We apply a heterogenous coefficient spatial autoregressive panel model from Aquaro, Bailey and Pesaran (2015) to explore competition/cooperation by Berlin fueling stations in setting prices for diesel and E5 fuel. Unlike the maximum likelihood estimation method set forth by Aquaro, Bailey and...

We explore origin-destination forecasting of commodity flows between 15 Spanish regions, using data covering the period from 1995 to 2004. The one-year-ahead forecasts are based on a recently introduced spatial autoregressive variant of the traditional gravity model. Gravity (or spatial...

LeSage and Pace (2009) consider the impact of omitted variables in the face of spatial dependence in the disturbance process of a linear regression relationship. Remarkably, they show that this can lead to a spatial regression model specification containing a spatial lag of the dependent and...

We explore origin-destination forecasting of commodity flows between 15 Spanish regions, using data covering the period from 1995 to 2004. The one-year-ahead forecasts are based on a recently introduced spatial autoregressive variant of the traditional gravity model. Gravity (or spatial...

We discuss Monte Carlo methodology that can be used to explore alternative approaches to estimating spatial regression models. Our focus is on models that include spatial lags of the dependent variable, e.g., the SAR specification: y = ρ W y X β Ε. A major point is that following publication...

We consider the role of local geographic peers in determining equilibrium firm behavior. We exploit in-transitivity in local peer-firm networks and utilize spatial econometric techniques to circumvent well-known challenges in estimating and interpreting empirical models of peer effects. We find...