Сравнение на методи

	Almost Ideal Demand System	Discrete Choice Demand Model
Област	Икономика	Икономика
Семейство	Regression model	Regression model
Година на възникване	1980	1995
Създател	Angus Deaton & John Muellbauer	Daniel McFadden (logit); Berry, Levinsohn & Pakes (random-coefficients aggregate demand)
Тип	Flexible complete demand system in budget-share form	Characteristics-based discrete-choice model of demand for differentiated products
Основополагащ източник	Deaton, A., & Muellbauer, J. (1980). An almost ideal demand system. The American Economic Review, 70(3), 312–326.	McFadden, D. (1974). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in Econometrics. Academic Press. ISBN: 9780127761503
Други названия	AIDS, Deaton-Muellbauer Demand System, LA-AIDS, Almost Ideal Demand Model	Discrete Choice Demand, Random-Coefficients Logit Demand, BLP Demand Model, Characteristics-Based Demand Model
Свързани	3	3
Резюме	The Almost Ideal Demand System (AIDS), introduced by Angus Deaton and John Muellbauer in 1980, is the workhorse flexible demand system in applied microeconomics. It models each good's budget share as a linear function of the logarithms of all prices and of log real total expenditure, derived from a flexible (PIGLOG) cost function. The form is 'almost ideal' because it satisfies the axioms of choice exactly, aggregates consistently over heterogeneous consumers, has a functional form that is a first-order approximation to any demand system, and can be estimated and tested for homogeneity and symmetry with linear regression once a price index is specified.	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.