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Zusatztext Franses' book takes the reader the whole way from fundamentals of time series analysis to the latest achievements! where the young author's own contribution is impressive ... The book gives many practical state of the art tricks and hints that an applied researcher will appreciate. Klappentext This book provides a self-contained account of periodic models for seasonally observed economic time series with stochastic trends. Two key concepts are periodic integration and periodic cointegration. Periodic integration implies that a seasonally varying differencing filter is required to remove a stochastic trend. Periodic cointegration amounts to allowing cointegration paort-term adjustment parameters to vary with the season. The emphasis is on useful econrameters and shometric models that explicitly describe seasonal variation and can reasonably be interpreted in terms of economic behaviour. The analysis considers econometric theory! Monte Carlo simulation! and forecasting! and it is illustrated with numerous empirical time series. A key feature of the proposed models is that changing seasonal fluctuations depend on the trend and business cycle fluctuations. In the case of such dependence! it is shown that seasonal adjustment leads to inappropriate results. Zusammenfassung This is an advanced graduate textbook in econometrics. A large proportion of the data studied by econometricians are series of observations of the same variables made over time (time series). This book provides a comprehensive account of how to allow for seasonal fluctuations in these data by using periodic models. Inhaltsverzeichnis Introduction 1: Concepts in Time Series Analysis 2: An introduction to seasonal time series 3: Seasonal adjustment 4: Seasonal integration and cointegration 5: Are seasons, trends, and cycles always independent? 6: Periodic autoregressive time series models 7: Periodic integration 8: Periodic cointegration 9: Conclusion Data Appendix ...
