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st: correcting standard errors for model with repeated observations insame time period

From   Adrian de la Garza <>
To   statalist <>
Subject   st: correcting standard errors for model with repeated observations insame time period
Date   Wed, 7 May 2008 01:14:57 -0400

Dear all,

I am running a linear regression that looks like this:

bondspread = a + macro*b + covariates*c + public/private_dummies + country_FE + e

where bondspread is the spread of a bond issued by a public or a private entity in a given country in period (year, quarter); macro are a bunch of macroeconomic variables such as the growth of GDP, total external debt/GDP ratio, etc.; covariates are a bunch of individual characteristics; and I have a dummy that tells me whether the institution issuing the bond was public or private, and country fixed effects (and maybe I will add year FE later and other things... but this is what I have now).

The problem is that I think that I should correct the standard errors of a simple OLS because one same country may issue multiple bonds in a given (year,quarter)... so, what I am doing is to cluster by country or at least by region (like "Latin America" or "East Asia" and such)... but I think I should do something else. Does anybody have an idea of how to make such correction or whether it is necessary at all?

To be more specific, this is kind of like what I have:

country year quarter bondspread
Mexico  1990 1         200
Mexico  1990 2         .
Mexico  1990 3         .
Mexico  1990 4         170
Mexico  1990 4         224
Mexico  1990 4         272
Mexico  1991 1         .
Mexico  1991 2         168
Brazil    1990 1         .
Brazil    1990 2         315
Brazil    1990 2         295
Brazil    1990 3         .
Brazil    1990 4         .
Brazil    1991 1         292
Brazil    1991 1         350
Brazil    1991 1         264

and so on. So, basically, Mexico can issue one or multiple bonds in a given period (because one of multiple different companies and local governments decide to issue debt) or can simply NOT issue at all (when spread is missing).

I know I probably need some sort of selection model (a la Heckman) to account for the fact that some countries may or may not issue at any given time... but do I need to account for the clumping of issues at any given time? And if so, how?

Thank you very much!

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