This dissertation examines metropolitan areas subject to exclusive cruising regulations which prevent taxis affiliated with one city from picking up passengers in other neighboring cities. It examines the regulatory structure that evolved in North America, compares exclusive cruising regulation to a combined regulatory regime, and proposes a market-based mechanism to improve upon existing regulations. The first chapter examines the evolution of regulation of the taxicab industry in different metropolitan areas in North America. It provides an explanation for the prevalence of price and quantity regulations at the local level, and why the industry remains heavily regulated despite numerous attempts at deregulation. The second chapter theoretically investigates the efficiency of exclusive cruising regulation when there are multiple exclusive cruising locations in close proximity. Conventional wisdom suggests it is better to operate a combined regulatory regime, thereby eliminating the empty return trips that occur under exclusive cruising regulation. Under combined regulation, however, drivers have an incentive to be in the location with the highest expected revenue. It is shown that this can undermine regulators' control over the allocation of taxis across disparate locations, outweighing losses from empty return trips. In such situations exclusive cruising regulation would be preferred to combined regulation. When locations are sufficiently similar, it is shown that combined regulation will be preferred to exclusive cruising. The third chapter proposes a regulatory exchange market as an alternative to existing regulatory structures. The proposed mechanism maintains separate affiliations, but allows taxi drivers to exchange the right to pick up passengers in each others' affiliated location by participating in a bilateral market. In this market, taxis can exchange the right to pick up passengers in each others' affiliated locations, for a price paid by market participants affiliated with one location to those affiliated with the other location. It is shown that such an exchange market can be designed to achieve superior outcomes to both exclusive cruising regulation and combined regulation modes. We describe situations where the regulatory exchange market cannot be dominated by any other conceivable regulatory mechanism.

Thesis advisor: Utku M. Unver / The Market Design approach, which involves the creation of markets with desirable properties, has been successfully applied to study a wide range of real-world economic problems. The market design approach is helpful in scenarios where money can’t be used as a medium of exchange to facilitate transactions. The allocation of school/college seats to students, assigning residency positions to physicians, cadet-branch matching, and exchange of organs like kidneys and liver are some problems that have been successfully studied using the market design approach. Typically, the market design approach concerns with the setting up of two-sided markets with agents on each side of the market having preferences over each other or agents on one side and objects (school seats, military branches, public health goods like beds, ventilators, etc.) on the other side with agents having preferences over the objects and objects having priority over the agents. Priority ranking of agents can be considered an entitlement ranking where agents with higher priority have the right for the object compared to the agent with lower priority. The insights from the matching theory are then used to create a mechanism that matches agents with agents or objects for the given set of preferences/priority ranking satisfying desirable properties. Primary among these properties is stability, an equilibrium concept for matching. Stable matching ensures that matched agents/objects on the two sides of the market do not have an incentive to break up their respective matching and form a better matching for themselves. In the market design problem of matching agents to objects, stability ensures that the agent’s priority for objects is not violated. Other properties include strategy-proofness, where agents do not have an incentive to misreport their preferences. Strategy-proof mechanisms are simple and ensure that high-information agents cannot game the system at the expense of low-information agents. The priority ranking thus used in matching agents to objects has been subject to much criticism. The underlying process that generates the priority rankings can be inherently discriminatory. Exam scores are used to generate the priority ranking in allocating school seats to students. In the New York City school system, there has been a growing call for abolishing exams since it is considered to favor students with more resources. Similarly, the priority system used in the exchange of organs like kidneys and liver and triage allocation of scarce resources and services like hospital beds, vaccines, and ventilators has received much criticism. Triage protocols are developed with a utilitarian notion of maximum benefit given the constraints. This can result in people with better access to health care resources being better positioned under a triage protocol than those with lesser access. The dissertation comprises two essays, joint work with Kenzo Imamura where I study the pairwise kidney-exchange problem and a ventilator sharing problem where I study the triage allocation of ventilator slots under sharing. In the first essay, I consider the problem of allocating ventilator slots for sharing under a triage protocol that generates the priority order. The triage protocol is considered discriminatory since patients with better access to health care through their life cycle have a better chance to be placed ahead in the order when compared with patients with lesser access to healthcare services. I consider the allocation of ventilator slots under a system of reserves, where slots are set-aside for types of patients to address the shortcoming of the triage protocol. Sharing is