We develop a general space-time filter applied to panel data models in order to control for heterogeneity as well as both time and spatial dependence. Treatment of initial period observations is analyzed when the number of time periods is small. A second issue relates to an implied restriction...

The focus here is on the log-normal version of the spatial interaction model. In this context, we consider spatial econometric specifications that can be used to accommodate two types of dependence scenarios, one involving endogenous interaction and the other exogenous interaction. These model...

Regional scientists frequently work with regression relationships involving sample data that is spatial in nature. For example, hedonic house-price regressions relate selling prices of houses located at points in space to characteristics of the homes as well as neighborhood characteristics....

This paper explores the contribution of knowledge capital to total factor productivity differences among regions within a regression framework. We provide an econometric derivation of the relationship and show that the presence of latent/unobservable regional knowledge capital leads to a model...

We use a spatial econometric extension of the traditional regression-based gravity model introduced in LeSage and Pace (2005) to model commodity flows between 35 regions in Austria. Our focus is on a formal methodology for incorporating information regarding the highway network into the 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...