The paper examines the relevance of unobserved spatial dependence between individual decision-makers in the analysis of discrete choices. To incorporate spatial interdependencies in the behavioral analysis, we propose a spatial random utility model of recreation demand. The model combines the...

Why do industrial clusters occur in space? Is it because industries need to stay close together to interact or, conversely, because they concentrate in certain portions of space to exploit favourable conditions like public incentives, proximity to communication networks, to big population...

The contention of this paper is that many social science research problems are too “wicked” to be suitably studied using conventional statistical and regression-based methods of data analysis. This paper argues that an integrated geospatial approach based on methods of machine learning is...

This paper provides an overview of the existing literature on panel data models with error cross-sectional dependence. We distinguish between spatial dependence and factor structure dependence and we analyse the implications of weak and strong cross-sectional dependence on the properties of the...

An approach to incorporate spatial dependence into Stochastic Frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial...

Notre étude a pour objectif de mesurer les effets spatiaux des externalités de connaissances sur la production de brevets des firmes, au niveau des villes. Nous utilisons une méthode originale basée sur le maximum d'entropie généralisé. Cette méthode permet de tester l'auto-correlation...