Difference in difference with a single group

[Oscar Weinzettl]

I may be misunderstanding something and need some help

So I am looking at inheritances and want to see what kind of effect receiving one could have on the labour supply of an individual. I want to use a difference in difference approach.

bys id: gen treatment=0 if (expectation==2 & f.gift_received==2) | (l.expectation==2 & gift_received==2) 
bys id: replace treatment=1 if (expectation==2 & f.gift_received==1) | (l.expectation==2 & gift_received==1)

In the data 2 is = 0. So the treated group are those that did not expect an inheritance but received one in time period 2, while the untreated are those that did not expect an inheritance and did not receive one.

mi estimate, esampvaryok: reg job_hours treatment time i.time#i.treatment, robust

Then I can execute the regression and I do get a result.

ultiple-imputation estimates                   Imputations       =          5
Linear regression                               Number of obs     =      1,114
                                                Average RVI       =     0.0278
                                                Largest FMI       =     0.0463
                                                Complete DF       =       1110
DF adjustment:   Small sample                   DF:     min       =     686.75
                                                        avg       =     993.23
                                                        max       =   1,103.02
Model F test:       Equal FMI                   F(   3, 1095.7)   =       4.63
Within VCE type:       Robust                   Prob > F          =     0.0032

--------------------------------------------------------------------------------
     job_hours |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
     treatment |  -3.349237   1.606441    -2.08   0.037    -6.501285   -.1971902
          time |   -1.93333   .9063042    -2.13   0.033    -3.711605   -.1550552
               |
time#treatment |
          0 1  |  -.3600156   2.466202    -0.15   0.884     -5.19907    4.479039
          1 0  |          0  (omitted)
          1 1  |          0  (omitted)
               |
         _cons |   36.44618   .6652147    54.79   0.000     35.14008    37.75228

The result is not that important since I still need to change something with the data anyway, but I did get a result.
So I am wondering, did I do this all correctly? I have one group of individuals in time period 1 and divide them into two depending on if they received or did not receive an inheritance in time period 2. Is this consistent with diff in diff since it usually is done with 2 separate groups of individuals were one received some sort of treatment and the other didn't?

From my stand point it should be doable. I would eliminate the need for a common trend assumption and the difference between these two groups would be the actual difference. Any comments?

[Oscar Weinzettl]

I am an idiot and had a huge blunder in my thought process. This is why when you are tipsy and think you discovered a huge issue with your work, you sleep over it.

Please ignore.