Practical Methods for Estimation of Dynamic Discrete Choice Models
介绍了条件选择概率（CCP）估计量，为估计动态离散选择问题提供更简单的方法，并展示了如何将其应用于处理丰富的未观测状态变量模式。
Many discrete decisions are made with an eye toward how they will affect future outcomes. Formulating and estimating the underlying models that generate these decisions is difficult. Conditional choice probability (CCP) estimators often provide simpler ways to estimate dynamic discrete choice problems. Recent work shows how to frame dynamic discrete choice problems in a way that is conducive to CCP estimation and demonstrates that CCP estimators can be adapted to handle rich patterns of unobserved state variables.