Journal ArticleDOI
Generalized Impulse Response Analysis in Linear Multivariate Models
H.Hashem Pesaran,Yongcheol Shin +1 more
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This paper proposed a generalized impulse response analysis for unrestricted vector autoregressive (VAR) and cointegrated VAR models, which does not require orthogonalization of shocks and is invariant to the ordering of the variables in the VAR.About:
This article is published in Economics Letters.The article was published on 1998-01-01. It has received 4693 citations till now. The article focuses on the topics: Impulse response & Autoregressive model.read more
Citations
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Journal ArticleDOI
Better to give than to receive: Predictive directional measurement of volatility spillovers
TL;DR: This paper used a generalized vector autoregressive framework to characterize daily volatility spillovers across US stock, bond, foreign exchange and commodities markets, from January 1999 to January 2010, and showed that despite significant volatility fluctuations in all four markets during the sample, cross-market volatility spillover were quite limited until the global financial crisis, which began in 2007.
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Effects of Word-of-Mouth Versus Traditional Marketing: Findings from an Internet Social Networking Site
TL;DR: In this paper, the effect of word-of-mouth (WOM) marketing on member growth at an Internet social networking site and compare it with traditional marketing vehicles is studied. But the authors employ a vector autoregressive (VAR) modeling approach.
Journal ArticleDOI
On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms
Francis X. Diebold,Kamil Yilmaz +1 more
TL;DR: In this paper, the authors propose several connectedness measures built from pieces of variance decomposition positions, and argue that they provide natural and insightful measures of connectedness among nancial asset returns and volatilities.
Journal ArticleDOI
Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets
TL;DR: In this article, the authors provide a simple and intuitive measure of interdependence of asset returns and/or volatilities, and formulate and examine precise and separate measures of return spillovers and volatility spillovers.
Journal ArticleDOI
Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets*
Francis X. Diebold,Kamil Yilmaz +1 more
TL;DR: In this paper, the authors provide a simple and intuitive measure of interdependence of asset returns and/or volatilities, and formulate and examine precise and separate measures of return spillovers and volatility spillovers.
References
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Journal ArticleDOI
Co-integration and Error Correction: Representation, Estimation and Testing
TL;DR: The relationship between co-integration and error correction models, first suggested in Granger (1981), is here extended and used to develop estimation procedures, tests, and empirical examples.
Journal ArticleDOI
Macroeconomics and reality
TL;DR: In this article, the authors argue that the style in which their builders construct claims for a connection between these models and reality is inappropriate, to the point at which claims for identification in these models cannot be taken seriously.
Book
Likelihood-Based Inference in Cointegrated Vector Autoregressive Models
TL;DR: In this paper, a detailed mathematical and statistical analysis of the cointegrated vector autoregresive model is given, with the main emphasis on the derivation of estimators and test statistics through a consistent use of the Guassian likelihood function.
Journal ArticleDOI
Impulse response analysis in nonlinear multivariate models
TL;DR: In this paper, the authors present a unified approach to impulse response analysis which can be used for both linear and nonlinear multivariate models and demonstrate the use of these measures for a nonlinear bivariate model of US output and the unemployment rate.
Book
Introduction to multiple time series analysis
TL;DR: The choice of point and interval forecasts as well as innovation accounting are presented as tools for structural analysis within the multiple time series context.
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