Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79265
Authors: 
Smith, Richard J.
Year of Publication: 
2004
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP17/04
Abstract: 
This paper proposes a new class of HAC covariance matrix estimators. The standard HAC estimation method re-weights estimators of the autocovariances. Here we initially smooth the data observations themselves using kernel function based weights. The resultant HAC covariance matrix estimator is the normalised outer product of the smoothed random vectors and is therefore automatically positive semi-definite. A corresponding efficient GMM criterion may also be defined as a quadratic form in the smoothed moment indicators whose normalised minimand provides a test statistic for the over-identifying moment conditions.
Subjects: 
GMM , HAC Covariance Matrix Estimation , Overidentifying Moments
JEL: 
C13
C30
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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