Some Identification Problems in the Cointegrated Vector Autoregressive Model

Some Identification Problems in the Cointegrated Vector Autoregressive Model PDF Author: Søren Johansen
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ISBN:
Category :
Languages : en
Pages :

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Some Identification Problems in the Cointegrated Vector Autoregressive Model

Some Identification Problems in the Cointegrated Vector Autoregressive Model PDF Author: Søren Johansen
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description


Some Identification Problems in the Cointegrated Vector Autoregressive Model

Some Identification Problems in the Cointegrated Vector Autoregressive Model PDF Author: Soren Johansen
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
An analysis of some identification problems in the cointegrated VAR is given. We give a new criteria for identification by linear restrictions on individual relations which is equivalent to the rank condition. We compare the asymptotic distribution of the estimators of alpha and beta when they are identified by linear restrictions on alpha and when they are identified by linear restrictions on alpha in which case a component of beta is asymptotically Gaussian. Finally we discuss identification of shocks by introducing the contemporaneous and permanent effect of a shock and the distinction between permanent and transitory shocks, which allows one to identify permanent shocks from the long-run variance and transitory shocks from the short-run variance.

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.

Likelihood-based Inference in Cointegrated Vector Autoregressive Models

Likelihood-based Inference in Cointegrated Vector Autoregressive Models PDF Author: Søren Johansen
Publisher: Oxford University Press, USA
ISBN: 0198774508
Category : Business & Economics
Languages : en
Pages : 280

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Book Description
This monograph is concerned with the statistical analysis of multivariate systems of non-stationary time series of type I. It applies the concepts of cointegration and common trends in the framework of the Gaussian vector autoregressive model.

Applied Time Series Econometrics

Applied Time Series Econometrics PDF Author: Helmut Lütkepohl
Publisher: Cambridge University Press
ISBN: 1139454730
Category : Business & Economics
Languages : en
Pages : 351

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Book Description
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.

Identifying Structural Breaks in Cointegrated Vector Autoregressive Models

Identifying Structural Breaks in Cointegrated Vector Autoregressive Models PDF Author: Håvard Hungnes
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
This article suggests an alternative formulation of the cointegrated vector autoregressive (VAR) model such that the coefficients for the deterministic terms have straightforward interpretations. These coefficients can be interpreted as growth rates and cointegration mean level coefficients and express long-run properties of the model. For example, the growth rate coefficients tell us how much to expect (unconditionally) the variables in the system to grow from one period to the next, representing the underlying (steady state) growth in the variables. The estimation of the proposed formulation is made operationally in GRaM, which is a program for Ox Professional. GRaM can be used for analysing structural breaks when the deterministic terms include shift dummies and broken trends. By applying a formulation with interpretable deterministic components, different types of structural breaks can be identified. Shifts in both intercepts and growth rates, or combinations of these, can be tested for. The ability to distinguish between different types of structural breaks makes the procedure superior compared with alternative procedures. Furthermore, the procedure utilizes the information more efficiently than alternative procedures. Finally, interpretable coefficients of different types of structural breaks can be identified.

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.

Modern Econometric Analysis

Modern Econometric Analysis PDF Author: Olaf Hübler
Publisher: Springer Science & Business Media
ISBN: 3540326936
Category : Business & Economics
Languages : en
Pages : 236

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Book Description
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.

Recent Developments in Cointegration

Recent Developments in Cointegration PDF Author: Katarina Juselius
Publisher: MDPI
ISBN: 3038429554
Category : Business & Economics
Languages : en
Pages : 219

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Book Description
This book is a printed edition of the Special Issue "Recent Developments in Cointegration" that was published in Econometrics

Model Reduction Methods for Vector Autoregressive Processes

Model Reduction Methods for Vector Autoregressive Processes PDF Author: Ralf Brüggemann
Publisher: Springer Science & Business Media
ISBN: 3642170293
Category : Mathematics
Languages : en
Pages : 226

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Book Description
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.