EconBase
← All papers

Identification of Random Coefficient Latent Utility Models

Roy Allen, John Rehbeck

arXiv 29 Feb 2020 · Econometrics

arXiv:2003.00276 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper provides nonparametric identification results for random coefficient distributions in perturbed utility models. We cover discrete and continuous choice models. We establish identification using variation in mean quantities, and the results apply when an analyst observes aggregate demands but not whether goods are chosen together. We require exclusion restrictions and independence between random slope coefficients and random intercepts. We do not require regressors to have large supports or parametric assumptions.

Citation extraction

78
references
137
in-text mentions
78
distinct cited
6
self-citations
9,950
main-text words

appendix boundary found by appendix_command · 73% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Fabian Dunker, Stefan Hoderlein, and Hiroaki Kaido (2017) Nonparametric identification of endogenous and heterogeneous aggregate demand models: complements, bundles and the market level1.00094100%
2Matthew Gentzkow (2007) Valuing new goods in a model with complementarity: Online newspapers1.00053100%
3Roy Allen and John Rehbeck (2019) Identification with additively separable heterogeneity self0.9209378%
4Jeremy T Fox, Kyoo il Kim, Stephen P Ryan, and Patrick Bajari (2012) The random coefficients logit model is identified0.88513569%
5Victor Chernozhukov, Iván Fernández-Val, and Whitney K Newey (2019) Nonseparable multinomial choice models in cross-section and panel data0.8746567%
6Eric Gautier and Yuichi Kitamura (2013) Nonparametric estimation in random coefficients binary choice models0.84333100%
7Hidehiko Ichimura and T Scott Thompson (1998) Maximum likelihood estimation of a binary choice model with random coefficients of unknown distribution0.84333100%
8Richard Blundell and James L Powell (2003) Endogeneity in nonparametric and semiparametric regression models0.73732100%
9Kyoo il Kim (2014) Identification of the distribution of random coefficients in static and dynamicdiscrete choice models0.73732100%
10Arthur Lewbel and Krishna Pendakur (2017) Unobserved preference heterogeneity in demand using generalized random coefficients0.73732100%

Showing the top 10 of 78 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Identification and estimation of multinomial choice models with latent special covariates0.58531