Dear Statalisters,

I have a question regarding the use of vce(robust) or vce(cluster ind) for my cross-sectional model. My dataset is small, with 116 observations.
The variable I concerned about is the dummy variable and it's only significant in the last case. There are differences in SE when I use vce(robust) or vce(cluster ind).
I want to ask if it's right if I use vce(cluster ind) in this model and I hope I could understand why there are big changes in my model.
I attached the code here with 3 model: OLS, vce(robust), vce(cluster ind).
Thank you so much.

Best regards,
Ha Nguyen
Code:

. reg Y dummy X1 size cash age2 analyst mbratio

      Source |       SS           df       MS      Number of obs   =       116
-------------+----------------------------------   F(7, 108)       =      2.43
       Model |  393.729615         7  56.2470879   Prob > F        =    0.0237
    Residual |  2499.90356       108  23.1472552   R-squared       =    0.1361
-------------+----------------------------------   Adj R-squared   =    0.0801
       Total |  2893.63317       115  25.1620276   Root MSE        =    4.8112

------------------------------------------------------------------------------
           Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       dummy |  -1.449351   .9828503    -1.47   0.143     -3.39753    .4988292
          X1 |   .0673247    .028259     2.38   0.019     .0113104     .123339
        size |  -.8122102    .400049    -2.03   0.045    -1.605177   -.0192437
        cash |  -15.73149   8.188105    -1.92   0.057    -31.96174    .4987515
        age2 |   .9146657   .4920407     1.86   0.066    -.0606444    1.889976
     analyst |   .0638981   .6261884     0.10   0.919    -1.177316    1.305112
     mbratio |  -.2066817   .2757556    -0.75   0.455    -.7532772    .3399137
       _cons |   14.04019   8.693411     1.62   0.109    -3.191661    31.27204


. reg Y dummy X1 size cash age2 analyst mbratio ,robust

Linear regression                               Number of obs     =        116
                                                F(7, 108)         =       1.84
                                                Prob > F          =     0.0870
                                                R-squared         =     0.1361
                                                Root MSE          =     4.8112

------------------------------------------------------------------------------
             |               Robust
           Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       dummy |  -1.449351   1.007996    -1.44   0.153    -3.447374    .5486733
          X1 |   .0673247   .0248537     2.71   0.008     .0180604     .116589
        size |  -.8122102   .3700793    -2.19   0.030    -1.545772   -.0786489
        cash |  -15.73149   9.472885    -1.66   0.100     -34.5084     3.04541
        age2 |   .9146657    .615406     1.49   0.140    -.3051757    2.134507
     analyst |   .0638981   .3762059     0.17   0.865    -.6818073    .8096035
     mbratio |  -.2066817   .1959103    -1.05   0.294    -.5950099    .1816464
       _cons |   14.04019   7.764501     1.81   0.073    -1.350401    29.43078
------------------------------------------------------------------------------

reg Y dummy X1 size cash age2 analyst mbratio , vce(cluster ind)

Linear regression                               Number of obs     =        116
                                                F(7, 13)          =      27.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1361
                                                Root MSE          =     4.8112

                                   (Std. Err. adjusted for 14 clusters in ind)
------------------------------------------------------------------------------
             |               Robust
           Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       dummy |  -1.449351   .6598815    -2.20   0.047    -2.874938   -.0237631
          X1 |   .0673247    .021427     3.14   0.008     .0210345    .1136149
        size |  -.8122102   .2410903    -3.37   0.005    -1.333054   -.2913664
        cash |  -15.73149   3.602049    -4.37   0.001    -23.51325    -7.94974
        age2 |   .9146657   .3727299     2.45   0.029     .1094317      1.7199
     analyst |   .0638981    .221543     0.29   0.778    -.4147165    .5425127
     mbratio |  -.2066817   .1792627    -1.15   0.270    -.5939553    .1805919
       _cons |   14.04019   4.305863     3.26   0.006     4.737936    23.34244
------------------------------------------------------------------------------