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Real time estimation of potential output and output gap for theeuro-area: comparing production function with unobserved componentsand SVAR approaches

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Author Info
Lemoine , Matthieu
Mazzi , Gian Luigi
Monperrus-Veroni , Paola
Reynes, Frédéric

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Abstract

We develop a new version of the production function (PF) approach usually used for estimating the output gap of the euro area. Our version does not call for any (often imprecise) measure of the capital stock and improves the estimation of the trend total factor productivity. We asses this approach by comparing it with two other multivariate methods mostly used for output gap estimates, a multivariate unobserved components (MUC) model and a Structural Vector Auto-Regressive (SVAR) model. The comparison is conducted by relying on assessment criteria such as the concordance of the turning points chronology with a reference one, the inflation forecasting power and the real-time consistency of the estimates. Two contributions are achieved. Firstly, we take into account data revisions and their impact on the output gap estimates by using vintage datasets coming from the Euro Area Business Cycle (EABCN) Real-Time Data-Base (RTDB). Secondly, the PF approach, generally employed by policy-makers despite of its difficult implementation, is assessed. We thus improve on previous papers which limited their assessment on other multivariate methods, e.g. MUC or SVAR models. The different methods show different ranks in relation to the three criteria. This new PF estimate appears highly concordant with the reference chronology. Its forecasting power appears favourable only for the shortest horizon (1 month). Finally, the SVAR model appears more consistent in real-time.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 13128.

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Date of creation: Nov 2008
Date of revision: Nov 2008
Handle: RePEc:pra:mprapa:13128

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Related research
Keywords: potential output; production function; state-space models; structural VARs;

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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