possible between patients who are compatible. In addition to addressing the shortcomings of the generated priority order, I focus on the question of what respecting the generating priority order in a sharing environment means. In the second essay, we consider the pairwise-kidney exchange problem, where incompatible patient donor pairs are matched with each other subject to patient donor pairs being compatible with each other and acceptable to each other under a priority order. The priority order is generated using a composite score which includes variables like the area of patient donor location and post-transplant medical survivability, among other factors. In response to the concerns, two mechanisms have been developed in the literature for pairwise-kidney exchange, a mechanism that facilitates pairwise-kidney exchange under a strict priority order and an egalitarian mechanism that doesn’t have a priority ordering among compatible patients. Owing to the utilitarian nature of priority order ranking, the egalitarian mechanism has not been considered for adoption. We develop a compromise mechanism between the egalitarian mechanism and the mechanism which respects strict priority order. We show that the compromise mechanism carries forward nice properties like strategy-proofness, which incentivizes each patient-donor pair to reveal their complete set of compatible patient-donor pairs and bridges the concern of a need for priority order with egalitarianism. The predominant literature in Matching theory considers matching agents with agents/objects under a priority order considering all agents to be equal and the priority ordering to be the only difference in consideration among agents. My dissertation contributes to the matching literature where different agents can vary in ways other than the priority ordering, and we try to find solutions that strive to address the inequity. I thank my advisors for their generous advice and feedback in shaping my dissertation. / Thesis (PhD) — Boston College, 2022. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

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Thesis advisor: M. Utku Ünver / Thesis advisor: M. Bumin Yenmez / This collection of two essays in market design examines the designs of affirmative action policies. In the first chapter, “Affirmative Action in Two Dimensions: A Multi-Period Apportionment Problem”, we study affirmative action policies that take the form of reserved seats or positions and apply at two levels simultaneously. For instance, in India, beneficiary groups are entitled to their proportion of reserved seats in public universities at both university and at department levels. We theoretically and empirically document the shortcomings of existing solutions. We propose a method with appealing theoretical properties and empirically demonstrate advantages over the existing solutions using recruitment advertisement data from India. Our problem also suggests possible extensions in the theory of apportionment (translating electoral votes into parliamentary seats). In the second chapter, “Impartial Rosters for Affirmative Action’’, we present an answer to this question for the case where all positions are homogeneous. Devising methods is particularly necessary when the number of seats is small. For instance, a university appoints at most one assistant professor of economics every year, while the country’s affirmative action policy has more than one beneficiary group. To ensure that, over a period of time, each beneficiary group respects the spirit of an affirmative action policy, India devised a tool called roster. We present a theory of designing rosters to argue that only a few rosters can be considered impartial in that they do not favor some beneficiaries over others. We provide a method that constructs the set of impartial rosters. We show that the existing roster of India is not one of them and favors categories with a larger proportion of seats relative to the smaller ones. / Thesis (PhD) — Boston College, 2022. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

This dissertation consists of three essays in market design. The first essay studies a dynamic allocation problem. The second presents a new model for many-to-one matching markets where colleges are matched to a large number of students. The third analyzes the effect of the minimum wage on training in internships. In many assignment problems items arrive stochastically over time, and must therefore be assigned dynamically. The first essay studies the social planers ability to dynamically match agents with heterogenous preferences to their preferred items. Impatient agents may misreport their preferences to receive an earlier assignment, causing welfare loss. The first essay presents a tractable model of the problem and mechanisms that minimize the welfare loss. The second essay, which is joint work with Eduardo Azevedo, considers the classical many-to-one matching problem when many students are assigned to a few large colleges. We show that stable matchings have a simple characterization. Any stable matching is equivalent to market clearing cutoffs — admission thresholds for each college. The essay presents a model where a continuum of students is to be matched to a finite number of schools. Using the cutoff representation we show that under broad conditions there is a unique stable matching, and that it varies continuously with respect to the underlying economy. The third essay, which is joint work with Michael Schwarz, looks at on the job training in firms. The firm recovers the cost of training by gradually training the worker over time, paying a wage below the workers marginal product and providing the remaining compensation in the form of training. When the worker’s productivity is close to the minimum wage the firm finds it profitable to front-load training, making the worker more productive and the training faster. A decrease in the minimal wage reduces the firm's incentive to front-load training, and can make training less efficient.

