Efficient tests for general persistent time variation in regression coefficients

• 成果类型: Article
• 署名作者: Elliott, Graham; Mueller, Ulrich K.
• 署名单位: Princeton University
• 刊物名称: REVIEW OF ECONOMIC STUDIES
• ISSN/ISSBN: 0034-6527
• DOI: 10.1111/j.1467-937X.2006.00402.x
• 发表日期: 2006
• 页码: 907-940
• 关键词: random-walk coefficients; structural-change; parameter instability; nuisance parameter; lucas critique; STABILITY; heteroskedasticity; constancy

摘要

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.