APPLIED TIME SERIES ECONOMETRICS LUTKEPOHL H. Księgarnia

A demonstration of how time series econometrics can be used in economics and finance.

Time series econometrics is used for predicting future developments of variables of interest such as economic growth, stock market volatility or interest rates. A model has to be constructed, accordingly, to describe the data generation process and to estimate its parameters. Modern tools to accomplish these tasks are provided in this volume, which also demonstrates by example how the tools can be applied.

Contents

Part I. Initial Tasks and Overview:

1. Introduction;
2. Setting up an econometric project;
3. Getting data;
4. Data handling;
5. Outline of chapters;

Part II. Univariate Time Series Analysis:

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:

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:

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:

33. Stylized facts of empirical price processes;
34. Univariate GARCH models;
35. Multivariate GARCH models;

Part VI. Smooth Transition Regression Modelling:

36. Introduction;
37. The model;
38. The modelling cycle;
39. Two empirical examples;
40. Final remarks;

Part VII. Nonparametric Time Series Modelling:

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 U.S.;
48. Example II: XETRA dax index;

Part VIII. The Software JMulTi:

49. Introduction to JMulTi;
50. Numbers, dates and variables in JMulTi;
51. Handling datasets;
52. Selecting, transforming and creating time series;
53. Managing variables in JMulTi;
54. Notes for econometric software developers;
55. Conclusion.

Paperback, 350 pages

Po otrzymaniu zamówienia poinformujemy,
czy wybrany tytuł polskojęzyczny lub anglojęzyczny jest aktualnie na półce księgarni.