Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-10T13:36:38.865Z Has data issue: false hasContentIssue false
  • English
  • Français

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

Published online by Cambridge University Press:  09 September 2016

Alicia N. Rambaldi ,
Hector O. Zapata  and
Ralph D. Christy
Alicia N. Rambaldi
Affiliation:
Department of Economics, Louisiana State University
Hector O. Zapata
Affiliation:
Department of Agricultural Economics and Agribusiness, Louisiana Agricultural Experiment Station, Louisiana State UniversityAgricultural Center, Baton Rouge, Louisiana
Ralph D. Christy
Affiliation:
Department of Agricultural Economics, Cornell University, Ithaca, New York
Get access Rights & Permissions [Opens in a new window]

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.

Keywords

cooperativesdiscriminant analysislogitprobitrank transformation
Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 24 , Issue 1 , July 1992 , pp. 163 - 169
Copyright
Copyright © Southern Agricultural Economics Association 1992

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Amemiya, T. “Qualitative Response Models: A Survey.” J. Econ. Lit., 29 (1981): 1483–1536.Google Scholar
Bera, A. K. “Aspects of Econometric Modeling.” Ph.D. thesis, Australian National University, 1982.Google Scholar
Collins, R. A., and Green, R. D.. “Statistical Methods for Bankruptcy Forecasting.” J.Econ. and Bus., 34 (1982): 349–354.Google Scholar
Conover, J., and Iman, R.. “The Rank Transformation as a Method of Discrimination with Some Examples.” Communication in Statistics—Theory and Methods, A9.5 (1980):465–487.Google Scholar
Fischer, M. L., and Moore, K.. “An Improved Credit Scoring Function for the St. Paul Bank for Cooperatives.” J. Agr. Coop. 1(1986): 11–21.Google Scholar
Fujikoshi, Y. “Selection of Variable in Discriminant Analysis and Canonical Correlation Analysis.” Proceedings of the Sixth International Symposium on Multivariate Analysis. Krishnaiah, P. R. (ed.). North-Holland Publishing Company, 1985, 219–236.Google Scholar
Hsiao, C. “Autoregressive Modeling of Canadian Money and Income Data.” J. Am. Stat. Assoc., September, 367, 74 (1979):553–560.Google Scholar
Johnson, M., Wang, C., and Ramberg, J.. “The Johnson Translation System in Monte Carlo Studies.” Commun. Statist-Simula. Computa., 11.5( 1982):521–525.Google Scholar
Johnson, R. B., and Hagan, A. R.. “Agricultural Loan Evaluation with Discriminant Analysis.” So. J. Agr. Econ., 5.2(1973): 57–62.Google Scholar
Judge, G., et al. The Theory and Practice of Econometrics. 2nd Edition. New York: Wiley and Sons, 1985.Google Scholar
Maddala, G. S., ed. Limited Dependent and Qualitative Variables in Econometrics. Cambridge University Press, 1983.Google Scholar
Mardia, K. V. “Applications of Some Measures of Multivariate Skewness and Kurtosis in Testing Normality and Robustness Studies.” Sankhya: The Indian J. Stat. Series B, Pt. 2, 36(1974): 115–128.Google Scholar
Mortensen, T., Watt, D. L., and Leistritz, F. L.. “Prediction Probability of Loan Default.” Agr. Fin. Rev., 48 (1988): 60–67.Google Scholar
Press, S. J., and Wilson, S.. “Choosing Between Logistic Regression and Discriminant Analysis.” J. Am. Stat. Assoc., 73(1978):699–705.Google Scholar
Rambaldi, A. “Evaluating the Financial Performance of Agricultural Cooperatives: a Multidimensional Model.” Masters thesis, Lousiana State University, Baton Rouge, Louisiana, 1988.Google Scholar
Scott, J. “The Probability of Bankruptcy: A Comparison of Empirical Predictions and Theoretical Models.” J. Bank, and Fin., 5(1981):317–344.Google Scholar