st: the newey2, number of lags and by function

[yilmag@rpi.edu]

Dear Listers,

I am running the 4-factor model to detect the abnormal returns of two 
portfolios using monthly returns data. My panelvar is the gvkey (firm id) 
and the timevar is from 2007m4 to 2008m3. Here is what I do:

tsset gvkey time

panel variable:  gvkey (strongly balanced)

time variable:  time, 2007m4 to 2008m3

delta:  1 month

//Carhart 4-Factor Model using equally weighted returns for each portfolio

newey2 ewxsret xsewretd smb hml umd if inlist(group,0), lag(3) force 

newey2 ewxsret xsewretd smb hml umd if inlist(group,1), lag(3) force

//Carhart 4-Factor Model using value weighted returns for each portfolio

newey2 vwxsret xsvwretd smb hml umd if inlist(group,0), lag(3) force 

newey2 vwxsret xsvwretd smb hml umd if inlist(group,1), lag(3) force

Basically the newey2 runs the OLS for each firm-month and averages across
time for a given group. Here are my questions:

1)In order to determine the optimal #of lags (I just used 3 but I don't 
have a justification), I try to use the post-estimation "varsoc" command 
but I get "either specify a varlist or the estimates() from either var or 
svar". When I specify the varlist as ewxsret, I get "repeated time values 
in sample" because ewxsret (equally weighted excess returns) is the same 
for all firms in a given portfolio (group) in a given month. How should I 
proceed with this?

2)How can I compare the constant terms from the above regressions? In other 
words, for equal weighted and value weighted settings, I want to see if the 
abnormal returns to two portfolios are statistically different from each 
other. I tried to use the "suest" command but it says that the models are 
estimated with a "nonstandard vce (Newey-West)". I want to stick with 
Newey-West because returns are heteroskedastic and autocorrelated. 

3)Is there a way to run the 4-factor model for both portfolios(groups) in 
one regression using newey2? I tried by/bys but it says that "newey2 may 
not be combined with by"

Thanks everyone in advance for the help.

Gokhan


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