Event count estimation
提出一种新的事件计数估计方法，能抵抗异常值、数据截断和过多零值，蒙特卡洛实验显示其在大样本下表现合理，且效率损失很小，适用于贸易引力模型等实证研究。
This paper proposes a new estimation procedure called Event Count Estimator (ECE). The estimator is straightforward to implement and is robust against outliers, censoring and ‘excess zeros’ in the data. The paper establishes asymptotic properties of the new estimator and the theoretical results are supported by several Monte Carlo experiments. Monte Carlo experiments also show that the estimator has reasonable properties in moderate to large samples. As such, the cost of trading efficiency for robustness here is negligible from an applied viewpoint. The practical usefulness of the new estimator is demonstrated via an empirical application of the Gravity Model of trade.