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st: Problem with the cluster-option in relogitq after relogit

From   joachim Wagner <>
Subject   st: Problem with the cluster-option in relogitq after relogit
Date   Mon, 20 Sep 2004 08:21:27 +0200

Dear All,

I am working with the Rare Events Logit program relogit.ado and the setx/relogitq - ados (written by Gary King and others). I am using an up to date version of Stata 8.2/SE. Friday last week I encountered what turned out a rather strange problem for me. I asked Gary King, but he replied that "cluster" is a Stata option, not something they in relogit programmed, so he can't answer my question. Therefore, I post my question to the list:

I am estimating empirical models to explain the propensity for becoming self-employed. I use a large data set for individuals, and ca. 3 percent of them are about to become self-employed - a rare event. Some of the variables in my models are not measured at the level of the individuals, but at the level of the regions the people live in. Therefore, I estimate the models with the cluster-option to get the estimated standard errors right. Everything is going well.

When I try to use setx/relogitq after estimating a model to "forecast" the probability that an individual with a given set of characteristics living in a region with a given set of characteristics will become self-employed, and when the model is estimated with the cluster-option, I get an error: r(506) matrix not positive definite.

Question: Why does this happen, and what can be done?

As a work-around I estimate the models without the cluster option; given that the estimated coefficients are the same, I think the estimated probabilities are fine. But what about the confidence intervals reported by relogitq?

Question: Can I proceed this way?

I would be very grateful for any comments etc.

All the best,


Prof. Dr. Joachim Wagner
University of Lueneburg
Institute of Economics
Campus 4.210
D-21332 Lueneburg
Phone: +49-4131-78-2330
Fax: +49-4131-78-2026

You can access working paper versions of some of my papers on the Social Science Research Network (SSRN) at the following URL:

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