Measuring the NAIRU with Reduced Uncertainty: A Multiple Indicator-Common Component Approach

Arabinda Basistha () and Richard Startz

No 46, Computing in Economics and Finance 2005 from Society for Computational Economics

Abstract: Standard estimates of the NAIRU or natural rate of unemployment are subject to considerable uncertainty. We show in this paper that using multiple indicators to extract an estimated NAIRU cuts in half uncertainty as measured by variance. The inclusion of an Okun’s Law relation is particularly valuable. We estimate the NAIRU as an unobserved component in a state-space model and show that using multiple indicators reduces both parametric uncertainty and filtering uncertainty. Additionally, our multivariate approach overcomes the “pile-up†problem observed by other investigators

Keywords: NAIRU; parametric uncertainty; filtering uncertainty (search for similar items in EconPapers)
JEL-codes: C32 E31 E32 (search for similar items in EconPapers)
Date: 2005-11-11
New Economics Papers: this item is included in nep-mac
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Citations: View citations in EconPapers (1)

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Working Paper: Measuring the NAIRU with Reduced Uncertainty: A Multiple Indicator-Common Component Approach (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf5:46

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