Efficient Tests for General Persistent Time Variation in Regression Coefficients
提出一类持久断裂过程的高效检验，涵盖多种系数不稳定形式，并给出一个简单易算的检验统计量，适用于异方差模型，对实证研究者判断模型稳定性有帮助。
There are a large number of tests for instability or breaks in coefficients in regression models designed for different possible departures from the stable model. We make two contributions to this literature. First, we consider a large class of persistent breaking processes that lead to asymptotically equivalent efficient tests. Our class allows for many or relatively few breaks, clustered breaks, regularly occurring breaks, or smooth transitions to changes in the regression coefficients. Thus, asymptotically nothing is gained by knowing the exact breaking process of the class. Second, we provide a test statistic that is simple to compute, avoids any need for searching over high dimensions when there are many breaks, is valid for a wide range of data-generating processes and has good power and size properties even in heteroscedastic models. Copyright 2006, Wiley-Blackwell.