The Spatial Autocorrelation problem is something that
needs to be considered because most elements in the
csts matrix are probably not independent. Not
checking to determine whether a csts is stationary
over time can lead to spurious conclusions and the
tests for stationarity for a panel over time are
different than Time Series tests for stationarity.
(Chapter 12 of Baltagi has a good explanation as to why.)
TL Long
Full Time Instructor
Department of Liberal Arts
Temple College
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------- Original Message -------
From : Joseph Young[mailto:[log in to unmask]]
Sent : 9/25/2008 2:40:50 PM
To : [log in to unmask]
Cc :
Subject : RE: Re: [POLMETH] Matching methods and TSCS
data
Propensity score matching is starting to become
common among IR types
who use TSCS data. The studies that I've seen in IR
that use it have
done so uncritically. In my dissertation, I use
matching on TSCS data
but correct for temporal correlation. One of the
assumptions of
matching is that observations are independent.
Clearly, most
observations within a panel are not independent.
This, in my opinion,
needs to considered, but I'd be interested to hear
what others think
as well. I'd be happy to share do-files, the
dissertation and a
possible fix for this problem. There is still the
problem of
potential spatial correlation, which I do not tackle.
The good (bad)
news is that this should affect all data not just TSCS.
Joe
**********************************
Joseph K. Young
Assistant Professor
Department of Political Science
Southern Illinois University
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http://mypage.siu.edu/jkyoung
**********************************
On Sep 25, 2008, at 10:46 AM, Carlos Rodriguez wrote:
> Dear list,
>
> I have the following doubt: is it possible
(correct) to do matching
> with time-series cross sectional data? I have only
seen it used with
> panel (cross-sectional) data.
> thanks
>
> carlos
>
>
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