Near Unit Root in the Spatial Autoregressive Model (2007)
| Citations: | 2 - 0 self |
BibTeX
@MISC{Lee07nearunit,
author = {Lung-fei Lee and Jihai Yu},
title = {Near Unit Root in the Spatial Autoregressive Model},
year = {2007}
}
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Abstract
This paper studies the spatial autoregressive (SAR) model for cross sectional data when the true spatial effect parameter is near unity. We decompose the data generating process (DGP) into an unstable component and a stable component and then establish asymptotic properties of QMLE, 2SLSE and linearized QMLE. The spatial effect estimator has a higher rate of convergence and other parameters have the regular p n rate. The higher rate of convergence reflects how fast the spatial root converges to unity. In contrast to near unit root time series, the estimators are all asymptotically normal. Similarly to the regular SAR model, QMLE and linearized QMLE are more efficient than 2SLSE.
