Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Стохастический анализ границы (SFA)× | Квантильная регрессия× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1977 | 1978 |
| Автор метода≠ | Aigner, Lovell & Schmidt (1977); Battese & Coelli (1995) for panels | Koenker & Bassett |
| Тип≠ | Frontier regression model | Conditional quantile regression |
| Основополагающий источник≠ | 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. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Другие названия≠ | SFA, stochastic frontier model, stochastic production frontier, Stokastik Sınır Analizi (SFA) | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Связанные≠ | 3 | 5 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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