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Small Sample Bias in Conditional Sum-of-Squares Estimators of Fractionally Integrated ARMA Models

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Author Info
Chung, Ching-Fan
Baillie, Richard T

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Abstract

This paper considers estimation of the parameters for the fractionally integrated class of processes known as ARFIMA. We consider the small sample properties of a conditional sum-of-squares estimator that is asymptotically equivalent to MLE. This estimator has the advantage of being relatively simple and can estimate all the parameters, including the mean, simultaneously. The simulation evidence we present indicates that estimation of the mean can make a considerable difference to the small sample bias and MSE of the other parameter estimates.

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Article provided by Springer in its journal Empirical Economics.

Volume (Year): 18 (1993)
Issue (Month): 4 ()
Pages: 791-806
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Handle: RePEc:spr:empeco:v:18:y:1993:i:4:p:791-806

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  1. Emma M. Iglesias & Garry D. A. Phillips, 2005. "Analysing one-month Euro-market interest rates by fractionally integrated models," Applied Financial Economics, Taylor and Francis Journals, vol. 15(2), pages 95-106, January. [Downloadable!] (restricted)
  2. Aaron Smallwood; Alex Maynard; Mark Wohar, 2005. "The Long and the Short of It: Long Memory Regressors and Predictive Regressions," Computing in Economics and Finance 2005 384, Society for Computational Economics. [Downloadable!]
  3. Jesús Gonzalo, Tae-Hwy Lee, 2000. "On the robustness of cointegration tests when series are fractionally intergrated," Journal of Applied Statistics, Taylor and Francis Journals, vol. 27(7), pages 821-827, September. [Downloadable!] (restricted)
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  4. Ossama Mikhail & Curtis J. Eberwein & Jagdish Handa, 2003. "Testing and Estimating Persistence in Canadian Unemployment," Econometrics 0311004, EconWPA. [Downloadable!]
  5. John T. Barkoulas & Christopher F. Baum & Mustafa Caglayan & Atreya Chakraborty, 1998. "Persistent Dependence in Foreign Exchange Rates? A Reexamination," Boston College Working Papers in Economics 377, Boston College Department of Economics, revised 21 Apr 2000. [Downloadable!]
  6. M. Ooms & J.A. Doornik, 1999. "Inference and forecasting for fractional autoregressive integrated moving average models; with an application to US and UK inflation," Econometric Institute Report 171, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
  7. Dmitri Koulikov, 2002. "Modeling Sequences of Long Memory Positive Weakly Stationary Random Variables," William Davidson Institute Working Papers Series 493, William Davidson Institute at the University of Michigan Stephen M. Ross Business School. [Downloadable!]
  8. Naoya Katayama, 2004. "Asymptotic Prediction Mean Squared Error for Strongly Dependent Processes with Estimated Parameters," Hi-Stat Discussion Paper Series d03-10, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
  9. Aaron D. Smallwood & Paul M. Beaumont, 2002. "An Asymptotic MLE Approach to Modelling Multiple Frequency GARMA Models," Computing in Economics and Finance 2002 285, Society for Computational Economics. [Downloadable!]
  10. Aaron Smallwood, 2005. "Joint Tests for Non-linearity and Long Memory: The Case of Purchasing Power Parity," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 9(2), pages 1227-1227. [Downloadable!] (restricted)
  11. Derek Bond & Michael J. Harrison & Edward J. O'Brien, 2005. "Testing for Long Memory and Nonlinear Time Series: A Demand for Money Study," Trinity Economics Papers tep20021, Trinity College Dublin, Department of Economics. [Downloadable!]
  12. Naoya Katayama, 2004. "Seasonally and Fractionally Differenced Time Series (revised, August 2006)," Hi-Stat Discussion Paper Series d03-11, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
  13. Jurgen A. Doornik & Marius Ooms, 2001. "Computational Aspects of Maximum Likelihood Estimation of Autoregressive Fractionally Integrated Moving Average Models," Economics Papers 2001-W27, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
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