I am using synth_runner in STATA 17. I got the exact same results when I run two specifications. depvar remains the same. In the second specification, I added one year of outcome variable in the predictorvars and it doesn't make any difference. I suspect that this is because training_proper(real>0) automatically generates predictors from both depvar and predictorvars. From the help file, it is not clear whether depvar is considered as a potential predictor. Is there any other reason that leads to the same results from these two specifications? Is there any way that I can use training_proper(real >0) option, but also use only one year's outcome variable as a predictor (I have multiple treatment units)?

I will use the data and code from synth_runner help file to illustrate the problem.

Code:
clear all
use smoking, clear
tsset state year
capture drop D

program my_pred, rclass
    args tyear
    return local predictors "beer(`=`tyear'-4'(1)`=`tyear'-1') lnincome(`=`tyear'-4'(1)`=`tyear'-1')"
end
program my_drop_units
    args tunit
    if `tunit'==39 qui drop if inlist(state,21,38)
    if `tunit'==3 qui drop if state==21
end
program my_xperiod, rclass
    args tyear
    return local xperiod "`=`tyear'-12'(1)`=`tyear'-1'"
end
program my_mspeperiod, rclass
args tyear
    return local mspeperiod "`=`tyear'-12'(1)`=`tyear'-1'"
end
generate byte D = (state==3 & year>=1989) | (state==7 & year>=1988)


* Specification 1

synth_runner cigsale retprice age15to24, d(D) pred_prog(my_pred) trends training_propr(`=13/18') drop_units_prog(my_drop_units)) xperiod_prog(my_xperiod) mspeperiod_prog(my_mspeperiod)


* Specification 2: add cigsale(1980) as a potential predictor

synth_runner cigsale cigsale(1980) retprice age15to24, d(D) pred_prog(my_pred) trends training_propr(`=13/18') drop_units_prog(my_drop_units)) xperiod_prog(my_xperiod) mspeperiod_prog(my_mspeperiod)
Stata output
Specification 1
Post-treatment results: Effects, p-values, standardized p-values
estimates pvals pvals_std
c1 -0.027493 0.3002191 0.0021914
c2 -0.0485773 0.1775018 0.0043828
c3 -0.0921521 0.0394449 0
c4 -0.1017043 0.0409058 0
c5 -0.1270111 0.0241052 0
c6 -0.1352273 0.0219138 0
c7 -0.141674 0.0262966 0
c8 -0.196867 0.0051132 0
c9 -0.1754307 0.0124178 0
c10 -0.1833944 0.0197224 0
c11 -0.1910038 0.0233747 0
c12 -0.1889059 0.0219138 0
Specification 2
Post-treatment results: Effects, p-values, standardized p-values
estimates pvals pvals_std
c1 -0.027493 0.3002191 0.0021914
c2 -0.0485773 0.1775018 0.0043828
c3 -0.0921521 0.0394449 0
c4 -0.1017043 0.0409058 0
c5 -0.1270111 0.0241052 0
c6 -0.1352273 0.0219138 0
c7 -0.141674 0.0262966 0
c8 -0.196867 0.0051132 0
c9 -0.1754307 0.0124178 0
c10 -0.1833944 0.0197224 0
c11 -0.1910038 0.0233747 0
c12 -0.1889059 0.0219138 0