Structural Vector Autoregressive Analysis

Structural Vector Autoregressive Analysis PDF Author: Lutz Kilian
Publisher: Cambridge University Press
ISBN: 1107196574
Category : Business & Economics
Languages : en
Pages : 757

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

Structural Vector Autoregressive Analysis

Structural Vector Autoregressive Analysis PDF Author: Lutz Kilian
Publisher: Cambridge University Press
ISBN: 1107196574
Category : Business & Economics
Languages : en
Pages : 757

Get Book Here

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

Empirical Identification of the Vector Autoregression

Empirical Identification of the Vector Autoregression PDF Author: Kevin D. Hoover
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
The M2 monetary aggregate is monitored by the Federal Reserve, using a broad brush theoretical analysis and an informal empirical analysis. This paper illustrates empirical identification of an eleven-variable system, in which M2 and the factors that the Fed regards as causes and effects are captured in a vector autogregression. Taking account of cointegration, the methodology combines recent developments in graph-theoretical causal search algorithms with a general-to-specific search algorithm to identify a fully specified structural vector autoregression (SVAR). The SVAR is used to examine the causes and effects of M2 in a variety of ways. We conclude that, while the Fed has rightly identified a number of special factors that influence M2 and while M2 detectably affects other important variables, there is 1) little support for the core quantity-theoretic approach to M2 used by the Fed; and 2) M2 is a trivial linkage in the transmission mechanism from monetary policy to real output and inflation.

Unconventional Identification in Vector Autoregressive Models: Empirical Essays on Credit, Risk and Uncertainty

Unconventional Identification in Vector Autoregressive Models: Empirical Essays on Credit, Risk and Uncertainty PDF Author: Maximilian Podstawski
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Structural Vector Autoregressive Analysis

Structural Vector Autoregressive Analysis PDF Author: Lutz Kilian
Publisher: Cambridge University Press
ISBN: 1108186874
Category : Business & Economics
Languages : en
Pages : 757

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Book Description
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.

Essays in Empirical Macroeconomics: Identification in Vector Autoregressive Models and Robust Inference in Early Warning Systems

Essays in Empirical Macroeconomics: Identification in Vector Autoregressive Models and Robust Inference in Early Warning Systems PDF Author: Martin Bruns
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Multiple Time Series Models

Multiple Time Series Models PDF Author: Patrick T. Brandt
Publisher: SAGE
ISBN: 1412906563
Category : Mathematics
Languages : en
Pages : 121

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Book Description
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.

The Cointegrated VAR Model

The Cointegrated VAR Model PDF Author: Katarina Juselius
Publisher: OUP Oxford
ISBN: 0191622966
Category : Business & Economics
Languages : en
Pages : 478

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Book Description
This valuable text provides a comprehensive introduction to VAR modelling and how it can be applied. In particular, the author focuses on the properties of the Cointegrated VAR model and its implications for macroeconomic inference when data are non-stationary. The text provides a number of insights into the links between statistical econometric modelling and economic theory and gives a thorough treatment of identification of the long-run and short-run structure as well as of the common stochastic trends and the impulse response functions, providing in each case illustrations of applicability. This book presents the main ingredients of the Copenhagen School of Time-Series Econometrics in a transparent and coherent framework. The distinguishing feature of this school is that econometric theory and applications have been developed in close cooperation. The guiding principle is that good econometric work should take econometrics, institutions, and economics seriously. The author uses a single data set throughout most of the book to guide the reader through the econometric theory while also revealing the full implications for the underlying economic model. To test ensure full understanding the book concludes with the introduction of two new data sets to combine readers understanding of econometric theory and economic models, with economic reality.

Empirical Vector Autoregressive Modeling

Empirical Vector Autoregressive Modeling PDF Author: Marius Ooms
Publisher: Springer Science & Business Media
ISBN: 3642487920
Category : Business & Economics
Languages : en
Pages : 397

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Book Description
1. 1 Integrating results The empirical study of macroeconomic time series is interesting. It is also difficult and not immediately rewarding. Many statistical and economic issues are involved. The main problems is that these issues are so interrelated that it does not seem sensible to address them one at a time. As soon as one sets about the making of a model of macroeconomic time series one has to choose which problems one will try to tackle oneself and which problems one will leave unresolved or to be solved by others. From a theoretic point of view it can be fruitful to concentrate oneself on only one problem. If one follows this strategy in empirical application one runs a serious risk of making a seemingly interesting model, that is just a corollary of some important mistake in the handling of other problems. Two well known examples of statistical artifacts are the finding of Kuznets "pseudo-waves" of about 20 years in economic activity (Sargent (1979, p. 248)) and the "spurious regression" of macroeconomic time series described in Granger and Newbold (1986, ยง6. 4). The easiest way to get away with possible mistakes is to admit they may be there in the first place, but that time constraints and unfamiliarity with the solution do not allow the researcher to do something about them. This can be a viable argument.

Structural Vector Autoregressive Analysis

Structural Vector Autoregressive Analysis PDF Author: Lutz Kilian
Publisher: Cambridge University Press
ISBN: 1108195288
Category : Business & Economics
Languages : en
Pages : 758

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Book Description
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.

Handbook of Research Methods and Applications in Empirical Macroeconomics

Handbook of Research Methods and Applications in Empirical Macroeconomics PDF Author: Nigar Hashimzade
Publisher: Edward Elgar Publishing
ISBN: 0857931024
Category : Business & Economics
Languages : en
Pages : 627

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Book Description
This comprehensive Handbook presents the current state of art in the theory and methodology of macroeconomic data analysis. It is intended as a reference for graduate students and researchers interested in exploring new methodologies, but can also be employed as a graduate text. The Handbook concentrates on the most important issues, models and techniques for research in macroeconomics, and highlights the core methodologies and their empirical application in an accessible manner. Each chapter is largely self-contained, whilst the comprehensive introduction provides an overview of the key statistical concepts and methods. All of the chapters include the essential references for each topic and provide a sound guide for further reading. Topics covered include unit roots, non-linearities and structural breaks, time aggregation, forecasting, the Kalman filter, generalised method of moments, maximum likelihood and Bayesian estimation, vector autoregressive, dynamic stochastic general equilibrium and dynamic panel models. Presenting the most important models and techniques for empirical research, this Handbook will appeal to students, researchers and academics working in empirical macro and econometrics.