RT Report
T1 Graphical modelling of multivariate panel data models
A1 Gil-Bermejo Lazo, Celia
A1 Onrubia Fernández, Jorge
A1 Sánchez Fuentes, Antonio Jesús
AB 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.
PB Instituto Complutense de Estudios Internacionales (ICEI)
YR 2022
FD 2022
LK https://hdl.handle.net/20.500.14352/4321
UL https://hdl.handle.net/20.500.14352/4321
LA eng
NO We thank Mar Delgado-Téllez as well as participants to 13th International Conference of the ERCIM WG on Computational and Methodological Statistics, the XXVIII & XXIX Encuentro de EconomíaPública and the 9th UECE Conference on Economic for their valuable comments.
NO Ministerio de Economía, Comercio y Empresa (España)
DS Docta Complutense
RD 25 abr 2025