Code:
 * Example generated by -dataex-. For more info, type help dataex clear input float(id monthly independent sales TreatZero lead2 lead3 lead4 lead5 lead6 lead7_backwards lag1 lag2 lag3 lag4 lag5 lag6 lead1) 1 672 0  249512 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 673 0  177712 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 674 0  109524 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 675 0   20776 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 676 0  846471 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 677 0  328806 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 678 0   46470 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 679 0  394758 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 680 0  301179 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 681 0  756129 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 682 0  116117 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 683 0  374293 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 684 0  432423 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 685 0  364780 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 686 0  797174 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 687 0  400569 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 688 0  126897 0 0 0 0 0 0 0 0 1 0 0 0 0 0 2 672 1   65104 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 673 1   77133 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 674 1   76200 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 675 1  218342 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 676 1   39265 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 677 1    6649 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 678 1   41677 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 679 1  156277 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 680 1   98535 0 0 0 0 0 1 0 0 0 0 0 0 0 0 2 681 1    3920 0 0 0 0 1 0 0 0 0 0 0 0 0 0 2 682 1  165573 0 0 0 1 0 0 0 0 0 0 0 0 0 0 2 683 1   73413 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 684 1   97216 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 685 1  106015 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 686 1   33066 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 687 1   54207 0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 688 1  118173 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 672 0  737203 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 673 0  306725 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 674 0  198990 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 675 0 1054751 0 0 0 0 0 0 1 0 0 0 0 0 0 0 3 676 0 1886147 0 0 0 0 0 1 0 0 0 0 0 0 0 0 3 677 0 1142545 0 0 0 0 1 0 0 0 0 0 0 0 0 0 3 678 0 1277825 0 0 0 1 0 0 0 0 0 0 0 0 0 0 3 679 0  397706 0 0 1 0 0 0 0 0 0 0 0 0 0 0 3 680 0 1354199 0 1 0 0 0 0 0 0 0 0 0 0 0 0 3 681 0 1348788 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 682 0  914274 1 0 0 0 0 0 0 0 0 0 0 0 0 0 3 683 0  805134 0 0 0 0 0 0 0 1 0 0 0 0 0 0 3 684 0  769588 0 0 0 0 0 0 0 0 1 0 0 0 0 0 3 685 0  292174 0 0 0 0 0 0 0 0 0 1 0 0 0 0 3 686 0 1236297 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 687 0   58338 0 0 0 0 0 0 0 0 0 0 0 1 0 0 3 688 0 1681455 0 0 0 0 0 0 0 0 0 0 0 0 1 0 4 672 1   82611 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 673 1  190401 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 674 1  122867 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 675 1  111444 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 676 1   44781 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 677 1  158895 0 0 0 0 1 0 0 0 0 0 0 0 0 0 4 678 1   71693 0 0 0 1 0 0 0 0 0 0 0 0 0 0 4 679 1   62140 0 0 1 0 0 0 0 0 0 0 0 0 0 0 4 680 1  321720 0 1 0 0 0 0 0 0 0 0 0 0 0 0 4 681 1  188944 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 682 1  179921 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 683 1  159214 0 0 0 0 0 0 0 1 0 0 0 0 0 0 4 684 1  118173 0 0 0 0 0 0 0 0 1 0 0 0 0 0 4 685 1  246030 0 0 0 0 0 0 0 0 0 1 0 0 0 0 4 686 1   83191 0 0 0 0 0 0 0 0 0 0 1 0 0 0 4 687 1  100867 0 0 0 0 0 0 0 0 0 0 0 1 0 0 4 688 1   42409 0 0 0 0 0 0 0 0 0 0 0 0 1 0 5 672 0   32247 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 673 0    9993 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 674 0   44384 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 675 0   28284 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 676 0    6873 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 677 0   35780 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 678 0     226 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 679 0   41062 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 680 0   34161 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 681 0    5773 0 0 0 0 0 1 0 0 0 0 0 0 0 0 5 682 0   12586 0 0 0 0 1 0 0 0 0 0 0 0 0 0 5 683 0   22660 0 0 0 1 0 0 0 0 0 0 0 0 0 0 5 684 0   40637 0 0 1 0 0 0 0 0 0 0 0 0 0 0 5 685 0   40881 0 1 0 0 0 0 0 0 0 0 0 0 0 0 5 686 0    3560 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 687 0    9365 1 0 0 0 0 0 0 0 0 0 0 0 0 0 5 688 0     852 0 0 0 0 0 0 0 1 0 0 0 0 0 0 6 672 0   94715 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 673 0    2692 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 674 0  123457 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 675 0  724462 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 676 0  871857 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 677 0   16821 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 678 0  499244 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 679 0  441009 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 680 0  429921 0 0 0 0 0 0 1 0 0 0 0 0 0 0 6 681 0  156341 0 0 0 0 0 1 0 0 0 0 0 0 0 0 6 682 0  461273 0 0 0 0 1 0 0 0 0 0 0 0 0 0 6 683 0  325237 0 0 0 1 0 0 0 0 0 0 0 0 0 0 6 684 0  302210 0 0 1 0 0 0 0 0 0 0 0 0 0 0 6 685 0  332281 0 1 0 0 0 0 0 0 0 0 0 0 0 0 6 686 0  298871 0 0 0 0 0 0 0 0 0 0 0 0 0 0 end format %tm monthly
I have a staggered diff in diff setting. In the dataset, lead values correspond to the indicator variables for pre-treatment values, whereas lag values correspond to the indicator variables for post-treatment values. The dependent variable is sales. This is my code
Code:
xtset id monthly  xtreg sales lead7_backwards lead6 lead5 lead4 lead3 lead2 lead1 TreatZero lag1 lag2 lag3 lag4 lag5 lag6 i.monthly, fe vce(cluster id)  coefplot, vertical omitted keep(lead6 lead5 lead4 lead3 lead2 lead1 TreatZero lag1 lag2 lag3 lag4 lag5 lag6) ciopts(recast(rcap)) yline(0) msymbol(d)
My question is, do I need to include lead7_backwards in the regression? Or instead, I need to run:

Code:
xtreg sales lead6 lead5 lead4 lead3 lead2 lead1 TreatZero lag1 lag2 lag3 lag4 lag5 lag6 i.monthly, fe vce(cluster id)