Hierarchical Bayesian Persuasion: Importance of Vice Presidents , Job Market Paper
In this paper, I study strategic information transmission in a hierarchy. Information is transmitted through a chain of agents to a decision maker whose action affects all agents’ payoffs. Each agent in the chain can conceal all or part of the information she receives. I prove that it is possible to focus on simple equilibria, where only the first agent ever conceals information. This allows me to formulate the hierarchical communication as a direct one between the initial sender and the decision maker subject to recursively-defined incentive compatibility constraints imposed by the intermediaries. In the binary-action case, regardless of the number of intermediaries, at most four agents determine the amount of information communicated to the decision maker. In this case, the results in this paper underscore the importance of choosing a pivotal vice president for maximizing the payoff of the decision maker, who is better off by appointing a like-minded but stubborn vice president. Moreover, I provide necessary and sufficient conditions for inefficient equilibria.
Indicator Choice in Pay-for-Performance, with Ali Shourideh and Ariel Zetlin-Jones
We study the classic principal-agent model when the signal observed by the principal is chosen by the agent. We fully characterize the optimal information structure from an agent’s perspective in a general moral hazard setting. Unlike standard information design, only the support of the distribution of beliefs is relevant to the agent. We show that the problem can be mapped into a geometrical game between the principal and the agent in the space of likelihood ratios. We use this representation result to show that coarse contracts are sufficient: The agent can achieve her best with binary signals. Additionally, we characterize conditions under which the agent is able to extract all the surplus and implement the efficient allocation under full information. Finally, we show that when effort and performance are one-dimensional, under a general class of models, threshold signals are optimal.
Pricing and Mergers in Complex Networks: The Case of Natural Gas Pipelines , with Ali Shourideh and Maryam Saeedi
Natural gas is a large and growing share of U.S. energy consumption; based on data from U.S. Energy Information Administration (EIA), in 2021, it accounted for 32% of the primary energy consumption, 38% of the electricity generation, and about half of home heating in the U.S. The transportation of natural gas from producer to consumer, however, is heavily regulated and relatively unexamined by economists. Using an extensive panel of daily data on natural gas flows through interstate pipelines from 2005 to 2016, we take the first steps of analyzing this networked market, We first perform demand estimation to derive price-elasticity of demand in different sectors: residential, commercial, industrial, and electric utility. Our results suggest that while demand in all these sectors is relatively inelastic with respect to the average price, electric utility is the most elastic sector and industrial sector is the most inelastic one. We then investigate one of the largest mergers among natural gas interstate pipelines. Our results suggest that this merger had a significant effect on natural gas transportation prices even though the two pipelines were not in the same physical market. Furthermore, we study the role of storage in the natural gas market and quantify the effect of temperature, storage, and pipeline congestion on natural gas prices. Our results suggest that storage and temperature are the main factors explaining the price shocks in the natural gas market where abundant storage dampens the effect of cold winter weather on natural gas prices. Finally, we explore the network effect in the natural gas market, evaluating the effect of changes in the temperature of one geographical region on all other regions. Our results suggest that a change or shock in one geographical region can have a significant effect on prices even in the farthest regions. This observation can be rationalized by the change of natural gas route in the pipeline network from low-demand regions to high-demand regions.
Work in Progress
Solving the Hierarchical Bayesian Persuasion
In the hierarchical Bayesian persuasion, a simple sufficient condition for the equilibrium amount of information revealed to the decision maker is that no agent prefers any less amount of information. However, this is not a necessary condition. In a work in progress, I study how we can approximate the equilibrium outcome using this observation.
Publications in Electrical and Computer Engineering
Energy-constrained distributed learning and classification by exploiting relative relevance of sensors’ data M. Mahzoon, C. Li, X. Li and P. Grover, in IEEE Journal on Selected Areas in Communications, vol. 34, no. 5, pp. 1417-1430, May 2016
Queue-based broadcast gossip algorithm for consensus S. Kar, R. Negi, M. Mahzoon and A. K. Sahu, 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2016, pp. 1259-1266
Using relative-relevance of data pieces for efficient communication, with an application to neural data acquisition M. Mahzoon, H. Albalawi, X. Li and P. Grover, 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2014, pp. 160-166
Information friction limits on computation P. Vyavahare, M. Mahzoon, P. Grover, N. Limaye and D. Manjunath, 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2014, pp. 93-100
From source model to quantum key distillation: An improved upper bound K. Keykhosravi, M. Mahzoon, A. Gohari and M. R. Aref, Iran Workshop on Communication and Information Theory (IWCIT), 2014, pp. 1-6