This dissertation consists of three essays examining the impact of information asymmetries in context of entrepreneurship and finance. Chapter 2, coauthored with Silvana Krasteva and Liad Wagman, focuses on the asymmetries between a firm and its (researcher) employee and studies the problem faced by a (researcher) employee when choosing whether to pursue an innovative idea as part of his employment at a firm or to form a start-up. An idea by its stand-alone value and by the degree of (positive or negative) externality that it may impose on the employing firm’s existing profits if brought to market. The employee has private information about the innovation and his ability to independently develop it. Internal exploration, while allowing the employee to take advantage of any exploration support offered by the firm, reduces the employee’s claim over his idea. We find that external exploration takes place for ideas weakly related to the firm’s existing offerings, with other ideas being explored internally. We show that if the firm increases its support for exploration, it can induce the internal research of a wider range of ideas; however, by doing so, the firm also increases the likelihood of employees departing to pursue independent ventures at a later stage of development. Chapter 3 analyzes the benefits of reducing information asymmetry in the credit markets. In their attempt to make more informed decisions, lenders of- ten use a variety of information contained in a borrower ’s credit report. We find that if a borrower expects his future lenders to base their decisions not only on his repayment history but also on other factors like his income, length of history, etc., then his incentives to repay his present loan are weakened. In this case, he is more likely to strategically default on his loan especially for very high levels of interest rates. However, use of this extra information assists the lender in expeditious screening of the borrowers. Based on our results, we recommend that, in order to minimize defaults, more repayment history based products should be offered by the lenders. Evidence supporting the validity of this recommendation is provided in Chapter 4, coauthored with Vijetha Koppa. Using data from Prosper.com, we analyze the effect of reporting repayment histories to an additional credit bureau on borrowers’ default rates and lenders’ internal rates of return. A differences- in-differences comparison between high risk and low risk borrowers reveals that for high risk borrowers, the default rates were 9 to 11 percentage points greater and the internal rates of return were 13 percentage points lower in the pre-change period.

This research provides improved support for missing data in the relational model and relational database systems. There is a need for a systematic method to represent and interpret missing data values in the relational model. A system that processes missing data needs to enable making reasonable decisions when some data values are unknown. The user must be able to understand query results with respect to these decisions. While a number of approaches have been suggested, none have been completely implemented in a relational database system. This research describes a missing data model that works within the relational model, is implemented in MySQL, and was validated by a user feasibility study.

This dissertation comprises three essays. The theme that unifies them is "experiments on corruption and preferences." The first essay (chapter 2) reports theory-testing experiments on the effect of yardstick competition (a form of government competition) on corruption. The second essay (chapter 3) reports theory-testing experiments on the effect of efficiency and transparency on corruption. Furthermore, this essay revisits the yardstick competition question by implementing an alternative experimental design and protocol. Finally, the third essay (chapter 4) reports a theory-testing randomized field experiment that identifies the causes and consequences of corruption. The first essay finds the following. Theoretically, the paper derives a main proposition which suggests that institutions with more noise give rise to an increase in corrupt behavior and a decrease in voter welfare. Empirically, the paper finds a few key results. First, there are an initial nontrivial proportion of good incumbents in the population. This proportion goes down as the experiment session progresses. Secondly, a large proportion of bad incumbents make theoretically inconsistent choices given the assumptions of the model. Third, overall evidence of yardstick competition is mild. Yardstick competition has little effect as a corruption-taming mechanism when the proportion of good incumbents is low. Namely, an institution that is characterized by a small number of good incumbents has little room for yardstick competition, since bad incumbents are likely to be replaced by equally bad incumbents. Thus, incumbents have less of an incentive to build a reputation. This is also the case in which (1) yardstick competition leads to non-increasing voter welfare and (2) voters are more likely to re-elect bad domestic incumbents. Finally, a partitioning of the data by gender suggests that males and females exhibit different degrees of learning depending on the payoffs they face. Furthermore, male voter behavior exhibits mild evidence of yardstick competition when voters face the pooling equilibrium payoff. The second essay finds the following. First, efficiency is an important determinant of corruption. A decrease in efficiency makes it more costly for incumbents to "do the right thing." This drives them to divert maximum rents. While voters retaliate slightly, voters tend to be worse off. Secondly, increased lack of a particular form of transparency (as defined in terms of an increase in risk in the distribution of the unit cost) leaves corrupt incumbent behavior unchanged. In particular, if the draw of the unit cost is unfavorable, incumbents tend to be less corrupt. Third, there is strong evidence of yardstick competition. On the incumbent's side, yardstick competition acts as a corruption-taming mechanism if the incumbent is female. On the voter's side, voters are less likely to re-elect the incumbent in the presence of yardstick competition. Specifically, voters pay attention to the difference between the tax signal in their own jurisdiction and that in another. As this difference increases, voters re-elect less. This gives true meaning to the concept of "benchmarking." Finally, the analysis sheds light on the role of history and beliefs on behavior. Beliefs are an important determinant of incumbents' choices. If an incumbent perceives a tax signal to be associated with a higher likelihood of re-election, he is more likely to choose it. On the voter's side, history tends to be important. In particular, voters are more likely to vote out incumbents as time progresses. This suggests that incumbents care about tax signals because they provide access to re-elections while voters use the history of taxes and re-elections in addition to current taxes to formulate their re-election decisions. Finally, the third essay finds the following. First, 19.08% of mail is lost. Secondly, money mail is more likely to be lost at a rate of 20.90% and this finding is significant at the 10% level. This finding suggests that loss of mail is systematic (non-random), which implies that this type of corruption is due to strategic behavior as opposed to plain shirking on the part of mail handlers. Third, we find that loss of mail is non-random across other observables. In particular, middle-income neighborhoods are more likely to experience lost (money) mail. Also, female heads of household in low-income neighborhoods are more likely to experience lost mail while female heads of household in high-income neighborhoods are much less likely to experience lost (money) mail. Finally, this form of corruption is costly to different stakeholders. The sender of mail bears a direct and an indirect cost. The direct cost is the value of the mail. The indirect cost is the cost of having to switch carriers once mail has been lost. Corruption is also costly to the intended mail recipient as discussed above. Finally, corruption is costly the mail company (SERPOST) in terms of lost revenue and to society in terms of loss of trust. Overall, the findings suggest that public-private partnerships need not increase efficiency by reducing corruption; particularly, when the institution remains a monopoly. Increased efficiency in mail delivery is likely to require (1) privatization and (2) competition; otherwise, the monopolist has no incentive to provide better service and loss of mail is likely to persist.

