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On the Equivalence of Location Choice Models: Conditional Logit, Nested Logit and Poisson

  • Kurt Schmidheiny
  • Marius Brülhart

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 CESifo Group Munich in its series CESifo Working Paper Series with number 2726.

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Date of creation: 2009
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Handle: RePEc:ces:ceswps:_2726
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