Maximum simulated likelihood and expectation-maximization methods to estimate random coefficients logit with panel data

The random coefficients Logit model allows a more realistic representation of agents’ behavior. However, the estimation of such model may involve simulation, which may become impractical when the number of random coefficients is large, because of what is known as the curse of dimensionality. In this