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st: re: time dummy in RE model


From   Kit Baum <[email protected]>
To   [email protected]
Subject   st: re: time dummy in RE model
Date   Mon, 25 Jul 2005 21:43:32 -0400

David M, in response to David G and me, said

Not to defend mis-specifying equations as a general strategy, but the issue
of losing degrees of freedom is possibly more serious than implied by some
of the responses to Alice's question. The loss of degrees of freedom has a
direct effect on the precision of the parameter estimates.

To turn the (rhetorical?) question around, if your estimates are unbiased
but completely unreliable, what have you gained? Remember, Alice was
talking about small samples.

One should consider both bias and precision (and their implications for the
job at hand) when making such decisions.


Indeed, the concept of mean square error trades off bias and precision. But what is at issue here is not merely bias, it is consistency. Bias will disappear in the limit. An instrumental variables estimator is biased in small samples, but if properly specified it will be consistent, with bias going to zero as N->\infty..

If however you specify the wrong DGP, you will be generating inconsistent estimates--that is, estimates whose bias does not diminish with sample size. What useful conclusions can be drawn from inconsistent estimates? There are some samples with insufficient information to provide much useful inference. No sensible solution to that problem involves specifying a demonstrably incorrect DGP.

Kit Baum, Boston College Economics
http://ideas.repec.org/e/pba1.html

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