The random coefficients logit model is identified
By Jeremy T. Fox, Kyoo il Kim, S. Ryan, Patrick Bajari. 2012
126 citations recorded by the source corpus.
The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the distribution of random coefficients in the multinomial logit model is nonparametrically identified. Our approach requires variation in product characteristics only locally and does not rely on the special regressors with large supports used in related papers. One of our two identification arguments is constructive. Both approaches may be applied to other choice models with random coefficients.
Subfields: Economics and Econometrics, Marketing
View Paper: https://www.semanticscholar.org/paper/a97927eacbec63486cee982094573429bca4a316
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Citations in the corpus
- Best practices for differentiated products demand estimation with PyBLP (2020, background): “Fox et al. (2012) and Iaria and Wang (2019) establish the real analyticity of the mixtures of logits under different conditions on the mixing distribution.”