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Abstract
This study utilizes comparisons and Probit regression analysis to determine the influence
of previous migrations and other variables on the likelihood of future migrations of
agricultural loan credit risk. The Farm Credit System association data set contains a large
number of lender risk-rated agricultural loans. The lender risk ratings used are less likely
to migrate than ratings based on credit score proxies. The results indicate that the
direction of previous migrations significantly influences future migrations in a trendreversal
pattern. Forecasting future migrations remains difficult even though the
marginal effect of a previous migration on the likelihood of a future migration is quite
large.