Business Faculty Publications
Title
Variance Decomposition Analysis for Nonlinear Economic Models
Document Type
Article
Publication Date
9-2020
Publication Title
Oxford Bulletin of Economics and Statistics
Keywords
Forecast error variance decomposition, nonlinear DSGE models, ZLB, law of total variance, Delta method, projection methods
Disciplines
Economics
Abstract
In this paper, we propose a new method called the total variance method and algorithms to compute and analyse variance decomposition for nonlinear economic models. We provide theoretical and empirical examples to compare our method with the only existing method called generalized forecast error variance decomposition (GFEVD). We find that the results from the two methods are different when shocks are multiplicative or interacted in nonlinear models. We recommend that when working with nonlinear models researchers should use the total variance method in order to see the importance of indirect variance contributions and to quantify correctly the relative variance contribution of each structural shock.
Recommended Citation
Isakin, Maksim and Ngo, Phuong V., "Variance Decomposition Analysis for Nonlinear Economic Models" (2020). Business Faculty Publications. 352.
https://engagedscholarship.csuohio.edu/bus_facpub/352
DOI
https://doi.org/10.1111/obes.12369
Version
Publisher's PDF
Volume
82
Issue
6
