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| Tobit删失回归模型× | 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≠ | 1958 | 1978 |
| 提出者≠ | James Tobin | Koenker & Bassett |
| 类型≠ | Censored regression (limited dependent variable) | Conditional quantile regression |
| 开创性文献≠ | Tobin, J. (1958). Estimation of Relationships for Limited Dependent Variables. Econometrica, 26(1), 24-36. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| 别名 | censored regression, limited dependent variable model, Tobit Modeli (Sansürlü Regresyon) | conditional quantile regression, regression quantiles, Kantil Regresyon |
| 相关≠ | 4 | 5 |
| 摘要≠ | The Tobit model is a regression for outcomes that are censored at a threshold, estimating the relationship by maximum likelihood. Introduced by James Tobin in 1958, it addresses the pile-up of observations at a limit (typically zero) in data such as spending, wages, or duration. | 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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