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Cem Cakmakli, Amsterdam U. Print
Thursday, 08 November 2012, 12:15 - 13:15

Cem Cakmakli, Amsterdam University

Posterior-Predictive Evidence on US Inflation Patterns using Alternative Phillips Curve Structures and Non-filtered Time Series.

Abstract: High and low frequency patterns in US inflation and marginal costs are modeled within New Keynesian Phillips Curves (NKPC) with forward and backward looking expectations. Special attention is paid to a comparison of the weak identification issue in models with filtered and observed time series. Persistence measures and the model’s forecasting performance are evaluated using a Bayesian simulation based approach. Posterior and predictive results show a reduction of the weak identification issue using original series and a systematic bias in inflation forecasts using the filtered series.  Better forecasting performance is obtained using an enlarged NKPC model with alternative expectation mechanisms.  Given the complete predictive distributions, tail probabilities of deflation are reported.

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