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Regression modelDifferentiated-products demand / industrial organization

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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Sources

  1. McFadden, D. (1974). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in Econometrics. Academic Press. ISBN: 9780127761503
  2. Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile prices in market equilibrium. Econometrica, 63(4), 841–890. DOI: 10.2307/2171802

How to cite this page

ScholarGate. (2026, June 22). Discrete-Choice Demand Estimation for Differentiated Products. ScholarGate. https://scholargate.app/en/economics/discrete-choice-demand

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ScholarGateDiscrete Choice Demand Model (Discrete-Choice Demand Estimation for Differentiated Products). Retrieved 2026-06-24 from https://scholargate.app/en/economics/discrete-choice-demand · Dataset: https://doi.org/10.5281/zenodo.20539026