Comparer des méthodes

	Analyse de la Frontière Stochastique (SFA)	Régression quantile
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1977	1978
Auteur d'origine	Aigner, Lovell & Schmidt (1977); Battese & Coelli (1995) for panels	Koenker & Bassett
Type	Frontier regression model	Conditional quantile regression
Source fondatrice	Aigner, D., Lovell, C.A.K. & Schmidt, P. (1977). Formulation and Estimation of Stochastic Frontier Production Function Models. Journal of Econometrics, 6(1), 21–37.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	SFA, stochastic frontier model, stochastic production frontier, Stokastik Sınır Analizi (SFA)	conditional quantile regression, regression quantiles, Kantil Regresyon
Apparentées	3	5
Résumé	Stochastic Frontier Analysis is a frontier regression model, introduced by Aigner, Lovell and Schmidt in 1977, that estimates a production, cost, or profit function while separating each unit's technical inefficiency from ordinary statistical noise. It splits the error term into a symmetric random component and a one-sided inefficiency component, producing firm- or country-level efficiency scores.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.