hi,

As part of my coursework i am analysing the effect of introduction of minimum wage on employment. before 2018 there was no minimum wage in the country and i have traced a number of household before and after the introduction of minimum wage . i am using a DID in stata to see whether with the introduction of minimum wage, they are employed or not employed but is not sure if the results and interpretation are correct.I have been reading and analysing many articles such as Card and Kruguer, villa etc

The equation i want to estimate is:
Employmentit = a + bMinWageit + cageit + d maritalstatusit + e educationit +et

I have run the following in command stata:
gen treat = 1 if income<8500
recode treat (.=0)

lab def treat_lab 0 "comparison" 1 "treatment"

. lab val treat treat_lab

. tabstat work, by( treat) stat(n mean min max sd)

treat | N mean min max sd
-----------+--------------------------------------------------
comparison | 167 1.473054 1 2 .500775
treatment | 77 1.467532 1 2 .5022165
-----------+--------------------------------------------------
Total | 244 1.471311 1 2 .5002023
--------------------------------------------------------------

. gen post = 1 if year>=2018
(61 missing values generated)

. recode post (.=0)
(post: 61 changes made)

. lab def post_lab 0 "pre" 1 "post"

. lab val post post_lab

. tabstat work , by(post) stat(n mean min max sd)

Summary for variables: work
by categories of: post

post | N mean min max sd
-------+--------------------------------------------------
pre | 61 1.393443 1 2 .4925677
post | 183 1.497268 1 2 .5013643
-------+--------------------------------------------------
Total | 244 1.471311 1 2 .5002023
----------------------------------------------------------

then i run a regression
reg work age sex qualific i.treat i.post i.treat#i.post

Source | SS df MS Number of obs = 41
-------------+------------------------------ F( 6, 34) = 4.19
Model | 4.14981202 6 .691635336 Prob > F = 0.0029
Residual | 5.60628554 34 .164890751 R-squared = 0.4254
-------------+------------------------------ Adj R-squared = 0.3239
Total | 9.75609756 40 .243902439 Root MSE = .40607

---------------------------------------------------------------------------------
work | Coef. Std. Err. t P>|t| [95% Conf. Interval]
----------------+----------------------------------------------------------------
age | -.0179714 .0050063 -3.59 0.001 -.0281455 -.0077973
sex | .1073487 .1305785 0.82 0.417 -.1580187 .3727162
qualific | .0000296 .0000296 1.00 0.324 -.0000305 .0000898
|
treat |
treatment | -.4479628 .4511149 -0.99 0.328 -1.364739 .4688129
|
post |
post | .2922316 .174639 1.67 0.103 -.0626777 .6471408
|
treat#post |
treatment#post | .7163889 .4794443 1.49 0.144 -.2579592 1.690737
|
_cons | 1.539442 .3754059 4.10 0.000 .7765256 2.302359
---------------------------------------------------------------------------------


I would be very much appreciated if you could kindly help or advise.

Thanks a lot.