2026-06-27T23:05:07Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/43212025-05-22T15:16:44Zcom_20.500.14352_14col_20.500.14352_17
Docta Complutense
author
Gil-Bermejo Lazo, Celia
author
Onrubia Fernández, Jorge
author
Sánchez Fuentes, Antonio Jesús
2023-06-16T14:11:54Z
2023-06-16T14:11:54Z
2022
https://hdl.handle.net/20.500.14352/4321
https://www.ucm.es/icei/file/wp0222
https://www.ucm.es/icei/working-papers
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.
eng
Atribución-NoComercial 3.0 España
Graphical modelling of multivariate panel data models
technical report
URL
https://docta.ucm.es/bitstreams/9334061d-15d5-4d9a-a62c-63d9a3242963/download
File
MD5
c513cc51621271579bf24a4b4e6a7ec2
1542188
application/pdf
WP02-22.pdf
URL
https://docta.ucm.es/bitstreams/a93a7dfd-3b89-47b4-b8a8-388f7ef729a3/download
File
MD5
550be63c3fccfe653845d629b0e07c68
33826
text/plain
WP02-22.pdf.txt