Dear all, I have a data set as follow,   ID year lag4_var lag5_var lag6_var lag7_var treat 1 2000 3 2 6 3 0 1 2001 6 7 8 9 0 1 2002 6 5 7 8 0 1 2003 6 7 11 8 1 1 2004 12 11 10 9 1 2 2015 6 7 8 9 0 2 2016 3 2 6 3 0 2 2017 13 1 5 6 1 2 2018 7 6 8 12 1 2 2019 5 22 5 6 1     in this data set, lag4_var = lag4(var) where var is some measurement of firm size for each ID/quarter. Similarly, lag5_var is the value of the 5 th previous quarterly ‘var’ and lag6_var is the value of the 6 th previous quarterly ‘var’, and so on. Treat is a dummy variable equals 1 if any of lag#_var greater than or equals 10, or equals to 0 if all the lag lag#_var less than 10.   I want to create an new variable, K. For observations with treat=1, K equals the earliest lag#_var that is greater than or equals 10. For observations with treat=0. K equals the latest (most current) lag#_var.   For example, for observation with ID=1 and year=2000, treat=0, and in this case K should be lag4_var as lag4_var is the most recent number for lag#_var. For observation with ID=1 and year=2004, treat=1, and in this case K should be lag6_var as lag6_var is the first and earliest lag#_var that is greater than 10.   So as a result, I want to have the following data set. ID year lag4_var lag5_var lag6_var lag7_var treat K 1 2000 3 2 6 3 0 3 1 2001 6 7 8 9 0 6 1 2002 6 5 7 8 0 6 1 2003 6 7 11 8 1 11 1 2004 12 11 10 9 1 10 2 2015 6 7 8 9 0 6 2 2016 3 2 6 3 0 3 2 2017 13 1 5 6 1 13 2 2018 7 6 8 12 1 12 2 2019 5 22 5 6 1 22   Thanks in advance for your help! ... View more

Dear all, I'm working on Fama Macbeth regression with rolling beta. My regression starts from 1970/1/1 to 2013/12/31. Each month, I run a cross sectional regression of individual stock returns on their individual betas. Betas on each regression are estimated using previous 36 month (3 years) data. For example, on 1970/1 regression, betas for each stock are estimated using data range from 1967/1/1 to 1970/1/1. on 1970/2 regression, betas for each stock are estimated using data range from 1967/2/1 to 1970/2/1, and so on. I use macro to this job. Following some text book suggestion, here is my Macro: %macro estim; %do x=36 % to 686;     data temp;       set gooddata;   if &x -35 <= n<= &x;   per=&x;     proc reg data=temp noprint outest=results;   model TRT1M=rm;  /*TRT1M is the stock return and rm is the market reutrn*/   by gvkey per;   quit;   proc append base=betas1 data=results; %end; %mend estim; where 686 is the maximum number of monthly observation I have in my sample.  However, not every stock have 686 month-observations, ranging form 40 to 686. My question is, if I fix my %do up to 686, SAS will only return returns for those stock with 686 observations and delete all other stocks, which is not what I want. I would like to have every stocks, no matter how many observations I have in the sample, to be reported in 'results'. How should modify this macro to achieve that. Thank you! Logan ... View more