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

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Arabinda Basistha
Richard Startz

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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

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 46.

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Date of creation: 11 Nov 2005
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Handle: RePEc:sce:scecf5:46

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Keywords: NAIRU; parametric uncertainty; filtering uncertainty;

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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
E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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  1. Mark W. Watson, 2007. "How accurate are real-time estimates of output trends and gaps?," Economic Quarterly, Federal Reserve Bank of Richmond, issue Spr, pages 143-161. [Downloadable!]
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