  We prove some efficient inference results concerning estimation of a
Ornstein-Uhlenbeck regression model, which is driven by a non-Gaussian stable
Levy process and where the output process is observed at high-frequency over a
fixed time period. Local asymptotics for the likelihood function is presented,
followed by a way to construct an asymptotically efficient estimator through a
suboptimal yet very simple preliminary estimator.
