Estimating the New Keynesian Output Gap for Armenia via a Bayesian Approach
Knarik Ayvazyan ()
Additional contact information
Knarik Ayvazyan: Monetary Policy Department, Central Bank of Armenia
Authors registered in the RePEc Author Service: Erik Vardanyan
No 4, Working Papers from Central Bank of Armenia
Abstract:
As the New Keynesian output gap cannot be observed in practice, there is quite some debate on what this variable actually looks like. Rather than taking the standard approach of using a time trend or the HP-filter to estimate it, this paper separates trend from cycle via Bayesian estimation of a New Keynesian model, augmented with an unobserved components model for output. This provides us with a model-consistent estimate of the output gap. This estimate is compared with popular proxies used in the literature. It turns out that the benefits of using the model-based approach mainly lie in real time. Model coefficients are easily interpretable, and the output gap series is consistent with a broader analysis of Armenian economic developments.
Keywords: Output Gap; Inflation; Unemployment; Unobservable Component Model; Bayesian Methods (search for similar items in EconPapers)
JEL-codes: C32 E31 E32 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2015-09
New Economics Papers: this item is included in nep-int
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Published in CBA Working Paper Series, September 2015
Downloads: (external link)
https://www.cba.am/EN/panalyticalmaterialsresearches/Analytical_05.10.2015.pdf First version, 2015 (application/pdf)
Related works:
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:ara:wpaper:004
Access Statistics for this paper
More papers in Working Papers from Central Bank of Armenia Contact information at EDIRC.
Bibliographic data for series maintained by Davit Hovhannisyan ( this e-mail address is bad, please contact ).