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What you are describing could mean either of two things: The underlying
economic theory is wrong and should be replaced by one supported by the
data. Or you are unlucky and have picked a very special dataset that is not
representative of the population. You have to make this pick yourself, I am
afraid...
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Erasmo Giambona
Gesendet: Mittwoch, 29. Juli 2009 10:09
An: statalist
Betreff: st: How to Reconcile R2 with Economic Significance
Dear Statalist,
I am trying to understand how to reconcile statistical and economc
significance.
Consider a simple model: y = a + b1x1 + b2x2 +e, fitted for panel data
and estimated via OLS. Suppose the t-values are respectively 10 and 2
for x1 and x2, implying that x1 contributes more to the R2 for the
model. Suppose also that a 1 standard deviation increase in x1 cause y
to increase by 2% from its mean while a 1 standard deviation increase
in x2 causes y to increase by 25% from its mean. Now, a simple
interpretation of a model R2 is that it is a proportion in the
variability of y that is accounted for by the model. Accordingly,
because of its t-value (and its effect on the R2), x1 would seem to be
one of the key drivers of this variabillity in y. However, from an
economic point of view, x1 seems to have a very marginal abillity in
explaining this variation in y (while x2 seems to be very important).
Statistical and economic significance would seem to lead to seemingly
"contradicting" results. Can someone provide some suggestions that
could help me reconciling statistical and economic significance?
Thanks,
Erasmo
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