Explaining cointegration analysis: Part 1

'Classical' econometric theory assumes that observed data come from a stati onary process, where means and variances are constant over time. Graphs of economic time series, and the historical record of economic forecasting, re veal the invalidity of such an assumption. Consequently, we discuss the imp ortance of stationarity for empirical modeling and inference; describe the effects of incorrectly assuming stationarity; explain the basic concepts of nonstationarity; note some sources of non-stationarity; formulate a class of nonstationary processes (autoregressions with unit roots) that seem empi rically relevant for analyzing economic time series; and show when an analy sis can be transformed by means of differencing and cointegrating combinati ons so stationarity becomes a reasonable assumption. We then describe how t o test for unit roots and cointegration. Monte Carlo simulations and empiri cal examples illustrate the analysis.