Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors

Dong Shin (), Dai-Gyoung Kim () and Han Kim ()

Metrika: International Journal for Theoretical and Applied Statistics, 2002, vol. 56, issue 3, 247-258

Abstract: For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the geeralized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization. Copyright Springer-Verlag 2002

Keywords: Efficiency; GLSE; OLSE; Sinusoidal surface; Spatial regression (search for similar items in EconPapers)
Date: 2002
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s001840100177 (text/html)
Access to full text is restricted to subscribers.

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:spr:metrik:v:56:y:2002:i:3:p:247-258

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2

DOI: 10.1007/s001840100177

Access Statistics for this article

Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze

More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().