Kailin Chen

Job Market Paper

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

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, equivalently characterized by (i) more dispersed posteriors and likelihood ratios in the sense of the linear convex order, (ii) a larger Lorenz zonoid—the set of statewise expectation profiles, and (iii) greater variability of the posterior mean. We apply the LB order to compare experiments in binary-action decision problems and in problems with quasiconcave payoffs, as analyzed by Kolotilin, Corrao, and Wolitzky (2025). Furthermore, the LB order enables the comparison of experiments in moral hazard problems, complementing the findings in Holmström (1979) and Kim (1995). Finally, the LB order applies to the comparison of experiments generating ex post signals in screening problems.

Working Papers

1.   Communication with Multiple Senders.

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

 Extended abstract in EC’24.

This paper analyzes a cheap talk model with one receiver and multiple senders. Each sender observes a noisy signal regarding an unknown state of the world. Existing literature (e.g., Levit and Malenko, 2011; Battaglini, 2017) focuses on scenarios where the receiver and senders have aligned preferences in each state. We further explore situations with disagreement states in which the receiver and the senders have misaligned preferences. We first show that, when the number of senders grows large, each sender's message must convey almost no information to the receiver. Furthermore, we identify a discontinuity in information transmission: with moderate conflict between the receiver and the senders, introducing an arbitrarily small probability of disagreement states causes complete unraveling, contrary to full learning predicted by the literature. Finally, we demonstrate that the receiver cannot fully learn the state even when receiving messages from arbitrarily many senders.

2.  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. 

3.  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 generally be beneficial for them. In particular,  when the number of agencies becomes large, the outcome approaches the agencies' first-best outcome.

4. Quasi‑Concavity, Convexity of Optimal Actions, and the Local Single‑Crossing Property. (draft available upon request)