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Newey West HAC for pooled cross-section data

5 messages · SHISHIR MATHUR, Achim Zeileis, shish

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On Tue, 26 Mar 2013, SHISHIR MATHUR wrote:

            
The result of your aggregation is a cross-section data set. Thus, there 
should be no correlation between the different observations - or in other 
terms, the ordering of your observations is completely arbitrary.

Consequently, there may be heteroskedasticity but not autocorrelation. So 
you may use HC standard errors but HAC should not be necessary. (Using HAC 
standard errors will still be consistent but less efficient.)
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On Tue, 26 Mar 2013, SHISHIR MATHUR wrote:

            
This may well be spatial (auto)correlation rather than temporal 
autocorrelation.
If there is a unique ordering of all observations by time, then you could 
in principle apply an autocorrelation correction for the data, e.g., via 
Newey-West.

But from what you describe above, it seems to be more important to capture 
spatial effects in the data, e.g., by using a spatial lag model (see 
lagsarlm in "spdep") or by using an additive spatial effect (see e.g. gam 
in "mgcv").
1 day later