Addressing Anticipation Effects in Finance

A wide range of empirical techniques cannot accurately estimate causal effects of policy events due to anticipation bias-agents making decisions based on beliefs about future policy outcomes. We show how researchers can refine estimates to account for these beliefs, by integrating reduced-form and structural estimation around observed outcomes of a single policy change. We illustrate the importance and implementation of the approach by applying it to the Paris Agreement, which is frequently used to understand how agents respond to a policy event that increased climate regulatory risk. We document that anticipation can bias both the magnitude and sign of the Paris Agreement's average treatment effect on firm outcomes (estimated from a standard model such as a difference-in-differences regression). We offer concrete guidance on how to account for the divergence between causal and estimated effects.