Spatial econometrics has been an ongoing research field. Recently, it has been extended to panel data settings. Spatial panel data models can allow cross sectional dependence as well as state dependence, and can also enable researchers to control for unknown heterogeneity. This paper reports...

Spatial panel models have panel data structures to capture spatial interactions across spatial units and over time. There are static as well as dynamic models. This text provides some recent developments on the specification and estimation of such models. The first part will consider estimation...

This paper proposes the C(α)-type test in the GMM framework to test the possible presence of spatial correlation through the spatial lag in the spatial autoregressive (SAR) model. This test statistics is especially useful for the SAR model with disturbances under unknown heteroskedasticity. We...

Yu et al. (2008) establish asymptotic properties of quasi-maximum likelihood estimators for a stable spatial dynamic panel model with fixed effects when both the number of individuals n and the number of time periods T are large. This paper investigates unstable cases where there are unit roots...

<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...

<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...

In this paper we derive the asymptotic properties of GMM estimators for the spatial dynamic panel data model with fixed effects when n is large, and T can be large, but small relative to n. The GMM estimation methods are designed with the fixed individual and time effects eliminated from the...

This paper considers a quasi-maximum likelihood estimation for a linear panel data model with time and individual fixed effects, where the disturbances have dynamic and spatial correlations which might be spatially stable or unstable. We first consider both separable and nonseparable...

This paper establishes asymptotic properties of quasi-maximum likelihood estimators for spatial dynamic panel data with both time and individual fixed effects when the number of individuals <italic>n</italic> and the number of time periods <italic>T</italic> can be large. We propose a data transformation approach to eliminate...