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Re: st: cluster() and robust option

From   James Fagg <>
Subject   Re: st: cluster() and robust option
Date   Tue, 16 Aug 2005 13:45:22 +0100

Hi Kit,

I am afraid I don't know the answer to your questions as I am a very new STATA user. However, I note that you talk about the sandwich / Huber / White variance estimator. I am working with a national dataset and a binary outcome. Many of the small areas that I am investigating have only one respondent.

I am using xtlogit to investigate area effects and I am wondering whether the sandwich estimator improves the estimates of the effects and whether I should / could use this with xtlogit?


Queen Mary, University of London

Kit Baum wrote:

Federico says

I am working with a cross-national data set. It includes observations for 20 developed countries in 1990. Since these countries are not randomly sampled, I thought to use the reg option cluster(country). In fact it specifies that the observations are not independent within groups
Is this a reasonable solution in this case?

If so, why do I obtain the same result by using robust option?
I wonder if robust standard errors are the statistical remedy both for no independent observations and heteroskedasticity?
So, what is the relationship between heteroschedasticity and no indipendent observations?
I ask thesw questions because I didn't find any answers on STATA manuals.

If you have only those 20 observations, robust and cluster(country) mean the same thing. The group of observations corresponding to the country is allowed to have a covariance matrix incorporating intra- country correlation, and the diagonal of that matrix is country- specific. But if you have only one obs. per country that matrix is a scalar with value equal to the "robust" (sandwich/Huber/White) variance estimator.

Cluster standard errors would make a difference if you have multiple observations per country (e.g. a panel). But there are other ways of skinning that cat, e.g. xtgls, xtgee etc.

Kit Baum, Boston College Economics

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