Assessing Structural VARs

Assessing Structural VARs

Author: Lawrence J. Christiano

Publisher:

Published: 2006

Total Pages: 72

ISBN-13:

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This paper analyzes the quality of VAR-based procedures for estimating the response of the economy to a shock. We focus on two key issues. First, do VAR-based confidence intervals accurately reflect the actual degree of sampling uncertainty associated with impulse response functions? Second, what is the size of bias relative to confidence intervals, and how do coverage rates of confidence intervals compare with their nominal size? We address these questions using data generated from a series of estimated dynamic, stochastic general equilibrium models. We organize most of our analysis around a particular question that has attracted a great deal of attention in the literature: How do hours worked respond to an identified shock? In all of our examples, as long as the variance in hours worked due to a given shock is above the remarkably low number of 1 percent, structural VARs perform well. This finding is true regardless of whether identification is based on short-run or long-run restrictions. Confidence intervals are wider in the case of long-run restrictions. Even so, long-run identified VARs can be useful for discriminating among competing economic models.


Structural Vector Autoregressive Analysis

Structural Vector Autoregressive Analysis

Author: Lutz Kilian

Publisher: Cambridge University Press

Published: 2017-11-23

Total Pages: 757

ISBN-13: 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.


Structural Vector Autoregressive Analysis

Structural Vector Autoregressive Analysis

Author: Lutz Kilian

Publisher: Cambridge University Press

Published: 2017-11-23

Total Pages: 757

ISBN-13: 1108186874

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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.


Multiple Time Series Models

Multiple Time Series Models

Author: Patrick T. Brandt

Publisher: SAGE

Published: 2007

Total Pages: 121

ISBN-13: 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.


Dissecting Taylor Rules in a Structural VAR

Dissecting Taylor Rules in a Structural VAR

Author: Woon Gyu Choi

Publisher: International Monetary Fund

Published: 2010-01-01

Total Pages: 29

ISBN-13: 1451918682

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This paper uncovers Taylor rules from estimated monetary policy reactions using a structural VAR on U.S. data from 1959 to 2009. These Taylor rules reveal the dynamic nature of policy responses to different structural shocks. We find that U.S. monetary policy has been far more responsive over time to demand shocks than to supply shocks, and more aggressive toward inflation than output growth. Our estimated dynamic policy coefficients characterize the style of policy as a "bang-bang" control for the pre-1979 period and as a gradual control for the post-1979 period.


Structural Econometric Models

Structural Econometric Models

Author: Eugene Choo

Publisher: Emerald Group Publishing

Published: 2013-12-18

Total Pages: 447

ISBN-13: 1783500530

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This volume focuses on recent developments in the use of structural econometric models in empirical economics. The first part looks at recent developments in the estimation of dynamic discrete choice models. The second part looks at recent advances in the area empirical matching models.


Handbook of Market Research

Handbook of Market Research

Author: Christian Homburg

Publisher: Springer

Published: 2021-12-03

Total Pages: 0

ISBN-13: 9783319574110

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In this handbook, internationally renowned scholars outline the current state-of-the-art of quantitative and qualitative market research. They discuss focal approaches to market research and guide students and practitioners in their real-life applications. Aspects covered include topics on data-related issues, methods, and applications. Data-related topics comprise chapters on experimental design, survey research methods, international market research, panel data fusion, and endogeneity. Method-oriented chapters look at a wide variety of data analysis methods relevant for market research, including chapters on regression, structural equation modeling (SEM), conjoint analysis, and text analysis. Application chapters focus on specific topics relevant for market research such as customer satisfaction, customer retention modeling, return on marketing, and return on price promotions. Each chapter is written by an expert in the field. The presentation of the material seeks to improve the intuitive and technical understanding of the methods covered.


Structural Equation Modeling With AMOS

Structural Equation Modeling With AMOS

Author: Barbara M. Byrne

Publisher: Psychology Press

Published: 2001-04

Total Pages: 348

ISBN-13: 1135667683

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This book illustrates the ease with which AMOS 4.0 can be used to address research questions that lend themselves to structural equation modeling (SEM). This goal is achieved by: 1) presenting a nonmathematical introduction to the basic concepts and appli.


A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling

A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling

Author: Larry Hatcher

Publisher: SAS Institute

Published: 2013-03-01

Total Pages: 444

ISBN-13: 1612903878

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Annotation Structural equation modeling (SEM) has become one of the most important statistical procedures in the social and behavioral sciences. This easy-to-understand guide makes SEM accessible to all userseven those whose training in statistics is limited or who have never used SAS. It gently guides users through the basics of using SAS and shows how to perform some of the most sophisticated data-analysis procedures used by researchers: exploratory factor analysis, path analysis, confirmatory factor analysis, and structural equation modeling. It shows how to perform analyses with user-friendly PROC CALIS, and offers solutions for problems often encountered in real-world research. This second edition contains new material on sample-size estimation for path analysis and structural equation modeling. In a single user-friendly volume, students and researchers will find all the information they need in order to master SAS basics before moving on to factor analysis, path analysis, and other advanced statistical procedures.


Topics in Structural VAR Econometrics

Topics in Structural VAR Econometrics

Author: Gianni Amisano

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 194

ISBN-13: 3642606237

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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.