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st: SE with cluster option


From   "Alexander Nervedi" <alexnerdy@hotmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: SE with cluster option
Date   Tue, 18 Oct 2005 17:42:09 +0000

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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