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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 241-270 |
| Number of pages | 30 |
| Journal | Spatial Economic Analysis |
| Volume | 8 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 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
- General Economics, Econometrics and Finance
- Statistics, Probability and Uncertainty
- Earth and Planetary Sciences (miscellaneous)