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Pooled Log Periodogram Regression
Author(s) -
SHIMOTSU KATSUMI,
PHILLIPS PETER C. B.
Publication year - 2002
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/1467-9892.00575
Subject(s) - mathematics , estimator , asymptotic distribution , statistics , periodogram , consistent estimator , consistency (knowledge bases) , delta method , asymptotic analysis , strong consistency , minimum variance unbiased estimator , econometrics , geometry
Estimation of the memory parameter in time series with long range dependence is considered. A pooled log periodogram regression estimator is proposed that utilizes a set of mL periodogram ordinates with L →∞ rather than m ordinates as in the conventional log periodogram estimator. Consistency and asymptotic normality of the pooled regression estimator are established. The pooled estimator is shown to have smaller asymptotic variance, but larger asymptotic bias, than the conventional log periodogram estimator. Finite sample performance is assessed in simulations and the methods are illustrated in an empirical application with inflation and stock returns.