Selecting The “Best” Prediction Model: An Application To Agricultural Cooperatives

Alicia Rambaldi (), Hector O. Zapata and Ralph D. Christy

Journal of Agricultural and Applied Economics, 1992, vol. 24, issue 1, 163-169

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.

Date: 1992
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Journal Article: SELECTING THE "BEST" PREDICTION MODEL: AN APPLICATION TO AGRICULTURAL COOPERATIVES (1992)
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