Hello ,
I have a problem that I have been thinking about for a week now and I do not understand what's missing.
Let me explain.
I perform a DID analysis with two treatment times.
12-week analysis. The first 4 weeks are the pre-treatment weeks. Then comes my first measure that lasts 4 weeks. Then a second measur coupled with the last one for another 4 weeks.
Firstly, I did:
reg Conso timeB treatedC did2B did2C i.companies, r
With, timeB: > 4 weeks <8 weeks. timeC: > 8 weeks. treated2: the companies that are affected by the measure. did2B: timeB * treated2. did3C: timeC * treated2.
So far it goes ... I test the effect of my first measure, as well as the effect of the complementarity of the two measures.
The problem is when I try to go further in my analysis.
The first step that I testing is information that transmits to the companies (very positive, positive, negative, very negative) and I would like to know which particular messages that impact my group
I tried everything but I have collinearity into variables. What makes me think that either I forgot a variable, either I have a variable too ... I tried all the configurations it does not work.
Can you help me and tell me what I'm missing?
Look my result (always with i.companies) :
gen did2BM1_CVC = did2B * MessCVC_VeryPositif
gen did2BM2_CVC = did2B * MessCVC_Positif
gen did2BM3_CVC = did2B * MessCVC_Negatif
gen did2BM4_CVC = did2B * MessCVC_VeryNegatif
gen did2CM1_CVC = did2C * MessCVC_TresPositif
gen did2CM2_CVC = did2C * MessCVC_Positif
gen did2CM3_CVC = did2C * MessCVC_Negatif
gen did2CM4_CVC = did2C * MessCVC_VeryNegatif
reg Conso_CVCkWhr timeB timeC treated2 MessCVC_VeryPositif MessCVC_Positif MessElec_Negatif MessCVC_VeryNegatif did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*
note: timeC omitted because of collinearity
note: treated2 omitted because of collinearity
note: MessCVC_VeryNegatif omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM4_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 14, 433) = 15.47
Prob > F = 0.0000
R-squared = 0.3206
Root MSE = 29.278
--------------------------------------------------------------------------------------
| Robust
Conso_CVC | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
timeB | 52.078 6.20647 8.39 0.000 39.87945 64.27655
timeC | 0 (omitted)
treated2 | 0 (omitted)
MessCVC_VeryPositif | .2319934 3.699472 0.06 0.950 -7.039162 7.503149
MessCVC_Positif | -15.01919 3.738668 -4.02 0.000 -22.36738 -7.670997
MessCVC_Negatif | 6.755781 4.797958 1.41 0.160 -2.674404 16.18596
MessCVC_VeryNegatif | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -36.77858 6.160245 -5.97 0.000 -48.88628 -24.67087
did2BM3_CVC | -31.12346 7.285944 -4.27 0.000 -45.44368 -16.80324
did2BM4_CVC | -30.23441 8.362945 -3.62 0.000 -46.67142 -13.79739
did2CM1_CVC | -.3091941 5.215349 -0.06 0.953 -10.55974 9.941355
did2CM2_CVC | -6.611578 4.299592 -1.54 0.125 -15.06225 1.839089
did2CM3_CVC | 7.325056 4.502705 1.63 0.105 -1.52482 16.17493
did2CM4_CVC | 0 (omitted)
Area | .0160128 .0126783 1.26 0.207 -.0089059 .0409314
NbEmployees | .657042 .3573753 1.84 0.067 -.0453641 1.359448
DaysWorked | 9.771915 3.384955 2.89 0.004 3.118929 16.4249
Temp_Ext | 1.46355 .3071469 4.76 0.000 .8598658 2.067234
Interet_Finant | 0 (omitted)
_cons | 2.426393 6.918078 0.35 0.726 -11.1708 16.02358
*/
reg Conso_CVCkWhr timeB timeC treated2 did2B did2C MessCVC_VeryPositif MessCVC_Positif MessCVC_Negatif MessCVC_VeryNegatif did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*
note: timeC omitted because of collinearity
note: treated2 omitted because of collinearity
note: did2B omitted because of collinearity
note: did2C omitted because of collinearity
note: MessCVC_VeryNegatif omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM4_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 14, 433) = 15.47
Prob > F = 0.0000
R-squared = 0.3206
Root MSE = 29.278
--------------------------------------------------------------------------------------
| Robust
