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Constructing Farm Level Yield Densities from Aggregated Data: Analysis and Comparison of Approaches

Author

Listed:
  • Cooper, Joseph C.
  • Langemeier, Michael R.
  • Schnitkey, Gary D.
  • Zulauf, Carl R.

Abstract

Yield variability can be significantly higher at the farm level than at more aggregated levels, including the county. However, due to a dearth of available farm level data, much stochastic analysis involving farm yields utilizes more aggregated yield data as a proxy for the farm level. We empirically evaluate farm-level variability using longitudinal farm level data sets available from the Kansas Farm Management Association and the Illinois Farm Business and Farm Management Association. For corn, soybeans, and wheat, we compare the farm level yield variability obtained from this data to that inferred from Federal crop insurance premiums. The farm management data exhibit lower yield variability than are implied by the crop insurance premiums.

Suggested Citation

  • Cooper, Joseph C. & Langemeier, Michael R. & Schnitkey, Gary D. & Zulauf, Carl R., 2009. "Constructing Farm Level Yield Densities from Aggregated Data: Analysis and Comparison of Approaches," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49216, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea09:49216
    DOI: 10.22004/ag.econ.49216
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    References listed on IDEAS

    as
    1. Cooper, Joseph, 2009. "Payments under the Average Crop Revenue Program: Implications for Government Costs and Producer Preferences," Agricultural and Resource Economics Review, Cambridge University Press, vol. 38(1), pages 49-64, April.
    2. Keith H. Coble & Robert Dismukes, 2008. "Distributional and Risk Reduction Effects of Commodity Revenue Program Design ," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 30(3), pages 543-553.
    3. Barry K. Goodwin, 2009. "Payment Limitations and Acreage Decisions under Risk Aversion: A Simulation Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 19-41.
    4. Langemeier, Michael R., 2005. "Comparison of 2002 Census and KFMA Farms," Staff Papers 117977, Kansas State University, Department of Agricultural Economics.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Finger, Robert, 2012. "Biases in Farm-Level Yield Risk Analysis due to Data Aggregation," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 61(1).
    2. Yehouenou, Lauriane S. M. & Barnett, Barry J. & Harri, Ardian & Coble, Keith H., 2016. "An Analysis of Factors Affecting Bias and Inefficiency in Area Yield Indexes Based on Aggregated Farm Yields," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230081, Southern Agricultural Economics Association.
    3. Conradt, Sarah & Bokusheva, Raushan & Finger, Robert & Kussaiynov, Talgat, 2014. "Yield Trend Estimation in the Presence of Farm Heterogeneity and Non-linear Technological Change," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 53(2), pages 1-20, May.
    4. Gerlt, Scott & Thompson, Wyatt & Miller, Douglas, 2014. "Exploiting the Relationship between Farm-Level Yields and County-Level Yields for Applied Analysis," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(2), pages 1-18.
    5. Finger, Robert, 2012. "Biases in Farm-Level Yield Risk Analysis due to Data Aggregation," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 61(01), pages 1-14, February.
    6. Leif Erec Heimfarth & Oliver Musshoff, 2011. "Weather index‐based insurances for farmers in the North China Plain," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 71(2), pages 218-239, August.
    7. Cooper, Joseph C., 2009. "ACRE: A Revenue-Based Alternative to Price-Based Commodity Payment Programs," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49180, Agricultural and Applied Economics Association.

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    Keywords

    Agricultural and Food Policy; Crop Production/Industries; Research Methods/ Statistical Methods; Risk and Uncertainty;
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