It is well understood that the two most popular empirical models of location choice-conditional logit and Poisson - return identical coefficient estimates when the regressors are not individual specific. We show that these two models differ starkly in terms of their implied predictions. The conditional logit model represents a zero-sum world, in which one region's gain is the other regions' loss. In contrast, the Poisson model implies a positive-sum economy, in which one region's gain is no other region's loss. We also show that all intermediate cases can be represented as a nested logit model with a single outside option. The nested logit turns out to be a linear combination of the conditional logit and Poisson models. Conditional logit and Poisson elasticities mark the polar cases and can therefore serve as boundary values in applied research.
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Paper provided by Institut d'Economia de Barcelona (IEB) in its series Working Papers with number
2009/14.
Find related papers by JEL classification: C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models R3 - Urban, Rural, and Regional Economics - - Production Analysis and Firm Location H73 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Interjurisdictional Differentials and Their Effects
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