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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: 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: 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: Gianni Amisano
Publisher:
ISBN: 9783642606243
Category :
Languages : en
Pages : 200
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Book Description
Author: Steven Durlauf
Publisher: Springer
ISBN: 0230280838
Category : Business & Economics
Languages : en
Pages : 417
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Book Description
Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
Author: Burcu Adıgüzel Mercangöz
Publisher: Springer Nature
ISBN: 3030541088
Category : Business & Economics
Languages : en
Pages : 465
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Book Description
This handbook presents emerging research exploring the theoretical and practical aspects of econometric techniques for the financial sector and their applications in economics. By doing so, it offers invaluable tools for predicting and weighing the risks of multiple investments by incorporating data analysis. Throughout the book the authors address a broad range of topics such as predictive analysis, monetary policy, economic growth, systemic risk and investment behavior. This book is a must-read for researchers, scholars and practitioners in the field of economics who are interested in a better understanding of current research on the application of econometric methods to financial sector data.
Author: Helmut Lütkepohl
Publisher: Springer Science & Business Media
ISBN: 3662026910
Category : Business & Economics
Languages : en
Pages : 556
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Book Description
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.
Author: Thomas B. Fomby
Publisher: Emerald Group Publishing Limited
ISBN: 9781781907528
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
Advances in Econometrics publishes original scholarly econometric papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics, throughout the empirical economic, business and social science literature.
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.
