Panel Index VAR Models: Specification, Estimation, Testing and Leading Indicators

Abstract:     
This Paper proposes a method to conduct inference in panel VAR models with cross-unit interdependencies and time variations in the coefficients. The set-up used is Bayesian, and Markov Chain Monte Carlo (MCMC) methods are used to estimate the posterior distribution of the features of interest. The model is re-parameterized to resemble an observable index model and specification searches are discussed. The approach can be used to construct multi-unit forecasts, leading indicators and to conduct policy analysis in multi-unit set-ups. The methodology is employed to construct leading indicators for inflation and GDP growth in the euro area.

Number of Pages in PDF File: 28

Keywords: Panel VAR, Bayesian methods, leading indicators, Markov Chain Monte Carlo methods

JEL Classification: C30, E50

working papers series