Least squares estimation for critical random coefficient first-order autoregressive processes

Critical random coefficient AR(1) processes are investigated where the random coefficient is binary, taking values -1 and 1. Asymptotic behavior of least squares estimator for the mean of the random coefficient is discussed. Ordinary least squares estimator is shown to be consistent. Weighted least squares estimator turns out to be asymptotically normally distributed. This enables us to present a unified limit result for the weighted least squares estimator valid for the stationary, explosive and critical cases. Also, a test of criticality is discussed.