Dynamic persuasion

I develop a model of dynamic persuasion. A sender has a …xed number of pieces of hard evidence that contains information about the quality of his proposal, each of which is either favorable or unfavorable. The sender may try to persuade a decision maker (DM) that she has enough favorable evidence by sequentially revealing at most one piece at a time. Presenting evidence is costly for the sender and delaying decisions is costly for the DM. I study the equilibria of the resulting dynamic communication game. The sender e¤ectively chooses when to give up persuasion and the DM decides when to make decision. Resolving the strategic tension requires probabilistic behavior from both parties. Typically, the DM will accept the sender’s proposal even when she knows that the sender’s evidence may be overall unfavorable. However, in a Pareto e¢ cient equilibrium, the other type of error does not occur unless delays costs are very large. Furthermore, the sender’s net gain from engaging in persuasion can be negative on the equilibrium path, even when persuasion is successful. I perform comparative statics in the costs of persuasion. I also characterize the DM’s optimal stochastic commitment rule and the optimal non-stochastic commitment rule; compared to the communication game, the former yields a Pareto improvement whereas the latter can leave even the DM either better or worse o¤. JEL Classi…cation: D82, D83. I am grateful to Navin Kartik for his continuous encouragement and advice through my Ph.D. life. I am also grateful to Bogachan Celen and Yeon-Koo Che. I thank Simon Board, Alessandra Casella, Qingmin Liu, Marcos Nakaguma, Bernard Salanie, Joel Sobel, Satoru Takahashi, Yuya Takahashi, Makoto Yano, and Tim Van Zandt for their comments. yColumbia University, 420 West 118th Street, New York, NY 10027; email: th2227@columbia.edu; Web: http://www.columbia.edu/~th2227/index.html.