1. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188. [Downloadable!] (restricted)
2. Ooms, Marius & Hassler, Uwe, 1997. "On the effect of seasonal adjustment on the log-periodogram regression," Economics Letters, Elsevier, vol. 56(2), pages 135-141, October. [Downloadable!] (restricted)
3. Jordi Gali & Mark Gertler, 2000. "Inflation Dynamics: A Structural Econometric Analysis," NBER Working Papers 7551, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
   Other versions:
   • Jordi Galí & Mark Gertler, 1998. "Inflation Dynamics: A Structural Econometric Analysis," Economics Working Papers 341, Department of Economics and Business, Universitat Pompeu Fabra. [Downloadable!]
   • Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October. [Downloadable!] (restricted)
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   • Bos, C.S. & Franses, P.H. & Ooms, M., 1998. "Long Memory and Level Shifts: Re-Analyzing Inflation Rates," Papers 9811/a, Erasmus University of Rotterdam - Econometric Institute.
   • 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. [Downloadable!]
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   • James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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Cited by:
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1. Siem Jan Koopman & Borus Jungbacker & Eugenie Hol, 2004. "Forecasting Daily Variability of the S&P 100 Stock Index using Historical, Realised and Implied Volatility Measurements," Tinbergen Institute Discussion Papers 04-016/4, Tinbergen Institute. [Downloadable!]
   Other versions:
   • Eugenie Hol & Siem Jan Koopman & Borus Jungbacker, 2004. "Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements," Computing in Economics and Finance 2004 342, Society for Computational Economics.
   • Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005. "Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 445-475, June. [Downloadable!] (restricted)
2. Chien-Chiang Lee & Chun-Ping Chang, 2007. "Mean reversion of inflation rates in 19 OECD countries: Evidence from panel Lm unit root tests with structural breaks," Economics Bulletin, Economics Bulletin, vol. 3(23), pages 1-15. [Downloadable!]
3. N. Hyung & P.H.B.F. Franses, 2001. "Structural breaks and long memory in US inflation rates," Econometric Institute Report 221, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
4. John W. Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Working Papers 07-1, Bank of Canada. [Downloadable!]
5. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Economics Working Papers ECO2006/3, European University Institute. [Downloadable!]
   Other versions:
   • Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 594-616. [Downloadable!] (restricted)
6. Claudio Morana, 2002. "Common Persistent Factors in Inflation and Excess Nominal Money Growth and a New Measure of Core Inflation," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 6(3), pages 1092-1092. [Downloadable!] (restricted)
7. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics. [Downloadable!]
   Other versions:
   • Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 127(1-2), pages 539-578. [Downloadable!] (restricted)