方法对比
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| 随机前沿分析 (SFA)× | 分位数回归× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1977 | 1978 |
| 提出者≠ | Aigner, Lovell & Schmidt (1977); Battese & Coelli (1995) for panels | Koenker & Bassett |
| 类型≠ | Frontier regression model | Conditional quantile regression |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | SFA, stochastic frontier model, stochastic production frontier, Stokastik Sınır Analizi (SFA) | conditional quantile regression, regression quantiles, Kantil Regresyon |
| 相关≠ | 3 | 5 |
| 摘要≠ | 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. |
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