Dear friends, I wrote a code that calculates eight lags and eight leads for each macro variable in my list and then uses OLS and WLS to calculate R-squared. But my code is not well written since for each lag and lead I had to copy-paste the same procedure and then manually modify it for the corresponding lag or lead. Is there any way I can create a loop for lags and leads, say, for i = 1:8, create lags, or for j =1:8, create leads and then run the following steps blah-blah-blah.   Also, once I created lags and leads for each macro variable, I have a column lag_1 or lead_1 and row that shows the name of the macrov variable.  But if later on I need to use, say BBB_lag_1 in my OLS regression, I don't know how to identify that specific cell. Does anyone know what the best way to assign names for each variable in column lag_1 that corresponds to the name of the appropriate row (say, BBB) and then attach the name of the appropriate column (say, lag_1). I am sorry for my English. It is probably confusing.   The code is attached.   libname UB 'blah-blah-blah'; %let macro = ub.macro_lgd_f1f8_LZ_YT; %let list = rGDP_grw rGDP_grw_yoy nGDP_grw nGDP_grw_yoy rDPI_grw rDPI_grw_yoy nDPI_grw nDPI_grw_yoy     ata ub.laglead; set &macro; array var_list(*) &list; do i = 1 to dim(var_list); variable = vname(var_list(i)); value = var_list(i); output; end; keep Date AVG_LGD variable value ; run; proc sort data=ub.laglead; by variable date; run; * Create 8 lags and 8 leads of each macro variable in the list; data ub.laglead; set ub.laglead; by variable; lag_1=ifn(first.variable=0,lag(value),.); lag_2=ifn(lag2(variable)=variable, lag2(value),.); lag_3=ifn(lag3(variable)=variable, lag3(value),.); lag_4=ifn(lag4(variable)=variable, lag4(value),.); lag_5=ifn(lag5(variable)=variable, lag5(value),.); lag_6=ifn(lag6(variable)=variable, lag6(value),.); lag_7=ifn(lag7(variable)=variable, lag7(value),.); lag_8=ifn(lag8(variable)=variable, lag8(value),.); if eof1=0 then set ub.laglead (firstobs=2 keep=value rename=(value=lead_1)) end=eof1; if last.variable then lead_1 =.; if eof2=0 then set ub.laglead (firstobs=3 keep=variable value rename=(variable=variable3 value=lead_2)) end=eof2; if variable3^= variable then lead_2 =.; drop variable3; if eof3=0 then set ub.laglead (firstobs=4 keep=variable value rename=(variable=variable4 value=lead_3)) end=eof3; if variable4^= variable then lead_3 =.; drop variable4; if eof4=0 then set ub.laglead (firstobs=5 keep=variable value rename=(variable=variable5 value=lead_4)) end=eof4; if variable5^= variable then lead_4 =.; drop variable5; if eof5=0 then set ub.laglead (firstobs=6 keep=variable value rename=(variable=variable6 value=lead_5)) end=eof5; if variable6^= variable then lead_5 =.; drop variable6; if eof6=0 then set ub.laglead (firstobs=7 keep=variable value rename=(variable=variable7 value=lead_6)) end=eof6; if variable7^= variable then lead_6 =.; drop variable7; if eof7=0 then set ub.laglead (firstobs=8 keep=variable value rename=(variable=variable8 value=lead_7)) end=eof7; if variable8^= variable then lead_7 =.; drop variable8; if eof8=0 then set ub.laglead (firstobs=9 keep=variable value rename=(variable=variable9 value=lead_8)) end=eof8; if variable9^= variable then lead_8 =.; drop variable9; run; *Calculate Rsquared using ordinary OLS; ** Run an OLS regression where the dependent variable is LGD and independent varialbe (one at a time) macroeconomic variable; proc reg