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Re: st: SE with cluster option


From   "Mark Schaffer" <M.E.Schaffer@hw.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: SE with cluster option
Date   Tue, 18 Oct 2005 19:17:49 +0100 (BST)

Al,

> 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 issue 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.

You are right - in effect, you have 4 observations ("super-observations"
is perhaps more accurate) to calculate your var-cov matrix, which means
you won't get very far this way.

> However the problem still remains if i cluster at the
> survey code (or household) level

Is there a clickable hyperlink on the missing F-stat in this case, and if
so, what does it say?

--Mark


> -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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Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3294
email: m.e.schaffer@hw.ac.uk
web: http://www.sml.hw.ac.uk/ecomes



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