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| Модел на Тобит за цензурирани регресии× | Квантилна регресия× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1958 | 1978 |
| Създател≠ | James Tobin | Koenker & Bassett |
| Тип≠ | Censored regression (limited dependent variable) | Conditional quantile regression |
| Основополагащ източник≠ | 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 ↗ |
| Други названия | censored regression, limited dependent variable model, Tobit Modeli (Sansürlü Regresyon) | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Свързани≠ | 4 | 5 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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