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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.
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.
Author: Tim Kovalenko
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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.
Author: Hilde C. Bjørnland
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
We estimate the interdependence between US monetary policy and the S&P 500 using structural VAR methodology. A solution is proposed to the simultaneity problem of identifying monetary and stock price shocks by using a combination of short-run and long-run restrictions that maintains the qualitative properties of a monetary policy shock found in the established literature (CEE 1999). We find great interdependence between interest rate setting and stock prices. Stock prices immediately fall by 1.5 per cent due to a monetary policy shock that raises the federal funds rate by ten basis points. A stock price shock increasing stock prices by one per cent leads to an increase in the interest rate of five basis points. Stock price shocks are orthogonal to the information set in the VAR model and can be interpreted as non-fundamental shocks. We attribute a major part of the surge in stock prices at the end of the 1990s to these non-fundamental shocks.
Author: Giovanni Angelini
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external instruments, considering the case in which r valid instruments are used to identify g ≥ 1 structural shocks, where r ≥ g. We endow the SVAR with an auxiliary statistical model for the external instruments which is a system of reduced form equations. The SVAR and the auxiliary model for the external instruments jointly form a 'larger' SVAR characterized by a particularly restricted parametric structure, and are connected by the covariance matrix of their disturbances which incorporates the 'relevance' and 'exogeneity' conditions. We discuss identification results and likelihood-based estimation methods both in the 'multiple shocks' approach, where all structural shocks are of interest, and in the 'partial shock' approach, where only a subset of the structural shocks is of interest. Overidentified SVARs with external instruments can be easily tested in our setup. The suggested method is applied to investigate empirically whether commonly employed measures of macroeconomic and financial uncertainty respond on-impact, other than with lags, to business cycle fluctuations in the U.S. in the period after the Global Financial Crisis. To do so, we employ two external instruments to identify the real economic activity shock in a partial shock approach.
Author: Yuriy Gorodnichenko
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This paper integrates imposing a factor structure on residuals in vector autoregressions (VARs) into structural VAR analysis. Identification, estimation and testing procedures are discussed. The paper applies this approach to the well-known problem of studying the effects of monetary policy in open economy VAR models. The use of factor structure in identifying structural shocks is shown to resolve three long-standing puzzles in VAR literature. First, the price level does not increase in response to a monetary tightening. Second, the exchange rate appreciates on impact and then gradually depreciates. Hence, no price level and exchange rate puzzles are found. Third, monetary policy shocks are much less volatile than suggested by standard VAR identification schemes. In addition, the paper suggests that the apparent weak contemporaneous cross-variable responses and strong own responses in structural VARs can be an artifact of identifying assumptions and vanish after imposing a factor structure on the shocks.
Author: Carlo Giannini
Publisher: Springer Science & Business Media
ISBN: 3662027577
Category : Business & Economics
Languages : en
Pages : 144
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Book Description
1. Introduction 1 2. Identification Analysis and F.I.M.L. Estimation for the K-Mode1 10 3. Identification Analysis and F.I.ML. Estimation for the C-Model 23 4. Identification Analysis and F.I.M.L. Estimation for the AB-Model 32 5. Impulse Response Analysis and Forecast Error Variance Decomposition in SVAR Modeling 44 5 .a Impulse Response Analysis 44 5.b Variance Decomposition (by Antonio Lanzarotti) 51 6. Long-run A-priori Information. Deterministic Components. Cointegration 58 6.a Long-run A-priori Information 58 6.b Deterministic Components 62 6.c Cointegration 65 7. The Working of an AB-Model 71 Annex 1: The Notions ofReduced Form and Structure in Structural VAR Modeling 83 Annex 2: Some Considerations on the Semantics, Choice and Management of the K, C and AB-Models 87 Appendix A 93 Appendix B 96 Appendix C (by Antonio Lanzarotti and Mario Seghelini) 99 Appendix D (by Antonio Lanzarotti and Mario Seghelini) 109 References 128 Foreword In recent years a growing interest in the structural VAR approach (SVAR) has followed the path-breaking works by Blanchard and Watson (1986), Bemanke (1986) and Sims (1986), especially in U.S. applied macroeconometric literature. The approach can be used in two different, partially overlapping directions: the interpretation ofbusiness cycle fluctuations of a small number of significantmacroeconomic variables and the identification of the effects of different policies.
Author: Gianni Amisano
Publisher: Springer Science & Business Media
ISBN: 3642606237
Category : Business & Economics
Languages : en
Pages : 194
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Book Description
In recent years a growing interest in the structural V AR approach (SV AR) has followed the path-breaking works by Blanchard and Watson (1986), Bernanke (1986) and Sims (1986), especially in the U.S. applied macroeconometric literature. The approach can be used in two different, partially overlapping, directions: the interpretation of business cycle fluctuations of a small number of significant macroeconomic variables and the identification of the effects of different policies. SV AR literature shows a common feature: the attempt to "organise", in a "structural" theoretical sense, instantaneous correlations among the relevant variables. In non-structural V AR modelling, instead, correlations are normally hidden in the variance covariance matrix of the V AR model innovations. of independent V AR analysis tries to isolate ("identify") a set shocks by means of a number of meaningful theoretical restrictions. The shocks can be regarded as the ultimate source of stochastic variation of the vector of variables which can all be seen as potentially endogenous. Looking at the development of SV AR literature we felt that it still lacked a formal general framework which could embrace the several types of models so far proposed for identification and estimation. This is the second edition of the book, which originally appeared as number 381 of the Springer series "Lecture notes in Economics of the first edition was Carlo and Mathematical Systems". The author Giannini.
Author: Gary Koop
Publisher: Now Publishers Inc
ISBN: 160198362X
Category : Business & Economics
Languages : en
Pages : 104
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Book Description
Bayesian Multivariate Time Series Methods for Empirical Macroeconomics provides a survey of the Bayesian methods used in modern empirical macroeconomics. These models have been developed to address the fact that most questions of interest to empirical macroeconomists involve several variables and must be addressed using multivariate time series methods. Many different multivariate time series models have been used in macroeconomics, but Vector Autoregressive (VAR) models have been among the most popular. Bayesian Multivariate Time Series Methods for Empirical Macroeconomics reviews and extends the Bayesian literature on VARs, TVP-VARs and TVP-FAVARs with a focus on the practitioner. The authors go beyond simply defining each model, but specify how to use them in practice, discuss the advantages and disadvantages of each and offer tips on when and why each model can be used.
Author: Phoebus Dhrymes
Publisher: Springer
ISBN: 3319659162
Category : Business & Economics
Languages : en
Pages : 637
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Book Description
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.
