Faculty of Economics and Business Administration Publications Database

Semiparametric Inference and Bandwidth Choice under Long Memory: Experimental Evidence

Authors:
Olivares, Maya
Source:
Volume: 6
Number: 1
Pages: 27 - 41
Month: January
Link External Source: Online Version
Year: 2013
Keywords: Fractional Integration; Approximate Normality; Bandwidth Selection
Abstract: The most widely used semiparametric estimators under fractional integration are variants of the local Whittle [LW] estimator. They are consistent for the long memory parameter d and follow a limiting normal distribution. Such properties require the bandwidth m to satisfy certain restrictions for the estimators to be "local" or semiparametric in large samples. Optimal rates for m are known and data-driven selection procedures have been proposed. A Monte Carlo study is conducted to compare the performance of the LW and the so-called exact LW estimators both in terms of experimental size when testing hypotheses about d and in terms of root mean squared error. In particular, the choice of the bandwidth is addressed. Further, competing approximations to limitting normality are compared.
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