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Re: st: Cluster robust se in logit fixed effects model

From   "Justina Fischer" <>
Subject   Re: st: Cluster robust se in logit fixed effects model
Date   Thu, 26 Jul 2012 13:42:49 +0200

Dear David,

depending on how the question is formulated you could treat it as a count-variable, applying negative binomial estimation methods.

Hope this helps

-------- Original-Nachricht --------
> Datum: Thu, 26 Jul 2012 11:34:45 +0000
> Von: "Deller, David R D" <>
> An: "" <>
> Betreff: st: Cluster robust se in logit fixed effects model

> Dear statalist,
> I am currently using a short and highly unbalanced panel data set to
> estimate a logit model of individuals committing property crime. Having run
> basic logit and probit regressions successfully I'm now running a fixed effects
> logit model using xtlogit, fe. As well as my dependent variable being
> binary most of my independent variables are dummies as I am using survey data
> composed largely of categorical questions. I want to obtain cluster robust
> standard errors as each individual represents a cluster who has errors which
> are likely to correlated through time.
> To get cluster robust standard errors when using xtlogit, fe Cameron and
> Trivedi (2010) advises to use the option vce(bootstrap). However, given that
> relatively few individuals commit property crime, when I run the code I
> get lots of "red x's" which indicate stata has posted a missing value. I
> believe these missing values are due to stata dropping variables in the
> resampling process for which no one commits a crime.
> My question is how does stata treat these missing values when it finally
> reports the standard errors? I know there are issues about the averaging
> process if one simply uses the bootstrap command and there are missing values.
> See:
> Does this same problem apply to the command vce(bootstrap)?
> I appreciate that even if this averaging problem doesn't occur with
> vce(bootstrap) the situation is not ideal as some of the standard error figures
> will be based on fewer replications than others.
> Any help would be much appreciated.
> Regards
> David Deller
> University of Essex
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Justina AV Fischer, PhD
COFIT Fellow
World Trade Institute
University of Bern


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