Asymptotic Efficiency of the OLS Estimator with Singular Limiting Sample Moment Matrices
Yoshimasa Uematsu
Global COE Hi-Stat Discussion Paper Series from Institute of Economic Research, Hitotsubashi University
Abstract:
This paper presents a time series model that has an asymptotically efficient ordinary least squares (OLS) estimator, irrespective of the singularity of its limiting sample moment matrices. In the literature on stationary time series analysis, Grenander and Rosenblatt's (1957) (G-R) classical result is used to judge the asymptotic efficiency of regression coefficients on deterministic regressors satisfying Grenander's condition. Without this condition, however, it is not obvious that the model is efficient. In this paper, we introduce such a model by proving the efficiency of the model with a slowly varying (SV) regressor under the same condition on error terms constrained in G-R. This kind of regressor is known to display asymptotic singularity in the sample moment matrices, as in Phillips (2007), such that Grenander's condition fails.
Date: 2011-10
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://gcoe.ier.hit-u.ac.jp/research/discussion/2008/pdf/gd11-208.pdf (application/pdf)
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:hst:ghsdps:gd11-208
Access Statistics for this paper
More papers in Global COE Hi-Stat Discussion Paper Series from Institute of Economic Research, Hitotsubashi University Contact information at EDIRC.
Bibliographic data for series maintained by Tatsuji Makino ().