This study introduces two Markov chain time approaches, time-homogeneous and nonhomogeneous models, for analyzing farm credit risk migration as alternatives to the traditional discrete-time (cohort) method. The Markov chain models are found to produce more accurate, reliable transition...

Logistic regression techniques for panel data are used to identify factors affecting farm credit transition probabilities. Results indicate that most farm‐specific factors do not have adequate explanatory influence on the probability of farm credit risk transition. Class upgrade probabilities...

This study introduces two Markov chain time approaches, time‐homogeneous and nonhomogeneous models, for analyzing farm credit risk migration as alternatives to the traditional discrete‐time (cohort) method. The Markov chain models are found to produce more accurate, reliable transition...

The migration approach to credit risk measurement is based on historic rates of movements of individual loans among the classes of a lender’s risk‐rating or credit‐scoring system. This article applies the migration concept to farm‐level data from Illinois to estimate migration rates for...