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A CENTRAL LIMIT THEOREM FOR MIXING TRIANGULAR ARRAYS OF VARIABLES WHOSE DEPENDENCE IS ALLOWED TO GROW WITH THE SAMPLE SIZE

Published online by Cambridge University Press:  23 September 2005

Christian Francq
Affiliation:
Université Lille III, GREMARS
Jean-Michel Zakoïan
Affiliation:
Université Lille III, GREMARS and CREST

Abstract

Conditions ensuring a central limit theorem for strongly mixing triangular arrays are given. Larger samples can show longer range dependence than shorter samples. The result is obtained by constraining the rate growth of dependence as a function of the sample size, with the usual trade-off of memory and moment conditions. An application to heteroskedasticity and autocorrelation consistent estimators is proposed.

Type
Notes and Problems
Copyright
© 2005 Cambridge University Press

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References

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