On the asymptotic bias of OLS in dynamic regression models with autocorrelated errors

DOI10.1007/s00362-006-0317-8zbMath1132.62348OpenAlexW2008150437MaRDI QIDQ849893

Toni Stocker

Publication date: 15 November 2006

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-006-0317-8

Mathematics Subject Classification ID

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

Related Items (5)

Further results on the \(h\)-test of Durbin for stable autoregressive processes ⋮ Testing for residual correlation of any order in the autoregressive process ⋮ A Durbin–Watson serial correlation test for ARX processes via excited adaptive tracking ⋮ On the asymptotic behavior of the Durbin-Watson statistic for ARX processes in adaptive tracking ⋮ Model-free tests for series correlation in multivariate linear regression

Cites Work

• New evidence on the small properties of estimators of SUR models with autocorrelated disturbances
• An efficient two-step estimator for the dynamic adjustment model with autoregressive errors
• Effects of autocorrelated errors on various least squares estimators a monte carlo study
• Tests for Serial Correlation in Regression Models with Lagged Dependent Variables and Serially Correlated Errors
• Time Series and Dynamic Models
• A Note on Serial Correlation Bias in Estimates of Distributed Lags
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