Pairwise difference estimators of censored and truncated regression models
DOI10.1016/0304-4076(94)90065-5zbMath0808.62038OpenAlexW2063953281MaRDI QIDQ1341196
Publication date: 16 March 1995
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0304-4076(94)90065-5
asymptotic normalityrank regressiontransformationsemiparametric estimationcovariatescovariance matrix estimationdependent variables\(M\)-estimatorstruncated regression modelminimizers of \(U\)-processespairwise differencingroot-\(n\)-consistencysemiparametric censored regression model
Applications of statistics to economics (62P20) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Statistical tables (62Q05)
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Cites Work
- Unnamed Item
- Asymmetric Least Squares Estimation and Testing
- U-processes: Rates of convergence
- Nonparametric estimation of the slope of a truncated regression
- Least absolute deviations estimation for the censored regression model
- Non-parametric maximum likelihood estimation of censored regression models
- A semi-parametric censored regression estimator
- Censored regression quantiles
- A distribution-free least squares estimator for censored linear regression models
- Functional limit theorems for U-processes
- Regression analysis with randomly right-censored data
- Robust estimation based on grouped-adjusted data in censored regression models
- Symmetrically Trimmed Least Squares Estimation for Tobit Models
- Approximation Theorems of Mathematical Statistics
- Simulation and the Asymptotics of Optimization Estimators
- Linear regression with censored data
- Trimmed Least Squares Estimation in the Linear Model
- Trimmed Lad and Least Squares Estimation of Truncated and Censored Regression Models with Fixed Effects
- Sample Selection Bias as a Specification Error
- Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression
- Estimating Regression Coefficients by Minimizing the Dispersion of the Residuals
- Regression Analysis when the Dependent Variable Is Truncated Normal
- The Limiting Distribution of the Maximum Rank Correlation Estimator
- Estimates of Regression Parameters Based on Rank Tests
- Estimates of Location Based on Rank Tests
- Nonparametric Estimate of Regression Coefficients
- Semiparametric estimation of employment duration models