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Discrete Choice Demand Model/Evidence
Method evidence record

Discrete Choice Demand Model

Discrete-choice demand models estimate the demand for differentiated products — cars, cereals, computers — by modeling consumers as choosing the single product that maximizes their random utility, where utility depends on the product's observed characteristics and price plus an unobserved quality term and an idiosyncratic taste shock. Aggregating individual choice probabilities yields predicted market shares, which are matched to observed shares to recover preference parameters. The framework spans the simple multinomial and nested logit of McFadden to the Berry-Levinsohn-Pakes (BLP) random-coefficients model that uses aggregate market data, allows flexible substitution, and instruments for price endogeneity.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Discrete-Choice Demand Estimation for Differentiated Products
Taxonomic method record · regression-model / economics
  • McFadden, D. (1974). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in Econometrics. Academic Press. · ISBN 9780127761503
  • Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile prices in market equilibrium. Econometrica, 63(4), 841–890. · DOI 10.2307/2171802
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyAlmost Ideal Demand Systemmachine-suggested · Relational suggestion, not evidence.Used in the same domainChoice Experiment Valuationmachine-suggested · Relational suggestion, not evidence.Same method familyDemand System Estimationmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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