On Discrete Location Choice Models

When estimating location choices, Poisson regressions and conditional logit models yield identical coefficient estimates (Guimarães et al., 2003). These econometric models involve polar assumptions as regards the similarity of the different locations. Schmidheiny and Brülhart (2011) reconcile these polar cases by introducing a fixed outside option transforming the conditional logit into a nested logit framework. This gives rise to a dissimilarity parameter (λ ∈ [0; 1]) equalling 1 in Poisson regressions (with completely dissimilar locations) and 0 in conditional logit models (with completely similar locations). The dissimilarity parameter is not identified in Schmidheiny and Brülhart (2011). We show that a choice consistent normalisation identifies λ and that, with panel data, its estimation is facilitated by adopting a Poisson regression approach