Orthogonality conditions for Tobit models with fixed effects and lagged dependent variables
From MaRDI portal
Publication:689429
DOI10.1016/0304-4076(93)90038-7zbMath0778.62105OpenAlexW2086553387MaRDI QIDQ689429
Publication date: 2 December 1993
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0304-4076(93)90038-7
fixed effectspanel data modelsmaximum likelihood estimatorTobit modelorthogonality conditionscensored regression modelslagged dependent variablesmethod of moments estimators
Related Items
Root-\(N\) consistent semiparametric estimators of a dynamic panel-sample-selection model ⋮ Identification of panel data models with endogenous censoring ⋮ Transformations and moment conditions for dynamic fixed effects logit models ⋮ Estimation of cross sectional and panel data censored regression models with endogeneity ⋮ Identification and estimation of nonlinear dynamic panel data models with unobserved covariates ⋮ Rank estimation of a generalized fixed-effects regression model ⋮ A two-stage approach to semilinear in-slide models ⋮ Testing identifying assumptions in nonseparable panel data models ⋮ Bayesian analysis of quantile regression for censored dynamic panel data ⋮ Bias corrections for two-step fixed effects panel data estimators ⋮ Leapfrog estimation of a fixed-effects model with unknown transformation of the dependent variable ⋮ A double-hurdle rational addiction model with heterogeneity: Estimating the demand for tobacco ⋮ Two-step estimation of panel data models with censored endogenous variables and selection bias ⋮ Estimation of tobit-type models with individual specific effects
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Large Sample Properties of Generalized Method of Moments Estimators
- Estimating Vector Autoregressions with Panel Data
- Formulation and estimation of dynamic models using panel data
- Pairwise difference estimators of censored and truncated regression models
- Symmetrically Trimmed Least Squares Estimation for Tobit Models
- Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data
- Trimmed Lad and Least Squares Estimation of Truncated and Censored Regression Models with Fixed Effects