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Persistence, Excess Volatility, and Volatility Clusters in Inflation

Resource Type
Dataset : survey data
  • Owyang, Michael T. (Federal Reserve Bank of St. Louis)
Other Title
  • Version 1 (Subtitle)
Publication Date
Free Keywords
inflation; monetary policy; research models
  • Abstract

    This paper presents a single, integrated model to explain the persistence and volatility characteristics of the United States inflation time series. Policymaker learning about a Markov-switching natural rate of unemployment in a neoclassical Phillips curve model with time-varying preferences produces inflation persistence, volatility clustering, and mean/variance correlation. The interaction between the policymaker's preferences and the Phillips curve generates the first and last results. Policymaker learning produces clusters of volatility as the monetary authority resets the learning algorithm whenever a shock to the Phillips curve occurs. Simulations using parameters estimated via Gibbs sampling confirms the theory.
  • Table of Contents


    • DS1: Dataset
Geographic Coverage
  • United States
Collection Mode
  • (1) The files submitted are a data file, 0111mod.txt, and a program file, 0111mop.prg. (2) These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator if further information is desired.

This study is freely available to the general public via web download.
Alternative Identifiers
  • 1251 (Type: ICPSR Study Number)

Update Metadata: 2015-08-05 | Issue Number: 6 | Registration Date: 2015-06-15

Owyang, Michael T. (2002): Persistence, Excess Volatility, and Volatility Clusters in Inflation. Version 1. Version: v1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset.