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A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve

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Author Info

  • Joshua C.C. Chan
  • Gary Koop
  • Simon M. Potter

Abstract

In this paper, we develop a bivariate unobserved components model for inflation and unemployment. The unobserved components are trend inflation and the non-accelerating inflation rate of unemployment (NAIRU). Our model also incorporates a time-varying Phillips curve and time-varying inflation persistence. What sets this paper apart from the existing literature is that we do not use unbounded random walks for the unobserved components, but rather use bounded random walks. For instance, trend inflation is assumed to evolve within bounds. Our empirical work shows the importance of bounding. We find that our bounded bivariate model forecasts better than many alternatives, including a version of our model with unbounded unobserved components. Our model also yields sensible estimates of trend inflation, NAIRU, inflation persistence and the slope of the Phillips curve.

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Bibliographic Info

Paper provided by Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University in its series CAMA Working Papers with number 2014-10.

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Length: 35 pages
Date of creation: Jan 2014
Date of revision:
Handle: RePEc:een:camaaa:2014-10

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Related research

Keywords: trend inflation; non-linear state space model; natural rate of unemployment; inflation targeting; Bayesian;

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  1. Charles L. Weise, 2012. "Political Pressures on Monetary Policy during the US Great Inflation," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(2), pages 33-64, April.
  2. Andrea Stella & James H. Stock, 2012. "A state-dependent model for inflation forecasting," International Finance Discussion Papers 1062, Board of Governors of the Federal Reserve System (U.S.).
  3. Koop, Gary & Korobilis, Dimitris, 2009. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," MPRA Paper 20125, University Library of Munich, Germany.
  4. Joshua Chan & Rodney Strachan, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," CAMA Working Papers 2012-13, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
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