Research

This paper explores the relationship between market accessibility and various participants’ welfare in an intermediated directed-search market. For a general class of meeting technologies, we provide a necessary and sufficient condition under which efficiency requires imperfect accessibility, such that each seller’s listing is only observed by some but not all buyers. We show that the platform optimally implements the efficient outcome, but fully extracts surplus from the transactions it intermediates. We also find that in general, buyers prefer to minimize market accessibility, while sellers prefer a weakly greater accessibility level than that which is socially efficient. The efficiency of imperfect accessibility is robust to the introduction of a second chance for unmatched buyers to search. 

We study the impact of a dominant incumbent’s acquisition on entry and R&D incentives in a model with multiple startups. The incumbent’s acquisition directly suppresses entry and can distort the non-target startup’s R&D incentives by creating a kill zone. The reduced threat of entry can also cause the incumbent to shelve the acquired technology. Despite these negative effects, acquisitions generally affect consumer welfare ambiguously due to synergy benefits. We study the design of merger policies aimed at minimizing acquisition-related harms. We also show that entry-for-buyout may not be a valid defence for startup acquisitions when accounting for non-target startups.

Sender maximizes how many receivers buy a widget of uncertain quality. She optimally chooses to target a receiver with whom to communicate. After communication, the target chooses whether to buy the widget and his choice is observed by other receivers with probability increasing in his popularity. We show that, independently of the Sender-target communication protocol, Sender optimally communicates with the target as if no other receiver exists, and a target's popularity is a double-edged sword for Sender.  We characterize the optimal choice of target under multiple protocols and establish that Sender can benefit from protocols that constrain her communication more.

A sender conveys scarce information to a number of receivers to maximize the sum of receiver payoffs. Each receiver’s payoff depends on the state of the world and an action she takes. The optimal action is state contingent. Under mild regularity conditions, we show that the payoff of each receiver is convex in the amount of information she receives. Thus, it is optimal for Sender to target information to a single receiver. We then study three extensions in which interior information allocations are optimal.

A principal incentivizes a team of symmetric agents to work on a project by offering them success-contingent bonuses. I assume the equilibrium selected under an incentive scheme is the limit of Level-K thinking. Agents' initial belief about others working, called culture, determines equilibrium selection. I show that a minimum cost incentive scheme which implements work offers a subset of workers the largest bonuses identically, and the remaining workers smaller bonuses. A more hardworking culture reduces the cost of implementing work and increases the number of agents offered the largest bonuses identically. This also implies a shorter bonus hierarchy when bonuses must be public, and more transparent incentives when bonuses can be private. For most cultures, the minimum-cost incentive scheme discriminates between agents both in terms of bonuses and information. Whether the minimum-cost incentive  public or private scheme discriminates more among agents depends on culture.

I study information design in symmetric binary action supermodular games. Agents choose to invest or not, and the designer always prefers higher aggregate investment. I assume the equilibrium selected under an information structure is the limit of Level-K thinking. The initial belief about aggregate investment, called the benchmark, determines equilibrium selection. Designer-preferred and adversarial selection coincide with extreme benchmarks. I show that all outcomes are implemented by information structures that send a fraction of agents identical signals, and others distinct signals. I construct a designer-optimal information structure from this class. I show that under it, raising the benchmark always increases aggregate investment and the fraction of agents receiving identical signals, but often has an ambiguous effect on agents' payoffs. Finally, the designer's loss when limited to public information is lower under higher benchmarks. My work elucidates on how payoff-irrelevant factors, captured by the benchmark, shape optimal information disclosure.

A company makes a take-it-or-leave-it offer to hire a worker. The worker can upskill at a cost after observing the offer. The worker's quality improvement from upskilling, which determines her outside option and the company's hiring benefit, is uncertain, and she observes only a signal of her quality before responding to the offer. We construct a class of information structures which support all second-best outcomes, under which the worker is fully informed if she takes the outside option, and mildly pessimistic if she works for the company. Using these, we find that due to the worker's moral hazard in upskilling, worker-preferred second-best outcomes yield lower total welfare and less upskilling, and the Pareto-frontier may be non-concave. These conclusions are robust to varying the match between the worker's quality and company's benefit, and the timing of upskilling.

We analyse the progressivity and redistributive effects of India’s income tax system utilizing Income Tax Department data for 2011–18. By fitting Lorenz and tax concentration curves to these data, we find that despite exhibiting high levels of progressivity, the redistributive effects of income taxes remain modest amongst tax assessees and miniscule within the adult population. We also find that plugging the gap between statutory and actual average tax rates will do little to improve redistributive effects, and lowering income thresholds for top marginal tax rates offers greater redistributive and revenue potential than reducing exemption limits or increasing top marginal tax rates.