Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models
Oxford Bulletin of Economics and Statistics
Published online on January 26, 2016
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.