Preface
1. Introduction
Part I. Traditional Methods: 2. Linear regression for seasonal adjustment
3. Moving averages for seasonal adjustment
4. Exponential smoothing methods
Part II. Probabilistic and Statistical Properties of Stationary Processes: 5. Some results on the univariate processes
6. The Box and Jenkins method for forecasting
7. Multivariate time series
8. Time-series representations
9. Estimation and testing (stationary case)
Part III. Time-series Econometrics: Stationary and Nonstationary Models: 10. Causality, exogeneity, and shocks
11. Trend components
12. Expectations
13. Specification analysis
14. Statistical properties of nonstationary processes
Part IV. State-space Models: 15. State-space models and the Kalman filter
16. Applications of the state-space model
References
Tables
Index.

Inhaltsangabe