A simple dynamic panel data approach for macro policy assessment

摘要

We propose a simple-to-implement dynamic panel difference-in-difference method to assess the impact of (place-based) macro policies. The idea is to exploit both serial correlation and cross-sectional dependence within a panel and implement a semi- difference-in-difference decomposition. Different from existing panel data methods, the proposed approach is easy to implement and conduct statistical inference and can incorporate multiple treated groups at different time thresholds. Monte Carlo simulations show the proposed estimator performs reasonably well with finite samples. An application to assess the general impact of a free trade zone policy is also provided.