Structural choice analysis with nested logit models
Florian Heiss
University of Mannheim, MEA
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Abstract. The nested logit model has become an important tool for the empirical
analysis of discrete outcomes. There is some confusion about its
specification of the outcome probabilities. Two major variants show up in
the literature. This paper compares both and finds that one of them (called
random utility maximization nested logit, RUMNL) is preferable in most
situations. Since the command nlogit of Stata 7.0 implements the
other variant (called non-normalized nested logit, NNNL), an implementation
of RUMNL called nlogitrum is introduced. Numerous examples support
and illustrate the differences between both specifications.
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Florian Heiss
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nlogitdn, nlogitrum, nested logit model, discrete choice, random utility maximization model
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