Estimating Output Gap and Potential Output for Russia and Its Uselfulness by Forecasting Inflation

Kloudová Dana ()
Additional contact information
Kloudová Dana: University of Economics, Prague

No 402134, Proceedings of Economics and Finance Conferences from International Institute of Social and Economic Sciences

Abstract: This paper deals with an estimation of output gap and potential output for Russian´s economy. Three methods of estimation have been used for estimating these two unobservable variables: Hodrick-Prescott filter, production function and SVAR model. All methods of estimation showed very similar course, although an obtained values were not identical. Then obtained values of the output gap were used to analyse the ability of output gap to forecast inflation. Two simple gap models were used for this purpose. The results showed that output gap could be used as useful indicator if inflation, according to all methods of estimation output gap.

Keywords: output gap; HP filter; SVAR model; production function; Kalman filter; inflation (search for similar items in EconPapers)
JEL-codes: C53 E31 E32 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2014-07
New Economics Papers: this item is included in nep-cis, nep-mac and nep-tra
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Proceedings of the Proceedings of the 2nd Economics & Finance Conference, Vienna, Jul 2014, pages 268-285

Downloads: (external link)
https://iises.net/proceedings/2nd-economics-financ ... id=4&iid=11&rid=2134 First version, 2014

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:sek:iefpro:0402134

Access Statistics for this paper

More papers in Proceedings of Economics and Finance Conferences from International Institute of Social and Economic Sciences
Bibliographic data for series maintained by Klara Cermakova ().