Bias in the ordinary least squares estimator in the dynamic linear regression model with autocorrelated disturbances

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Abstract

We consider the bias in the Ordinary Least Squares estimator in the linear regression model with a lagged dependent variable as regressor. Results are obtained with independent and autocorrelated disturbances. Asymptotic results are obtained analytically, and finite sample results based on a Monte Carlo study. The substantial biases found suggest the need for an alternative estimator to Ordinary Least Squares and powerful tests for autocorrelated disturbances in the dynamic model.

Original languageEnglish
Pages (from-to)791-815
Number of pages25
JournalCommunications in Statistics - Simulation and Computation
Volume16
Issue number3
DOIs
Publication statusPublished - 1 Jan 1987

Keywords

  • asymptotic bias
  • autoregstessive diisturbances
  • finite sample bias
  • lagged dependent variables

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