Investigating Inflation Dynamics and Structural Change with an Adaptive ARFIMA Approach
AbstractPrevious models of monthly CPI inflation time series have focused on possible regime shifts, non-linearities and the feature of long memory. This paper proposes a new time series model, named Adaptive ARFIMA; which appears well suited to describe inflation and potentially other economic time series data. The Adaptive ARFIMA model includes a time dependent intercept term which follows a Flexible Fourier Form. The model appears to be capable of succesfully dealing with various forms of breaks and discontinities in the conditional mean of a time series. Simulation evidence justifies estimation by approximate MLE and model specfication through robust inference based on QMLE. The Adaptive ARFIMA model when supplemented with conditional variance models is found to provide a good representation of the G7 monthly CPI inflation series.
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Bibliographic InfoPaper provided by ICER - International Centre for Economic Research in its series ICER Working Papers - Applied Mathematics Series with number 06-2009.
Length: 15 pages
Date of creation: May 2009
Date of revision:
ARFIMA; FIGARCH; long memory; structural change; inflation; G7.;
Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-05-23 (All new papers)
- NEP-CBA-2009-05-23 (Central Banking)
- NEP-ECM-2009-05-23 (Econometrics)
- NEP-ETS-2009-05-23 (Econometric Time Series)
- NEP-MAC-2009-05-23 (Macroeconomics)
- NEP-MON-2009-05-23 (Monetary Economics)
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- Charles S. Bos & Philip Hans Franses & Marius Ooms, 1998.
"Long Memory and Level Shifts: Re-Analyzing Inflation Rates,"
Tinbergen Institute Discussion Papers
98-039/4, Tinbergen Institute.
- Philip Hans Franses & Marius Ooms & Charles S. Bos, 1999. "Long memory and level shifts: Re-analyzing inflation rates," Empirical Economics, Springer, vol. 24(3), pages 427-449.
- Franses, Ph.H.B.F. & Ooms, M. & Bos, C.S., 1998. "Long memory and level shifts: re-analysing inflation rates," Econometric Institute Research Papers EI 9811, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Christopher F. Baum & John T. Barkoulas & Mustafa Caglayan, 1999.
"Persistence in International Inflation Rates,"
Southern Economic Journal,
Southern Economic Association, vol. 65(4), pages 900-913, April.
- Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
- Jushan Bai, 1995.
"Estimating Multiple Breaks One at a Time,"
95-18, Massachusetts Institute of Technology (MIT), Department of Economics.
- Brunner, Allan D & Hess, Gregory D, 1993.
"Are Higher Levels of Inflation Less Predictable? A State-Dependent Conditional Heteroscedasticity Approach,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 11(2), pages 187-97, April.
- Allan D. Brunner & Gregory D. Hess, 1990. "Are higher levels of inflation less predictable? A state-dependent conditional heteroskedasticity approach," Finance and Economics Discussion Series 141, Board of Governors of the Federal Reserve System (U.S.).
- Diebold, Francis X. & Inoue, Atsushi, 2001.
"Long memory and regime switching,"
Journal of Econometrics,
Elsevier, vol. 105(1), pages 131-159, November.
- Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002.
"Inflation, forecast intervals and long memory regression models,"
International Journal of Forecasting,
Elsevier, vol. 18(2), pages 243-264.
- Charles S. Bos & Philip Hans Franses & Marius Ooms, 2001. "Inflation, Forecast Intervals and Long Memory Regression Models," Tinbergen Institute Discussion Papers 01-029/4, Tinbergen Institute.
- Claudio Morana & Fabio Cesare Bagliano, 2007. "Inflation and monetary dynamics in the USA: a quantity-theory approach," Applied Economics, Taylor & Francis Journals, vol. 39(2), pages 229-244.
- Hyung, N. & Franses, Ph.H.B.F., 2001.
"Structural breaks and long memory in US inflation rates: do they matter for forecasting?,"
Econometric Institute Research Papers
EI 2001-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Hyung, Namwon & Franses, Philip Hans & Penm, Jack, 2006. "Structural breaks and long memory in US inflation rates: Do they matter for forecasting?," Research in International Business and Finance, Elsevier, vol. 20(1), pages 95-110, March.
- George Kapetanios, 2002. "Testing for Neglected Nonlinearity in Long Memory Models," Working Papers 473, Queen Mary, University of London, School of Economics and Finance.
- Denise R. Osborn & Marianne Sensier, 2009.
"Uk Inflation: Persistence, Seasonality And Monetary Policy,"
Scottish Journal of Political Economy,
Scottish Economic Society, vol. 56(1), pages 24-44, 02.
- Denise Osborn & Marianne Sensier, 2007. "UK inflation: persistance, seasonality and monetary policy," The School of Economics Discussion Paper Series 0716, Economics, The University of Manchester.
- Baillie, Richard T. & Kapetanios, George, 2007. "Testing for Neglected Nonlinearity in Long-Memory Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 447-461, October.
- Perron, P. & Bai, J., 1995.
"Estimating and Testing Linear Models with Multiple Structural Changes,"
Cahiers de recherche
9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
- Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
- Morana Claudio, 2002. "Common Persistent Factors in Inflation and Excess Nominal Money Growth and a New Measure of Core Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-40, November.
- Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
- Katsumi Shimotsu, 2006. "Simple (but effective) tests of long memory versus structural breaks," Working Papers 1101, Queen's University, Department of Economics.
- Christian Conrad & Berthold R. Haag, 2006. "Inequality Constraints in the Fractionally Integrated GARCH Model," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(3), pages 413-449.
- Ooms, M. & Doornik, J.A., 1999. "Inference and Forecasting for Fractional Autoregressive Integrated Moving Average Models, with an application to US and UK inflation," Econometric Institute Research Papers EI 9947/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- de Figueiredo, Erik Alencar, 2010. "Dynamics of regional unemployment rates in Brazil: Fractional behavior, structural breaks, and Markov switching," Economic Modelling, Elsevier, vol. 27(5), pages 900-908, September.
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