Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models

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Lanne , M & Nyberg , H 2016 , ' Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models ' , Oxford Bulletin of Economics and Statistics , vol. 78 , no. 4 , pp. 595-603 . https://doi.org/10.1111/obes.12125

Title: Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models
Author: Lanne, Markku; Nyberg, Henri
Contributor organization: Department of Political and Economic Studies (2010-2017)
Economics
Financial and Macroeconometrics
Date: 2016-08
Language: eng
Number of pages: 9
Belongs to series: Oxford Bulletin of Economics and Statistics
ISSN: 0305-9049
DOI: https://doi.org/10.1111/obes.12125
URI: http://hdl.handle.net/10138/231658
Abstract: We propose a new generalized forecast error variance decomposition with the attractive property that the proportions of the impact accounted for by innovations in each variable sum to unity. Our decomposition is based on the generalized impulse response function, and it can easily be obtained by simulation. The new decomposition is illustrated in an empirical application to US output growth and interest rate spread data.
Subject: IMPULSE-RESPONSE ANALYSIS
SWITCHING STRUCTURAL VAR
PREDICT OUTPUT
G-7 COUNTRIES
YIELD CURVE
INFLATION
SPREAD
GROWTH
CREDIT
511 Economics
Peer reviewed: Yes
Usage restriction: openAccess
Self-archived version: acceptedVersion


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