Thesis advisor: Utku Unver / Thesis advisor: Bumin Yenmez / This dissertation consists of two chapters. Both are centered around the theory and design of markets, in which the use of money is prohibited and/or strongly undesirable. In my first chapter, I study multi-object assignment problems. Here, the assignment of graduate students to teaching assistant positions over the course of two semesters, serves as an illustrative application. In my second chapter, I propose an alternative way to distribute asylum seekers among European member states based on the preferences of both sides. Chapter 1: Multi-Object Assignment: Booster Draft In my first chapter, I ask the question of how to divide among a set of n individuals a set of n × m indivisible objects without using monetary transfers, in a way that is efficient, incentive compatible, and ex-post fair. A well known impossibility result shows that the only mechanisms that are both incentive compatible and efficient are dictatorship mechanisms. I fill a gap in the literature by describing a novel mechanism that is both incentive compatible and fair in the responsive preference domain. The mechanism is inspired by booster drafts used in competitive card game tournaments. The idea is to arbitrarily divide the set n × m objects into m \boosters" (sets) of size n and specify a priority order for each such booster. Afterwards the individuals pick objects from the boosters in order of priority. The outcome of the booster draft mechanism can be improved if additional knowledge about a particular market is incorporated into the creation of boosters. I point out a special case of multi-object assignment problems, motivated by the allocation of teaching assignments among graduate students. In this domain the creation of the boosters is straightforward. Indeed, at the Boston College economics department, graduate students are assigned exactly one fall and one spring semester task over the academic year. Here the optimal way of creating boosters is to group up all spring teaching assignments in one booster and all fall semester assignments in the other. In this case the balanced booster draft is not only strategyproof and fair, but also weakly efficient (dominance efficient). Moreover, for this restricted assignment domain I characterize the set of all booster drafts as any (strongly) strategyproof, neutral and non-bossy mechanism. In the final part of the paper I take a closer look at the teaching assistant assignment problem, using date on the submitted rankings over semester-tasks by graduate students. The simulation exercise provides additional evidence that the proposed mechanism is a sensible practical solution. In particular, I show that for a simple measure of welfare students prefer a balanced booster draft to a serial dictatorship mechanism if they are mildly risk averse. Chapter 2: An Alternative Asylum Assignment The 2015 refugee crisis has demonstrated the necessity of revising the current European asylum system. As an alternative, I propose to take into account preferences of asylum seekers as well as preferences of member states. Asylum seekers indicate how long they are willing to wait for their asylum application for any given member state, allowing them to avoid overburdened member states by opting for \less popular" member states. Within the market design literature, this is the first paper proposing to match asylum seekers as opposed to refugees. In other words, its stays much closer to the template of the Common European Asylum System. From a theoretical perspective, it turns out that the asylum seeker framework can be formulated as an application of the well-known matching with contracts model by Hatfield and Milgrom (2005a). This simplifies the analysis a great deal, as matching with contracts is a well studied framework within the matching/market design literature. I show that the standard cumulative offer mechanism (Gale and Shapley, 1962a; Hatfield and Kojima, 2010a) is asylum seeker incentive compatible and leads to stable outcomes, using the fact that the proposed choice functions have a completion satisfying substitutability and the law of aggregate demand Hatfield and Kominers (2016). Moreover, stability implies two sided Pareto efficiency, giving consideration to both preferences of member states and asylum seekers. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

