Censored Regression Models with Unobserved Stochastic Censoring Thresholds / Forrest D. Nelson.

By:

Nelson, Forrest D

Contributor(s):

National Bureau of Economic Research

Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w0063.Publication details: Cambridge, Mass. National Bureau of Economic Research 1974.Description: 1 online resource: illustrations (black and white)Online resources:

Available additional physical forms:

Hardcopy version available to institutional subscribers

Abstract: The "Tobit" model is a useful tool for estimation of regression models with a truncated or limited dependent variable, but it requires a threshold which is either a known constant or an observable and independent variable. The model presented here extends the Tobit model to the censored case where the threshold is an unobserved and not necessarily independent random variable. Maximum likelihood procedures can be employed for joint estimation of both the primary regression equation and the parameters of the distribution of that random threshold. The appropriate likelihood function is derived, the conditions necessary for identification are revealed, and the particular estimation difficulties are discussed. The model is illustrated by an application to the determination of a housewife's value of time.

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Working Paper	Biblioteca Digital	Colección NBER	nber w0063 (Browse shelf(Opens below))	Not For Loan

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Previous	nber w0060 The Variances of Regression Coefficient Estimates Using Aggregate Data /	nber w0061 Factoring LP Block-Angular Bases /	nber w0062 The Private Enforcement of Law /	nber w0063 Censored Regression Models with Unobserved Stochastic Censoring Thresholds /	nber w0064 Data Analysis, Communication, and Control /	nber w0065 Rational Distributed Lag Structural Form--A General Econometric Model /	nber w0066 Detecting and Assessing the Problems Caused by Multi-Collinearity: A Useof the Singular-Value Decomposition /	Next

December 1974.

The "Tobit" model is a useful tool for estimation of regression models with a truncated or limited dependent variable, but it requires a threshold which is either a known constant or an observable and independent variable. The model presented here extends the Tobit model to the censored case where the threshold is an unobserved and not necessarily independent random variable. Maximum likelihood procedures can be employed for joint estimation of both the primary regression equation and the parameters of the distribution of that random threshold. The appropriate likelihood function is derived, the conditions necessary for identification are revealed, and the particular estimation difficulties are discussed. The model is illustrated by an application to the determination of a housewife's value of time.