Efficient Likelihood Inference In Nonstationary Univariate Models
Recent literature shows that embedding fractionally integrated time series models with spectral poles at the long-run and/or seasonal frequencies in autoregressive frameworks leads to estimators and test statistics with non-standard limiting distributions that must be simulated on a case-by-case basis. However, we show that by embedding the models in a general I(d) framework the resulting estimators and tests regain all the desirable properties from standard statistical analysis. We derive the time domain maximum likelihood estimator and show that it is consistent, asymptotically normal, and under Gaussianity asymptotically efficient in the sense that it has asymptotic variance equal to the inverse of the Fisher information matrix. The three likelihood based test statistics (Wald, likelihood ratio, and Lagrange multiplier) are asymptotically equivalent and have the usual asymptotic chi-squared distribution and under the additional assumption of Gaussianity they are locally most powerful. In the special case where the dynamics of the model is characterized by a scalar parameter, we show that, in addition, the two-sided tests achieve the Gaussian power envelope of all invariant and unbiased tests, i.e. they are uniformly most powerful invariant unbiased. The finite sample properties of the tests are evaluated by Monte Carlo experiments. In contrast to what might be expected from the literature, the likelihood ratio test is found to outperform the Lagrange multiplier and Wald tests.
(This abstract was borrowed from another version of this item.)
Volume (Year): 20 (2004)
Issue (Month): 01 (February)
|Contact details of provider:|| Postal: |
Web page: http://journals.cambridge.org/jid_ECTEmail:
References listed on IDEAS
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.:
- Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996.
"Efficient Tests for an Autoregressive Unit Root,"
Econometric Society, vol. 64(4), pages 813-36, July.
- Tom Doan, . "ERSTEST: RATS procedure to perform Elliott-Rothenberg-Stock unit root tests," Statistical Software Components RTS00066, Boston College Department of Economics.
- Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc.
- Tom Doan, . "GLSDETREND: RATS procedure to perform local to unity GLS detrending," Statistical Software Components RTS00077, Boston College Department of Economics.
- Herman J. Bierens, 2000.
"Complex Unit Roots and Business Cycles: Are They Real?,"
Econometric Society World Congress 2000 Contributed Papers
0197, Econometric Society.
- Bierens, Herman J., 2001. "Complex Unit Roots And Business Cycles: Are They Real?," Econometric Theory, Cambridge University Press, vol. 17(05), pages 962-983, October.
When requesting a correction, please mention this item's handle: RePEc:cup:etheor:v:20:y:2004:i:01:p:116-146_20. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Keith Waters)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.