Nonstationary time series analysis and cointegration

Nonstationary Time Series Analysis and Cointegration shows major developments in the econometric analysis of the long run (of nonstationarity and cointegration) - a field which has developed dramatically over the last twelve years to have a profound effect on econometric analysis in general. The papers here describe and evaluate new methods, provide useful overviews, and show detailed implementations helpful to practitioners. Papers include two substantive analyses of economic forecasting, based around an integral understanding of integration and cointegration and an evaluation of real business cycle models. There is an evaluation of different cointegration estimators and a new test for cointegration. There is a discussion of the effects of seasonality, looking at seasonal unit roots and at encompassing modelling with seasonally unadjusted versus adjusted data. A different style of nonstationarity is raised in a discussion of testing for inflationary bubbles and for time-varying transition probabilities in Hamilton's Markov switching model. This volume provides wide-ranging coverage of the literature, showing the importance of nonstationarity and cointegration.