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Re: st: RE: [Non Stata] Estimation strategy for a belief learning model.


From   austin nichols <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: [Non Stata] Estimation strategy for a belief learning model.
Date   Mon, 8 Aug 2005 15:49:11 -0400

Still unclear.  Does gamma vary across individual players?
Or is it a parameter of the game structure only?
Why don't you write out f(g,X) in Stata code for us?

-----Original Message-----
From: Antoine Terracol [mailto:terracol@univ-paris1.fr]
Sent: Monday, August 08, 2005 3:31 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: RE: [Non Stata] Estimation strategy for a belief
learning model.

thanks for your answer, but I think I have been unclear in my first message.

I have a theoretical model for the formation of beliefs, where the
belief in round t is a function of the past history of the game (denoted
X), and a gamma parameter, so the "theoretical" belief is f(gamma,X).
The belief for each strategy is updated independantly of the others
(i.e. the belief of a given strategy depends only on past occurences of
the strategy, not on the history of other strategies), but the updating
rule ensures that beliefs sum up to one.

The players have been asked to report their beliefs, which I label
"actual" beliefs.

What I want to do is to estimate the gamma parameter using "actual"
beliefs as the dependant variable, f(gamma,X) and an error term in the RHS:

Actual belief = f(gamma,X) + epsilon

Using this equation, I could estimate the gamma parameter using only
data on beliefs for a given strategy, but that would be inefficient
since I would make no use of the information provided by other beliefs.

...

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