A Computationally Practical Simulation Estimation for Dynamic Panel Tobit Models

This paper provides a computationally practical simulation estimation for the dynamic panel Tobit model with large categories of dependence structures. The simulation estimators are conducted through correlated random effects approach. The log-likelihood function is simulated and maximized through procedures based on a recursive algorithm formulated by GHK and Gibbs sampling simulators. The initial conditions problem is discussed in details. The simulation estimators discussed in this paper have been implemented by Scholz et al. (2006) to study retirement savings. Monte Carlo experiments indicate that the simulation estimators perform strikingly well, especially in the case of the Gibbs estimator, even for a small simulation size.