[PDF] Structural Vector Autoregressions eBook

Author : Lutz Kilian
Publisher : Cambridge University Press
Page : 757 pages
File Size : 32,13 MB
Release : 2017-11-23
Category : Business & Economics
ISBN : 1107196574

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This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields.

Author : Helmut Lütkepohl
Publisher : Cambridge University Press
Page : 351 pages
File Size : 44,44 MB
Release : 2004-08-02
Category : Business & Economics
ISBN : 1139454730

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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.

Author : Lutz Kilian
Publisher : Cambridge University Press
Page : 758 pages
File Size : 10,10 MB
Release : 2017-11-23
Category : Business & Economics
ISBN : 1108195288

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Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It provides guidance to empirical researchers as to the most appropriate modeling choices, methods of estimating, and evaluating structural VAR models. The book traces the evolution of the structural VAR methodology and contrasts it with other common methodologies, including dynamic stochastic general equilibrium (DSGE) models. It is intended as a bridge between the often quite technical econometric literature on structural VAR modeling and the needs of empirical researchers. The focus is not on providing the most rigorous theoretical arguments, but on enhancing the reader's understanding of the methods in question and their assumptions. Empirical examples are provided for illustration.

Author : Phoebus Dhrymes
Publisher : Springer
Page : 637 pages
File Size : 21,2 MB
Release : 2017-11-21
Category : Business & Economics
ISBN : 3319659162

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This book provides a rigorous introduction to the principles of econometrics and gives students and practitioners the tools they need to effectively and accurately analyze real data. Thoroughly updated to address the developments in the field that have occurred since the original publication of this classic text, the second edition has been expanded to include two chapters on time series analysis and one on nonparametric methods. Discussions on covariance (including GMM), partial identification, and empirical likelihood have also been added. The selection of topics and the level of discourse give sufficient variety so that the book can serve as the basis for several types of courses. This book is intended for upper undergraduate and first year graduate courses in economics and statistics and also has applications in mathematics and some social sciences where a reasonable knowledge of matrix algebra and probability theory is common. It is also ideally suited for practicing professionals who want to deepen their understanding of the methods they employ. Also available for the new edition is a solutions manual, containing answers to the end-of-chapter exercises.

Author : Olaf Hübler
Publisher : Springer Science & Business Media
Page : 236 pages
File Size : 12,20 MB
Release : 2007-04-29
Category : Business & Economics
ISBN : 3540326936

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In this book leading German econometricians in different fields present survey articles of the most important new methods in econometrics. The book gives an overview of the field and it shows progress made in recent years and remaining problems.

Author : Ralf Brüggemann
Publisher : Springer
Page : 218 pages
File Size : 13,4 MB
Release : 2004-01-14
Category : Mathematics
ISBN : 9783540206439

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1. 1 Objective of the Study Vector autoregressive (VAR) models have become one of the dominant research tools in the analysis of macroeconomic time series during the last two decades. The great success of this modeling class started with Sims' (1980) critique of the traditional simultaneous equation models (SEM). Sims criticized the use of 'too many incredible restrictions' based on 'supposed a priori knowledge' in large scale macroeconometric models which were popular at that time. Therefore, he advo cated largely unrestricted reduced form multivariate time series models, unrestricted VAR models in particular. Ever since his influential paper these models have been employed extensively to characterize the underlying dynamics in systems of time series. In particular, tools to summarize the dynamic interaction between the system variables, such as impulse response analysis or forecast error variance decompo sitions, have been developed over the years. The econometrics of VAR models and related quantities is now well established and has found its way into various textbooks including inter alia Llitkepohl (1991), Hamilton (1994), Enders (1995), Hendry (1995) and Greene (2002). The unrestricted VAR model provides a general and very flexible framework that proved to be useful to summarize the data characteristics of economic time series. Unfortunately, the flexibility of these models causes severe problems: In an unrestricted VAR model, each variable is expressed as a linear function of lagged values of itself and all other variables in the system.

Author : Patrick T. Brandt
Publisher : SAGE
Page : 121 pages
File Size : 49,48 MB
Release : 2007
Category : Mathematics
ISBN : 1412906563

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Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.

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File Size : 15,63 MB
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The Federal Reserve Bank of Richmond presents the full text of an article entitled "On the Identification of Structural Vector Autoregressions," by Pierre-Daniel G. Sarte. The article was published in the Summer 1997 issue of "Economic Quarterly." Sarte discusses the problem of identification in structural vector autoregression (VAR) estimation.