The estimation of misspecified long memory models

We consider time series that, possibly after integer differencing or integrating or other detrending, are covariance stationary with spectral density that is regularly varying near zero frequency, and unspecified elsewhere. This semiparametric framework includes series with short, long and negative memory. We consider the consistency of the popular log-periodogram memory estimate that, conventionally but wrongly, assumes the spectral density obeys a pure power law. The local-to zero misspecification leads to increased bias, such that the usual central limit theorem may only hold for bandwidths entailing considerable imprecision. The order of the bias is calculated for several slowly-varying factors, and some discussion of mean squared error and bandwidth choice is included.