Reputation, Learning and Project Choice in Frictional Economies

I introduce a dynamic model of learning and random meetings between a long-lived agent with unknown ability and heterogenous projects with observable types. There is incomplete yet symmetric information about the agent's ability. She needs to accept the contacting projects and create success to learn her type. Alternatively, lack of success during a match leads to a reputational loss followed from Bayesian learning, in that the reputation is interpreted as the posterior belief about the agent's ability. Developing a self-type learning framework with endogenous outside option, I find the optimal matching strategy of the agent, that determines what types of projects the agent with a certain level of reputation will accept. Comparing with a perfect information benchmark, I show learning incentives lead to larger matching sets in the optimum

Risk minimization and portfolio diversification

We consider the problem of minimizing capital at risk in the Black-Scholes setting. The portfolio problem is studied given the possibility that a correlation constraint between the portfolio and a financial index is imposed. The optimal portfolio is obtained in closed form. The effects of the correlation constraint are explored; it turns out that this portfolio constraint leads to a more diversified portfolio

Binary Mechanisms under Privacy-Preserving Noise

We study mechanism design for public-good provision under a noisy privacy-preserving transformation of individual agents' reported preferences. The setting is a standard binary model with transfers and quasi-linear utility. Agents report their preferences for the public good, which are randomly ``flipped,'' so that any individual report may be explained away as the outcome of noise. We study the tradeoffs between preserving the public decisions made in the presence of noise (noise sensitivity), pursuing efficiency, and mitigating the effect of noise on revenue

Essays in Venture Capital, Reputation and Learning

In chapter 1, I study the experimentation dynamics of a decision maker (DM) in a two-armed bandit setup ([5]), where the agent holds ambiguous beliefs regarding the distribution of the return process of one arm and is certain about the other one. The DM entertains Multiplier preferences à la [27], thus I frame the decision making environment as a twoplayer differential game against nature in continuous time. I characterize the DM’s value function and her optimal experimentation strategy that turns out to follow a cut-off rule with respect to her belief process. The belief threshold for exploring the ambiguous arm is found in closed form and is shown to be increasing with respect to the ambiguity aversion index. I then study the effect of provision of an unambiguous information source about the ambiguous arm. Interestingly, I show that the exploration threshold rises unambiguously as a result of this new information source, thereby leading to more conservatism. This analysis also sheds light on the efficient time to reach for an expert opinion. The results of this chapter has been recently published in [61].In chapter 2, I introduce a dynamic model of random search where ex ante heterogeneous venture capitalists (investors) with unknown abilities match with a variety of startups (projects). There is incomplete yet symmetric information about investors’ types, whereas the projects’ types are publicly observable to all investors. In the unique stationary equilibrium, the matching sets, value functions and steady state distributions are endogenously determined. Interpreting the market posterior belief about the venture capitalists’ ability as their reputation, I study the outcomes of the economy when the success or failure of the projects create feedback effects: innovation spillovers and reputational externalities. When there are positive spillovers from successful early stage projects to late stage business opportunities, I show increased levels of search frictions could save the market from breakdown caused by the neglect of spillover effect. When the reputational externality is at play, namely when the deal flow of each investor is inversely impacted by the distribution of other investors’ reputation, I show the proportion of the high ability inactive investors is inefficiently high, and the projects suffer from early termination