Conso_CVCkWhr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
timeB | 52.078 6.20647 8.39 0.000 39.87945 64.27655
timeC | 0 (omitted)
treated2 | 0 (omitted)
did2B | 0 (omitted)
did2C | 0 (omitted)
MessCVC_VeryPositif | .2319934 3.699472 0.06 0.950 -7.039162 7.503149
MessCVC_Positif | -15.01919 3.738668 -4.02 0.000 -22.36738 -7.670997
MessCVC_Negatif | 6.755781 4.797958 1.41 0.160 -2.674404 16.18596
MessCVC_VeryNegatif | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -36.77858 6.160245 -5.97 0.000 -48.88628 -24.67087
did2BM3_CVC | -31.12346 7.285944 -4.27 0.000 -45.44368 -16.80324
did2BM4_CVC | -30.23441 8.362945 -3.62 0.000 -46.67142 -13.79739
did2CM1_CVC | -.3091941 5.215349 -0.06 0.953 -10.55974 9.941355
did2CM2_CVC | -6.611578 4.299592 -1.54 0.125 -15.06225 1.839089
did2CM3_CVC | 7.325056 4.502705 1.63 0.105 -1.52482 16.17493
did2CM4_CVC | 0 (omitted)
Area | .0160128 .0126783 1.26 0.207 -.0089059 .0409314
NbEmployees | .657042 .3573753 1.84 0.067 -.0453641 1.359448
DaysWorked | 9.771915 3.384955 2.89 0.004 3.118929 16.4249
Temp_Ext | 1.46355 .3071469 4.76 0.000 .8598658 2.067234
Interet_Finant | 0 (omitted)
_cons | 2.426393 6.918078 0.35 0.726 -11.1708 16.02358
*/
reg Conso_CVCkWhr timeB timeC treated2 did2B did2C did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*
note: timeC omitted because of collinearity
note: treated2 omitted because of collinearity
note: did2B omitted because of collinearity
note: did2C omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM1_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 11, 436) = 20.89
Prob > F = 0.0000
R-squared = 0.2783
Root MSE = 30.071
--------------------------------------------------------------------------------
| Robust
Conso_CVCkWhr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------+----------------------------------------------------------------
timeB | 57.83895 5.898884 9.81 0.000 46.24517 69.43274
timeC | 0 (omitted)
treated2 | 0 (omitted)
did2B | 0 (omitted)
did2C | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -38.73751 5.970948 -6.49 0.000 -50.47293 -27.00209
did2BM3_CVC | -37.57747 7.253134 -5.18 0.000 -51.83292 -23.32201
did2BM4_CVC | -35.76314 8.474267 -4.22 0.000 -52.41863 -19.10765
did2CM1_CVC | 0 (omitted)
did2CM2_CVC | -2.962981 3.936796 -0.75 0.452 -10.70044 4.774475
did2CM3_CVC | 8.791522 4.485909 1.96 0.051 -.0251723 17.60822
did2CM4_CVC | -2.948393 3.558306 -0.83 0.408 -9.941958 4.045172
Area | .0215022 .0131952 1.63 0.104 -.004432 .0474363
NbEmployees | .8065384 .3155003 2.56 0.011 .1864479 1.426629
DaysWorked | 9.75966 3.459424 2.82 0.005 2.960439 16.55888
Temp_Ext | 1.347507 .2983757 4.52 0.000 .7610738 1.933941
Interet_Finant | 0 (omitted)
_cons | -3.071327 6.958276 -0.44 0.659 -16.74726 10.60461
--------------------------------------------------------------------------------
*/
reg Conso_CVCkWhr timeB timeC did2B did2C did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*note: timeC omitted because of collinearity
note: did2B omitted because of collinearity
note: did2C omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM1_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 11, 436) = 20.89
Prob > F = 0.0000
R-squared = 0.2783
Root MSE = 30.071
--------------------------------------------------------------------------------
| Robust
Conso_CVCkWhr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------+----------------------------------------------------------------
timeB | 57.83895 5.898884 9.81 0.000 46.24517 69.43274
timeC | 0 (omitted)
did2B | 0 (omitted)
did2C | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -38.73751 5.970948 -6.49 0.000 -50.47293 -27.00209
did2BM3_CVC | -37.57747 7.253134 -5.18 0.000 -51.83292 -23.32201
did2BM4_CVC | -35.76314 8.474267 -4.22 0.000 -52.41863 -19.10765
did2CM1_CVC | 0 (omitted)
did2CM2_CVC | -2.962981 3.936796 -0.75 0.452 -10.70044 4.774475
did2CM3_CVC | 8.791522 4.485909 1.96 0.051 -.0251723 17.60822
did2CM4_CVC | -2.948393 3.558306 -0.83 0.408 -9.941958 4.045172
