Dear all,

I am trying to understand the tfdiff command before applying it to my data. To do so, I simulated some variables as follow:

Code:
clear all
set obs 2000 // set the number of individuals
set seed 101 // set seed to obtain the same results
generate id=_n // generate individual specific ID
generate Treated=1 if _n>=1000 //Treatment=1 for the second half of the sample
replace Treated=0 if Treated==.
expand 11 // create 11 observations (years) for each initial
by id, sort: generate time=_n // year of observation

*create fake y's
*small changes
generate c=rnormal(0,0.001)
* y before treatment
gen y=.
replace y=0.5+c
replace y=0.8+c if time>6 & Treated==1

*tfdiff where the treatment is in year 6
tfdiff y  Treated, model(fe) pvar(id) tvar(time) t(6) datatype(panel) test_pt graph ci(10) vce(r) save_graph(second) save_results(secondresults)
In short, I create 2000 fake individuals, each observed during 11 fake years. half of the group is treated in year 6 and gets a higher y after that (0.8+c).
However, the tfdiff command does not work and I get the following error:

Code:
tfdiff y  Treated, model(fe) pvar(id) tvar(time) t(6) datatype(panel) test_pt graph ci(10) vce(r) save_graph(second) save_results(secondresults)


***********************************************************
Data type: PANEL
***********************************************************


***********************************************************
Model type: Fixed-effect
***********************************************************
       panel variable:  id (strongly balanced)
        time variable:  time, 1 to 11
                delta:  1 unit
note: 1.Treated omitted because of collinearity

Fixed-effects (within) regression               Number of obs     =     22,000
Group variable: id                              Number of groups  =      2,000

R-sq:                                           Obs per group:
     within  = 0.9999                                         min =         11
     between = 1.0000                                         avg =       11.0
     overall = 0.9999                                         max =         11

                                                F(20,1999)        =   1.32e+07
corr(u_i, Xb)  = 0.0167                         Prob > F          =     0.0000

                                 (Std. Err. adjusted for 2,000 clusters in id)
------------------------------------------------------------------------------
             |               Robust
           y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       1._D2 |  -.0000507   .0000451    -1.12   0.262    -.0001392    .0000378
       1._D3 |   .0000433   .0000442     0.98   0.328    -.0000435    .0001301
       1._D4 |   .0000112   .0000438     0.26   0.799    -.0000748    .0000972
       1._D5 |  -.0000242    .000045    -0.54   0.592    -.0001124    .0000641
       1._D6 |   .0000199    .000044     0.45   0.651    -.0000664    .0001062
       1._D7 |    .000021   .0000448     0.47   0.639    -.0000669    .0001089
       1._D8 |   .0000207   .0000443     0.47   0.640    -.0000661    .0001075
       1._D9 |  -8.99e-06   .0000459    -0.20   0.845    -.0000991    .0000811
      1._D10 |   5.46e-06   .0000424     0.13   0.898    -.0000777    .0000886
      1._D11 |  -.0000241   .0000446    -0.54   0.590    -.0001116    .0000635
             |
 Treated#_D2 |
        1 1  |   .0000844   .0000631     1.34   0.181    -.0000393    .0002081
             |
 Treated#_D3 |
        1 1  |   8.52e-06    .000062     0.14   0.891    -.0001131    .0001302
             |
 Treated#_D4 |
        1 1  |  -.0000217   .0000627    -0.35   0.729    -.0001447    .0001013
             |
 Treated#_D5 |
        1 1  |   .0000183   .0000645     0.28   0.776    -.0001081    .0001448
             |
 Treated#_D6 |
        1 1  |  -.0000747   .0000633    -1.18   0.238    -.0001989    .0000495
             |
 Treated#_D7 |
        1 1  |   .2999783   .0000648  4629.74   0.000     .2998512    .3001054
             |
 Treated#_D8 |
        1 1  |   .2999739   .0000623  4817.36   0.000     .2998517     .300096
             |
 Treated#_D9 |
        1 1  |   .3000474    .000064  4690.53   0.000      .299922    .3001729
             |
Treated#_D10 |
        1 1  |   .3000106   .0000618  4856.36   0.000     .2998894    .3001317
             |
Treated#_D11 |
        1 1  |   .3000671   .0000624  4811.29   0.000     .2999448    .3001894
             |
       _cons |   .5000022   .0000212  2.4e+04   0.000     .4999607    .5000437
-------------+----------------------------------------------------------------
     sigma_u |  .00030983
     sigma_e |   .0010023
         rho |  .08721817   (fraction of variance due to u_i)
------------------------------------------------------------------------------


----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
******************************************************************************
**************** TEST FOR 'PARALLEL TREND' ***********************************
******************************************************************************
Null to be tested:
_b[1.w]=_b[1.w#1._D2]= _b[1.w#1._D3]= _b[1.w#1._D4]=0
[1.w] not found
r(111);
Any idea why I get this "[1.w] not found"?

Thanks a lot for your help,
Best,
Pierre