Gravity Estimations with Interval Data: Revisiting the Impact of Free Trade Agreements
指出使用区间或平均数据估计引力模型存在偏差，主张采用连续年度数据以更准确捕捉贸易政策调整的动态效应，避免估计结果向下偏误并提高效率。
We challenge the common practice of estimating gravity equations with interval or averaged data in order to capture dynamic‐adjustment effects to trade‐policy changes. Instead, we point to a series of advantages of using consecutive‐year data recognizing dynamic‐adjustment effects. Our analysis reveals that, relative to interval or averaged data, the use of consecutive‐year data avoids downward‐biased effect estimates due to the distribution of trade‐policy events during an event window as well as due to anticipation (pre‐interval) and delayed (post‐interval) effects, and it improves the efficiency of effect estimates due to the use of more data.