**Category:** Estimation

**Author resource:** Mark (Shuai) Ma

**External link:** https://sites.google.com/site/markshuaima/home

/*April ,2014*/ /*This sas macro code is modified by Mark (Shuai) Ma based on the two-way clustered SE code from Professor John McInnis :*/ /*According to Petersen (2008) and Thompson (2011),*/ /*there are three steps to estimate two-way clustered SEs: */ /*1. estimate firm-clustered VARIANCE-COVARIANCE matrix V firm,*/ /*2. estimate time-clustered VARIANCE-COVARIANCE matrix V time,*/ /*3. estimate heteroskedasticity robust white VARIANCE-COVARIANCE matrix (V white) when there is only one observations each firm-time intersection,*/ /*or, estimate firm-time intersection clustered VARIANCE-COVARIANCE matrix (V firm-time) when there is more than one observations each firm-time intersection,*/ /*This code allows the user to closely follows the formula given by Petersen (2008) and Thompson (2011).*/ /*If you use this code, please add a footnote:*/ /*To obtain unbiased estimates in finite samples,the clustered standard error is adjusted by (N-1)/(N-P)× G/(G-1), */ /*where N is the sample size, P is the number of independent variables, and G is the number of clusters. */ /*For details, please see my note on two-way clustered standard errors avaiable on SSRN and */ /*my websitehttps://sites.google.com/site/markshuaima/home.*/ /*Lastly, I post this code for the communication purpose without */ /*any warranty or guaranty of accuracy or support. */ /*I tried my best to ensure the accuracy of the codes, */ /*but I could not exclude the possibility that there might still be errors. If any error is found, please get me know immediately.*/ /*********************************************************************/ /*input explanations */ /*you only need to change the names of datasets and variables and "multi" value , */ /*in the following command and results will be in dataset "A.results":*/ /*%REG2DSE(y=DV, x=INDV, firm=firmid, time=timeid, multi=0, dataset=A.data, output=A.results);*/ /*1. A.data: A is your library name, data is your input dataset name,*/ /*A.results : A is your library name, results is the name you want for your output dataset ,*/ /*2. DV: the dependent variable, */ /*INDV: the list of your independent variable(s),*/ /*3. firmid: the firm identifier (such as gvkey, permno) ,*/ /*timeid: the time identifier (such as fyear, date),*/ /*4. multi=0 or 1 (you may need to choose whether you use 0 or 1 ) */ /* if you have one observation per firm-time (two dimendions) intersection, you need to have multi=0*/ /* if you have multiple observations per firm-time (two dimendions) intersection, you need to have multi=1*/ /*********************************************************************/ %MACRO reg2DSE(y, x, firm, time, multi, dataset,output); proc surveyreg data=&dataset; cluster &firm; model &Y = &X /covb ; ods output covb=firm; 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 / 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; proc reg data=&dataset; model &y = &x /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;keep parameter estimate;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; 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 &output; merge parm B; tstat=estimate/stderr;run; %MEND reg2DSE;

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