We consider treatment effect estimation via a difference-in-difference approach for data with local spatial interaction such that the outcome of observed units depends on their own treatment as well as on the treatment status of proximate neighbors. We show that under standard assumptions...

Spatial effects are endemic in models based on spatially referenced data. The increased awareness of the relevance of spatial interactions, spatial externalities and networking effects among actors, evoked the area of spatial econometrics. Spatial econometrics focuses on the specification and...

It is shown that the null distribution of the F-test in a linear regression is rather non-robust to spatial autocorrelation among the regression disturbances. In particular, the true size of the test tends to either zero or unity when the spatial autocorrelation coefficient approaches the...

The paper considers tests against for autocorrelation among the disturbances in linear regression models that can be expressed as ratios of quadratic forms. It shows that such tests are in general not unbiased and that power can even drop to zero for certain regressors and spatial weight...

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...