Abstract This paper shows that collusive behavior of firms in production with lump-sum payment licensing may occur in an infinitely repeated duopoly if both firms adopt a two-period strategy to interact with each other. It is profitable for the patent-holding firm with non-drastic cost-reducing innovation to use licensing as a strategic means to induce the opponent to cooperate in pursuit of joint profit. It is proved that there exists a Pareto dominant two-period strategy profile, which is an equilibrium in both equilibrium and out-of-equilibrium paths. Furthermore, it is shown that the duration of punishment while two firms are in the out-of-equilibrium is endogenously determined.

ABSTRACT This dissertation constructs three strategic trade models. The first model is a single-shot two-stage game model of intra-industry trade with trade retaliation against government provided export subsidies and lobbying by foreign firm on domestic government¡¦s import tariff. The second model is an infinite repeated game model of intra-industry where the history of government and firm interaction is the basis for constructing trade strategies. The third model is a single-shot three-stage game model of intra-industry trade with the linkage between domestic and foreign intermediate-input and final-good industries and the choice of optimal export subsidies in the two industries for two governments. Chapter 1 introduces the motivation, objectives, framework, and literature review of this dissertation. The literature review is organized as follows. Initially we review the foundations of the basic intra-industry trade model, where our model is rooted. Next we present the more significant papers that describe the sensitivity of the basic model, because our repeated game model will show yet another way that the basic model is sensitive. Next we present some dynamic game theoretic results, which we use to construct our repeated game model. Finally, we review some papers related to intermediate input and strategic trade. The first model is developed in Chapter 2. We discover that there are two perfect strategy subgame perfect equilibria in this model. And then an import tariff is available, and using that tariff will remove the benefits originally conferred by an export subsidy. Active trade policy is not eliminated by the two governments and tariff policy is larger than subsidy policy. Hence, an import tariff will more than offset the anticipated gains from a subsidy policy. There is no reason to believe that one equilibrium is better or more likely than another, because the highest payoffs equilibrium of the two governments and domestic firm is not the best payoff equilibrium of the foreign firm. We used the single-shot game model of Chapter 2 and molded it into a repeated game in Chapter 3. First, we found the set of Nash equilibria toward solving the repeated game model. Second, we only focused on the subgame perfect equilibria from the infinite Nash equilibria¡¦s set. We used the result in Fudenberg and Maskin (1986) to define the subgame perfect equilibria. Third, we showed that in the repeated game a subgame perfect strategy of free trade can increase all players¡¦ payoffs which are better than the single-shot game equilibrium payoffs. Chapter 4 develops the third model. We observe how domestic and foreign governments choose their optimum export subsidy policies for their intermediate input and final good production by using the linkage between domestic and foreign intermediate-input and final-good industries under the condition of vertical specialization. The result indicates that under the condition of vertical specialization, the two governments will choose positive export subsidies for their final goods while they will give no subsidies for their intermediate inputs. Chapter 5 presented the implications of vertical specialization on the cross-strait economy and trade. To maintain the competitive advantage of Taiwan economy and smoothly upgrade industry structure, transferring the labor-intensive industry and the labor-intensive production sections to China seems an optimum choice under the principle of comparative advantages. Nevertheless, for Taiwan, the upgrade of local industries has never stopped, but with the acceleration of industrial relocation, the transformation of production and trade structures are also taking place. The impact carried by this transformation is extensive and profound. In addition to obvious impact on the economic perspective, if the structure of employment market cannot react in time, a great social cost may be incurred. How to utilize the edge of industrial specialization between the Strait to strengthen Taiwanese industries¡¦ competitive, enhance product development ability through cooperation with multinational enterprises, dominate product development, and establish a center of task division for regional industries can be one of the main focuses in the development of Taiwan¡¦s industrial policy.

