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
>
> _________________________________________________________________
> Express yourself instantly with MSN Messenger! Download today - it's FREE!
> http://messenger.msn.click-url.com/go/onm00200471ave/direct/01/
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
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: [email protected]
web: http://www.sml.hw.ac.uk/ecomes
__________________________________________________________________
DISCLAIMER:
This e-mail message is subject to http://www.hw.ac.uk/disclaim.htm
__________________________________________________________________
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
