Difference in Difference modeling. How to separate the treated group from the control group in the dataset

[Agbenyo Wonder]

Hello, can anyone please help me on the command to differentiate my control group from treated groups. I am working on crop insurance on cocoa farmers income in Ghana and I have a total of 600 samples. The programme was rolled in some parts of the Ashanti region in Ghana. Out of the 6 districts, I gather data from, it was revealed that only two of the districts were treated and the rest four were not treated. Attached is a sample of my data please
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* Example generated by -dataex-. To install: ssc install dataex
clear
input byte(ACF MS Gen Edu Hsz Fexp AgeF) int MAI byte Plns
46 2 1 3 8 10  4 1500 0
50 2 1 1 4 17  5 1650 0
35 1 1 3 6  6  3 1000 0
46 4 1 3 4 11  3 1900 0
50 2 1 1 6 19  3 1850 0
39 2 1 2 3  8  5  890 0
45 2 1 1 4 15  6 1760 0
37 2 1 1 3  9  5  790 0
48 2 2 1 3 13  3    . 0
53 2 1 1 7 20  5 1800 0
35 2 1 1 4 11  6  480 0
43 2 1 1 4  9  5 1570 0
43 2 2 1 3 10  3 2690 0
58 2 1 2 8 23  5  890 0
45 2 2 1 5 10  5    . 0
40 2 1 2 4  5  4 1350 0
50 5 2 2 6 20 10  950 0
36 2 1 1 2  6  7 1580 0
40 2 1 1 3  7  4    . 0
53 2 2 1 5 30  3 1500 0
50 2 1 1 8 17  5  580 0
50 2 2 2 7 13  6  700 0
35 2 1 2 2  6  2  970 0
47 2 2 2 4  5  5 1000 0
49 2 1 2 4 12  3 1800 0
55 2 1 1 8 21 12  800 0
39 2 1 2 2  4  6 2040 0
50 2 2 1 6 18 15  750 0
36 2 1 3 2  5 10  640 0
55 2 1 1 7 23  2 1830 0
50 2 1 3 6 13  8 1830 0
58 2 2 2 7 30  5 1900 0
35 2 2 2 3  6  4 2100 0
54 5 1 2 7 16  6    . 0
37 1 1 1 4  5  4 2010 0
41 2 1 2 2 12  8 1000 0
52 2 1 1 8 12  5 1070 0
54 2 2 1 6 30  7    . 0
55 2 1 1 7 24  5 1200 0
35 1 1 1 2 10  3  500 0
57 4 1 2 7 23  6 1750 0
48 2 1 2 8 14  4 2940 0
39 2 1 2 3 13  3 2400 0
56 2 2 1 6 19 12    . 0
55 2 1 1 7 19  9 2800 0
47 2 2 2 3 15 14 1790 0
51 5 1 1 4 23  5 2800 0
53 2 1 1 6 12  5 1700 0
48 2 1 2 5 11  3 1800 0
40 2 2 2 4  9  2 1300 0
54 2 1 2 6 11  4 1750 0
47 2 1 1 5 14  3 1400 0
49 2 2 1 6  5  5  700 0
54 2 1 1 9 20  6  800 0
50 2 2 1 6 25  4  300 0
49 2 1 1 5 18  6  700 0
55 2 1 2 7 20  7 1000 0
56 2 2 2 6 18  5 2100 0
35 2 1 1 4 12  4  500 0
48 2 1 2 6  8  6 5000 0
31 2 1 2 4  8  5 1950 0
46 2 1 2 3 20  7 2080 0
50 2 1 2 5 23  7 1600 0
56 2 1 3 7 16  5  690 0
43 2 1 2 3 13  3  900 0
44 2 2 1 4 12  4  900 0
53 5 2 2 5 20  4  850 0
45 2 2 2 4 12  6 1800 0
53 2 1 2 7 24  4 1500 0
52 4 2 2 6 20  6    . 0
50 2 2 3 5 32  4 1050 0
30 1 1 2 4 21  6 1200 0
35 2 2 2 3  4  5 1750 0
39 2 1 4 3  5  6    . 0
31 2 1 1 3  7  7 1500 0
38 2 1 2 5  4  4 2650 0
50 2 1 4 7 20  5    . 0
42 2 1 2 4 12  9 1450 0
49 5 2 2 4  5 10 1470 0
48 2 1 4 3 10  4 1740 0
50 2 1 3 6 20  6    . 0
37 2 2 4 4  4  5  400 0
52 4 1 2 8 19  4  680 0
46 2 2 1 4 20  6 2350 0
40 2 1 3 4 12  6 1450 0
31 1 2 4 2  8  9 1290 0
40 2 1 3 3  3  8 1800 0
43 2 2 1 4  5  6 4000 0
35 2 1 4 3  6  4 1600 0
51 2 2 1 5 16  8 1480 0
46 2 2 2 3 21  9 1370 0
40 2 1 2 2  8 10 1460 0
58 5 1 2 6 16  5 1590 0
43 4 1 1 3  9  7 1640 0
45 2 1 1 4  7 10 1000 0
37 2 2 2 2  4  5 1850 0
48 2 2 2 5 10  4 1500 0
36 2 2 2 2  4  3 1490 0
40 4 1 1 3  5  5 1350 0
30 1 1 3 3  9 10 4000 0
end

