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
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