Distance-based methods for measuring spatial concentration such as the DurantonOverman index undergo an increasing popularity in the spatial econometrics community. However, a limiting factor for their usage is their computational complexity since both their memory requirements and running-time are in O(n2). In this paper, we present an algorithm with constant memory requirements and an improve...

This article outlines the type of research infrastructure needed to complement existing commercial Geographic Information System (GIS) environments to perform state-of-the-art spatial analysis of real estate markets. The emphasis is on the relevance of a spatial data analytic perspective and on the operational setting in which this can be implemented. These ideas are part of an overall framewor...

We study the impact of local competition on assortments' attractiveness. The first aim of our paper is to provide a simple and reproducible way to delineate a store trading area using widely available census data. The second aim is to develop a model of retail sales that takes into account competition intensity as well as assortment composition factors (namely price level and variety). We use s...

The journal Computational Statistics and Data Analysis aims to have regular issues in Computational Econometrics. Of particular interest are papers in important areas of econo-metric applications where both computational techniques and numerical methods have a major impact. The goal is to provide sources of information about the most recent developments in computational econometrics that are cu...

The SAR model is widely used in spatial econometrics to model Gaussian processes on a discrete spatial lattice, but for large datasets, fitting it becomes computationally prohibitive, and hence, its usefulness can be limited. A computationally-efficient spatial model is the spatial random effects (SRE) model, and in this article, we calibrate it to the SAR model of interest using a generalisati...