Explaining Cointegration Analysis: Part 1
讨论平稳性对经济时间序列建模的重要性，解释非平稳性的概念与来源，介绍单位根和协整的检验方法，并用蒙特卡洛模拟和实证例子说明分析过程。
'Classical' econometric theory assumes that observed data come from a stationary process, where means and variances are constant over time. Graphs of economic time series, and the historical record of economic forecasting, reveal the invalidity of such an assumption. Consequently, we discuss the importance of stationarity for empirical modeling and inference; describe the effects of incorrectly assuming stationarity; explain the basic concepts ofnon -stationarity; note some sources of non-stationarity; formulate a class of non -stationary processes (autoregressions with unit roots) that seem empirically relevant for analyzing economic time series; and show when an analysis can be transformed by means of differencing and cointegrating combinations so stationarity becomes a reasonable assumption. We then describe how to test for unit roots and cointegration. Monte Carlo simulations and empirical examples illustrate the analysis.