Testing Parameter Constancy in Stationary Vector Autoregressive Models Against Continuous Change
提出一种检验平稳向量自回归模型参数是否随时间平滑变化的统计检验方法，该检验包含结构突变作为特例，且渐近分布理论标准，模拟显示其表现优于广义Chow检验。
In this article we derive a parameter constancy test of a stationary vector autoregressive model against the hypothesis that the parameters of the model change smoothly over time. A single structural break is contained in this alternative hypothesis as a special case. The test is a generalization of a single-equation test of a similar hypothesis proposed in the literature. An advantage here is that the asymptotic distribution theory is standard. The performance of the tests is compared to that of generalized Chow-tests and found satisfactory in terms of both size and power.