Area | .0215022 .0131952 1.63 0.104 -.004432 .0474363
NbEmployees | .8065384 .3155003 2.56 0.011 .1864479 1.426629
DaysWorked | 9.75966 3.459424 2.82 0.005 2.960439 16.55888
Temp_Ext | 1.347507 .2983757 4.52 0.000 .7610738 1.933941
Interet_Finant | 0 (omitted)
_cons | -3.071327 6.958276 -0.44 0.659 -16.74726 10.60461
--------------------------------------------------------------------------------
*/
reg Conso_CVCkWhr timeB timeC did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*
note: timeC omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM1_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 11, 436) = 20.89
Prob > F = 0.0000
R-squared = 0.2783
Root MSE = 30.071
--------------------------------------------------------------------------------
| Robust
Conso_CVCkWhr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------+----------------------------------------------------------------
timeB | 57.83895 5.898884 9.81 0.000 46.24517 69.43274
timeC | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -38.73751 5.970948 -6.49 0.000 -50.47293 -27.00209
did2BM3_CVC | -37.57747 7.253134 -5.18 0.000 -51.83292 -23.32201
did2BM4_CVC | -35.76314 8.474267 -4.22 0.000 -52.41863 -19.10765
did2CM1_CVC | 0 (omitted)
did2CM2_CVC | -2.962981 3.936796 -0.75 0.452 -10.70044 4.774475
did2CM3_CVC | 8.791522 4.485909 1.96 0.051 -.0251723 17.60822
did2CM4_CVC | -2.948393 3.558306 -0.83 0.408 -9.941958 4.045172
Area | .0215022 .0131952 1.63 0.104 -.004432 .0474363
NbEmployees | .8065384 .3155003 2.56 0.011 .1864479 1.426629
DaysWorked | 9.75966 3.459424 2.82 0.005 2.960439 16.55888
Temp_Ext | 1.347507 .2983757 4.52 0.000 .7610738 1.933941
Interet_Finant | 0 (omitted)
_cons | -3.071327 6.958276 -0.44 0.659 -16.74726 10.60461
--------------------------------------------------------------------------------
*/
I have a problem that I have been thinking about for a week now and I do not understand what's missing.
Let me explain.
I perform a DID analysis with two treatment times.
12-week analysis. The first 4 weeks are the pre-treatment weeks. Then comes my first measure that lasts 4 weeks. Then a second measur coupled with the last one for another 4 weeks.
Firstly, I did:
reg Conso timeB treatedC did2B did2C i.companies, r
With, timeB: > 4 weeks <8 weeks. timeC: > 8 weeks. treated2: the companies that are affected by the measure. did2B: timeB * treated2. did3C: timeC * treated2.
So far it goes ... I test the effect of my first measure, as well as the effect of the complementarity of the two measures.
The problem is when I try to go further in my analysis.
The first step that I testing is information that transmits to the companies (very positive, positive, negative, very negative) and I would like to know which particular messages that impact my group
I tried everything but I have collinearity into variables. What makes me think that either I forgot a variable, either I have a variable too ... I tried all the configurations it does not work.
Can you help me and tell me what I'm missing?
Look my result (always with i.companies) :
gen did2BM1_CVC = did2B * MessCVC_VeryPositif
gen did2BM2_CVC = did2B * MessCVC_Positif
gen did2BM3_CVC = did2B * MessCVC_Negatif
gen did2BM4_CVC = did2B * MessCVC_VeryNegatif
gen did2CM1_CVC = did2C * MessCVC_TresPositif
gen did2CM2_CVC = did2C * MessCVC_Positif
gen did2CM3_CVC = did2C * MessCVC_Negatif
gen did2CM4_CVC = did2C * MessCVC_VeryNegatif
reg Conso_CVCkWhr timeB timeC treated2 MessCVC_VeryPositif MessCVC_Positif MessElec_Negatif MessCVC_VeryNegatif did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*
note: timeC omitted because of collinearity
note: treated2 omitted because of collinearity
note: MessCVC_VeryNegatif omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM4_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 14, 433) = 15.47
Prob > F = 0.0000
R-squared = 0.3206
Root MSE = 29.278
--------------------------------------------------------------------------------------
