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

Fabio Canova and Matteo Ciccarelli

No 4033, CEPR Discussion Papers from Centre for Economic Policy Research

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.

Keywords: Panel var; Bayesian methods; Leading indicators; Markov chain monte carlo methods (search for similar items in EconPapers)
JEL-codes: C30 E50 (search for similar items in EconPapers)
Date: 2003-08
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://cepr.org/publications/DP4033 (application/pdf)

Related works:
Working Paper: PANEL INDEX VAR MODELS: SPECIFICATION, ESTIMATION, TESTING AND LEADING INDICATORS (2002)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:4033

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP4033

Access Statistics for this paper

More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK.
Bibliographic data for series maintained by CEPR ().