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
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