Bias Correction of Semiparametric Long Memory Parameter Estimators via the Pre-filtered Sieve Bootstrap

This paper investigates bootstrap-based bias correction of semiparametric estimators of the long memory parameter, \(d\), in fractionally integrated processes. The re-sampling method involves the application of the sieve bootstrap to data pre-filtered by a preliminary semiparametric estimate of the long memory parameter. Theoretical justification for using the bootstrap technique to bias adjust log periodogram and semiparametric local Whittle estimators of the memory parameter is provided in the case where the true value of \(d\) lies in the range \(0\leq d