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Maximum Likelihood Estimators for ARMA and ARFIMA Models: A Monte Carlo Study

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Michael A. Hauser (University of Economics and Business Administration Vienna)
Abstract

We analyze by simulation the properties of two time domain and two frequency domain estimators for low order autoregressive fractionally integrated moving average Gaussian models, ARFIMA (p,d,q). The estimators considered are the exact maximum likelihood for demeaned data, EML, the associated modified profile likelihood, MPL, and the Whittle estimator with, WLT, and without tapered data, WL. Length of the series is 100. The estimators are compared in terms of pile-up effect, mean square error, bias, and empirical confidence level. The tapered version of the Whittle likelihood turns out to be a reliable estimator for ARMA and ARFIMA models. Its small losses in performance in case of ``well-behaved'' models are compensated sufficiently in more ``difficult'' models. The modified profile likelihood is an alternative to the WLT but is computationally more demanding. It is either equivalent to the EML or more favorable than the EML. For fractionally integrated models, particularly, it dominates clearly the EML. The WL has serious deficiencies for large ranges of parameters, and so cannot be recommended in general. The EML, on the other hand, should only be used with care for fractionally integrated models due to its potential large negative bias of the fractional integration parameter. In general, one should proceed with caution for ARMA(1,1) models with almost canceling roots, and, in particular, in case of the EML and the MPL for inference in the vicinity of a moving average root of +1.

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Paper provided by EconWPA in its series Econometrics with number 9809001.

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Length: 34 pages
Date of creation: 30 Sep 1998
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Handle: RePEc:wpa:wuwpem:9809001

Note: Type of Document - LaTex/Postscript/Zipped; prepared on ULTRIX HP; to print on PostScript; pages: 34 ; figures: 2 files (text.ps and figures.ps) in one zip-file. forthcoming in a special edition on long range dependence of the Journal of Statistical Planning and Inference
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Related research
Keywords: fractional integration; Whittle likelihood; modified profile likelihood; data taper; pile-up effect;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions

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References listed on IDEAS
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  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. Sowell, Fallaw, 1992. "Modeling long-run behavior with the fractional ARIMA model," Journal of Monetary Economics, Elsevier, vol. 29(2), pages 277-302, April. [Downloadable!] (restricted)
  3. Cheung, Yin-Wong & Diebold, Francis X., 1994. "On maximum likelihood estimation of the differencing parameter of fractionally-integrated noise with unknown mean," Journal of Econometrics, Elsevier, vol. 62(2), pages 301-316, June. [Downloadable!] (restricted)
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  4. Ansley, Craig F. & Newbold, Paul, 1980. "Finite sample properties of estimators for autoregressive moving average models," Journal of Econometrics, Elsevier, vol. 13(2), pages 159-183, June. [Downloadable!] (restricted)
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Verspagen,Bart, 1999. "Intellectual Property Rights in the World Economy," Research Memoranda 016, Maastricht : MERIT, Maastricht Economic Research Institute on Innovation and Technology. [Downloadable!]
  2. Silverberg, G. & Verspagen, Bart, 1999. "Long Memory in Time Series of Economic Growth and Convergence," ECIS Working Papers 99.8, Eindhoven Centre for Innovation Studies, Eindhoven University of Technology. [Downloadable!]
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