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This is my first time trying statalist so kindly pardon me if i did not do something right. Thanks and looking forward to your wonderful suggestions.

[Bri hakim]

Hi agbenyo could you please tell the variable you used for treatment

[Agbenyo Wonder]

Hello, Bri thanks for the reply. I was able to get the following commands yesterday.

gen did=treated*time

diff Income, t(treated) p(time)

Currently, my problem is I do not know why my control and treated variables do not have standard errors and t-statistics. check the result below, please

DIFFERENCE-IN-DIFFERENCES ESTIMATION RESULTS
Number of observations in the DIFF-IN-DIFF: 518
Before After
Control: 223 122 345
Treated: 100 73 173
323 195

Outcome var. MAI S. Err. t P>t

Before
Control 1563.857
Treated 1749.200
Diff (T-C) 185.343 89.814 2.06 0.040**
After
Control 1423.770
Treated 1488.904
Diff (T-C) 65.134 110.426 0.59 0.556

Diff-in-Diff -120.210 142.339 0.84 0.399

R-square: 0.02
* Means and Standard Errors are estimated by linear regression
**Inference: *** p<0.01; ** p<0.05; * p<0.1

[Bri hakim]

Hi agbenyo did you run that after installing "diff"?

I am assuming that you are looking at diff in means since you are comparing wages (continuous outcome) If you are looking at the DID in means have you tried "reg" in your command instead of diff, it should look as follows

reg outcome time treated did, r

where did is your interaction term

[Agbenyo Wonder]

