英文摘要 |
In the academic circle, it is usually hypothesized as a single distribution function for the duration model while applying to Schmidt and Witte's (1989) split population duration model. When we applied this model to the bank runs in the Credit Department of Farmer's Institutions, it has discovered that there is a bimodal distribution in the hazard rate function, and that is not apropos to continuously hypothesizing it as a single distribution function for the reason that a single distribution function does not include a bimodal distribution hazard function. In this study, we chose a mixed distribution function for the duration model, for example, two log-normal and log-logistic; one log-normal and log-logistic; one log-normal, and one log-normal with Weibull, which could all produce a bimodal distribution hazard rate function. After that, we used these mixed distributions to re-estimate the split population duration model; also used the AIC Value, Likelihood Ratio Test, and t-test to compare the quality of different models, and it showed that the mixed split population duration model is better than the single distribution model. From this empirical result, we have found that the parameter estimating value of both the ratio of insured borrowing to total borrowing and whether to join deposit insurance are positive and significant. For the customers who have high ratio of insured borrowing to total borrowing or have joined deposit insurance would likely to have later bank runs, which relatively proved that they would have lower the risk of bank runs. |