La réforme du secteur de l'électricité du Nigeria a eu lieu en 2010-2013 mais a été jugée infructueuse par la plupart des parties prenantes. L'échec de la réforme est illustré par une myriade de défis économiques, institutionnels, techniques, financiers et sociopolitiques apparemment insurmontables. Cette thèse a pour objectif de proposer des solutions viables aux défis (ex post) auxquels fait face le secteur électrique du Nigéria, en empruntant aux approches de l'économie de l'énergie sur le market design et la régulation. Elle identifie les principales causes de l'échec de la dernière réforme du secteur : privatisation incomplète, intégration horizontale des opérations de transport et de réseau, infrastructure d'approvisionnement gazière sous-développée et cadre réglementaire faible et inefficace. Ainsi, elle recommande de renforcer le cadre réglementaire comme un bon point de départ pour résoudre les problèmes sectoriels (ex-post) de la réforme.Ensuite, cette thèse démontre que des enchères inversées bien conçues peuvent être un mécanisme de marché approprié à la situation du Nigéria, en précisant les variables importantes pour une implémentation réussie. Cette thèse affirme également que ces variables devraient être fondées sur un cadre institutionnel et réglementaire solide pour réussir. Elle recommande donc de concevoir des enchères inversées pour la technologie de stockage solaire photovoltaïque hors réseau /minigrid, en tant que solution potentielle pour accroître l'accès à l'électricité, attirer les investissements, et également discuté de la voie à suivre afin d’adapter la conception au cadre de marché discuter / réglementaire existant.Enfin, cette thèse comble certaines lacunes de l'état de l'art du secteur électrique nigérian en appliquant et combinant des systèmes d’informations géographiques (GIS), un outil d’optimisation de système énergétique et des connaissances du market design et de la régulation. Elle a identifié les clusters de consommateurs les plus peuplées sans accès à l'électricité, fait des projections de la demande de charge et déterminé les tailles de stockage PV et de batteries optimisées sur le plan techno-économique pour obtenir une alimentation de haute qualité d’électricité avec une certaine gestion de la demande. Également, elle a analysé les besoins en terrains / la disponibilité pour obtenir une liste restreinte de 233 clusters de 7,2 millions d'habitants, nécessitant un solaire photovoltaïque de 3 280 MW pour la vente aux enchères proposée. Enfin, cette thèse a examiné la voie à suivre pour adapter la conception proposée de la vente aux enchères de stockage d’énergie solaire photovoltaïque et de stockage au cadre de market design/réglementaire existant. / The Nigeria Power sector reform was performed in the year 2010-2013 but has been adjudged unsuccessful by most stakeholders. The failure of the reform is evidenced by a myriad of seemingly insurmountable economic, institutional, technical, financial and socio-political challenges. This thesis aims to propose workable solutions to the challenges in the Nigeria Power sector (ex-post) reform from the field of market design and regulation in energy economics. It finds incomplete privatization coupled with the horizontal integration of the transmission and network operations, underdeveloped gas supply infrastructure and the ineffective/weak regulatory framework as the root causes of the reform failure. Thus, it recommends strengthening the regulatory framework as a good starting point to resolve sectoral problems (ex-post) reform.Furthermore, it argues that reverse auction has the potential to be successful in Nigeria with well-designed market variables and provides the market design variables adaptable to the Nigeria case to achieve a successful auction run. It also argues that these variables should be built on a foundation of a robust institutional and regulatory framework to be successful. It thus recommends designing reverse auctions for offgrid/minigrid solar PV plus storage technology as a potential solution to increase power access and attract investment and also discussed the pathway to adapt the design to the existing market/regulatory framework. In addition, it applied and combined Geographical Information System (GIS), energy system optimization tool and market/regulation knowledge to bridge some knowledge gap in the Nigeria Power sector. It identified the most populated consumer clusters without electricity access, made load demand projections and determined the techno-economically optimized PV plus battery storage sizes to achieve high quality power supply with some demand side management. Furthermore, it analyzed the land requirements/availability to achieve a shortlist of 233 clusters with 7.2 million people that require 3,280 MW solar PV for the proposed auction. Finally, it discussed the pathway to adapt the proposed solar PV plus storage auction design to the existing market/regulatory framework.