| Robust
Conso_CVC | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
timeB | 52.078 6.20647 8.39 0.000 39.87945 64.27655
timeC | 0 (omitted)
treated2 | 0 (omitted)
MessCVC_VeryPositif | .2319934 3.699472 0.06 0.950 -7.039162 7.503149
MessCVC_Positif | -15.01919 3.738668 -4.02 0.000 -22.36738 -7.670997
MessCVC_Negatif | 6.755781 4.797958 1.41 0.160 -2.674404 16.18596
MessCVC_VeryNegatif | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -36.77858 6.160245 -5.97 0.000 -48.88628 -24.67087
did2BM3_CVC | -31.12346 7.285944 -4.27 0.000 -45.44368 -16.80324
did2BM4_CVC | -30.23441 8.362945 -3.62 0.000 -46.67142 -13.79739
did2CM1_CVC | -.3091941 5.215349 -0.06 0.953 -10.55974 9.941355
did2CM2_CVC | -6.611578 4.299592 -1.54 0.125 -15.06225 1.839089
did2CM3_CVC | 7.325056 4.502705 1.63 0.105 -1.52482 16.17493
did2CM4_CVC | 0 (omitted)
Area | .0160128 .0126783 1.26 0.207 -.0089059 .0409314
NbEmployees | .657042 .3573753 1.84 0.067 -.0453641 1.359448
DaysWorked | 9.771915 3.384955 2.89 0.004 3.118929 16.4249
Temp_Ext | 1.46355 .3071469 4.76 0.000 .8598658 2.067234
Interet_Finant | 0 (omitted)
_cons | 2.426393 6.918078 0.35 0.726 -11.1708 16.02358
*/
reg Conso_CVCkWhr timeB timeC treated2 did2B did2C MessCVC_VeryPositif MessCVC_Positif MessCVC_Negatif MessCVC_VeryNegatif did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*
note: timeC omitted because of collinearity
note: treated2 omitted because of collinearity
note: did2B omitted because of collinearity
note: did2C omitted because of collinearity
note: MessCVC_VeryNegatif omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM4_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 14, 433) = 15.47
Prob > F = 0.0000
R-squared = 0.3206
Root MSE = 29.278
--------------------------------------------------------------------------------------
| Robust
Conso_CVCkWhr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------------+----------------------------------------------------------------
timeB | 52.078 6.20647 8.39 0.000 39.87945 64.27655
timeC | 0 (omitted)
treated2 | 0 (omitted)
did2B | 0 (omitted)
did2C | 0 (omitted)
MessCVC_VeryPositif | .2319934 3.699472 0.06 0.950 -7.039162 7.503149
MessCVC_Positif | -15.01919 3.738668 -4.02 0.000 -22.36738 -7.670997
MessCVC_Negatif | 6.755781 4.797958 1.41 0.160 -2.674404 16.18596
MessCVC_VeryNegatif | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -36.77858 6.160245 -5.97 0.000 -48.88628 -24.67087
did2BM3_CVC | -31.12346 7.285944 -4.27 0.000 -45.44368 -16.80324
did2BM4_CVC | -30.23441 8.362945 -3.62 0.000 -46.67142 -13.79739
did2CM1_CVC | -.3091941 5.215349 -0.06 0.953 -10.55974 9.941355
did2CM2_CVC | -6.611578 4.299592 -1.54 0.125 -15.06225 1.839089
did2CM3_CVC | 7.325056 4.502705 1.63 0.105 -1.52482 16.17493
did2CM4_CVC | 0 (omitted)
Area | .0160128 .0126783 1.26 0.207 -.0089059 .0409314
NbEmployees | .657042 .3573753 1.84 0.067 -.0453641 1.359448
DaysWorked | 9.771915 3.384955 2.89 0.004 3.118929 16.4249
Temp_Ext | 1.46355 .3071469 4.76 0.000 .8598658 2.067234
Interet_Finant | 0 (omitted)
_cons | 2.426393 6.918078 0.35 0.726 -11.1708 16.02358
*/
reg Conso_CVCkWhr timeB timeC treated2 did2B did2C did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*
note: timeC omitted because of collinearity
note: treated2 omitted because of collinearity
note: did2B omitted because of collinearity
note: did2C omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM1_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 11, 436) = 20.89
Prob > F = 0.0000
R-squared = 0.2783
Root MSE = 30.071
--------------------------------------------------------------------------------
| Robust
Conso_CVCkWhr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------+----------------------------------------------------------------
timeB | 57.83895 5.898884 9.81 0.000 46.24517 69.43274
timeC | 0 (omitted)
treated2 | 0 (omitted)
did2B | 0 (omitted)
did2C | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -38.73751 5.970948 -6.49 0.000 -50.47293 -27.00209
