Monitoring structural change in dynamic econometric models
提出一系列波动型检验方法，用于在已知历史回归关系稳定的情况下，监测新数据是否仍符合该关系。扩展了基于回归系数估计的检验，引入OLS残差、重新缩放统计量和替代渐近边界，并应用于德国M1货币需求、美国劳动生产率和S&P 500股票收益三个数据集。
Abstract The classical approach to testing for structural change employs retrospective tests using a historical data set of a given length. Here we consider a wide array of fluctuation‐type tests in a monitoring situation—given a history period for which a regression relationship is known to be stable, we test whether incoming data are consistent with the previously established relationship. Procedures based on estimates of the regression coefficients are extended in three directions: we introduce (a) procedures based on OLS residuals, (b) rescaled statistics and (c) alternative asymptotic boundaries. Compared to the existing tests our extensions offer ease of computation, improved size in finite samples for dynamic models and better power against certain alternatives, respectively. We apply our methods to three data sets, German M1 money demand, US labour productivity and S&P 500 stock returns. Copyright © 2005 John Wiley & Sons, Ltd.