<title>Abstract</title> This paper studies the spatial autoregressive (SAR) model for cross-sectional data when the coefficient of the spatial lag of the dependent variable is near unity. We decompose the data generating process into an unstable component and a stable one, and establish asymptotic properties...

<title>Abstract</title> This paper investigates the quasi-maximum likelihood estimation of spatial dynamic panel data models where spatial weights matrices can be time varying. We find that QML estimate is consistent and asymptotically normal. We investigate marginal impacts of explanatory variables in this...

<title>Abstract</title> This paper investigates the quasi-maximum likelihood estimation of spatial dynamic panel data models where spatial weights matrices can be time varying. We find that QML estimate is consistent and asymptotically normal. We investigate marginal impacts of explanatory variables in this...

Abstract This paper investigates the spurious regression in the spatial setting where the regressant and regressors may be generated from possible nonstationary spatial autoregressive processes. Under the near unit root specification with a row-normalized spatial weights matrix, it is shown that...