Carlos A. Manzanares

A Data-Driven State Aggregation Approach for Dynamic Discrete Choice Models

In dynamic discrete choice models, a commonly studied problem is estimating parameters of agent reward functions (also known as ’structural’ parameters) using agent behavioral data. This task is also known as inverse reinforcement learning. Maximum likelihood estimation for such models requires dyna…