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Long memory with stochastic variance model: A recursive analysis for US inflation

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  • Bos, Charles S.
  • Koopman, Siem Jan
  • Ooms, Marius

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.

Suggested Citation

  • Bos, Charles S. & Koopman, Siem Jan & Ooms, Marius, 2014. "Long memory with stochastic variance model: A recursive analysis for US inflation," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 144-157.
  • Handle: RePEc:eee:csdana:v:76:y:2014:i:c:p:144-157
    DOI: 10.1016/j.csda.2012.11.019
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    7. Todea, Alexandru, 2016. "Cross-correlations between volatility, volatility persistence and stock market integration: the case of emergent stock markets," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 208-215.
    8. Phillip, Andrew & Chan, Jennifer & Peiris, Shelton, 2020. "On generalized bivariate student-t Gegenbauer long memory stochastic volatility models with leverage: Bayesian forecasting of cryptocurrencies with a focus on Bitcoin," Econometrics and Statistics, Elsevier, vol. 16(C), pages 69-90.
    9. Rinke, Saskia & Busch, Marie & Leschinski, Christian, 2017. "Long Memory, Breaks, and Trends: On the Sources of Persistence in Inflation Rates," Hannover Economic Papers (HEP) dp-584, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    10. Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
    11. Canarella, Giorgio & Miller, Stephen M., 2017. "Inflation targeting and inflation persistence: New evidence from fractional integration and cointegration," Journal of Economics and Business, Elsevier, vol. 92(C), pages 45-62.
    12. Nima Nonejad, 2019. "Has the 2008 financial crisis and its aftermath changed the impact of inflation on inflation uncertainty in member states of the european monetary union?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(2), pages 246-276, May.
    13. Richard Hunt & Shelton Peiris & Neville Weber, 2022. "Estimation methods for stationary Gegenbauer processes," Statistical Papers, Springer, vol. 63(6), pages 1707-1741, December.

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