In this paper, we propose an iterative approach within a threshold quantile regression framework to identify sequential structural breaks. We apply it to a time series analysis with a focus on establishing a connection between structural breaks in the gasoline consumption function and extreme events in the economy. The estimated structural breaks and piecewise relationship between Australia’s automobile gasoline consumption and household disposable income are consistent with economic intuition. Moreover, the heterogeneity in their relation across various quantiles and over different time periods divided by the identified structural breaks is revealed in a systematic manner. The comparison with a state-of-practice approach demonstrates the validity and efficiency of our approach.

在本文中，我们提出了一种在阈值分位数回归框架内的迭代方法来识别顺序结构中断。我们将其应用于时间序列分析，重点是在汽油消费函数的结构性断裂与经济中的极端事件之间建立联系。澳大利亚汽车汽油消费与家庭可支配收入之间的结构性断裂和分段关系的估计值与经济直觉一致。此外，以系统的方式揭示了它们在不同分位数和不同时间段内除以已识别的结构断裂之间的关系的异质性。与实践状态方法的比较证明了我们方法的有效性和效率。