data=ub.laglead outest=ub.OLS_est_value tableout; by variable; model AVG_LGD=value/selection=rsquare b; output out=ub.OLS_pred_value residual=OLS_residual_value predicted=OLS_predicted_value; run; *ods graphics off; proc print data=ub.OLS_est_value; run; ****************************EIGHT LAGS *****************************; * Lag 1; *ods graphics on; proc reg data=ub.laglead outest=ub.OLS_est_lag_1 tableout; by variable; model AVG_LGD=lag_1/selection=rsquare b; output out=ub.OLS_pred_lag1 residual=OLS_residual_lag1 predicted=OLS_predicted_lag1; run; *ods graphics off; proc print data=ub.OLS_est_lag_1; run; * Lag 2; proc reg data=ub.laglead outest=ub.OLS_est_lag_2 tableout; by variable; model AVG_LGD=lag_2/selection=rsquare b; output out=ub.OLS_pred_lag2 residual=OLS_residual_lag2 predicted=OLS_predicted_lag2; run; *ods graphics off; proc print data=ub.OLS_est_lag_2; run; * Lag 3; proc reg data=ub.laglead outest=ub.OLS_est_lag_3 tableout; by variable; model AVG_LGD=lag_3/selection=rsquare b; output out=ub.OLS_pred_lag3 residual=OLS_residual_lag3 predicted=OLS_predicted_lag3; run; *ods graphics off; proc print data=ub.OLS_est_lag_3; run; * Lag 4; proc reg data=ub.laglead outest=ub.OLS_est_lag_4 tableout; by variable; model AVG_LGD=lag_4/selection=rsquare b; output out=ub.OLS_pred_lag4 residual=OLS_residual_lag4 predicted=OLS_predicted_lag4; run; *ods graphics off; proc print data=ub.OLS_est_lag_4; run; * Lag 5; proc reg data=ub.laglead outest=ub.OLS_est_lag_5 tableout; by variable; model AVG_LGD=lag_5/selection=rsquare b; output out=ub.OLS_pred_lag5 residual=OLS_residual_lag5 predicted=OLS_predicted_lag5; run; *ods graphics off; proc print data=ub.OLS_est_lag_5; run; * Lag 6; proc reg data=ub.laglead outest=ub.OLS_est_lag_6 tableout; by variable; model AVG_LGD=lag_6/selection=rsquare b; output out=ub.OLS_pred_lag6 residual=OLS_residual_lag6 predicted=OLS_predicted_lag6; run; *ods graphics off; proc print data=ub.OLS_est_lag_6; run; * Lag 7; proc reg data=ub.laglead outest=ub.OLS_est_lag_7 tableout; by variable; model AVG_LGD=lag_7/selection=rsquare b; output out=ub.OLS_pred_lag7 residual=OLS_residual_lag7 predicted=OLS_predicted_lag7; run; *ods graphics off; proc print data=ub.OLS_est_lag_7; run; * Lag 8; proc reg data=ub.laglead outest=ub.OLS_est_lag_8 tableout; by variable; model AVG_LGD=lag_8/selection=rsquare b; output out=ub.OLS_pred_lag8 residual=OLS_residual_lag8 predicted=OLS_predicted_lag8; run; *ods graphics off; proc print data=ub.OLS_est_lag_8; run; ****************************EIGHT LEADS *****************************; * Lead 1; *ods graphics on; proc reg data=ub.laglead outest=ub.OLS_est_lead_1 tableout; by variable; model AVG_LGD=lead_1/selection=rsquare b; output out=ub.OLS_pred_lead1 residual=OLS_residual_lead1 predicted=OLS_predicted_lead1; run; *ods graphics off; proc print data=ub.OLS_est_lead_1; run; * Lead 2; proc reg data=ub.laglead outest=ub.OLS_est_lead_2 tableout; by variable; model AVG_LGD=lead_2/selection=rsquare b; output out=ub.OLS_pred_lead2 residual=OLS_residual_lead2 predicted=OLS_predicted_lead2; run; *ods graphics off; proc print data=ub.OLS_est_lead_2; run; * Lead 3; proc reg data=ub.laglead outest=ub.OLS_est_lead_3 tableout; by variable; model AVG_LGD=lead_3/selection=rsquare b; output out=ub.OLS_pred_lead3 residual=OLS_residual_lead3 predicted=OLS_predicted_lead3; run; *ods graphics off; proc print data=ub.OLS_est_lead_3; run; * Lead 4; proc reg data=ub.laglead