<b> </b> This paper studies the random effects model and the fixed effects model for spatial panel data. The model includes a Cliff and Ord type spatial lag of the dependent variable as well as a spatially lagged one‐way error component structure, accounting for both heterogeneity and spatial...

This paper studies the spatial random effects and spatial fixed effects model. The model includes a Cliff and Ord type spatial lag of the dependent variable as well as a spatially lagged one-way error component structure, accounting for both heterogeneity and spatial correlation across units. We...

We propose to test for spatial correlation of the disturbances using estimated residuals of the within estimator. We derive asymptotic properties of the test and present simulation evidence to show that it also works well in finite samples.

This paper examines the impact of economic conditions and local attitudes on investors’ decisions to opt for a green building certificate. The study is based on property locations in 211 counties and uses a fixed-effects estimator for a panel data set of 10,624 office buildings over 10...

We study dynamic panel data models where the long run outcome for a particular crosssection is affected by a weighted average of the outcomes in the other cross-sections. We show that imposing such a structure implies several cointegrating relationships that are nonlinear in the coefficients to...

In this paper, I propose an instrumental variable (IV) estimation procedure to estimate global VAR (GVAR) models and show that it leads to consistent and asymptotically normal estimates of the parameters. I also provide computationally simple conditions that guarantee that the GVAR model is stable.

I consider a panel vector-autoregressive model with cross-sectional dependence of the disturbances characterized by a spatial autoregressive process. I propose a three-step estimation procedure. Its first step is an instrumental variable estimation that ignores the spatial correlation. In the...

I consider a panel vector autoregressive (panel VAR) model with cross sectional dependence of the model disturbances that can be characterized by a first order spatial autoregressive process. I derive asymptotic properties of a constrained maximum likelihood estimator that uses a consistent...

I illustrate the importance of choosing the correct space in empirical applications of spatial econometric models. I consider different spatial weighting matrices in an SAR(1) model -- contiguity matrix, distance based matrix and their variants adjusted for size of each observation. I show...