did2BM3_CVC | -37.57747 7.253134 -5.18 0.000 -51.83292 -23.32201
did2BM4_CVC | -35.76314 8.474267 -4.22 0.000 -52.41863 -19.10765
did2CM1_CVC | 0 (omitted)
did2CM2_CVC | -2.962981 3.936796 -0.75 0.452 -10.70044 4.774475
did2CM3_CVC | 8.791522 4.485909 1.96 0.051 -.0251723 17.60822
did2CM4_CVC | -2.948393 3.558306 -0.83 0.408 -9.941958 4.045172
Area | .0215022 .0131952 1.63 0.104 -.004432 .0474363
NbEmployees | .8065384 .3155003 2.56 0.011 .1864479 1.426629
DaysWorked | 9.75966 3.459424 2.82 0.005 2.960439 16.55888
Temp_Ext | 1.347507 .2983757 4.52 0.000 .7610738 1.933941
Interet_Finant | 0 (omitted)
_cons | -3.071327 6.958276 -0.44 0.659 -16.74726 10.60461
--------------------------------------------------------------------------------
*/
reg Conso_CVCkWhr timeB timeC did2B did2C did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*note: timeC omitted because of collinearity
note: did2B omitted because of collinearity
note: did2C omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM1_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 11, 436) = 20.89
Prob > F = 0.0000
R-squared = 0.2783
Root MSE = 30.071
--------------------------------------------------------------------------------
| Robust
Conso_CVCkWhr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------+----------------------------------------------------------------
timeB | 57.83895 5.898884 9.81 0.000 46.24517 69.43274
timeC | 0 (omitted)
did2B | 0 (omitted)
did2C | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -38.73751 5.970948 -6.49 0.000 -50.47293 -27.00209
did2BM3_CVC | -37.57747 7.253134 -5.18 0.000 -51.83292 -23.32201
did2BM4_CVC | -35.76314 8.474267 -4.22 0.000 -52.41863 -19.10765
did2CM1_CVC | 0 (omitted)
did2CM2_CVC | -2.962981 3.936796 -0.75 0.452 -10.70044 4.774475
did2CM3_CVC | 8.791522 4.485909 1.96 0.051 -.0251723 17.60822
did2CM4_CVC | -2.948393 3.558306 -0.83 0.408 -9.941958 4.045172
Area | .0215022 .0131952 1.63 0.104 -.004432 .0474363
NbEmployees | .8065384 .3155003 2.56 0.011 .1864479 1.426629
DaysWorked | 9.75966 3.459424 2.82 0.005 2.960439 16.55888
Temp_Ext | 1.347507 .2983757 4.52 0.000 .7610738 1.933941
Interet_Finant | 0 (omitted)
_cons | -3.071327 6.958276 -0.44 0.659 -16.74726 10.60461
--------------------------------------------------------------------------------
*/
reg Conso_CVCkWhr timeB timeC did2BM1_CVC did2BM2_CVC did2BM3_CVC did2BM4_CVC did2CM1_CVC did2CM2_CVC did2CM3_CVC did2CM4_CVC Area NbEmployees DaysWorked Temp_Ext Interet_Finant, r
/*
note: timeC omitted because of collinearity
note: did2BM1_CVC omitted because of collinearity
note: did2CM1_CVC omitted because of collinearity
note: Interet_Finant omitted because of collinearity
Linear regression Number of obs = 448
F( 11, 436) = 20.89
Prob > F = 0.0000
R-squared = 0.2783
Root MSE = 30.071
--------------------------------------------------------------------------------
| Robust
Conso_CVCkWhr | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------+----------------------------------------------------------------
timeB | 57.83895 5.898884 9.81 0.000 46.24517 69.43274
timeC | 0 (omitted)
did2BM1_CVC | 0 (omitted)
did2BM2_CVC | -38.73751 5.970948 -6.49 0.000 -50.47293 -27.00209
did2BM3_CVC | -37.57747 7.253134 -5.18 0.000 -51.83292 -23.32201
did2BM4_CVC | -35.76314 8.474267 -4.22 0.000 -52.41863 -19.10765
did2CM1_CVC | 0 (omitted)
did2CM2_CVC | -2.962981 3.936796 -0.75 0.452 -10.70044 4.774475
did2CM3_CVC | 8.791522 4.485909 1.96 0.051 -.0251723 17.60822
did2CM4_CVC | -2.948393 3.558306 -0.83 0.408 -9.941958 4.045172
Area | .0215022 .0131952 1.63 0.104 -.004432 .0474363
NbEmployees | .8065384 .3155003 2.56 0.011 .1864479 1.426629
DaysWorked | 9.75966 3.459424 2.82 0.005 2.960439 16.55888
Temp_Ext | 1.347507 .2983757 4.52 0.000 .7610738 1.933941
Interet_Finant | 0 (omitted)
_cons | -3.071327 6.958276 -0.44 0.659 -16.74726 10.60461
--------------------------------------------------------------------------------
*/
Comment