wheat breeding programs. Variety performance trial data for Kansas winter wheat are used to summarize the evolution of wheat yields over the time period 1985 to 2011. A measure of yield potential is compared to actual on-farm yields to derive implications for wheat industry stakeholders. Persistent and expanding yield gaps between potential yield and actual on-farm yield are measured and analyzed. Producers’ variety adoption decisions explain a relatively small portion of this gap, and producers have become more effective at identifying and adopting yield-enhancing varieties over time. The largest portion of these gaps was explained by on-farm production decisions.

Suggested Citation

  • Jesse Tack & Andrew Barkley & Lawton Lanier Nalley, 2015. "Estimating Yield Gaps With Limited Data: An Application to United States Wheat," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(5), pages 1464-1477.
    • Handle: RePEc:oup:ajagec:v:97:y:2015:i:5:p:1464-1477.
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    File URL: http://hdl.handle.net/10.1093/ajae/aau157
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    Citations

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    Cited by:

    1. Takeshima, Hiroyuki & Nasir, Abdullahi Mohammed, 2017. "The role of the locations of public sector varietal development activities on agricultural productivity: Evidence from northern Nigeria:," NSSP working papers 42, International Food Policy Research Institute (IFPRI).
    2. Liu, Ziheng & Lu, Qinan, 2023. "Ozone stress and crop harvesting failure: Evidence from US food production," Food Policy, Elsevier, vol. 121(C).
    3. Ko, Minkyong & Ramsey, Austin F., 2022. "Warming Temperatures and Potential Adaptation through Breeding: Evidence from U.S. Soft Winter Wheat," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322102, Agricultural and Applied Economics Association.
    4. Gramig, Benjamin M. & Yun, Seong Do, 2016. "Days Suitable for Fieldwork in the US Corn Belt:Climate, Soils and Spatial Heterogeneity," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235726, Agricultural and Applied Economics Association.
    5. Ruixue Wang & Roderick M. Rejesus & Jesse B. Tack & Joseph V. Balagtas & Andy D. Nelson, 2022. "Quantifying the Yield Sensitivity of Modern Rice Varieties to Warming Temperatures: Evidence from the Philippines," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(1), pages 318-339, January.
    6. Jayson L. Lusk & Jesse Tack & Nathan P. Hendricks, 2018. "Heterogeneous Yield Impacts from Adoption of Genetically Engineered Corn and the Importance of Controlling for Weather," NBER Chapters, in: Agricultural Productivity and Producer Behavior, pages 11-39, National Bureau of Economic Research, Inc.
    7. Hendricks, Nathan P. & Stigler, Matthieu M., 2020. "Global Yield Distributions since 1960," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304570, Agricultural and Applied Economics Association.

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