Browsing by Subject "Economics, Theory"

In many multiagent settings, a decision must be made based on the preferences of multiple agents, and agents may lie about their preferences if this is to their benefit. In mechanism design, the goal is to design procedures (mechanisms) for making the decision that work in spite of such strategic behavior, usually by making untruthful behavior suboptimal. In automated mechanism design, the idea is to computationally search through the space of feasible mechanisms, rather than to design them analytically by hand. Unfortunately, the most straightforward approach to automated mechanism design does not scale to large instances, because it requires searching over a very large space of possible functions. In this thesis, we adopt an approach to automated mechanism design that is computationally feasible. Instead of optimizing over all feasible mechanisms, we carefully choose a parameterized subfamily of mechanisms. Then we optimize over mechanisms within this family. Finally, we analyze whether and to what extent the resulting mechanism is suboptimal outside the subfamily. We apply (computationally feasible) automated mechanism design to three resource allocation mechanism design problems: mechanisms that redistribute revenue, mechanisms that involve no payments at all, and mechanisms that guard against false-name manipulation.

I characterize optimal long term contracts offered by a monopolist to a buyer whose private valuation evolves according to a branching process with privately known transition probability. The optimal contract can be implemented in a simple way, and presents the buyer with a tradeoff between a high initial fixed fee and low future prices. In an interaction with a long time horizon, the relationship will terminate prematurely with probability close to one. Optimal mechanisms are quite different from models in which the transition probability is known, and the buyer's private information is his initial valuation. Optimal contracts resemble the structure of term life insurance contracts, and have features similar to actual interactions between retailers and suppliers.

This dissertation uses game theoretic models to examine the effects of agent anonymity on markets for goods and for information. In open, anonymous settings, such as the Internet, anonymity is relatively easy to obtain --- oftentimes another email address is sufficient. By becoming anonymous, agents can participate in various mechanisms (such as elections, opinion polls, auctions, etc.) multiple times. The first chapter (joint work with Vincent Conitzer) studies elections that disincentivize voters from voting multiple times. A voting rule is false-name-proof if no agent ever benefits from casting additional votes. In elections with two alternatives, it is shown that there is a unique false-name-proof voting rule that is most responsive to votes. The probability that this rule selects the majority winner converges to 1 as the population grows large. Methods to design analogous rules for elections with 3 or more alternatives are proposed. The second chapter (also joint work with Vincent Conitzer) extends the analysis in the first chapter to broader mechanism design settings, where the goal is to disincentivize agents from participating multiple times. The cost model from the first chapter is generalized and revelation principles are proven. The third chapter studies a setting where firms are able to recognize their previous customers, and may use information about consumers' purchase histories to price discriminate (which may incentivize consumers to be anonymous). The formal model considers a monopolist and a continuum of heterogeneous consumers, where consumers are able to maintain their anonymity at some cost. It is shown that when consumers can costlessly maintain their anonymity, they all individually choose to do so, which paradoxically results in the highest profit for the monopolist. Increasing the cost of anonymity can benefit consumers, but only up to a point; at that point, the effect is reversed. Some of the results are extended to a setting with two competing firms selling differentiated products. Finally, the cost of maintaining anonymity is endogenized by considering a third party that can make consumers anonymous for a fee of its choosing. It is shown that this third party would prefer to be paid by the firm for allowing consumers to costlessly maintain their anonymity.

This work analyzes the impact of regulation policies in two distinct settings.

Chapter 1 provides an overview of the existing theoretical literature on innovation and entrepreneurship. It summarizes some of the main findings of the effect of various means of protecting intellectual property on the innovation incentives and the level of entrepreneurship activity. A general observation is that much of the existing work compares the extremes of no protection and perfect protection and the resulting prediction is that perfect protection leads to higher innovation incentives. This is puzzling in light of the empirical evidence that shows the opposite trend. Chapter 2 explicitly takes into account the fact that patent protection is imperfect and likely to lie in between the two extremes. In addition, in more than 70% of infringement cases in the U.S., infringement damages are calculated according to the so-called reasonable royalties rule that essentially awards a portion of the imitator's realized revenues to the innovator. I show that incorporating these two facts result in a non-monotonic relationship between the patent strength and R&D investment if one moves from zero protection to perfect protection in a continuous way. The intuition is that when protection is less than perfect, though not zero, equilibrium may involve both imitation and damages. Viewing damages as an alternative source of profits, the innovator may be less aggressive in pursuing R&D as patents become stronger. This result has important welfare implications. Besides the well-known effect of reducing welfare due to less competitive markets, stronger protection can further curtail welfare by decreasing R&D investment.

Chapter 3, coauthored with Professor Huseyin Yildirim, studies situations, in which one buyer sequentially negotiates with multiple suppliers to acquire goods or services that are either complements or substitutes to each other. We find that the buyer weakly prefers private negotiations because it creates strategic uncertainty about the outcomes from earlier negotiations, leading to less aggressive pricing. For substitutes, this strategic uncertainty is more beneficial for short expiries because long ones allow purchasing decisions to be made after all negotiations are over, creating enough competition on their own and leading to Bertrand prices. In contrast to substitutes, for which suppliers are in direct competition, complements create incentives for suppliers to coordinate their prices to extract the additional surplus resulting from the complementarities of their goods. In this case, introducing uncertainty through privacy is more beneficial for the buyer as suppliers' bargaining powers increase vis-á-vis the buyer because it creates greater coordination concerns. This leads to a somewhat surprising result that the buyer could benefit from negotiating with more powerful suppliers. The model enables an evaluation of certain laws and regulations that govern bilateral negotiations. For instance, open record/open meetings laws, setting rules on public access of information, generate efficient outcomes, but in general are harmful to the buyer. Similarly, the FTC's cooling-off rule sets long expiries by giving the buyer three days to cancel a contract, which generates efficient outcomes when goods are substitutes because of suppliers' Bertrand pricing, but reduces efficiency when goods are complements since long expiries make coordination harder to sustain.

This dissertation computes the optimal monetary and fiscal policy for small open and emerging economies in an estimated medium-scale model. The model departs from the conventional approach as it encompasses all the major nominal and real rigidities normally found in the literature in a single framework. After estimating the model using Bayesian techniques for one small open economy and one emerging economy, the Ramsey solution for the optimal monetary and fiscal policy is computed. Results show that foreign shocks have a strong influence in the dynamics of emerging economies, when compared to the designed optimal policy for a developed small open economy. For both economies, inflation is low, but very volatile, while taxes follow the traditional results in the literature with high taxes over labor income and low taxes for capital income.