Credit risk and market risk have already been explored intensively and the reliable models of credit risk and market risk have also been developed progressively. This study try to find a method pricing the CDO (Collateralized Debt Obligation) based on Incomplete information credit model. For the various approaches to CDO valuation, the most widely accepted is the Copula approach. The Copula approach is considered suitable for describing default correlation. Combining with Monte Carlo Simulation, it can price CDO effectively.

This thesis consists of an introduction and five articles. A common theme in all the articles is optimal timing when acting on a financial market. The main topics are optimal selling of an asset, optimal exercising of an American option, optimal stopping games and optimal strategies in trend following trading. In all the articles, we consider a financial market different from the standard Black-Scholes market. In two of the articles this difference consists in allowing for jumps of the underlying process. In the other three, the difference is that we have incomplete information about the drift of the underlying process. This is a natural assumption in many situations, including the case of a true buyer of an American option, trading in a market which exhibits trends, and optimal liquidation of an asset in the presence of a bubble. These examples are all addressed in this thesis.

Social networks constitute a major channel for the diffusion of information and the formation of attitudes in a society. Introducing a dynamic model of social learning, the first part of this thesis studies the emergence of socially influential individuals and groups, and identifies the characteristics that make them influential. The second part uses a Bayesian network game to analyse the role of social interaction and conformism in the making of decisions whose returns or costs are ex ante uncertain.

This thesis is composed of three chapters. Chapter 1 considers the existence of equilibria in games with complete information, where players may have non-ordered and discontinuous preferences. Chapter 2 studies the issues on the existence of pure and behavioral strategy equilibria in games with incomplete information and discontinuous payoffs. We consider the standard setting with Bayesian preferences as well as the case in which players may face ambiguity. Chapter 3 extends the classical results on the Walras-core existence and equivalence to an ambiguous asymmetric information economy, where agents maximize maximin expected utilities (MEU). These results are based on the papers He and Yannelis (2014, 2015a,b,c, 2016a,b). In the first chapter, we propose the condition of "continuous inclusion property" to handle the difficulty of discontinuous payoffs in various general equilibrium and game theory models. Such discontinuities arise naturally in economic situations, including auction, price competition of firms and also patent races. Based on the continuous inclusion property, we establish the equilibrium existence result in a very general framework with discontinuous payoffs. On one hand, this condition is sufficiently general from the methodological point of view, as it unifies almost all special conditions proposed in the literature. On the other hand, our condition is also potentially useful from the realistic point of view, as it could be applied to deal with many economic models which cannot be studied before because of the presence of the discontinuity. In the second chapter, I study the existence problem of pure and behavioral strategy equilibria in discontinuous games with incomplete information. The framework of games with incomplete information is standard as in the literature, except for that we allow players' payoffs to be discontinuous. We illustrate by examples that the Bayesian equilibria may not exist in such games and the previous results are not applicable to handle this problem. We propose some general conditions to retain the existence of both pure strategy and behavioral strategy Bayesian equilibrium, and show that our condition is tight. In addition, we study the equilibrium existence problem in discontinuous games under incomplete information and ambiguity, and show that the maximin framework solves the equilibrium existence issue without introducing any additional condition. In the last chapter, I study a general equilibrium model with incomplete information by adopting the maximin expected utilities. The model is powerful enough to describe the behaviors of risk averse agents that cannot be explained by the standard assumption of subjective expected utilities. I use this new formulation to extend many classical results in general equilibrium theory by incorporating ambiguity into the model. In addition, the desirable incentive compatibility property is shown in our model with maximin expected utilities, while this property will typically fail in the traditional setup. Specifically, the existence results are shown for various equilibrium notions in a general equilibrium model, and the incentives can be guaranteed when all agents use the maximin expected utilities.

