Per citar aquest document: http://ddd.uab.cat/record/114779
Priors about observables in vector autoregressions
Jarocinski, Marek
Marcet, Albert
Universitat Autònoma de Barcelona. Unitat de Fonaments de l'Anàlisi Econòmica
Universitat Autònoma de Barcelona. Institut d'Anàlisi Econòmica

Data: 2013
Descripció: 36 p.
Col·lecció: Working papers ; 929.13
Resum: Standard practice in Bayesian VARs is to formulate priors on the autoregressive parameters, but economists and policy makers actually have priors about the behavior of observable variables. We show how this kind of prior can be used in a VAR under strict probability theory principles. We state the inverse problem to be solved and we propose a numerical algorithm that works well in practical situations with a very large number of parameters. We prove various convergence theorems for the algorithm. As an application, we first show that the results in Christiano et al. (1999) are very sensitive to the introduction of various priors that are widely used. These priors turn out to be associated with undesirable priors on observables. But an empirical prior on observables helps clarify the relevance of these estimates: we find much higher persistence of output responses to monetary policy shocks than the one reported in Christiano et al. (1999) and a significantly larger total effect.
Drets: Tots els drets reservats
Llengua: Anglès.
Document: workingPaper
Matèria: Decisió estadística bayesiana, Teoria de la ; Política monetària ; Models economètrics

Adreça alternativa: http://hdl.handle.net/2072/211452


36 p, 436.3 KB

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