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Stochastic Frontier Analysis (SFA)×Regresja kwantylowa×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania19771978
TwórcaAigner, Lovell & Schmidt (1977); Battese & Coelli (1995) for panelsKoenker & Bassett
TypFrontier regression modelConditional quantile regression
Źródło pierwotneAigner, D., Lovell, C.A.K. & Schmidt, P. (1977). Formulation and Estimation of Stochastic Frontier Production Function Models. Journal of Econometrics, 6(1), 21–37. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Inne nazwySFA, stochastic frontier model, stochastic production frontier, Stokastik Sınır Analizi (SFA)conditional quantile regression, regression quantiles, Kantil Regresyon
Pokrewne35
PodsumowanieStochastic 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.
ScholarGateZbiór danych
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  2. 2 Źródła
  3. PUBLISHED
  1. v1
  2. 2 Źródła
  3. PUBLISHED

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ScholarGatePorównaj metody: Stochastic Frontier Analysis · Quantile Regression. Pobrano 2026-06-17 z https://scholargate.app/pl/compare