Parametric and Semi-Parametric Efficient Tests for Parameter Instability

This article examines asymptotically point optimal tests for parameter instability in realistic circumstances when little information about the unstable parameter process and error distribution is available. We first show that, under a correctly specified error distribution, if the unstable parameter processes converge weakly to a Wiener process, then any asymptotic optimal tests for structural breaks and time-varying parameters are asymptotically equivalent. Our finding is then extended to a semi-parametric set-up in which the error distribution is treated as an unknown infinite-dimensional nuisance parameter. We find that semi-parametric tests can be adaptive without further restrictive conditions on the error distribution.