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# st: bias in panel FE

 From "Isabella King" To Subject st: bias in panel FE Date Tue, 18 Dec 2012 20:51:57 +0800

```Thank Maarten and Nick.

Best,
Isabella

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten Buis
Sent: Tuesday, December 18, 2012 5:32 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: biasness in panel FE

On Tue, Dec 18, 2012 at 9:04 AM, Isabella King wrote:
> I am currently working with panel fixed effects model. My dataset has
> 176 obs. My question is : whether this small sample size will result
> in biasness in estimation results, especially when I try to use IV to
> instrument one endogenous variable?

The first step is to specify what it is exactly that you want to estimate.
Remember that bias is just a shorthand for "the coefficient does not
estimate what I want to know". So whether or not a coefficient is biased
depends on what it is  it is supposed to estimate. The problem is that a
statement like "I just want to know the effect of x on y" is often not
precise enough as it can be interpreted in different ways and these
different ways often matter as they lead to different conclusions. What I
find often helpful is to think in terms of two (hypothetical) groups and the
effect is some comparison (difference or ratio) of means or medians or ...
of the dependent variable. So the trick is to think carefully about what
defines these groups and what is it that you want to compare.

After that you can look at your data and possible methods and see how each
approximate the thing you want to know. Typically, you'll never get there
entirely. The trick is not to try to give the "final answer", but instead a
contribution to the scientific debate where you add a piece of imperfect
evidence to the body of evidence available in this debate.

Hope this helps,
Maarten

---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
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