Maxim Senkov

I am a researcher at the European Research University (ERUNI) in Ostrava, Czech Republic. I obtained my PhD in Economics from CERGE-EI in Prague. In 2022, I visited the Department of Economics at the University of Oxford as a Recognised Student. 

I am an applied economic theorist specializing in information economics. 

Research interests: information design, costly information acquisition, dynamic incentive problems.

References:                                                 

Jan Zápal (CERGE-EI, Chair),            

Ole Jann (CERGE-EI),                            

Inés Moreno de Barreda (Oxford),

 Filip Matějka (CERGE-EI)                   

Curriculum Vitae

email: maxim.senkov(at)eruni(dot)org

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This summer, I will be presenting at:

Working papers

Optimally Biased Expertise (with Andrei Matveenko, Pavel Ilinov, and Egor Starkov)

Revise and Resubmit at the Economic Journal

Abstract. 

This paper shows that a biased principal can strictly benefit from delegating to a misaligned agent. We consider a “delegated expertise” problem in which the agent has a learning advantage 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 from a more informed decision always outweighs the cost of a small misalignment.

Abstract.

We compare two scenarios in a model where politicians offer local public goods to heterogeneous voters: one where politicians have access to data on voters and thus can target specific ones, and another where politicians only decide on the level of spending. When the budget is small, or the public good has a high value, access to voter information leads the winner to focus on poorer voters, enhancing voter welfare. With a larger budget or less crucial public goods, politicians target a narrow group of swing voters, which harms the voter welfare.

Abstract. 

We study a Bayesian persuasion model with two-dimensional states of the world, in which the sender (she) and receiver (he) have heterogeneous prior beliefs and care about different dimensions. The receiver is a naive agent who has a simplistic worldview: he ignores the dependency between the two dimensions of the state. We provide a characterization for the sender's gain from persuasion both when the receiver is naive and when he is rational. We show that the receiver benefits from having a simplistic worldview if and only if it makes him perceive the states in which his interest is aligned with the sender as less likely.

Abstract. 

In a continuous-time moral hazard problem, an agent chooses to start shirking either if the multistage project is completed or if the project is unlikely to be completed before the final date. A principal wants to convince the agent to incur effort as long as possible and can design the flow of information about the progress of the project to persuade the agent. If the project is sufficiently promising ex ante, then the principal commits to providing only the good news that the project is accomplished. If the project is not promising enough ex ante, the principal persuades the agent to start incurring effort by committing to provide not only good news but also bad news that a project milestone has not been reached by an interim date. We show that it is optimal for the principal to promise immediate provision of the good news and to release the bad news at a deterministic date - an interim deadline. The model sheds light on a supervisor-supervisee relationship in scientific research.

Abstract. 

We study a Bayesian persuasion 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.

Work in progress

 A Theory of Democratic Backsliding (with Artyom Jelnov)