京都大学 / 0048 / 新制・課程博士 / 博士(経済学) / 甲第21526号 / 経博第594号 / 新制||経||289(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 関口 格, 准教授 菊谷 達弥, 教授 原 千秋 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DGAM

<p>Selfish routing is frequently discussed. The general framework of a system of non-cooperative users can be used to model many different optimization problems such as network routing, traffic or transportation problems.</p> <p>It is well known that the Wardrop user equilibria (i.e. the user optima) generally do not optimize the overall system cost in a traffic routing problem.</p> <p>In order to induce the equilibrium flow to be as close to the optimal flow as possible, the term “toll” is introduced. With the addition of tolls, a traffic system does not show the actual cost to the users but the displayed cost of users, which is the summation of the actual cost and the toll. A common behavioral assumption in traffic network modeling is that every user chooses a path which is perceived as the shortest path, then the whole system achieves the equilibrium of the displayed cost. It is proved that there exists an optimal toll which can induce the equilibrium flow under displayed cost to be the optimal flow in reality.</p> <p>However, this conclusion holds only if the selfish routing executes only once. If the game is played repeatedly, the users will detect the difference between the actual and displayed costs. Then, they will not completely trust the information given by the system and calculate the cost. The purpose of this thesis is to find out the optimal strategy given by the system–how to set tolls in order to maintain the flow as close to the optimal flow as possible.</p> / Master of Science (MSc)

<p>We study the application of reputation as an instigator of beneficial user behavior in selfish routing and when the network users rely on the network coordinator for information about the network. Instead of using tolls or artificial delays, the network coordinator takes advantage of the users' insufficient data, in order to manipulate them through the information he provides. The issue that arises then is what can be the coordinator's gain without compromising by too much on the trust the users put on the information provided, i.e., by maintaining a reputation for (at least some) trustworthiness.</p> <p>Our main contribution is the modeling of such a system as a repeated game of incomplete information in the case of single-commodity general networks. This allows us to apply known folk-like theorems to get bounds on the price of anarchy that are better than the well-known bounds without information manipulation.</p> / Master of Computer Science (MCS)

<p>This dissertation is a collection of three papers, each one being a chapter. The running subject of interest in all the papers is the strategic behavior of individuals in different environments. In the first chapter, I experimentally investigate collusive behavior under simultaneous interaction in multiple strategic settings, a phenomenon which I call multiple contacts. I investigate how multiple contacts impact collusive behavior when the players are symmetric or asymmetric. The second chapter is a joint work with Dr. Brian Roberson. In this chapter, we examine the role of cognitive diversity in teams on performance in a large innovation contest setting. We use a theoretical model to derive conditions under which increasing diversity can improve the performance in the large contest. Finally, in the third chapter, a joint work with Dr. Yaroslav Rosokha and Dr. Masha Shunko, we experimentally study players' behavior when they interact in an infinitely repeated environment, where the state of the world in each period is stochastic and dependent on a transition rule. Our main questions are how the transition rule impacts behavior and whether asymmetry in players impacts this.</p> <p><br></p> <p>In the first chapter, I study the phenomenon of multiple contacts using a laboratory experiment with multiple symmetric or asymmetric prisoners' dilemma games. When agents interact in multiple settings, even if defection or deviation from collusion in one setting can not be credibly punished in the same setting, it may be punishable in other settings. This can increase the incentive to collude. I observe a statistically significant increase in probability of punishment in one game after defection in another game under multiple contacts, but only when the games are asymmetric in payoffs. While punishment of defection increases in some situations, I do not find any significant increase in collusion due to multiple contacts in either symmetric or asymmetric environment. In addition to this result, to find further support for the theory which suggests that agents should use different strategies under multiple contacts, I estimate the underlying strategies that subjects use in my experiment. To this end, I modify popular strategies (e.g., Grim Trigger, Tit-for-Tat, etc.) to condition on the history observed in multiple strategic settings. I find that only for games with asymmetric payoffs subjects use these modified strategies in the presence of multiple contacts.</p> <p><br></p> <p>The second chapter is a theoretical work. In our model of large team innovation contest, teams develop an innovation using the skills or perspectives (tools) belonging to individual team members and the costly effort they provide.</p> <p>Prizes are awarded based on the values of the teams' innovations. Within a team, the team members posses different skills or perspectives (tools) which may be applied to innovation problems. For a given innovation problem and a given level of team effort, different combinations of tools within a team may generate different values for the team innovation. In this context, we examine the issues of individual team performance as a function of a team's own composition and the overall performance of the contest as a function of the compositions of the teams. We find that the question of whether increasing diversity leads to an increase in expected performance, for both an individual team and the overall contest, depends on the efficiency with which teams are able to effectively apply diverse sets of tools to innovation problems. Thus, our paper provides a channel -- other than a direct cost of diversity -- through which diversity can be beneficial or detrimental depending on how efficient teams are at utilizing diverse sets of team member tools.</p> <p><br></p> <p>The final chapter is another experimental study. We study an enviroment where individuals interact with each other in a prisoners' dilemma game repeatedly over time. However, the payoffs of the prisoners' dilemma game is decided stochastically using a transition rule. We vary the transition rule from alternation to random and study the change in subject behavior when the interaction is either symmetric or asymmetric. Our results show that in asymmetric environment, alternation can improve cooperation rates.</p> <p>With random transition rule, symmetric environment is more conducive to cooperation. We find that asymmetric environment with random transition rules performs the worst in terms of cooperation rates.</p>

