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.
|Number of pages||25|
|Journal||Communications in Statistics - Simulation and Computation|
|Publication status||Published - 1 Jan 1987|
- asymptotic bias
- autoregstessive diisturbances
- finite sample bias
- lagged dependent variables