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Using Data Mining To Detect Anomalous Producer Behavior: An Analysis Of Soybean Production And The Federal Crop Insurance Program

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  • Olson, Stacey
  • Little, Bertis B.
  • Lovell, Ashley C.

Abstract

The analysis was conducted on the USDA's Risk Management Agency insurance data and NRCS Land Resource Regions from 1994 - 2001 to assist RMA in improving program integrity. The objective is to develop a data-mining algorithm that identifies anomalous producers and counties within LRRs based upon the percentage of acres harvested.

Suggested Citation

  • Olson, Stacey & Little, Bertis B. & Lovell, Ashley C., 2003. "Using Data Mining To Detect Anomalous Producer Behavior: An Analysis Of Soybean Production And The Federal Crop Insurance Program," 2003 Annual Meeting, February 1-5, 2003, Mobile, Alabama 35223, Southern Agricultural Economics Association.
  • Handle: RePEc:ags:saeatm:35223
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    File URL: http://purl.umn.edu/35223
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    References listed on IDEAS

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    1. Vincent H. Smith & Barry K. Goodwin, 1996. "Crop Insurance, Moral Hazard, and Agricultural Chemical Use," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 428-438.
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    Keywords

    Risk and Uncertainty;

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