Contracting in space: An application of spatial statistics to discrete-choice models

Abstract We develop tests for spatial-error correlation and methods of estimation in the presence of such correlation for discrete-choice models. The tests, which are based on the notion of a generalized residual, are a set of orthogonality conditions that should be satisfied under the null. When the restrictions are rejected, the full model can be estimated by generalized method of moments. These techniques are used to evaluate spatial patterns in retail-gasoline contracts. We examine whether the spatial configuration is random or whether there is a tendency towards clustering or dispersion of contract types. The data consist of all contracts between integrated oil companies and their branded service stations in the city of Vancouver. Six metrics or measures of closeness are examined: Euclidean distance, competition along streets, a combination of the first two, nearest neighbors along streets, nearest neighbors in Euclidean distance, and neighbors that share a common marked boundary.

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