In this paper, a Poisson gravity model is introduced that incorporates spatial dependence of the explained variable without relying on restrictive distributional assumptions of the underlying data generating process. The model comprises a spatially filtered component including the origin,...

Digital ecosystems like Airbnb or Uber have fundamentally changed their respective domains, and an increasing number of organizations are now considering how they can benefit from the underlying concepts. While several examples of systems that are generally accepted as digital ecosystems exist...

Spatial Filter for spatial autoregressive models like the spatial Durbin Model have seen a great interest in the recent literature. Pace et al. (2011) show that the spatial filtering methods developed by Griffith (2000) have desireable estimation properties for some parameters associated with...

The speed of income convergence in Europe remains one of the hot topics in regional economics. Recently Bayesian Model Averaging (BMA) applied to spatial autoregressive models seems to have gained more popularity. BMA averages over some predetermined number of so called top models, ranked by the...

This paper focuses on several estimation methods for SAR- models in case of missing observations in the dependent variable. First, we show with an example and then in general, how missing observations can change the model and thus resulting in the failure of the 'traditional' estimation methods....