We use Bayesian Markov Chain Monte Carlo methods to estimate two mod els of post WWII U.S. inflation rates with drifting stochastic volatility and drifting coefficients. One model is univariate, the other a multivariate autoregression. We define the inflation gap as the deviation of inflation from a pure random walk component of inflation and use both of our models to study changes over time in the persistence of the inflation gap measured in terms of short to medium term predicability.
We present evidence that our measure of the persistence of the inflation gap increased until Volcker brought mean inflation down in the early 1980s and that it then fell during the chairmanships of Volcker and Greenspan. Stronger evidence for movements in inflation gap persistence emerges from the VAR than from the univariate model.
This paper studies how inflation persistence has changed since the Great Inflation. We distinguish the persistence of inflation from the persistence of a component of it called the inflation gap. Our first message is that although inflation remains highly persistent, the inflation gap became less persistent after the Volcker disinflation. Our second message is that multivariate information helps to detect changes in inflation gap persistence. Although the univariate evidence is mixed, a clearer picture emerges from a VAR.
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Inflation starts in Latin America and the Caribbean
