Consistency and asymptotic unbiasedness of \(S^ 2\) in the serially correlated error components regression model for panel data
From MaRDI portal
Publication:1815629
DOI10.1007/BF02926588zbMath0858.62103MaRDI QIDQ1815629
Publication date: 18 November 1996
Published in: Statistical Papers (Search for Journal in Brave)
weak consistencypanel dataerror component modelordinary least squaresasymptotic unbiasednessOLS-estimatordisturbance varianceserially correlated time effects
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05)
Related Items (5)
Marcinkiewicz–Zygmund type strong law of large numbers for weighted sums of random variables with infinite moment and its applications ⋮ A note on \(S^{2}\) in a spatially correlated error components regression model for panel data ⋮ Strong laws for weighted sums of \(m\)-extended negatively dependent random variables and its applications ⋮ Complete consistency of estimators for regression models based on extended negatively dependent errors ⋮ Testing the null hypothesis of zero serial correlation in short panel time series: a comparison of tail probabilities
Cites Work
- Unnamed Item
- Unnamed Item
- Estimators of the disturbance variance in econometric models. Small- sample bias and the existence of moments
- Consistency, asymptotic unbiasedness and bounds on the bias of \(s^ 2\) in the linear regression model with error component disturbances
- Matrix Analysis
- Bounds for the Bias of the Least Squares Estimator of @s^2 in the Case of a First-Order Autoregressive Process (Positive Autocorrelation)
- Dynamic Aspects of Earning Mobility
- Useful matrix transformations for panel data analysis: a survey
- Bounds on the Variance of Regression Coefficients Due to Heteroscedastic or Autoregressive Errors
This page was built for publication: Consistency and asymptotic unbiasedness of \(S^ 2\) in the serially correlated error components regression model for panel data
