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Measuring the Euro area output gap using a multivariate unobserved components model containing phase shifts

Measuring the Euro area output gap using a multivariate unobserved components model containing... Several recent studies have used multivariate unobserved components models to identify the output gap and the non-accelerating inflation rate of unemployment. A key assumption of these models is that one common cycle component, such as the output gap, drives the cyclical fluctuations in all variables included in the model. This article also uses the multivariate approach to estimate the euro area output gap and the trends and cycles in other macroeconomic variables. However, it adopts a flexible way of linking the output gap to the cycle components in the other variables, in that we do not impose any leading or lagging restrictions between cycle components, as has been done in most previous studies. Our approach also allows us to assess the strength of cycle association and cross-correlation among cycle components using the model’s parameter estimates. Finally, we demonstrate that our multivariate model can provide a satisfactory historical output gap estimate and also a ‘real-time’ estimate for the aggregate euro area. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Empirical Economics Springer Journals

Measuring the Euro area output gap using a multivariate unobserved components model containing phase shifts

Chen, Xiaoshan; Mills, Terence
Empirical Economics , Volume 43 (2) – Aug 12, 2011
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References (29)

Publisher
Springer Journals
Copyright
Copyright © 2011 by Springer-Verlag
Subject
Economics; Econometrics; Statistics for Business/Economics/Mathematical Finance/Insurance; Economic Theory/Quantitative Economics/Mathematical Methods
ISSN
0377-7332
eISSN
1435-8921
DOI
10.1007/s00181-011-0495-7
Publisher site
See Article on Publisher Site

Abstract

Several recent studies have used multivariate unobserved components models to identify the output gap and the non-accelerating inflation rate of unemployment. A key assumption of these models is that one common cycle component, such as the output gap, drives the cyclical fluctuations in all variables included in the model. This article also uses the multivariate approach to estimate the euro area output gap and the trends and cycles in other macroeconomic variables. However, it adopts a flexible way of linking the output gap to the cycle components in the other variables, in that we do not impose any leading or lagging restrictions between cycle components, as has been done in most previous studies. Our approach also allows us to assess the strength of cycle association and cross-correlation among cycle components using the model’s parameter estimates. Finally, we demonstrate that our multivariate model can provide a satisfactory historical output gap estimate and also a ‘real-time’ estimate for the aggregate euro area.

Journal

Empirical Economics – Springer Journals

Published: Aug 12, 2011

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