Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/89407
Authors: 
Moneta, Alessio
Year of Publication: 
2005
Series/Report no.: 
LEM Working Paper Series 2003/07
Abstract: 
The identification of a VAR requires differentiating between correlation and causation. This paper presents a method to deal with this problem. Graphical models, which provide a rigorous language to analyze the statistical and logical properties of causal relations, associate a particular set of vanishing partial correlations to every possible causal structure. The structural form is described by a directed graph and from the analysis of the partial correlations of the residuals the set of acceptable causal structures is derived. This procedure is applied to an updated version of the King et al. (American Economic Review, 81, (1991), 819) data set and it yields an orthogonalization of the residuals consistent with the causal structure among contemporaneous variables and alternative to the standard one, based on a Choleski factorization of the covariance matrix of the residuals.
Subjects: 
Structural VARs
Identification
Directed Acyclic Graphs
Causality
Impulse Response Functions
JEL: 
C32
C49
E32
Document Type: 
Working Paper

Files in This Item:
File
Size
372.79 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.