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st: Re: Ramsey test interpretation

From   Kit Baum <[email protected]>
To   [email protected]
Subject   st: Re: Ramsey test interpretation
Date   Sat, 19 Sep 2009 06:10:06 -0400

That is not quite right either, as Jeff Wooldridge clearly explains in his undergrad text "Introductory econometrics". What is being tested is the functional form of the X's you have included. A significant Ramsey test is evidence that, say, including X in levels is inadequate, compared to including a nonlinear f(X). As a high-order polynomial can approximate any f(X), the test can pick that up.

But the test---despite its poor choice of nomenclature, 'ovtest: omitted variables test' in Stata---does NOT test whether you have left out variables Z1, Z1^2, etc. where Zs are completely different variables. It does not (and can not) test the maintained hypothesis that y = X b + u, with no Zs in X. In other words, the Ramsey test's ability to test the specification of a possibly 'short model' is limited to considering whether its 'shortness' may be due to leaving out powers of Xs, interactions of Xs, etc., and does not really consider 'omitted variables' in the broader sense.


On Sep 19, 2009, at 2:33 AM, Clive wrote:

Many scholars incorrectly interpret a non-significant F ratio to
support the conclusion that we have included all the relevant
variables, when it actually means that there are almost certainly no
omitted _nonlinear_ variables to include on our model.

In your case, F is significant, so you may well have omitted some
quadratic, cubic or otherwise nonlinear variables (or, indeed,
nonlinear transformations of your existing variables) in your model.
Once you've included them and fit the model, running -ovtest- again
may produce a different outcome.

Kit Baum   |   Boston College Economics & DIW Berlin   |
An Introduction to Stata Programming |
   An Introduction to Modern Econometrics Using Stata  |

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