All,
On Monday early morning, I posted a query a spurious regression problem I
was having. In line with the Statalist FAQ, I've decided to rearrange this
query and provide more detail (which perhaps should have been provided
anyway), as well as make the methodological context clearer. I post this
with some trepidation!
My variables of interest are concerned with net votes. The dependent
variable is GENCH = change in a party's vote at the current general
election from the previous one. The key independent variable is MIDCH =
change in a party's midterm election vote from the previous general
election. I hypothesise that MIDCH has a significant effect on GENCH over
time (or, over several GEs). In the models I've fitted so far (using both
-reg- and -xtgls-) I have found this to be the case for all parties. So
far, so good.
At a recent workshop, however, I was told both of these variables may be
influenced by a third variable (let's call it REGION) and, once controlled
for, there may be no relationship between GENCH and MIDCH. How should one
handle this in a time-series context? -ivreg- would appear to be ruled
out, since this deals with endogeneity. -xtgls- could be used regardless,
but this may be a dangerous option to take given the above. I'm not
entirely sure if simultaneous equation models would help here or not.
What I do know, however, is that the key variables in my models are all
differenced, and time trends have been fitted, which goes part of the way
to solving this problem (if, indeed, I have it). If anybody has any
comments, I'd be very grateful to you.
CLIVE NICHOLAS |t: 0(044)191 222 5969
Politics |e: [email protected]
Newcastle University |http://www.ncl.ac.uk/geps
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