outest=ub.OLS_est_lead_4 tableout; by variable; model AVG_LGD=lead_4/selection=rsquare b; output out=ub.OLS_pred_lead4 residual=OLS_residual_lead4 predicted=OLS_predicted_lead4; run; *ods graphics off; proc print data=ub.OLS_est_lead_4; run; * Lead 5; proc reg data=ub.laglead outest=ub.OLS_est_lead_5 tableout; by variable; model AVG_LGD=lead_5/selection=rsquare b; output out=ub.OLS_pred_lead5 residual=OLS_residual_lead5 predicted=OLS_predicted_lead5; run; *ods graphics off; proc print data=ub.OLS_est_lead_5; run; * Lead 6; proc reg data=ub.laglead outest=ub.OLS_est_lead_6 tableout; by variable; model AVG_LGD=lead_6/selection=rsquare b; output out=ub.OLS_pred_lead6 residual=OLS_residual_lead6 predicted=OLS_predicted_lead6; run; *ods graphics off; proc print data=ub.OLS_est_lead_6; run; * Lead 7; proc reg data=ub.laglead outest=ub.OLS_est_lead_7 tableout; by variable; model AVG_LGD=lead_7/selection=rsquare b; output out=ub.OLS_pred_lead7 residual=OLS_residual_lead7 predicted=OLS_predicted_lead7; run; *ods graphics off; proc print data=ub.OLS_est_lead_7; run; * Lead 8; proc reg data=ub.laglead outest=ub.OLS_est_lead_8 tableout; by variable; model AVG_LGD=lead_8/selection=rsquare b; output out=ub.OLS_pred_lead8 residual=OLS_residual_lead8 predicted=OLS_predicted_lead8; run; *ods graphics off; proc print data=ub.OLS_est_lead_8; run; ... 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Dear all,  Thank you for checking my post. I need to estimate Rsquares using weighted least squares using individual regressions: LGD = alpha + beta * v(1) + epsilon  ...   LGD = alpha + beta * v(2000) + epsilon   I wrote the code but am not sure that the code does what I want. How can I extract one variable from &list (I have 2000 variables) and run WLS? Could you please help me if anyone knows how to do it.  Thank you in advance.    %let macro = ub.test; %let list = GDP FE ; proc reg data=ub.test outest=ub.est tableout; model LGD=&list/selection=rsquare b; run;       ** run the original regression to get the residuals**; proc reg data=ub.test; model LGD=&list; output out=ub.pred residual=residual; run;   ** compute the absolute and squared residuals**; data ub.resid; set ub.pred; absresid=abs(residual); sqresid=residual**2; proc reg data=ub.resid;   **run a regression with the absolute residuals vs. X to get the estimated standard deviation **; model absresid=&list; output out=ub.s_weights predicted=s_hat;   **run a regression with the squared residuals vs. X to get the estimated standard deviation **; model sqresid=&list; output out=ub.v_weights predicted=v_hat; run;   ** compute the weights using the estiamted standard deviations**; data ub.s_weights; set ub.s_weights; s_weight=1/(s_hat**2); label s_weight = "weights using absolute residuals"; data ub.v_weights; set ub.v_weights; v_weight=1/v_hat; label v_weight = "weights using squared residuals";   ** do the weighted least squares using the weights from the estiamted standard deviations **; proc reg data=ub.v_weights; weight v_weight; model LGD=&list; run;   ... View more

Dear all, I am new to SAS. I would appreciate it if anyone helps me. I have to write a code that calculates a cross correlation between one fixed variable and 2000 other macro variables and put it all in a table. To do it manually will take a lot of time. How can I create an array of macro variables and then use proc corr command in the loop? Thank you in advance.  Yelena   ... View more