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st: RE: Econometrics question

From   "Martin Weiss" <>
To   <>
Subject   st: RE: Econometrics question
Date   Mon, 29 Mar 2010 20:50:50 +0200


The significance also depends on the number of observations in the
estimation sample, so the "weighted average" need not carry over to the
standard error estimation:

sysuse auto, clear
reg price weight length
est store full
reg price weight length in 1/`=_N/2'
est store firsthalf
reg price weight length in `=_N/2+1'/l
est store secondhalf
estimates table full firsthalf secondhalf, se style(oneline)


-----Original Message-----
[] On Behalf Of kokootchke
Sent: Montag, 29. März 2010 20:39
To: statalist
Subject: st: Econometrics question

Dear Stata users, 

I have a basic econometric question and I'm hoping you can help me out. I am
running a regression of bond spreads on various variables denoting domestic
economic conditions, and country fixed effects; I'm clustering my standard
errors by quarter, e.g.

xi: regress LogSpread GDPgrowth DebtToGDP, cluster(time)

I have quarterly data for 40 different countries, although it's a very
unbalanced panel because the spread of the bond is for new bond issues and a
lot of countries don't issue new bonds every quarter. So, the data would
look something like this:

Country   Time   Spread GDPgrowth 
Argentina 1991q1 400    3.0
Argentina 1994q4 450    2.5
Argentina 2001q3 800    0.7
Brazil    1993q2 ...
Brazil    1993q4 ...
Brazil    1994q1 ...
Colombia ...

When I run a simple regression like the one above for the full sample, I
obtain a coefficient for GDPgrowth of -0.073***

Then if I run this same regression for two separate subsamples for the years
1991-1997 and 1998-2006, my coefficients for GDPgrowth are -0.056 and 0.009,
both insignificant.

In my experience, the full sample coefficient would in general be some sort
of weighted average of the two coefficients obtained from subsample
regressions. So, I don't understand why this is not the case here... 

The number of observations in the two subsamples add up to the number of
observations in the full sample estimations.

Any ideas?


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