Abstract
Schmidt and Witte (1989) present a split population duration model in which the decisions of whether and when to start an event must be independent due to the absence of a closed-form result for the integration. This paper following Leung and Yu (2002, 2007) develops an interdependently split population duration model which allows the interdependence of the decisions of whether and when to start an event. We apply the Monte Carlo simulation to resolve the integration problem. We show the independent split population duration model is hence nested in our interdependently split population duration model. Our model is applied to investigate the bank runs events of the credit departments of farmers' institutions. The results show the superiority of our model to other duration models according to the criteria of AIC, likelihood ratio test, and t-ratio test. The empirical results show that both the ratio of borrowing capital to total capital and the overdue ratio are positively correlated with the probability of runs and the hazard rate to run while the liquidity ratio is negatively correlated with them. More importantly, our result shows banks with higher deposit interest rates are easier to trigger runs, which is consistent with the finding of Schumacher (2000).