st: SE with cluster option

["Alexander Nervedi" <alexnerdy@hotmail.com>]

Hi Everyone,

I was wondering what may explain the following F(.,.) valuse when i use the 
cluster option. I have about 40 households per cluister, and four clusters 
(total of 168 unique households). I'd like to run the model at the cluster 
level to estimate a Difference in Difference model.

Initially I thought the issues was that since there are only 4 clusters, I'd 
not be able to estimate it since its using 4 cluster means to estimate the 
standard errors. However the problem still remains if i cluster at the 
survey code (or household) level

-MODEL 1 -

reg y1 DiD vdc post season cdum2 cdum4, cluster(clust)

Regression with robust standard errors                 Number of obs =     
672
                                                                     F(  1, 
    3) =       .
                                                                     Prob > 
F      =       .
                                                                     
R-squared     =  0.1220
Number of clusters (village) = 4                           Root MSE      =  
.29762

------------------------------------------------------------------------------
            |               Robust
   cropfail |      Coef.   Std. Err.      t    P>|t|     [95% Conf. 
Interval]
-------------+----------------------------------------------------------------
        DiD |   .1867678   .0381533     4.90   0.016     .0653468    
.3081888
  cdum1  |   .0407624   .0190767     2.14   0.122    -.0199481    .1014729
      post |   .0377531   .0255782     1.48   0.236    -.0436482    
.1191544
     season |  -.0803571   .0418741    -1.92   0.151    -.2136192    
.0529049
      cdum2 |   .0830587   5.54e-16        .   0.000     .0830587    
.0830587
      cdum4 |    .085874   1.02e-15        .   0.000      .085874     
.085874
      _cons |   .1601304   .0901628     1.78   0.174    -.1268078    
.4470686
------------------------------------------------------------------------------


-MODEL 2 -

reg y1 DiD vdc post season vdum2 vdum4, cluster(survey)
Regression with robust standard errors                 Number of obs =     
672
                                                                     F(  5, 
  167) =       .
                                                                     Prob > 
F      =       .
                                                                     
R-squared     =  0.1220
Number of clusters (survey) = 168                      Root MSE      =  
.29762

------------------------------------------------------------------------------
            |               Robust
   cropfail |      Coef.   Std. Err.      t    P>|t|     [95% Conf. 
Interval]
-------------+----------------------------------------------------------------
        DiD |   .1867678   .0788515     2.37   0.019     .0310936     
.342442
  cdum1 |   .0407624    .012909     3.16   0.002     .0152765    .0662484
       post |   .0377531   .0240521     1.57   0.118    -.0097322    
.0852384
     season |  -.0803571   .0200387    -4.01   0.000     -.119919   
-.0407952
      cdum2 |   .0830587   .0201067     4.13   0.000     .0433627    
.1227547
      cdum4 |    .085874   .0476556     1.80   0.073     -.008211     
.179959
      _cons |   .1601304   .0483279     3.31   0.001     .0647181    
.2555428
------------------------------------------------------------------------------


-MODEL 3 -
. reg y1 DiD vdc post season vdum2 vdum4, robust

Regression with robust standard errors                 Number of obs =     
672
                                                      F(  6,   665) =   
10.49
                                                      Prob > F      =  
0.0000
                                                      R-squared     =  
0.1220
                                                      Root MSE      =  
.29762

------------------------------------------------------------------------------
            |               Robust
   cropfail |      Coef.   Std. Err.      t    P>|t|     [95% Conf. 
Interval]
-------------+----------------------------------------------------------------
        DiD |   .1867678   .0658962     2.83   0.005     .0573781    
.3161575
   cdum1 |   .0407624   .0144458     2.82   0.005     .0123976    .0691272
       post |   .0377531   .0276749     1.36   0.173    -.0165876    
.0920938
    season |  -.0803571   .0229621    -3.50   0.000    -.1254441   
-.0352702
    cdum2 |   .0830587   .0206597     4.02   0.000     .0424926    .1236247
    cdum4 |    .085874   .0436286     1.97   0.049     .0002076    .1715403
      _cons |   .1601304   .0566039     2.83   0.005     .0489866    
.2712742
------------------------------------------------------------------------------


Model 1 estimates the SEs at the cluster level, while Model 2 does it at the 
ID level. Model 3 uses the robust option. and everything works out fine. The 
help suggests that I may be estimating more parameters than i can possible 
estimate with the data. I am not sure i see that since i have a sample of 
over 670 observations, and I am estimating betwen 5 - 8 variable at most.

I was hoping someone has some intuition here as to what may be messing me 
up.

thanks.
al

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