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RE: st: Direction of the effect of the cluster command on the standard error depends on the inclusion of a control variable
From
DE SOUZA Eric <[email protected]>
To
"[email protected]" <[email protected]>
Subject
RE: st: Direction of the effect of the cluster command on the standard error depends on the inclusion of a control variable
Date
Thu, 6 Jan 2011 12:36:18 +0100
You can find a good presentation of cluster sampling issues (Lecture 7) -- and, indeed, an excellent course in recent development in econometrics -- here:
http://www.cemmap.ac.uk/resources/resources25.php
You have both the slides and the lecture notes.
The level supposes a good basis in econometrics.
Eric
Eric de Souza
College of Europe
Brugge (Bruges), Belgium
http://www.coleurope.eu
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Jacob Felson
Sent: 06 January 2011 01:30
To: [email protected]
Subject: Re: st: Direction of the effect of the cluster command on the standard error depends on the inclusion of a control variable
Justina,
Thank you for your input. Is it improper to use the cluster command with only 4 nations? I will attempt #2.
Jacob Felson
On Wed, Jan 5, 2011 at 7:20 PM, Justina Fischer <[email protected]> wrote:
> Hi,
>
> just two caveats
>
> 1) Using cluster-option, you should have a decent number of clusters
> to profit from its beneficial characteristics (Kit can probably
> highlight on this). I guess 4 clusters is far from large....
>
> 2) in cross-sectional micro data, I would use cluster-option when my
> variable of interest varies only across countries, as standard errors
> are then corrected for this. For example, this could be an
> institution, like democracy
>
>
> to your question: is z a vector of country-characteristics in your
> micro model? That could possibly explain your finding...
>
> Justina
>
>
> [email protected] schrieb: -----
>
> An: [email protected]
> Von: Jacob Felson <[email protected]>
> Gesendet von: [email protected]
> Datum: 06.01.2011 01:01AM
> Thema: st: Direction of the effect of the cluster command on the
> standard error depends on the inclusion of a control variable
>
> I wonder if anyone might be able to provide an explanation for the
> following scenario. I'm wondering why the direction of the change in
> a standard error affected by the use of the cluster command depends on
> the whether another control variable is included. My inquiry is more
> theoretical than practical, as I'm not wondering "what I should do"
> but rather, simply "why is this happening?" Let me elaborate below.
>
> Consider the following variables:
>
> y, the dependent variable
> x, the independent variable of greatest interest, which is moderately
> correlated with y and with z z, another independent variable, which is
> correlated with y at about 0.5.
>
> nation - the data was collected in 4 different nations by different
> organizations.
>
>
> I am examining the standard errors (SE) for the coefficient of
> variable x from the following four models:
>
> 1. Regress y on x, without clustering on nation.
> 2. Regress y on x, with clustering on nation.
>
> 3. Regress y on x and z without clustering on nation.
> 4. Regress y on x and z with clustering on nation.
>
>
> The SE of the coefficient for x is LARGER in model 2 than in model 1.
> This suggests there is a positive intercluster correlation. That is,
> the residuals are more similar to each other within nations than we
> would expect by chance alone. I suppose there is a preponderance of
> positive residuals in some nations and a preponderance of negative
> residuals in other nations.
>
> The SE of the coefficient for x is SMALLER in model 4 than in model 3.
> This suggests there is a negative intercluster correlation. That is,
> the residuals are less similar to each other within nations than we
> would expect by chance.
>
>
> So the effect that clustering on nation has on the SE of x depends on
> whether a third variable, z, is controlled. Why is this?
>
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