This research complements and combines market microstructure theory and mechanism design to optimize the market structure of financial markets systematically. We develop an agent-based model featuring near-zero-intelligence traders operating in a call market with a wide range of trading rules governing the determination of prices, which orders are executed as well as a range of parameters regarding market intervention by market makers and the presence of informed traders. The market structure which generates the best market performance is determined by applying the search technique Population-based Incremental Learning, guided by a number of performance measures, including maximizing trading volume or price, minimizing bid-ask spread or return volatility. We investigate the credibility of our model by observing the trading behavior of near-zero-intelligence traders with stylized facts in real markets. Based on computer simulations, we conform that the model is capable to reproduce some of the most important stylized facts found in financial markets. Thereafter, we investigate the best found market structure using both single-objective optimization and multi-objective optimization techniques. Our results suggest that the best-found combination of trading rules used to enhance trading volume may not be applied to achieve other objectives, such as reducing bid-ask spread. The results of single-objective optimization experiments show that significantly large tick sizes appear in the best market structures in most cases, except for the case of maximizing trading volume. The tick size is always correlated with the selection of multi-price rules. Though there is no particular combination of priority rule and multiprice rule achieving the best market performance, the time priority rule and the closest multi-price rule are the most frequently obtained rules. The level of market transparency and the extend of market maker intervention show ambiguous results as their representative parameter values change in a wide range. We also nd that the results of multi-objective optimization experiments are much similar to those obtained in the single-objective optimization experiments, except for the market transparency represented by the fraction of informed trader, which shows a clear trend in the multi-objective optimization. Using the results obtained from this research we can derive recommendations for exchanges and regulators on establishing the optimal market structure; for securities issuers on choosing the best exchange for their listing; and for investors on choosing the most suitable exchange for trading.

Cette thèse étudie l'affectation centralisée des enseignants aux écoles et un nouveau modèle d'appariement inspirée par cette dernière.Dans le premier chapitre, nous développons un modèle théorique de réaffectation afin d'étudier le problème de réaffecter des enseignants titulaires enseignant au sein d'un établissement et demandant une mutation. Le problème est similaire à celui d'affecter des élèves dans des écoles. Dans ce cas, l'algorithme à Acceptation Différée a été identifié comme étant le seul algorithme qui: i) est stable, ii) efficace et qui iii) incite les élèves à soumettre sincèrement leurs préférences. La différence principale avec le problème d'affecter des élèves aux écoles est que les enseignants ont déjà une position initiale au sein d'un établissement. On doit donc prendre en compte une contrainte additionnelle, la Rationalité Individuelle (RI): un enseignant doit être affecté dans un établissement qu'il préfère faiblement à son établissement d'origine. Pour prendre en compte cette contrainte, une modification de l'algorithme à Acceptation Différée a été identifiée dans la littérature académique et utilisé en pratique pour affecter les enseignants aux écoles en France. Nous montrons que cet algorithme modifié souffre d'un important défaut: il n'est pas efficace au sens fort. Il est en effet possible de réaffecter les enseignants aux écoles de telle sorte que: i) les enseignants obtiennent une école qu'ils préfèrent et ii) les écoles obtiennent des enseignants mieux classés. Partant de ce constat, nous identifions la classe de tous les algorithmes, les algorithmes Block-Exchange (BE), qui ne souffrent pas de ce défaut. Parmi eux, nous montrons qu'il en existe un unique qui incite les enseignants à soumettre leurs préférences sincèrement: le Teacher Optimal Block-Exchange algorithm (TO-BE). En utilisant un modèle de marché large, nous montrons théoriquement que ces algorithmes ont de