The Dynamics of Business Cycles: Stylized Facts, Economic Theory, Econometric Methodology and Applications

I. Methodology.- 1. Importance of Stylized Facts.- 1.1 Limitations of statistical testing.- 1.2 Evaluating economic models.- 2. Further Methodological Issues.- 2.1 Continuous versus discrete time models.- 2.2 Models of cyclical growth versus models of fluctuations.- 2.3 Detrending the data.- 2.4 Annual versus quarterly data.- 2.5 Applying models to more than one country.- II. Business Cycle Stylized Facts.- 3. Stylized Facts: Method.- 3.1 Characterizing deviations from trend: spectral analysis.- 3.2 Spectral estimation: the maximum-entropy spectrum.- 3.3 Cross spectral analysis: interpretation and estimation.- 4. Stylized Facts: Results.- 4.1 Main aggregates of national accounts.- 4.2 Longer series of fixed investment.- 4.3 Private consumption.- 4.4 Nominal variables.- 4.5 Relationship between real and nominal variables.- III. Business Cycle Models.- 5. SOA Models.- 5.1 The SOA of equipment investment.- 5.2 Recent research on inventories.- 5.3 The SOA of production and inventories.- 5.4 Errors in measurement.- 5.5 Empirical results.- 6. Consumption.- 6.1 Two models of consumption.- 6.2 Estimated consumption equations.- 6.3 Complete models.- 6.4 Empirical results.- 6.5 Appendix: computation of permanent income.- 7. Prices and Wages.- 7.1 Introduction.- 7.2 Price and consumption equations.- 7.3 Complete model.- 7.4 Empirical results.- 7.5 Summary: explaining business cycle stylized facts.- IV. Cyclical Growth.- 8. Determinants of Growth.- 8.1 Growth, saving and productivity.- 8.2 Design of the model.- 9. A Real Model of Cyclical Growth.- 9.1 Formulation of the cyclical growth model.- 9.2 Steady state.- 9.3 Deviations from steady state and stability.- 9.4 Time-varying productivity growth.- 9.5 Parameter restrictions and exogenous variables.- 9.6 Empirical results.- 9.7 Appendix I: Linearizations.- 9.8 Appendix II: Linearization error.- V. Continuous Time Econometrics.- 10. Estimating Continuous Time Models.- 10.1 Linear stochastic differential equations.- 10.2 Estimation of a first order system.- 11. The Discrete Kalman Filter.- 11.1 The state space model.- 11.2 The Kalman filter: recursive formulas and ML-estimates.- 11.3 Initialising the Kalman filter.- 12. An Exact Gaussian Estimator for General Linear Continuous Time Models.- 12.1 The exact discrete analogue.- 12.2 Evaluation of integrals.- 12.3 Efficient computation of the filter.- 12.4 Exogenous variables.- 12.5 Fixed-interval smoothing.- 13. Further Topics.- 13.1 Asymptotic properties of the estimators.- 13.2 Sensitivity analysis.- 13.3 A Monte-Carlo study.- 13.4 Spectral densities of continuous time models.- 13.5 Numerical maximization.- 13.6 Partial adjustment equations.- Conclusions.- A. Abbreviations.- B. Data.- References.