Measurement of Filters’ Efficiencies and Application Of NNSFDI Method

Melike Bildirici and Selçuk Alp

Economic Research-Ekonomska Istraživanja, 2012, vol. 25, issue 4, 937-958

Abstract: The study aims to propose the neural network filter based on NNSFDI method as an alternative filter in economics; namely, Baxter-King, Hodrick-Presscott, Christiano and Fitzgerald and Kalman filters. In this paper, it was used two different data which consist of the annual unemployment rates for 1923 – 2008 periods and the monthly inflation rates for 1964:02 – 2009:07 periods.The performance of the new method proposed and the main stream filters were, in particular, evaluated based on the annual and monthly data. The empirical findings suggest that the newly proposed NNFSDI model provedid better forecast results compared to Kalman, HP, BK and CF filters for different data sets when evaluated in the light of different error criteria such as MSE, RMSE and MAPE

Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/1331677X.2012.11517540 (text/html)
Access to full text is restricted to subscribers.

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:taf:reroxx:v:25:y:2012:i:4:p:937-958

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rero20

DOI: 10.1080/1331677X.2012.11517540

Access Statistics for this article

Economic Research-Ekonomska Istraživanja is currently edited by Marinko Skare

More articles in Economic Research-Ekonomska Istraživanja from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().