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From |
Antoine Terracol <Antoine.Terracol@univ-paris1.fr> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: [Non Stata] Estimation strategy for a belief learning model. |

Date |
Mon, 08 Aug 2005 17:53:13 +0200 |

Dear _all,

In the context of an economic experiment, I have data on the elicited beliefs of individuals on the probability that their opponent plays strategy A, B or C in the next round.

I want to fit a learning model (Cheung and Friedman (1997) "Individual Learning in Normal Form Games: Some Laboratory Results," Games and Economic Behavior, 19, 46-76.) on the data to see wether it describes reasonably well the learning process of individuals.

For a given strategy, say strategy A, I can estimate the parameters of the theoritical model by running the following maximuml likelihood regression:

Actual Belief = Theoretical Belief + epsilon

where epsilon is a disturbance random variable

However, because I only use the belief for a given strategy, I throw away valuable information (beliefs on strategy B)

I obvioulsy (??) can't simply multiply the likelihood contributions for both beliefs since they are almost mechanicaly negatively correlated; and I'm not sure wether using a bivariate distribution for the error terms would be appropriate.

I'd appreciate any hint or advice on the subject...

Best,

Antoine.

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