Censored regression models with unobserved, stochastic censoring thresholds

DOI10.1016/0304-4076(77)90003-3zbMath0373.62022OpenAlexW3126000587MaRDI QIDQ1244766

Forrest D. Nelson

Publication date: 1977

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: http://www.nber.org/papers/w0063.pdf

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Nonparametric estimation (62G05)

Related Items (10)

Non-parametric maximum likelihood estimation of censored regression models ⋮ A semi-parametric censored regression estimator ⋮ Bayesian analysis of censored linear regression models with scale mixtures of normal distributions ⋮ Maximum likelihood estimation of a spatial autoregressive Tobit model ⋮ The Tobit model with a non‐zero threshold ⋮ Likelihood Estimation for Censored Random Vectors ⋮ A non-iterative Bayesian sampling algorithm for censored Student-tlinear regression models ⋮ Specification testing when score test statistics are identically zero ⋮ Tobit models: A survey ⋮ A latent structure double hurdle regression model for exploring heterogeneity in consumer search patterns.

Cites Work

• Estimation of Relationships for Limited Dependent Variables
• Shadow Prices, Market Wages, and Labor Supply
• On the Relative Efficiencies of Gradient Methods
• A New Algorithm for Unconstrained Optimization
• Some Statistical Models for Limited Dependent Variables with Application to the Demand for Durable Goods

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