Hi,
Thanks for the link.
Actually I've already looked at this link before but as I don't understand the code its hard for me to use it...
could you please transform the following regression:
proc panel data=invest.table_regressionfinal ;
id GVKEY DATADATE;
model r_tmw=eps_deflate deltaeps_deflate/fixone ;
run;
into the "fama Macbeth" code (which include Newey-West adjustment for standard errors)
which is presented at the link as:
proc sort data=pe; by variable; run;
%let lags=3;
ods output parameterestimates=nw;
ods listing close;
proc model data=pe;
by variable;
instruments / intonly;
estimate=a;
fit estimate / gmm kernel=(bart,%eval(&lags+1),0) vardef=n; run;
quit;
ods listing;
proc print data=nw; id variable;
var estimate--df; format estimate stderr 7.4;
run;
More over, I havn't found in the web the implication of this method, meaning what is the different in using
"fama Macbeth" method comper to a regular regression?
Thanks,
Lior