Library Header Image
LSE Research Online LSE Library Services

Omitted budget constraint bias in discrete-choice demand models

Pesendorfer, Martin, Schiraldi, Pasquale ORCID: 0000-0003-2469-1734 and Silva-Junior, Daniel (2023) Omitted budget constraint bias in discrete-choice demand models. International Journal of Industrial Organization, 86. p. 102889. ISSN 0167-7187

[img] Text (Pesendorfer_omitted-budget-constraint--published) - Published Version
Available under License Creative Commons Attribution.

Download (1MB)

Identification Number: 10.1016/j.ijindorg.2022.102889


A large body of discrete-choice demand studies estimate a demand model in which the consumer’s budget constraint is not taken into account. We illustrate how incorrectly specifying the consideration set, when in fact the budget constraint binds for some products, may bias the demand estimates. We illustrate and quantify the nature of the bias in three ways: (i) in analytical examples; (ii) in field data commonly used in the literature and (iii) in a Monte Carlo study. We find that the price sensitivity can be substantially lower when correctly imposing the budget constraint, and own-price elasticities are typically overestimated although the direction of the own-price elasticity bias is in general ambiguous and depends on the income distribution.

Item Type: Article
Official URL:
Additional Information: © 2022 The Authors
Divisions: Economics
Subjects: H Social Sciences > HB Economic Theory
JEL classification: D - Microeconomics > D1 - Household Behavior and Family Economics > D10 - General
D - Microeconomics > D4 - Market Structure and Pricing > D40 - General
L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L10 - General
L - Industrial Organization > L6 - Industry Studies: Manufacturing > L62 - Automobiles; Other Transportation Equipment
Date Deposited: 16 Nov 2022 15:45
Last Modified: 15 Apr 2024 16:45

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics