Newey West HAC for pooled cross-section data

Thanks for the reply Achim. The reason I suspect autocorrelation is 
because I think that ?within the same neighborhood, homes sold a few 
months back are likely to impact the price of homes sold subsequently.
This may well be spatial (auto)correlation rather than temporal 
autocorrelation.
In fact the DW test and Breusch-Pagan test come out to be significant. 
So even though the data is not time series (that is, I do not have 
repeated observations for the same house), ? however, the houses sold 
close in time to each other are in the data set.
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").
Thanks,
Shish

On Tue, Mar 26, 2013 at 3:51 PM, Achim Zeileis <Achim.Zeileis at uibk.ac.at>
wrote:
      On Tue, 26 Mar 2013, SHISHIR MATHUR wrote:

            Hello:
            My dataset set contains several thousand rows of
            data, with each row
            containing information for a house. The variables
            include the sale price of
            the house, the quarter and year of sale, the
            attributes of the house, and
            the attributes of the neighborhood and the city in
            which the house is
            located. The data is for a 10-year period. No house
            is repeated in the
            dataset. In summary, the dataset can be termed
            pooled cross-section data.

            My question: Can I estimate Newey-West HAC standard
            errors for a model that
            estimates the effect of various independent
            variables on the sale price of
            the house? ?My understanding is that Newey-West can
            be used for time series
            and panel data. However, I am not sure whether it
            can be used for pooled
            cross-section data. ?If yes, can you refer me to a
            specific source, such as
            a paper or a book?

      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.)

            --
            Best,
            Shish

            ? ? ? ? [[alternative HTML version deleted]]

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--
Best,
Shishir

Newey West HAC for pooled cross-section data

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