Estimation et mise à l'épreuve d'une Régression linéaire à racine quasi unitaire dans l'expression erreur autorégressive spatiale

Badi H. Baltagi; Chihwa Kao; Long Liu

doi:10.1080/17421772.2012.760133

Estimation et mise à l'épreuve d'une Régression linéaire à racine quasi unitaire dans l'expression erreur autorégressive spatiale

Translated title of the contribution: The Estimation and Testing of a Linear Regression with Near Unit Root in the Spatial Autoregressive Error Term

Badi H. Baltagi, Chihwa Kao, Long Liu

Department of Economics

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

This paper considers the estimation of a linear regression involving the spatial autoregressive (SAR) error term which is nearly nonstationary. The asymptotics properties of the ordinary least squares (OLS), true generalized least squares (GLS) and feasible generalized least squares (FGLS) estimators as well as the corresponding Wald test statistics are derived. Monte Carlo results are conducted to study the sampling behavior of the proposed estimators and test statistics.

Translated title of the contribution	The Estimation and Testing of a Linear Regression with Near Unit Root in the Spatial Autoregressive Error Term
Original language	French
Pages (from-to)	241-270
Number of pages	30
Journal	Spatial Economic Analysis
Volume	8
Issue number	3
DOIs	https://doi.org/10.1080/17421772.2012.760133
State	Published - Sep 1 2013

Keywords

generalized least squares
maximum likelihood estimation
ordinary least squares
spatial autocorrelation
two-stage least squares

ASJC Scopus subject areas

Geography, Planning and Development
Economics, Econometrics and Finance(all)
Statistics, Probability and Uncertainty
Earth and Planetary Sciences (miscellaneous)

Access to Document

10.1080/17421772.2012.760133

Cite this

@article{34a57e7e115142998cdd5019bf5274c7,

title = "Estimation et mise {\`a} l'{\'e}preuve d'une R{\'e}gression lin{\'e}aire {\`a} racine quasi unitaire dans l'expression erreur autor{\'e}gressive spatiale",

abstract = "This paper considers the estimation of a linear regression involving the spatial autoregressive (SAR) error term which is nearly nonstationary. The asymptotics properties of the ordinary least squares (OLS), true generalized least squares (GLS) and feasible generalized least squares (FGLS) estimators as well as the corresponding Wald test statistics are derived. Monte Carlo results are conducted to study the sampling behavior of the proposed estimators and test statistics.",

keywords = "generalized least squares, maximum likelihood estimation, ordinary least squares, spatial autocorrelation, two-stage least squares",

author = "Baltagi, {Badi H.} and Chihwa Kao and Long Liu",

year = "2013",

month = sep,

day = "1",

doi = "10.1080/17421772.2012.760133",

language = "French",

volume = "8",

pages = "241--270",

journal = "Spatial Economic Analysis",

issn = "1742-1772",

publisher = "Routledge",

number = "3",

}

TY - JOUR

T1 - Estimation et mise à l'épreuve d'une Régression linéaire à racine quasi unitaire dans l'expression erreur autorégressive spatiale

AU - Baltagi, Badi H.

AU - Kao, Chihwa

AU - Liu, Long

PY - 2013/9/1

Y1 - 2013/9/1

N2 - This paper considers the estimation of a linear regression involving the spatial autoregressive (SAR) error term which is nearly nonstationary. The asymptotics properties of the ordinary least squares (OLS), true generalized least squares (GLS) and feasible generalized least squares (FGLS) estimators as well as the corresponding Wald test statistics are derived. Monte Carlo results are conducted to study the sampling behavior of the proposed estimators and test statistics.

AB - This paper considers the estimation of a linear regression involving the spatial autoregressive (SAR) error term which is nearly nonstationary. The asymptotics properties of the ordinary least squares (OLS), true generalized least squares (GLS) and feasible generalized least squares (FGLS) estimators as well as the corresponding Wald test statistics are derived. Monte Carlo results are conducted to study the sampling behavior of the proposed estimators and test statistics.

KW - generalized least squares

KW - maximum likelihood estimation

KW - ordinary least squares

KW - spatial autocorrelation

KW - two-stage least squares

UR - http://www.scopus.com/inward/record.url?scp=84884357011&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84884357011&partnerID=8YFLogxK

U2 - 10.1080/17421772.2012.760133

DO - 10.1080/17421772.2012.760133

M3 - Article

AN - SCOPUS:84884357011

SN - 1742-1772

VL - 8

SP - 241

EP - 270

JO - Spatial Economic Analysis

JF - Spatial Economic Analysis

IS - 3

ER -

Estimation et mise à l'épreuve d'une Régression linéaire à racine quasi unitaire dans l'expression erreur autorégressive spatiale

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this