Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system

Timothy Cogley, Sergei Morozov, Thomas J. Sargent

    Research output: Contribution to journalArticle

    Abstract

    We estimate a Bayesian vector autoregression for the U.K. with drifting coefficients and stochastic volatilities. We use it to characterize posterior densities for several objects that are useful for designing and evaluating monetary policy, including local approximations to the mean, persistence, and volatility of inflation. We present diverse sources of uncertainty that impinge on the posterior predictive density for inflation, including model uncertainty, policy drift, structural shifts and other shocks. We use a recently developed minimum entropy method to bring outside information to bear on inflation forecasts. We compare our predictive densities with the Bank of England's fan charts.

    Original languageEnglish (US)
    Pages (from-to)1893-1925
    Number of pages33
    JournalJournal of Economic Dynamics and Control
    Volume29
    Issue number11
    DOIs
    StatePublished - Nov 2005

    Keywords

    • Bayesian analysis
    • Forecasting
    • Inflation

    ASJC Scopus subject areas

    • Economics and Econometrics
    • Control and Optimization
    • Applied Mathematics

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