Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
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.