A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve
AbstractIn 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 InfoPaper 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.
Length: 35 pages
Date of creation: Jan 2014
Date of revision:
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More information through EDIRC
trend inflation; non-linear state space model; natural rate of unemployment; inflation targeting; Bayesian;
Other versions of this item:
- Joshua C C Chan & Gary Koop & Simon M Potter, 2012. "A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve," ANU Working Papers in Economics and Econometrics 2012-590, Australian National University, College of Business and Economics, School of Economics.
- NEP-ALL-2014-02-15 (All new papers)
- NEP-FOR-2014-02-15 (Forecasting)
- NEP-MAC-2014-02-15 (Macroeconomics)
- NEP-SOG-2014-02-15 (Sociology of Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Koop, Gary & Korobilis, Dimitris, 2009.
"Bayesian Multivariate Time Series Methods for Empirical Macroeconomics,"
20125, University Library of Munich, Germany.
- Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
- Gary Koop & Dimitris Korobilis, 2009. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Working Paper Series 47_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
- 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.
- Chan, Joshua & Strachan, Rodney, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," MPRA Paper 39360, University Library of Munich, Germany.
- 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.
- 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.).
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