Wednesday, 6 December, 2023

Maxim Senkov: Essays in Strategic Information Provision

Dissertation Committee:

Jan Zápal (CERGE-EI, chair)

Ole Jann (CERGE-EI)

Filip Matějka (CERGE-EI)

Defense Committee:

Ctirad Slavík (CERGE-EI, chair)

Yiman Sun (CERGE-EI)

Miroslav Zelený (Faculty of Mathematics and Physics, CU)


Maxim Ivanov, Ph.D. (McMaster University)

Ludmila Matysková, Ph.D. (University of Alicante)

Online connection: https://call.lifesizecloud.com/19809786, passcode: 9861


In the first chapter,  we show that a biased principal can strictly benefit from hiring an agent with misaligned preferences or beliefs. We consider a ``delegated expertise'' problem in which the agent has an advantage in acquiring information relative to the principal.  We show that it is optimal for a principal who is ex ante biased towards one action to select an agent who is less biased. Such an agent is more uncertain ex ante about what the best course of action is and would acquire more information. The benefit to the principal of a better-informed decision always outweighs the cost of a small misalignment. Further, we show that selecting an optimally misaligned agent is a valuable tool that performs on par with optimal contracting (while imposing no additional cost on the principal) and outperforms restricted delegation. Finally, we show that all results continue to hold if the agent has to recommend an action instead of being able to choose it directly.

In the second chapter, I study a game between an agent and a principal in a dynamic information design framework. A principal funds a multistage project and retains the right to cut the funding if it stagnates at some point. An agent wants to convince the principal to fund the project as long as possible, and can design the flow of information about the progress of the project in order to persuade the principal. If the project is sufficiently promising ex ante, then the agent commits to providing only the good news that the project is accomplished. If the project is not promising enough ex ante, the agent persuades the principal to start the funding by committing to provide not only good news but also the bad news that a project milestone has not been reached by an interim deadline. I demonstrate that the outlined structure of optimal information disclosure holds irrespective of the agent's profit share, benefit from the flow of funding, and the common discount rate.

In the third chapter, we study an information design model in which the state space is finite, the sender and the receiver have state-dependent quadratic loss functions, and their disagreement regarding the preferred action is of arbitrary form. This framework enables us to focus on the understudied sender's trade-off between the informativeness of the signal and the concealment of the state-dependent disagreement about the preferred action. In particular, we study which states are pooled together in the supports of posteriors of the optimal signal. We provide an illustrative graph procedure that takes the form of preference misalignment and outputs potential representations of the state-pooling structure. Our model provides insights into situations in which the sender and the receiver care about two different but connected issues, for example, the interaction of a political advisor who cares about the state of the economy with a politician who cares about the political situation.

Full Text: "Essays in Strategic Information Provision"