Measuring Inflation Persistence: A Structural Time Series Approach

Abstract

Time series estimates of inflation persistence incur an upward bias if shifts in the inflation target of the central bank remain unaccounted for. Using a structural time series approach we measure different sorts of inflation persistence allowing for an unobserved timevarying inflation target. Unobserved components are identified using Kalman filtering and smoothing techniques. Posterior densities of the model parameters and the unobserved components are obtained in a Bayesian framework based on importance sampling. We find that inflation persistence, expressed by the halflife of a shock, can range from 1 quarter in case of a costpush shock to several years for a shock to longrun inflation expectations or the output gap.

Keywords: Inflation persistence, inflation target, Kalman filter, Bayesian analysis

JEL Classification: C11, C13, C22, C32, E31