Kailin Chen

Working Papers

1. Ranking Statistical Experiments via the Linear Convex Order and the Lorenz Zonoid: Economic Applications. (supplementary material)

Revise & Resubmit @ Econometrica

Previously circulated under the title ``Experiments in the Linear Convex Order".

 Extended abstract in EC’25.

This paper introduces a novel ranking of statistical experiments, the linear-Blackwell (LB) order, which can equivalently be characterized by (i) the dispersion of the induced posterior and likelihood ratios in the sense of the linear convex order, (ii) the size of the Lorenz zonoid (the set of statewise expectation profiles), or (iii) the variability of the posterior mean. We apply the LB order to compare experiments in binary-action decision problems and in decision problems with quasi-concave payoffs, as analyzed by Kolotilin, Corrao, and Wolitzky (2025). We also use it to compare experiments in moral hazard problems, building on Holmström (1979) and Kim (1995), and in screening problems with ex post signals.

2. Communication as Voting.

Previously circulated under the title ``Learning from Strategic Sources".

 Extended abstract in EC’24.

This paper analyzes a cheap-talk model with multiple senders and one receiver. Each sender observes a noisy signal about an unknown state and sends a message; the receiver observes the message tally and chooses a policy. This setting shares certain features with voting models (e.g., Feddersen and Pesendorfer, 1997, 1998). The existing literature (e.g., Levit and Malenko, 2011; Battaglini, 2017) focuses on scenarios in which the receiver and the senders agree on the preferred policy in each state. In contrast, we explore environments in which the receiver and the senders disagree over the preferred policy in some states. We establish an equilibrium no-conflict result: in any non-babbling equilibrium, the senders and the receiver agree on the preferred policy at every realized message tally. We show that information aggregation fails, and the receiver cannot fully learn the state even as the number of senders grows large. We also identify a discontinuity in information transmission relative to the implications of the existing literature. Finally, introducing a mediator can improve information transmission and restore efficiency.

3.  Collective Experimentation with Correlated Payoffs.

Revise & Resubmit @ Theoretical Economics

This paper studies an exponential bandit model in which a group of agents collectively decide whether to undertake a risky action. This action is implemented if the fraction of agents voting for it exceeds a predetermined threshold. Building on Strulovici (2010), which assumes the agents' payoffs are independent, we explore the case in which the agents' payoffs are correlated. During experimentation, each agent learns individually whether she benefits from the risky action; in this way, she also gains information about its overall desirability. Furthermore, each agent is able to learn indirectly from the others, because in making her decisions, she conditions on being pivotal (i.e., she assumes her vote will determine the collective outcome). We show that, when the number of agents is large, increasing the threshold for implementing the risky action leads to increased experimentation. However, information regarding the overall desirability of the risky action is effectively aggregated only if the threshold is sufficiently low. 

4.  Fishing for Approval. (with Stephan Lauermann and  Mehmet Ekmekci)

Submitted

This paper analyzes situations in which a candidate requires a single endorsement from one of a group of approval agencies and undertakes a costly search to obtain it. The candidate's ability to approach multiple agencies in succession and ``fish'' for approval exempts high-quality candidates from accidental rejections but enables low-quality candidates to obtain erroneous approvals. While the possibility of fishing hurts the agencies in some particular cases, it will be generally beneficial for them. In particular,  when the number of agencies becomes large, the outcome approaches the agencies' first-best outcome.

Short Notes

1.  Quasi‑Concavity, Convexity of Optimal Actions, and the Local Single‑Crossing Property.