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Applied Time Series Econometrics

Applied Time Series Econometrics

$57.00 (P)

Part of Themes in Modern Econometrics

Helmut Lütkepohl, Jörg Breitung, Ralf Brüggemann, Helmut Herwartz, Timo Teräsvirta, Rolf Tschernig, Markus Krätzig
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  • Date Published: August 2004
  • availability: Available
  • format: Paperback
  • isbn: 9780521547871

$ 57.00 (P)
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About the Authors
  • 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.

    • The treatment includes methodological advances on the subject matter in a particularly cohesive fashion
    • Emphasizes applications in economics and finance and goes through a number of empirical studies in some detail
    • The user friendly software JMulTi is provided to supplement the text which may be used in advanced coursework
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    Product details

    • Date Published: August 2004
    • format: Paperback
    • isbn: 9780521547871
    • length: 352 pages
    • dimensions: 229 x 152 x 20 mm
    • weight: 0.49kg
    • contains: 69 b/w illus. 38 tables
    • availability: Available
  • Table of Contents

    Preface
    Notation and abbreviations
    List of contributors
    Part I. Initial Tasks and Overview Helmut Lütkepohl:
    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 Lütkepohl:
    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 Lütkepohl:
    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 Jörg Breitung, Ralf Brüggemann and Helmut Lütkepohl:
    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 Teräsvirta:
    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 Krätzig:
    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.

  • Editors

    Helmut Lütkepohl, European University Institute, Florence
    Helmut Lütkepohl is Professor of Economics at the European University Institute in Florence, Italy. He is on leave from Humboldt University Berlin where he has been Professor of Econometrics in the Faculty of Economics and Business Administration since 1992. He had previously been Professor of Statistics at the University of Kiel (1987–1992) and the University of Hamburg (1985-1987) and was Visiting Assistant Professor at the University of California, San Diego (1984-85). Professor Lütkepohl is Associate Editor of Econometric Theory, the Journal of Applied Econometrics, Macroeconomic Dynamics, Empirical Economics and Econometric Reviewa. He has published extensively in learned journals and books and is author, co-author and editor of a number of books in econometrics and time series analysis. Professor Lütkepohl is the author of Introduction to Multiple Time Series Analysis (1991) and a Handbook of Matrices (1996). His current teaching and research interests include methodological issues related to the study of nonstationary, integrated time series and the analysis of the transmission mechanism of monetary policy in the Euro area.

    Markus Krätzig, Humboldt-Universität zu Berlin
    Markus Krätzig is a doctoral student in the Department of Economics at Humboldt University, Berlin.

    Contributors

    Helmut Lütkepohl, Jörg Breitung, Ralf Brüggemann, Helmut Herwartz, Timo Teräsvirta, Rolf Tschernig, Markus Krätzig

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