This dissertation consists of three essays in Economic Theory. The rst essay proposes and studies a new solution concept for games with incomplete information. In game theory, there is a basic methodological dichotomy between Harsanyi's \game-theoretic" view and Aumann's \Bayesian decision-theoretic" view of the world. We follow the game theoretic view, propose and study interim partially correlated rationalizability for games with incomplete information. We argue that the distinction between this solution concept and the interim correlated rationalizability studied by Dekel, Fudenberg and Morris (2007) is fundamental, in that the latter implicitly follows Aumann's Bayesian view. Our main result shows that two types provide the same prediction in interim partially correlated rationalizability if and only if they have the same in nite hierarchy of beliefs over conditional beliefs. We also establish an equivalence result between this solution concept and the Bayesian solution{a notion of correlated equilibrium proposed by Forges (1993). The second essay studies the relationship between correlated equilibrium the redundancy embedded in type spaces. The Bayesian solution is a notion of correlated equilibrium proposed by Forges (1993), and hierarchies of beliefs over conditional beliefs are introduced by Ely and Peski (2006) in their study of interim rationalizability. We study the connection between the two concepts. We say that two type spaces are equivalent if they represent the same set of hierarchies of beliefs over conditional beliefs. We show that the correlation embedded in equivalent type spaces can be characterized by partially correlating devices, which send correlated signals to players in a belief invariant way. Since such correlating devices also implement the Bayesian solution, we establish that the Bayesian solution is invariant across equivalent type spaces. The third essay studies the existence of equilibria for rst-price sealed bid auctions when bidders form a network and each bidder observes perfectly their neighbors' private valuations. Asymmetry in bidders' positions in the network creates asymmetry in bidders' knowledge. We show the existence of pure-strategy equilibrium. / text

abstract: Bayesian networks are powerful tools in system reliability assessment due to their flexibility in modeling the reliability structure of complex systems. This dissertation develops Bayesian network models for system reliability analysis through the use of Bayesian inference techniques. Bayesian networks generalize fault trees by allowing components and subsystems to be related by conditional probabilities instead of deterministic relationships; thus, they provide analytical advantages to the situation when the failure structure is not well understood, especially during the product design stage. In order to tackle this problem, one needs to utilize auxiliary information such as the reliability information from similar products and domain expertise. For this purpose, a Bayesian network approach is proposed to incorporate data from functional analysis and parent products. The functions with low reliability and their impact on other functions in the network are identified, so that design changes can be suggested for system reliability improvement. A complex system does not necessarily have all components being monitored at the same time, causing another challenge in the reliability assessment problem. Sometimes there are a limited number of sensors deployed in the system to monitor the states of some components or subsystems, but not all of them. Data simultaneously collected from multiple sensors on the same system are analyzed using a Bayesian network approach, and the conditional probabilities of the network are estimated by combining failure information and expert opinions at both system and component levels. Several data scenarios with discrete, continuous and hybrid data (both discrete and continuous data) are analyzed. Posterior distributions of the reliability parameters of the system and components are assessed using simultaneous data. Finally, a Bayesian framework is proposed to incorporate different sources of prior information and reconcile these different sources, including expert opinions and component information, in order to form a prior distribution for the system. Incorporating expert opinion in the form of pseudo-observations substantially simplifies statistical modeling, as opposed to the pooling techniques and supra Bayesian methods used for combining prior distributions in the literature. The methods proposed are demonstrated with several case studies. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2016

This thesis is about game theory, its general application to different games, and its different notions. We are going to focus on how different solutions can be found depending on how we view the game in question. We will particularly focus on games where the information is incomplete. In order to do so, we will use a game named ”The battle of sexes” as a guide throughout the entire thesis. We will adapt that game to the different kinds of games we will talk about. The importance with game theory and why it is an interesting field of study is that it gives a way to mathematically understand and analyse various situations in different other fields and real life areas. In this thesis we will not go deeper into the applications of game theory, but will mostly focus on the mathematical part of the field, and understanding how to find different desired outcomes for a given game. We will primarily lay out the fundamentals of game theory, in order for the reader to understand the basic notions of a game, a equilibria, and have the necessary knowledge to explore the field. Guillermo Owen’s book Game theory covers the field in a wider sense than this thesis, and is an interesting lecture to broaden ones knowledge on game theory.