I think Maarten's right, it's probably differences due to finite precision arithmetic. Try using doubles and see if it goes away.
This kind of thing is hardly unusual and is even more marked in nonlinear problems such as numerical optimization, where you simply can't expect more than about eight digits in double precision for many problems. Root finding for the derivative of a function is inherently harder than for the function itself.
-----Original Message-----
From: "G.B.Li" <[email protected]>
To: [email protected]
Sent: 9/10/2008 3:27 AM
Subject: st: why do fixed-effects estimates differ?
Hi all:
I use two methods to control for fixed effects: (1) use dummy variables, (2) demean all the variables.
Results turn out to be highly close, but not identical. The difference is no more than 0.000001。
In theory, they should be identical. How to explain the trivial differences?
(I guess it is related to my huge sample size. When I try both methods with a very small dataset, there is no such difference.)
Many thanks！
GBL
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