Fractionally Integrated Long Horizon Regressions

Lee Jin ()
Additional contact information
Lee Jin: National University of Singapore

Studies in Nonlinear Dynamics & Econometrics, 2007, vol. 11, issue 1, 20

Abstract: We consider long horizon regression models where the disturbance and the predictor are possibly fractionally integrated. Asymptotic distributions of the OLS estimator and of the test statistic are given. It is found that the t-statistic diverges at the rate of square root of T, where T is the sample size. Thus, it is desirable to use the scaled test statistic, as it converges to a well-defined limit, which depends on the memory parameters through the functionals on the fractional Wiener processes. Simulation studies present some empirical distributions of the scaled test statistic according to different values of the memory parameters. The proposed model with fractional processes is empirically more tractable than the model with local to unity processes, since memory parameters are consistently estimable unlike localizing parameters in the latter model.

Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://doi.org/10.2202/1558-3708.1337 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sndecm:v:11:y:2007:i:1:n:6

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/snde/html

DOI: 10.2202/1558-3708.1337

Access Statistics for this article

Studies in Nonlinear Dynamics & Econometrics is currently edited by Bruce Mizrach

More articles in Studies in Nonlinear Dynamics & Econometrics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().