We describe econometric techniques to treat spatial autocorrelation in multiequation cross-section models. The cross-section approaches discussed here are heavily based on the spatial GMM procedure, proposed by Conley (1999). An extension for fullinformation instrumental variable models is...

The goal of this paper is to evaluate the results of regional economic growth estimates at multiple spatial scales using spatial panel data models. The spatial scales examined are minimum comparable areas, micro-regions, meso-regions and states over the period between 1970 and 2000. Alternative...

This paper investigates spatial dependence in the prices of office buildings in Hong Kong, London, Los Angeles, New York City, Paris and Tokyo for 2007 to 2013. Compared to prior literature, we find low economic impact from spatial dependence in all six markets, and spatial and spatial-temporal...

This paper applies a non-parametric heteroscedasticity and autocorrelation consistent (HAC) estimator of error terms in the context of the spatial autoregressive model of GDP per capita convergence of European regions at NUTS 2 level. By introducing the spatial dimension, it looks how the...

We develop a novel theoretical framework for studying ecosystems in which interacting state variables which are affected by management decisions diffuse in space. We identify (i) mechanisms creating spatial patterns when economic agents maximize profit at each site by ignoring the impact of...

In this paper, we discuss the substantive range of spatial interdependence in political and related social sciences. We offer a generic theoretical model demonstrating that interdependence arises whenever utilities of one actor depend on the choices of other actors - i.e., inter alia, in all...