賽局理論(Game Theory)大多假設理性決策，單一回合賽局通常可由理論證明均衡(Equilibrium)或是最佳決策，然而如果賽局重複進行，不見得只存在單一均衡，光從理論推導可能無法找到所有均衡。以囚犯困境(Prisoner Dilemma)為例，理論均衡為不合作，若重複的賽局中存有互利關係，不合作可能不是最佳選擇。近年來，經濟學家藉由和統計實驗設計類似的賽局實驗(Game Experiment)，探討賽局在理論與實際間的差異，並以學習模型(Learning Model)描述參賽者的決策及行為，但學習模型的優劣大多依賴誤差大小判定，但誤差分析結果可能與資料有關(Data Dependent)。有鑑於學習模型在模型選取上的不足，本文引進統計分析的模型選取及殘差檢定，以實證資料、配合電腦模擬評估學習模型。 本文使用的實證資料，屬於囚犯困境的重複賽局(Repeated Game)，包括四種不同的實驗設定，參加賽局實驗者（或是「玩家」）為政治大學大學部學生；比較學習模型有四種：增強學習模型(Reinforcement Learning model)、延伸的增強學習模型(Extend Reinforcement Learning Model)、信念學習模型(Belief Learning Model)、加權經驗吸引模型(Experience-Weighted Attraction Model)。實證及模擬分析發現，增強學習模型較適合用於描述囚犯困境資料，無論是較小的誤差或是適合度分析，增強學習模型都有較佳的結果；另外，也發現玩家在不同實驗設定中的反應並不一致，將玩家分類後會有較佳的結果。 / In game theory, the optimal strategy (or equilibrium) of one-shot games usually can be solved theoretically. But, the optimal strategies of repeated games are likely not unique and are more difficult to find. For example, the defection is the optimal decision for the one-shot Prisoner Dilemma (PD) game. But for the repeated PD game, if the players can benefit from cooperation between rounds then the defection won’t be the only optimal rule. In recent years, economists design game experiments to explore the behavior in repeated games and use the learning models to evaluate the player’s choices. Most of the evaluation criteria are based on the estimation and prediction errors, but the results are likely to be data dependent. In this study, we adapt the model selection process in regression analysis and apply the idea to evaluate learning models. We use empirical data, together with Monte Carlo simulation, to demonstrate the evaluation process. The empirical data used are repeated PD game, including four different experimental settings, and the players of the game are from National Chengchi University in Taiwan. Also, we consider four learning models: Reinforcement learning (RL) model, Extend Reinforcement learning (ERL) model, Belief Learning (BL) model, and Experience-weighted attraction (EWA) model. We found that the RL model is more appropriate to describe the PD data. In addition, the behaviors of players in a group can be quite different and separating the players into different sets can reduce the estimation errors.