Semiparametric identification and estimation of discrete choice models for bundles

Fu Ouyang; Thomas Tao Yang; Hanghui Zhang

doi:10.1016/j.econlet.2020.109321

Semiparametric identification and estimation of discrete choice models for bundles

Fu Ouyang^*, Thomas Tao Yang, Hanghui Zhang

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

We study (point) identification of preference coefficients in semiparametric discrete choice models for bundles. The approach to the identification uses an “identification at infinity” (Chamberlain, 1986) insight in combination with median independence restrictions on unobservables. We propose two-stage maximum score (MS) estimators and show their consistency. Monte Carlo evidence demonstrates that our approach performs satisfactorily in finite samples.

Original language	English
Article number	109321
Journal	Economics Letters
Volume	193
DOIs	https://doi.org/10.1016/j.econlet.2020.109321
Publication status	Published - Aug 2020

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title = "Semiparametric identification and estimation of discrete choice models for bundles",

abstract = "We study (point) identification of preference coefficients in semiparametric discrete choice models for bundles. The approach to the identification uses an “identification at infinity” (Chamberlain, 1986) insight in combination with median independence restrictions on unobservables. We propose two-stage maximum score (MS) estimators and show their consistency. Monte Carlo evidence demonstrates that our approach performs satisfactorily in finite samples.",

keywords = "Bundle choices, Identification at infinity, Maximum score estimation, Median independence, Semiparametric model",

author = "Fu Ouyang and Yang, {Thomas Tao} and Hanghui Zhang",

note = "Publisher Copyright: {\textcopyright} 2020 Elsevier B.V.",

year = "2020",

month = aug,

doi = "10.1016/j.econlet.2020.109321",

language = "English",

volume = "193",

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AU - Ouyang, Fu

AU - Yang, Thomas Tao

AU - Zhang, Hanghui

PY - 2020/8

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N2 - We study (point) identification of preference coefficients in semiparametric discrete choice models for bundles. The approach to the identification uses an “identification at infinity” (Chamberlain, 1986) insight in combination with median independence restrictions on unobservables. We propose two-stage maximum score (MS) estimators and show their consistency. Monte Carlo evidence demonstrates that our approach performs satisfactorily in finite samples.

AB - We study (point) identification of preference coefficients in semiparametric discrete choice models for bundles. The approach to the identification uses an “identification at infinity” (Chamberlain, 1986) insight in combination with median independence restrictions on unobservables. We propose two-stage maximum score (MS) estimators and show their consistency. Monte Carlo evidence demonstrates that our approach performs satisfactorily in finite samples.

KW - Bundle choices

KW - Identification at infinity

KW - Maximum score estimation

KW - Median independence

KW - Semiparametric model

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U2 - 10.1016/j.econlet.2020.109321

DO - 10.1016/j.econlet.2020.109321

M3 - Article

SN - 0165-1765

VL - 193

JO - Economics Letters

JF - Economics Letters

M1 - 109321

ER -

Semiparametric identification and estimation of discrete choice models for bundles

Abstract

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