Long memory with stochastic variance model: A resursive analysis for U.S. inflation

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The time series characteristics of postwar US inflation have been found to vary over time. The changes are investigated in a model-based analysis where the time series of inflation is specified by a long memory autoregressive fractionally integrated moving average process with its variance modelled by a stochastic volatility process. Estimates of the parameters are obtained by a Monte Carlo maximum likelihood method. A long sample of monthly core inflation is considered in the analysis as well as subsamples of varying length. The empirical results reveal major changes in the variance, in the order of integration, in the short memory characteristics, and in the volatility of volatility. The findings provide further evidence that the time series properties of inflation are not stable over time. © 2013 Elsevier B.V. All rights reserved.
LanguageEnglish
Pages144-157
JournalComputational Statistics and Data Analysis
Volume76
Issue numberAugust
DOIs
Publication statusPublished - 2014

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Long Memory
Inflation
Time series
Data storage equipment
Volatility
Random processes
Integrated Process
Moving Average Process
Maximum likelihood
Stochastic Volatility
Maximum Likelihood Method
Model
Vary
Model-based
Estimate

Cite this

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title = "Long memory with stochastic variance model: A resursive analysis for U.S. inflation",
abstract = "The time series characteristics of postwar US inflation have been found to vary over time. The changes are investigated in a model-based analysis where the time series of inflation is specified by a long memory autoregressive fractionally integrated moving average process with its variance modelled by a stochastic volatility process. Estimates of the parameters are obtained by a Monte Carlo maximum likelihood method. A long sample of monthly core inflation is considered in the analysis as well as subsamples of varying length. The empirical results reveal major changes in the variance, in the order of integration, in the short memory characteristics, and in the volatility of volatility. The findings provide further evidence that the time series properties of inflation are not stable over time. {\circledC} 2013 Elsevier B.V. All rights reserved.",
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Long memory with stochastic variance model: A resursive analysis for U.S. inflation. / Bos, C.S.; Koopman, S.J.; Ooms, M.

In: Computational Statistics and Data Analysis, Vol. 76, No. August, 2014, p. 144-157.

Research output: Contribution to JournalArticleAcademicpeer-review

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AU - Koopman, S.J.

AU - Ooms, M.

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AB - The time series characteristics of postwar US inflation have been found to vary over time. The changes are investigated in a model-based analysis where the time series of inflation is specified by a long memory autoregressive fractionally integrated moving average process with its variance modelled by a stochastic volatility process. Estimates of the parameters are obtained by a Monte Carlo maximum likelihood method. A long sample of monthly core inflation is considered in the analysis as well as subsamples of varying length. The empirical results reveal major changes in the variance, in the order of integration, in the short memory characteristics, and in the volatility of volatility. The findings provide further evidence that the time series properties of inflation are not stable over time. © 2013 Elsevier B.V. All rights reserved.

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