Applied Time Series Econometrics (Hardcover)

Preface; Notation and abbreviations; List of contributors; Part I. Initial Tasks and Overview Helmut Lutkepohl: 1. Introduction; 2. Setting up an econometric project; 3. Getting data; 4. Data handling; 5. Outline of chapters; Part II. Univariate Time Series Analysis Helmut Lutkepohl: 6. Characteristics of time series; 7. Stationary and integrated stochastic processes; 8. Some popular time series models; 9. Parameter estimation; 10. Model specification; 11. Model checking; 12. Unit root tests; 13. Forecasting univariate time series; 14. Examples; 15. Where to go from here; Part III. Vector Autoregressive and Vector Error Correction Models Helmut Lutkepohl: 16. Introduction; 17. VARs and VECMs; 18. Estimation; 19. Model specification; 20. Model checking; 21. Forecasting VAR processes and VECMs; 22. Granger-causality analysis; 23. An example; 24. Extensions; Part IV. Structural Vector Autoregressive Modelling and Impulse Responses Jorg Breitung, Ralf Bruggemann and Helmut Lutkepohl: 25. Introduction; 26. The models; 27. Impulse response analysis; 28. Estimation of structural parameters; 29. Statistical inference for impulse responses; 30. Forecast error variance decomposition; 31. Examples; 32. Conclusions; Part V. Conditional Heteroskedasticity Helmut Herwartz: 33. Stylized facts of empirical price processes; 34. Univariate GARCH models; 35. Multivariate GARCH models; Part VI. Smooth Transition Regression Modelling Timo Terasvirta: 36. Introduction; 37. The model; 38. The modelling cycle; 39. Two empirical examples; 40. Final remarks; Part VII. Nonparametric Time Series Modelling Rolf Tschernig: 41. Introduction; 42. Local linear estimation; 43. Bandwidth and lag selection; 44. Diagnostics; 45. Modelling the conditional volatility; 46. Local linear seasonal modelling; 47. Example I: average weekly working hours in the United States; 48. Example II: XETRA dax index; Part VIII. The Software JMulTi Markus Kratzig: 49. Introduction to JMulTi; 50. Numbers, dates and variables in JMulTi; 51. Handling data sets; 52. Selecting, transforming and creating time series; 53. Managing variables in JMulTi; 54. Notes for econometric software developers; 55. Conclusion; References; Index.