# Identifying the Effect of Persuasion

## TL;DR

This paper clarifies the causal interpretation of persuasion measures, showing that common metrics often overestimate true persuasion effects, and introduces new parameters and methods for accurate causal inference.

## Contribution

It formally defines the causal persuasion rate using the potential outcome framework and develops methods for its identification and estimation.

## Key findings

- Common persuasion measures often overstate the true causal effect.
- The paper provides practical methods for accurate causal inference of persuasion.
- It introduces new parameters of interest for measuring persuasion effects.

## Abstract

This paper examines a commonly used measure of persuasion whose precise interpretation has been obscure in the literature. By using the potential outcome framework, we define the causal persuasion rate by a proper conditional probability of taking the action of interest with a persuasive message conditional on not taking the action without the message. We then formally study identification under empirically relevant data scenarios and show that the commonly adopted measure generally does not estimate, but often overstates, the causal rate of persuasion. We discuss several new parameters of interest and provide practical methods for causal inference.