On the bias of the least squares estimator for the first order autoregressive process

DOI10.1007/BF00050668zbMath0694.62040OpenAlexW2065148745MaRDI QIDQ909399

Alain Le Breton, Pham Dinh Tuan

Publication date: 1989

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00050668

zbMATH Keywords

stableasymptotic biasleast squares estimatorunstableexplosiveestimator of the first order autoregressive processexact formula for the bias

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (10)

The finite-sample effects of VAR dimensions on OLS bias, OLS variance, and minimum MSE estimators ⋮ APPROXIMATE DISTRIBUTION OF PARAMETER ESTIMATORS FOR FIRST-ORDER AUTOREGRESSIVE MODELS ⋮ Heteroscedasticity-robust estimation of autocorrelation ⋮ Bartlett corrections in cointegration testing ⋮ From short to long memory: aggregation and estimation ⋮ Asymptotic theory of least squares estimators for nearly unstable processes under strong dependence ⋮ Asymptotic properties of the MLE for the autoregressive process coefficients under stationary Gaussian noise ⋮ Inference About the First-Order Autoregressive Coefficient ⋮ Moments in Pearson's four-step uniform random walk problem and other applications of very well-poised generalized hypergeometric series ⋮ Least Squares Bias in Time Series with Moderate Deviations from a Unit Root

Cites Work

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• On Asymptotic Distributions of Estimates of Parameters of Stochastic Difference Equations
• The Limiting Distribution of the Serial Correlation Coefficient in the Explosive Case
• Consistency and Limit Distributions of Estimators of Parameters in Explosive Stochastic Difference Equations
• Inference in stochastic processes. II
• The Limiting Distribution of the Serial Correlation Coefficient in the Explosive Case II
• Asymptotic expansions for the mean and variance of the serial correlation coefficient
• NOTE ON BIAS IN THE ESTIMATION OF AUTOCORRELATION

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