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

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  • Arabinda Basistha
  • Richard Startz

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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Bibliographic Info

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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Cited by:
  1. Lawrence J. Christiano & Mathias Trabandt & Karl Walentin, 2010. "DSGE models for monetary policy analysis," CQER Working Paper 2010-02, Federal Reserve Bank of Atlanta.
  2. Mathias Trabandt & Karl Walentin & Lawrence J. Christiano, 2010. "Involuntary Unemployment and the Business Cycle," 2010 Meeting Papers 129, Society for Economic Dynamics.
  3. 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.
  4. Charles A. Fleischman & John M. Roberts, 2011. "From many series, one cycle: improved estimates of the business cycle from a multivariate unobserved components model," Finance and Economics Discussion Series 2011-46, Board of Governors of the Federal Reserve System (U.S.).
  5. Berger, Tino & Kempa, Bernd, 2011. "Bayesian estimation of the output gap for a small open economy: The case of Canada," Economics Letters, Elsevier, vol. 112(1), pages 107-112, July.

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