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This paper introduces two continuous time models, i.e. time homogenous and non-homogenous Markov chain models, for analyzing farm credit migration as alternatives to the traditional discrete time model cohort method. Results illustrate that the two continuous time models provide more detailed, accurate and reliable estimates of farm credit migration rates than the discrete time model. Metric comparisons among the three transition matrices show that the imposition of the potentially unrealistic assumption of time homogeneity still produces more accurate estimates of farm credit migration rates, although the equally reliable figures under the non-homogenous time model seem more plausible given the greater relevance and applicability of the latter model to farm business conditions.


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