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Three Essays on Information Economics


Zhang, Qiaoxi (2016) Three Essays on Information Economics. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9TB14WS.


The main theme of my thesis is how uncertainty affects behaviors. I explore how agents seek to resolve uncertainty in different environments. In Chapter 1, agents learn from the messages of informed experts in a signaling game. In Chapter 2, an agent learns about a fixed and uncertain physical environment through dynamic experimentation. In the last chapter, agents learn about others' preferences through the outcome of a central matching mechanism.

Motivated by the question of how opposing political candidates who are policy experts can communicate to voters in a way that helps them win the election, I study a delegation problem with two informed, self-interested agents. Agents make proposals before the decision maker decides to whom to delegate a task. The innovation is that there are multiple issues that the principal and agents care about, and the agents can be vague about any issue in their proposals. Intuition says that agents should be specific about the issues that they are trusted on and vague about other issues. I find the opposite: an agent is disadvantaged by revealing information about certain issues to the decision maker, those on which he is trusted by the principal on. The reason is that doing so enables his opponent to take advantage of this revealed information and undercut him. Essentially, when the principal is on an agent's side for some issue, that agent does not want to be specific, because it creates a visible target for his opponent to react to. He wants to be vague, because that allows the principal's ignorance about the optimal action create an insurmountable obstacle for his opponent. As a result, it is to an agent's advantage to be vague about the issue that he is trusted on.

The second chapter investigates the implication of biased updating in dynamic experimentation such as a firm's R&D process. People exhibit near miss effect during gambling. For example, if the first two wheels of a slot machine indicate a potential final outcome of jackpot but the last wheel indicates a loss, people are motivated to gamble more. An outcome that is close to a success but is still a failure is called a "near miss." In this chapter, I explain the near miss effect in a firm's repeated R&D process. There are two factors that sequentially affect the profitability of R&D, both of which are uncertain. First is whether the R&D team is skilled enough to make a technical breakthrough. If a breakthrough occurs, then a second factor comes into play, which is whether the market demand is high enough to make the product profitable. Moreover, good news for the first stage is a prerequisite for learning about the second stage. In each one of the infinite periods, the decision maker of the firm decides whether to involve in risky R&D and observe whether the outcome is a failure (no breakthrough), a success (with breakthrough and high market demand), or a near miss (with breakthrough but low market demand). I assume that the decision maker of the firm learns about the skill of the team properly, but when she updates about the market demand, she updates incorrectly and overweighs her prior. In particular, her posterior about the market demand is a convex combination of her prior and the Bayesian posterior. This bias affects the relative updating of the two factors, which gives rise to the near miss effect: after a near miss is observed, the decision maker values doing R&D more than before although she has received no payoff.

I show that if the decision maker is sufficiently biased and overweighs her prior enough, then she exhibits the near miss effect. I also compare the near miss effect for decision makers with different degrees of biases. As it turns out, the more biased a decision maker is, the more sever she exhibits the near miss effect. However, given the decision maker's belief about the two factors, the more biased she is, the less she values R&D. Consequently, the value of R&D is highest for a Bayesian.

In the last chapter, I study how well a centralized matching mechanism works when agents do not know others' preferences. I consider a standard two-sided marriage matching problem, except that agents only know their own preferences. Roth(1989) proved by an example the non-existence of a mechanism with at least one stable equilibria. In his proof, an agent is allowed to report a preference that is realized with ex ante zero probability, which violates the setup of a Bayesian game. Instead, by restricting agents to report only preferences with positive realization probabilities, I show that Roth's result still holds. More interestingly, as long as agents are allowed to form blocking pairs after a matching outcome is announced, the final outcome is always stable with respect to the true preferences. This means that even when the mechanism fails to produce a stable outcome, it can still release enough information for agents to initialize a blocking pair, which induces a stable outcome.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:information economics; competition in delegation; experimentation; matching
Degree Grantor:California Institute of Technology
Division:Humanities and Social Sciences
Major Option:Social Science
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Echenique, Federico
Thesis Committee:
  • Echenique, Federico (chair)
  • Yariv, Leeat
  • Agranov, Marina
  • Palfrey, Thomas R.
Defense Date:4 May 2016
Non-Caltech Author Email:jdzhangqx (AT)
Record Number:CaltechTHESIS:05272016-192342051
Persistent URL:
Zhang, Qiaoxi0000-0002-3139-7659
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9806
Deposited By: Qiaoxi Zhang
Deposited On:04 Jun 2016 00:48
Last Modified:04 Oct 2019 00:13

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