Combining fixed effects industry dummies with two way clustered standard errors

Orange123 — Wed, 13 Oct 2021 13:10:17 GMT

Hello community,

Currently I am working on a project with economical penal data. I am trying to replicate a paper in which the author runs a regression with industry dummies and standard errors adjusted by a two-dimensional cluster at the firm and year levels. I think I know how to include the industry dummies (fixed effect) into my code. I am using the following:

proc glm data=&dataset;
class ff12;
model &y = &x ff12 /solution ;
run;
quit;

Online I have found one source for two-way clustered standard errors which can be found here: https://sites.google.com/site/markshuaima/home/two-way-clustered-standard-errors-and-sas-code

And it looks as follows:

%MACRO REG2DSE(y, x, firm, time, multi, dataset, output);

proc surveyreg data=&dataset;
cluster &firm;
model &Y = &X /covb ;
ods output covb=firm;
ods output FitStatistics=fit;
run;quit;

proc surveyreg data=&dataset;
cluster &time;
model &Y = &X /covb ;
ods output covb=time;
run;quit;

%if &multi=1 %then %do;

proc surveyreg data=&dataset;
cluster &time &firm;
model &y = &x /adjrsq covb;
ods output covb=both ;
ods output parameterestimates=parm;
run;quit;

data parm; set parm;keep parameter estimate;run;

%end;

%else %if &multi=0 %then %do;

/* >> my attempt
proc glm data=&dataset;
class ff12;
model &y = &x ff12 /solution ;
ods output acovest=both ;
ods output parameterestimates=parm;
run;
quit;

/*>>original code

proc reg data=&dataset;
model &y = &x / adjrsq vif tol hcc acov covb ;
ods output acovest=both ;
ods output parameterestimates=parm;
run;quit;
*/
data both; set both; parameter=Variable; run;

data both; set both;drop variable Dependent Model;run;

data parm; set parm;parameter=Variable;Estimates=Estimate;keep parameter estimates;run;

%end;

data parm1; set parm;
n=_n_;m=1;keep m n;run;

data parm1;set parm1;
by m;if last.m;keep n;run;

data both; set both;
keep intercept &x;
run;
data firm; set firm;
keep intercept &x;
run;
data time; set time;
keep intercept &x;
run;

data fit1; set fit;
parameter=Label1;
Estimates=nValue1;
if parameter="R-square" then output;
run;

data fit1; set fit1;
n=1;
keep parameter Estimates n;
run;
proc iml;use both;read all var _num_ into Z;print Z;use firm;read all var _num_ into X;print X;
use time;read all var _num_ into Y;print Y;use parm1;
read all var _num_ into n;print n;B=X+Y-Z;C=I(n);D=J(n,1);E=C#B;
F=E*D;G=F##.5;
print B;print G;
create b from G [colname='stderr']; append from G;quit;

data results; merge parm B ;
tstat=estimates/stderr;n=0;run;

data resultsfit; merge results fit1;by n;
run;

data &output; set resultsfit;
drop n;
run;

%MEND REG2DSE;

I have marked my attempt as well as the original code. Could someone please explain to me how I can combine these two issues?

Any help is highly appreciated!

topic Combining fixed effects industry dummies with two way clustered standard errors in Statistical Procedures

Combining fixed effects industry dummies with two way clustered standard errors