Improved HAC Covariance Matrix Estimation Based on Forecast Errors

We propose computing HAC covariance matrix estimators based on one-stepahead forecasting errors. It is shown that this estimator is consistent and has smaller bias than other HAC estimators. Moreover, the tests that rely on this estimator have more accurate sizes without sacrificing its power.

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Year of publication:	2006-09
Authors:	Kuan, Chung-Ming ; Hsieh, Yu-Wei
Institutions:	Institute of Economics, Academia Sinica
Subject:	forecast error \| HAC estimator \| kernel estimator \| recursive residual \| robust test

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Extent:	application/pdf
Series:	IEAS Working Paper : academic research.
Type of publication:	Book / Working Paper
Notes:	Number 06-A008 8 pages
Classification:	C12 - Hypothesis Testing ; C22 - Time-Series Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10008632888