Tobit model (original) (raw)
Das Tobit-Modell ist ein auf James Tobin zurückgehendes ökonometrisches Modell zur Analyse beschränkt abhängiger Variablen (zensierte Daten). Da die abhängige Variable nur auf einem bestimmten Wertebereich existiert, sind normale Regressionsparameter nicht die bestmöglichen Schätzer, sodass die Schätzfunktion korrigiert werden muss. Diese Korrektur ist im Tobit-Modell implementiert.
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| dbo:abstract | Das Tobit-Modell ist ein auf James Tobin zurückgehendes ökonometrisches Modell zur Analyse beschränkt abhängiger Variablen (zensierte Daten). Da die abhängige Variable nur auf einem bestimmten Wertebereich existiert, sind normale Regressionsparameter nicht die bestmöglichen Schätzer, sodass die Schätzfunktion korrigiert werden muss. Diese Korrektur ist im Tobit-Modell implementiert. (de) El modelo Tobit es un modelo estadístico propuesto por James Tobin (1958) para describir la relación entre una variable dependiente no negativa y una variable independiente (o vector ) . El término Tobit fue derivado del nombre truncando de Tobin y añadiendo, por analogía, el it como en el modelo probit o en el modelo logit. El modelo supone que existe una variable latente (no observable por ejemplo) . Esta variable depende linealmente de a través de un parámetro(vector) que determina la relación entre la variable independiente (o vector) y la variable latente (Tal como en un modelo lineal). Además, hay un término de error con una distribución normal para captar las influencias aleatorias en esta relación. La variable observable se define como igual a la variable latente cuando la variable latente es superior a cero y cero en caso contrario. donde es una variable latente: (es) Le modèle tobit est un modèle statistique utilisé pour décrire une relation entre une variable dépendante censurée et une variable indépendante. Il a été proposé par l'économiste James Tobin. (fr) In statistics, a tobit model is any of a class of regression models in which the observed range of the dependent variable is censored in some way. The term was coined by Arthur Goldberger in reference to James Tobin, who developed the model in 1958 to mitigate the problem of zero-inflated data for observations of household expenditure on durable goods. Because Tobin's method can be easily extended to handle truncated and other non-randomly selected samples, some authors adopt a broader definition of the tobit model that includes these cases. Tobin's idea was to modify the likelihood function so that it reflects the unequal sampling probability for each observation depending on whether the latent dependent variable fell above or below the determined threshold. For a sample that, as in Tobin's original case, was censored from below at zero, the sampling probability for each non-limit observation is simply the height of the appropriate density function. For any limit observation, it is the cumulative distribution, i.e. the integral below zero of the appropriate density function. The tobit likelihood function is thus a mixture of densities and cumulative distribution functions. (en) |
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| rdfs:comment | Das Tobit-Modell ist ein auf James Tobin zurückgehendes ökonometrisches Modell zur Analyse beschränkt abhängiger Variablen (zensierte Daten). Da die abhängige Variable nur auf einem bestimmten Wertebereich existiert, sind normale Regressionsparameter nicht die bestmöglichen Schätzer, sodass die Schätzfunktion korrigiert werden muss. Diese Korrektur ist im Tobit-Modell implementiert. (de) Le modèle tobit est un modèle statistique utilisé pour décrire une relation entre une variable dépendante censurée et une variable indépendante. Il a été proposé par l'économiste James Tobin. (fr) El modelo Tobit es un modelo estadístico propuesto por James Tobin (1958) para describir la relación entre una variable dependiente no negativa y una variable independiente (o vector ) . El término Tobit fue derivado del nombre truncando de Tobin y añadiendo, por analogía, el it como en el modelo probit o en el modelo logit. donde es una variable latente: (es) In statistics, a tobit model is any of a class of regression models in which the observed range of the dependent variable is censored in some way. The term was coined by Arthur Goldberger in reference to James Tobin, who developed the model in 1958 to mitigate the problem of zero-inflated data for observations of household expenditure on durable goods. Because Tobin's method can be easily extended to handle truncated and other non-randomly selected samples, some authors adopt a broader definition of the tobit model that includes these cases. (en) |
| rdfs:label | Tobit-Modell (de) Modelo Tobit (es) Modèle tobit (fr) Tobit model (en) |
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