signaling with private monitoringnew

Signaling with Private Monitoring

We study dynamic signaling when the informed party does not observe the signals generated by her actions. A long-run player signals her type continuously over time to a myopic second player who privately monitors her behavior; in turn, the myopic player transmits his private inferences back through an imperfect public signal of his actions. Preferences are linear-quadratic and the information structure is Gaussian. We construct linear Markov equilibria using belief states up to the long-run player’s second-order belief. Because of the private monitoring, this state is an explicit function of the long-run player’s past play. A novel separation effect then emerges through this second-order belief channel, altering the traditional signaling that arises when beliefs are public. Applications to models of leadership, reputation, and trading are examined.

verifying and sharing500

Fake News in Social Media: A Supply and Demand Approach

We introduce a model of a platform in which users encounter news of unknown veracity. Users vary in their propensity to share news and can learn the veracity of news at a cost. In turn, the production of fake news is both more sensitive to sharing rates and cheaper than its truthful counterpart. As in traditional markets, the prevalence of fake news is determined by a demand and a supply of misinformation. Unlike traditional markets, the exercise of market power is generally limited unless segmentation methods are employed. Combating fake news by lowering verification costs can be ineffective due to the demand for misinformation only weakly reducing, while the use of algorithms that imperfectly filter news for users can lead to more prevalence and diffusion of misinformation. Our findings highlight the important role that natural elasticity measures have for policy evaluation. 

A Note on the Comparative Statics of Optimal Procurement Auctions

We find a sufficient condition such that a distributional upgrade on a seller’s cost distribution implies a lower expected procurement cost for a buyer. We also show that even under the strongest assumption about this upgrade made in the literature so far, the seller can be worse off, even if this upgrade is costless.