Template-type: ReDIF-Paper 1.0  
Author-Name: Celia Gil-Bermejo Lazo
Author-Workplace-Name: Instituto Complutense de Estudios Internacionales (ICEI), Universidad Complutense de Madrid.
Author-Name: Jorge Onrubia Fernández
Author-Workplace-Name: Instituto Complutense de Estudios Internacionales (ICEI), Universidad Complutense de Madrid.
Author-Name: Antonio Jesús Sánchez Fuentes
Author-Workplace-Name: Instituto Complutense de Estudios Internacionales (ICEI), Universidad Complutense de Madrid.
Title: Graphical modelling of multivariate panel data models
Abstract: In this paper, we propose a new approach to both test Granger Causality in a multivariate panel data environment and determine one ultimate “causality path” 
	excluding those relationships which are redundant. For the sake of concreteness, we combine recent developments introduced to estimate Granger causality procedure 
	based on Meta-analysis in heterogeneous mixed panels (Emirmahmutoglu and Kose, 2011 and Dumitrescu and Hurlin, 2012) and graphical models proposed in a growing 
	literature (Spirtes et al, 2000, Demiralp and Hoover, 2003, Eicher, 2007 and 2012) searching iteratively for the existing dependencies between a multivariate set of 
	information. Finally, we illustrate our proposal by revisiting existing studies in the context of panel Vector Autoregressive (VAR) models to the analysis of the 
	fiscal policy-growth nexus.
Keywords: Granger causality; Panel data; Causal maps
Creation-Date: 2022
Length: 18 pages
Number: 2202
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/wpaper22-02.txt
File-URL: https://eprints.ucm.es/id/eprint/74263/1/WP02-22.pdf
File-Format: Application/pdf
File-Function: Full text
Handle: RePEc:ucm:wpaper:2202