Template-Type: ReDIF-Paper 1.0
Series: Tinbergen Institute Discussion Papers
Creation-Date: 2013-01-10
Number: 13-011/III
Author-Name: Nalan Basturk
Author-Workplace-Name: Erasmus University Rotterdam
Author-Name: Cem Cakmakli
Author-Workplace-Name: University of Amsterdam
Author-Name: Pinar Ceyhan
Author-Workplace-Name: Erasmus University Rotterdam
Author-Name: Herman K. van Dijk
Author-Workplace-Name: Erasmus University Rotterdam, and VU University Amsterdam
Title: Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series
Abstract: Changing time series properties of US inflation and economic activity are analyzed within a class of extended Phillips Curve (PC) models. First, the misspecification effects of mechanical removal of low frequency movements of these series on posterior inference of a basic PC model are analyzed using a Bayesian simulation based approach. Next, structural time series models that describe changing patterns in low and high frequencies and backward as well as forward inflation expectation mechanisms are incorporated in the class of extended PC models. Empirical results indicate that the proposed models compare favorably with existing Bayesian Vector Autoregressive and Stochastic Volatility models in terms of fit and predictive performance. Weak identification and dynamic persistence appear less important when time varying dynamics of high and low frequencies are carefully modeled. Modeling inflation expectations using survey data and adding level shifts and stochastic volatility improves substantially in sample fit and out of sample predictions. No evidence is found of a long run stable cointegration relation between US inflation and marginal costs. Tails of the complete predictive distributions indicate an increase in the probability of disinflation in recent years.
Classification-JEL: C11, C32, E31, E37
Keywords: New Keynesian Phillips curve, unobserved components, level shifts, inflation expectations
File-Url: https://papers.tinbergen.nl/13011.pdf
File-Format: application/pdf
File-Size: 1250785 bytes
Handle: RePEc:tin:wpaper:20130011