Articoli correlati a Applied Time Series Econometrics
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A demonstration of how time series econometrics can be used in economics and finance.
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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 is a doctoral student in the Department of Economics at Humboldt University, Berlin.
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Applied Time Series Econometrics (Themes in Modern Econometrics)
Editore:
Cambridge University Press (edition ), 2004
ISBN 10: 0521547873
ISBN 13: 9780521547871
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Paperback. Condizione: Good. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience. Codice articolo 0521547873-11-1
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Applied Time Series Econometrics
Editore:
Cambridge University Press, 2004
ISBN 10: 0521547873
ISBN 13: 9780521547871
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Applied Time Series Econometrics (Themes in Modern Econometrics)
Editore:
Cambridge University Press, 2004
ISBN 10: 0521547873
ISBN 13: 9780521547871
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Applied Time Series Econometrics (Themes in Modern Econometrics)
Editore:
Cambridge University Press, 2004
ISBN 10: 0521547873
ISBN 13: 9780521547871
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Applied Time Series Econometrics Themes in Modern Econometrics
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Cambridge University Press, 2010
ISBN 10: 0521547873
ISBN 13: 9780521547871
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gebundene Ausgabe. Condizione: Gut. 323 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); Einbandkanten sind leicht bestoßen; Buchschnitt staubschmutzig; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. Sprache: Englisch Gewicht in Gramm: 600. Codice articolo 1719543
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Applied Time Series Econometrics (Themes in Modern Econometrics)
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Applied Time Series Econometrics (Themes in Modern Econometrics)
Editore:
Cambridge University Press, 2004
ISBN 10: 0521547873
ISBN 13: 9780521547871
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Applied Time Series Econometrics (Themes in Modern Econometrics)
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Applied Time Series Econometrics (Themes in Modern Econometrics)
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Applied Time Series Econometrics (Paperback)
Editore:
Cambridge University Press, Cambridge, 2004
ISBN 10: 0521547873
ISBN 13: 9780521547871
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Paperback. Condizione: new. Paperback. Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780521547871
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