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* Example generated by -dataex-. To install: ssc install dataex
clear
input int id byte t long treated float fte byte(bk kfc roys wendys) float _diff
 1 0 1    31 1 0 0 0 0
 1 1 1    40 1 0 0 0 1
 2 0 1    13 1 0 0 0 0
 2 1 1  12.5 1 0 0 0 1
 3 0 1  12.5 0 1 0 0 0
 3 1 1   7.5 0 1 0 0 1
 4 0 1    16 0 0 1 0 0
 4 1 1    20 0 0 1 0 1
 5 0 1    20 0 0 1 0 0
 5 1 1    25 0 0 1 0 1
 6 0 1     3 0 0 1 0 0
 6 1 1     6 0 0 1 0 1
 8 0 1     . 0 0 0 1 0
 8 1 1  27.5 0 0 0 1 1
 9 0 1    32 1 0 0 0 0
 9 1 1    16 1 0 0 0 1
10 0 1    25 1 0 0 0 0
10 1 1  22.5 1 0 0 0 1
11 0 1    25 1 0 0 0 0
11 1 1    24 1 0 0 0 1
12 0 1 18.25 1 0 0 0 0
12 1 1  22.5 1 0 0 0 1
13 0 1  12.5 0 1 0 0 0
13 1 1   7.5 0 1 0 0 1
14 0 1    14 0 1 0 0 0
14 1 1  12.5 0 1 0 0 1
15 0 1  15.5 0 0 1 0 0
15 1 1    15 0 0 1 0 1
16 0 1    17 0 0 1 0 0
16 1 1  15.5 0 0 1 0 1
17 0 1    10 0 0 1 0 0
17 1 1  21.5 0 0 1 0 1
18 0 1  27.5 0 0 1 0 0
18 1 1    27 0 0 1 0 1
19 0 1  19.5 1 0 0 0 0
19 1 1    28 1 0 0 0 1
21 0 1    11 0 1 0 0 0
21 1 1   5.5 0 1 0 0 1
22 0 1  10.5 0 0 1 0 0
22 1 1  10.5 0 0 1 0 1
23 0 1  12.5 1 0 0 0 0
23 1 1    21 1 0 0 0 1
24 0 1  22.5 1 0 0 0 0
24 1 1    25 1 0 0 0 1
26 0 1  37.5 1 0 0 0 0
26 1 1    20 1 0 0 0 1
27 0 1     9 0 1 0 0 0
27 1 1   3.5 0 1 0 0 1
28 0 1     7 0 1 0 0 0
28 1 1     7 0 1 0 0 1
29 0 1   3.5 0 1 0 0 0
29 1 1   6.5 0 1 0 0 1
30 0 1     8 0 1 0 0 0
30 1 1   5.5 0 1 0 0 1
31 0 1    12 0 1 0 0 0
31 1 1  13.5 0 1 0 0 1
32 0 1 20.25 0 0 1 0 0
32 1 1  14.5 0 0 1 0 1
33 0 1    22 0 0 1 0 0
33 1 1  11.5 0 0 1 0 1
34 0 1  12.5 0 0 1 0 0
34 1 1  14.5 0 0 1 0 1
35 0 1 28.25 0 0 0 1 0
35 1 1    22 0 0 0 1 1
36 0 1    14 0 0 0 1 0
36 1 1  27.5 0 0 0 1 1
37 0 0  25.5 1 0 0 0 0
37 1 0  18.5 1 0 0 0 0
38 0 1    25 1 0 0 0 0
38 1 1    20 1 0 0 0 1
39 0 0    17 1 0 0 0 0
39 1 0  12.5 1 0 0 0 0
40 0 0    20 1 0 0 0 0
40 1 0  19.5 1 0 0 0 0
41 0 0  13.5 1 0 0 0 0
41 1 0    21 1 0 0 0 0
42 0 0    19 1 0 0 0 0
42 1 0    11 1 0 0 0 0
45 0 0    12 1 0 0 0 0
45 1 0    17 1 0 0 0 0
46 0 0  37.5 1 0 0 0 0
46 1 0    21 1 0 0 0 0
47 0 0  32.5 1 0 0 0 0
47 1 0  22.5 1 0 0 0 0
48 0 0    16 1 0 0 0 0
48 1 0    20 1 0 0 0 0
49 0 0  9.75 0 1 0 0 0
49 1 0   7.5 0 1 0 0 0
50 0 0    11 0 1 0 0 0
50 1 0    14 0 1 0 0 0
51 0 0   7.5 0 1 0 0 0
51 1 0  13.5 0 1 0 0 0
56 0 0    30 0 0 0 1 0
56 1 0    18 0 0 0 1 0
57 0 0    35 0 0 0 1 0
57 1 0    16 0 0 0 1 0
58 0 0  20.5 0 0 0 1 0
58 1 0    14 0 0 0 1 0
59 0 0   7.5 0 0 0 1 0
59 1 0     8 0 0 0 1 0
end
label values treated treated
label def treated 0 "PA", modify
label def treated 1 "NJ", modify

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Hello, please can anyone help me with this problem? The data above is from http://fmwww.bc.edu/repec/bocode/c/CardKrueger1994.dta
(Dataset from Card&Krueger (1994))
When following their estimation in relation to DID with no covariates with the command diff fte, t(treated) p(t) their output reported the standard error of both control and treated group in the baseline(before) same as in the follow up(After) but using the same data and command in Stata 15 my output only report that of the standard errors of the differences without the standard errors of the control and treated groups.
I want to find out if there is something I am not doing right and I need your help. thanks

DIFFERENCE-IN-DIFFERENCES ESTIMATION RESULTS
Number of observations in the DIFF-IN-DIFF: 801
Before After
Control: 78 77 155
Treated: 326 320 646
404 397
--------------------------------------------------------
Outcome var. | fte | S. Err. | |t| | P>|t|
----------------+---------+---------+---------+---------
Before | | | |
Control | 19.949 | | |
Treated | 17.065 | | |
Diff (T-C) | -2.884 | 1.135 | -2.54 | 0.011**
After | | | |
Control | 17.542 | | |
Treated | 17.573 | | |
Diff (T-C) | 0.030 | 1.143 | 0.03 | 0.979
| | | |
Diff-in-Diff | 2.914 | 1.611 | 1.81 | 0.071*
--------------------------------------------------------
R-square: 0.01
* Means and Standard Errors are estimated by linear regression
**Inference: *** p<0.01; ** p<0.05; * p<0.1