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Selecting The "Best" Prediction Model: An Application To Agricultural Cooperatives

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  • Rambaldi, Alicia N.
  • Zapata, Hector O.
  • Christy, Ralph D.

Abstract

A credit scoring function incorporating statistical selection criteria was proposed to evaluate the credit worthiness of agricultural cooperative loans in the Fifth Farm Credit District. In-sample (1981-1986) and out-of-sample (1988) prediction performance of the selected models were evaluated using rank transformation discriminant analysis, logit, and probit. Results indicate superior out-of-sample performance for the management oriented approach relative to classification of unacceptable loans, and poor performance of the rank transformation in out-of-sample prediction.

Suggested Citation

  • Rambaldi, Alicia N. & Zapata, Hector O. & Christy, Ralph D., 1992. "Selecting The "Best" Prediction Model: An Application To Agricultural Cooperatives," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 24(1), pages 1-7, July.
  • Handle: RePEc:ags:sojoae:30380
    DOI: 10.22004/ag.econ.30380
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    References listed on IDEAS

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    Agribusiness;

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