Abstract

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.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call