Bias correction of OLSE in the regression model with lagged dependent variables.

DOI10.1016/S0167-9473(99)00108-5zbMath1046.62094OpenAlexW2119612645MaRDI QIDQ1583509

Hisashi Tanizaki

Publication date: 26 October 2000

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(99)00108-5

zbMATH Keywords

OLSEexogenous variablesnonnormal errorAR(p) modellagged dependent variablemean-unbiased estimatormedian-unbiased estimator

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Monte Carlo methods (65C05)

Related Items (6)

On least-squares bias in the \(AR(p)\) model: Bias correction using the bootstrap methods ⋮ The finite-sample effects of VAR dimensions on OLS bias, OLS variance, and minimum MSE estimators ⋮ The ability to correct the bias in the stable AD(1,1) model with a feedback effect ⋮ Heteroscedasticity-robust estimation of autocorrelation ⋮ Higher-order asymptotic expansions of the least-squares estimation bias in first-order dynamic regression models ⋮ Bias-adjusted estimation in the ARX(1) model

Cites Work

• The exact moments of OLS in dynamic regression models with non-normal errors
• Edgeworth approximations in first-order stochastic difference equations with exogenous variables
• The exact moments of the least squares estimator for the autoregressive model
• Exact distributions, density functions and moments of the least squares estimator in a first-order autoregressive model
• NOTES ON BIAS IN ESTIMATION
• Asymptotic Expansions Associated with the AR(1) Model with Unknown Mean
• An Approximation to the Distribution of the Least Square Estimator in an Autoregressive Model with Exogenous Variables
• The Bias of Autoregressive Coefficient Estimators
• Asymptotically exact confidence intervals of cusum and cusumsq tests: a numerical derivation using simulation technique
• Exactly Median-Unbiased Estimation of First Order Autoregressive/Unit Root Models
• Computing the distribution of quadratic forms in normal variables
• First Order Autoregression: Inference, Estimation, and Prediction
• Asymptotic expansions for the mean and variance of the serial correlation coefficient
• BIAS IN THE ESTIMATION OF AUTOCORRELATIONS
• NOTE ON BIAS IN THE ESTIMATION OF AUTOCORRELATION

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