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st: RE: Cluster Robust Standard Errors for Cross Country Data


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Cluster Robust Standard Errors for Cross Country Data
Date   Mon, 2 Jul 2012 16:08:46 +0100

Gordon,

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> Abekah Nkrumah
> Sent: 02 July 2012 10:32
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Cluster Robust Standard Errors for Cross Country Data
> 
> Dear Stata List,
> 
> I have pooled cross-section household datasets from 20 
> countries. For each of these countries, the data was 
> collected via cluster sampling meaning there will be 
> intra-cluster correlations which will affect the validity of 
> the standard errors. If I were carrying out my estimations on 
> a single country I know that I could correct for the possible 
> bias in the standard errors by using the variable containing 
> the cluster ids to estimate cluster robust standard errors.
> 
> In the present case where I have pooled (i.e appended as in 
> stata) the household cross-section data from 20 different 
> countries, will it be right to still use the variable 
> containing the cluster ids to estimate the cluster robust 
> standard errors? Note that now the cluster ids will be for 
> all 20 countries.

This is problematic.  The consistency of the cluster-robust covariance
estimator is asymptotic in the number of clusters, and 20 isn't very far
on the way to infinity.  Clustering on country is probably not a great
idea.

An alternative is to cluster on household ID and to use country dummies
when you pool the data.  This would allow for arbitrary within-household
correlation (via clustering on household ID) and invariant
within-country correlation (via the country dummies).

HTH,
Mark

> I will appreciate your help.
> 
> Thank you very much
> 
> Gordon
> 
> --
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