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

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  • 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.

Suggested Citation

  • Joshua C.C. Chan & Gary Koop & Simon M. Potter, 2014. "A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve," CAMA Working Papers 2014-10, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2014-10
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    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2014-01/10_2014_chan_koop_potter.pdf
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    References listed on IDEAS

    as
    1. Michael Dotsey & Shigeru Fujita & Tom Stark, 2018. "Do Phillips Curves Conditionally Help to Forecast Inflation?," International Journal of Central Banking, International Journal of Central Banking, vol. 14(4), pages 43-92, September.
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    Keywords

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