Inference and Forecasting for ARFIMA Models With an Application to US and UK Inflation
AbstractPractical aspects of likelihood-based inference and forecasting of series with long memory are considered, based on the arfima(p; d; q) model with deterministic regressors. Sampling characteristics of approximate and exact first-order asymptotic methods are compared. The analysis is extended using modified profile likelihood analysis, which is a higher-order asymptotic method suggested by Cox and Reid (1987). The relevance of the differences between the methods is investigated for models and forecasts of monthly core consumer price inflation in the US and quarterly overall consumer price inflation in the UK.
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Bibliographic InfoArticle provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.
Volume (Year): 8 (2004)
Issue (Month): 2 (May)
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- Wolfgang Härdle & Julius Mungo, 2008. "Value-at-Risk and Expected Shortfall when there is long range dependence," SFB 649 Discussion Papers SFB649DP2008-006, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Cheung, Yin-Wong & Chung, Sang-Kuck, 2009.
"A Long Memory Model with Mixed Normal GARCH for US Inflation Data,"
Santa Cruz Department of Economics, Working Paper Series
qt2202s99q, Department of Economics, UC Santa Cruz.
- Cheung, Yin-Wong & Chung, Sang-Kuck, 2009. "A Long Memory Model with Mixed Normal GARCH for US Inflation Data," Santa Cruz Department of Economics, Working Paper Series qt94r403d2, Department of Economics, UC Santa Cruz.
- Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Society for Computational Economics, vol. 38(4), pages 517-539, November.
- Evans, Mark, 2011. "Steel consumption and economic activity in the UK: The integration and cointegration debate," Resources Policy, Elsevier, vol. 36(2), pages 97-106, June.
- Ying Chen & Wolfgang Härdle & Uta Pigorsch, 2009.
"Localized Realized Volatility Modelling,"
SFB 649 Discussion Papers
SFB649DP2009-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Charfeddine, Lanouar & Guégan, Dominique, 2012.
"Breaks or long memory behavior: An empirical investigation,"
Physica A: Statistical Mechanics and its Applications,
Elsevier, vol. 391(22), pages 5712-5726.
- Lanouar Charfeddine & Dominique Guegan, 2009. "Breaks or long memory behaviour : An empirical investigation," Documents de travail du Centre d'Economie de la Sorbonne 09022, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
- Cleomar Gomes da Silva & Maria Carolina da Silva Leme, 2008. "Inflation and Interest Rate: Which one is more persistent in Brazil?," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807181224190, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
- Roxana Chiriac & Valeri Voev, 2008.
"Modelling and Forecasting Multivariate Realized Volatility,"
CoFE Discussion Paper
08-06, Center of Finance and Econometrics, University of Konstanz.
- Roxana Chiriac & Valeri Voev, 2011. "Modelling and forecasting multivariate realized volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 922-947, 09.
- Roxana Chiriac & Valeri Voev, 2008. "Modelling and Forecasting Multivariate Realized Volatility," CREATES Research Papers 2008-39, School of Economics and Management, University of Aarhus.
- Wolfgang Härdle & Julius Mungo, 2007. "Long Memory Persistence in the Factor of Implied Volatility Dynamics," SFB 649 Discussion Papers SFB649DP2007-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- C.S. Bos & S.J. Koopman & M. Ooms, 2007. "Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks," Tinbergen Institute Discussion Papers 07-099/4, Tinbergen Institute.
- Matteo Pelagatti & Pranab Sen, 2009. "A robust version of the KPSS test based on ranks," Working Papers 20090701, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
- Morten Ørregaard Nielsen & Per Frederiksen, 2008. "Fully Modified Narrow-Band Least Squares Estimation of Stationary Fractional Cointegration," Working Papers 1171, Queen's University, Department of Economics.
- Charles S. Bos & Siem Jan Koopman & Marius Ooms, 2007. "Long memory modelling of inflation with stochastic variance and structural breaks," CREATES Research Papers 2007-44, School of Economics and Management, University of Aarhus.
- Doornik, Jurgen A. & Ooms, Marius, 2008. "Multimodality in GARCH regression models," International Journal of Forecasting, Elsevier, vol. 24(3), pages 432-448.
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