Department of Economics and Business Economics

A New Time-Varying Parameter Autoregressive Model for US Inflation Expectations

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DOI

  • Markku Lanne
  • Jani Luoto, Univ Helsinki, University of Helsinki, Dept Polit & Econ Studies, Econ

We study the evolution of U.S. inflation by means of a new noncausal autoregressive model with time-varying parameters that outperforms the corresponding causal and constant-parameter noncausal models in terms of fit and forecast accuracy. Our model also beats the unobserved component stochastic volatility (UCSV) model, one of the best-performing univariate inflation forecasting models, in terms of both point and density forecasts. We also show how the new Keynesian Phillips curve can be estimated based on our noncausal model. Both expected and lagged inflation turn out important, but the former dominates in determining the current inflation.

Original languageEnglish
JournalJournal of Money, Credit and Banking
Volume49
Issue5
Pages (from-to)969-995
Number of pages27
ISSN0022-2879
DOIs
Publication statusPublished - Aug 2017

    Research areas

  • noncausal autoregression, new Keynesian Phillips curve, time-varying parameters, stochastic volatility, inflation forecasting, PREDICTIVE ABILITY, INTEREST-RATES, FINANCIAL DATA, FORECAST, VARIABLES, GREENBOOK, ACCURACY, PRICES, TESTS

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