Arbeitspapier

Inference in Bayesian proxy-SVARs

Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop algorithms for exact finite sample inference in this class of time series models, commonly known as proxy-SVARs. Our algorithms make independent draws from the normal-generalized-normal family of conjugate posterior distributions over the structural parameterization of a proxy-SVAR. Importantly, our techniques can handle the case of set identification and hence they can be used to relax the additional exclusion restrictions unrelated to the external instruments often imposed to facilitate inference when more than one instrument are used to identify more than one equation, as in Mertens and Montiel-Olea (2018).

Sprache
Englisch

Erschienen in
Series: Working Paper ; No. 2018-16

Klassifikation
Wirtschaft
Statistical Simulation Methods: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Thema
SVARs
external instruments
importance sampler

Ereignis
Geistige Schöpfung
(wer)
Arias, Jonas E.
Rubio-Ramírez, Juan Francisco
Waggoner, Daniel F.
Ereignis
Veröffentlichung
(wer)
Federal Reserve Bank of Atlanta
(wo)
Atlanta, GA
(wann)
2018

DOI
doi:10.29338/wp2018-16
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Arias, Jonas E.
  • Rubio-Ramírez, Juan Francisco
  • Waggoner, Daniel F.
  • Federal Reserve Bank of Atlanta

Entstanden

  • 2018

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