One of the central challenges to inference in the context of potentially interdependent observations, known as Galton's Problem, is the difficulty distinguishing spatially correlated observations due to observed units exposure to spatially correlated shocks from spatial correlation in outcomes...

This paper considers the problem of identification, estimation and inference in the case of spatial panel data models with heterogeneous spatial lag coefficients, with and without (weakly) exogenous regressors, and subject to heteroskedastic errors. A quasi maximum likelihood (QML) estimation...

In this paper, we introduce the concept of fractional integration for spatial autoregressive models. We show that the range of the dependence can be spatially extended or diminished by introducing a further fractional integration parameter to spatial autoregressive moving average models (SARMA)....