meilleures performances en termes de mouvement et de bien-être des enseignants que l'algorithme actuel. Nous utilisons ensuite une base de données sur l'affectation des enseignants aux écoles du secondaire en France en 2013 pour quantifier les gains possibles que nos algorithmes peuvent apporter. Dans un cadre de réaffectation pur sans enseignant néotitulaire et places vacantes, nous montrons qu'il est possible de plus que double le nombre d'enseignants obtenant une nouvelle affectation.Dans le second chapitre, nous concevons un algorithme pratique, inspiré de nos résultats du chapitre précédent, pour la procédure française d'affectation des enseignants du secondaire. Plus globalement, cette conception a également pour but de fournir un outil face à deux problèmes importants communs aux pays de l'OCDE: i) le manque d'attractivité de la profession enseignants et ii) les importantes inégalités de réussites des élèves issus de milieux sociaux différents. Nous considérons l'ensemble du marché français composé des enseignants titulaires demandant une réaffectation, les enseignants sans affectation initiale et des places vacantes. Améliorer la mobilité des enseignants permet de leur donner de meilleures perspectives de carrière ce qui peut potentiellement attirer plus d'entrants dans la profession. Mais cette mobilité accrue peut entrainer l'affectation de plus d'enseignants peu expérimentés au sein d'académies déjà très défavorisées, affectant in fine la réussite des élèves au sein de celles-ci. Nous proposons un algorithme flexible qui permet de mieux contrôler le mouvement et la distribution des enseignants au sein de régions, notamment celles très désavantagées. En utilisant les données françaises d'affectation de 2013, nous simulons plusieurs scénarios contre factuels et montrons que notre algorithme peut prendre en compte plusieurs objectifs de politique publique. / This thesis studies the centralized assignment of teachers to schools and a new matching framework inspired by it. In the first chapter, we develop a theoretical model of reassignment to study the problem of reassigning tenured teachers who already have a position and are willing to move to another school. The problem is similar to the one of assigning students to schools. In this case, the well known Deferred Acceptance algorithm has been identified as the only algorithm that: i) is stable ii) efficient and iii) gives incentives to students to report their true preferences. The main difference with the problem of assigning students to schools is that teachers have an initial assignment. One has to consider an additional constraint, Individual Rationality (IR): a teacher must receive a school that he weakly prefers to his initial one. To incorporate this constraint, a modification of the Deferred Acceptance algorithm has been identified in the academic literature and used in practice to assign teachers to schools in France. We show that this modified algorithm has a serious drawback: it is not efficient in a strong sense. Indeed, it is possible to reassign teachers to schools such that both: i) teachers obtain a school that they prefer and ii) schools are assigned teachers that they rank higher. Thus, we identify the class of all algorithms, the Block-Exchange (BE) algorithms, that do not suffer from this drawback. Among them, we show that there is a unique one that gives good incentives to teachers to report their true preferences, the Teacher Optimal Block-Exchange algorithm (TO-BE). In using a large market setting, we theoretically show that these algorithms perform better in terms of movement and welfare for teachers than the currently used one. We then use a dataset on the assignment of teachers to schools in France in 2013 to quantify the possible gains that can bring our algorithms. In a reassignment setting with no newly tenured teachers or empty seats, we show that we can more than double the number of teachers obtaining a new assignment. In the second chapter, we aim to design a practical algorithm, inspired by our findings in the previous chapter, for the French assignment system of teachers to schools. More generally, this design also aims to provide a tool about two important issues common to OECD countries: i) the lack of attractiveness of the teaching profession and ii) the high achievement inequality between students from different social backgrounds. We consider the complete French market composed of tenured teachers looking for a reassignment, newly tenured teachers with no initial assignment and empty positions. In improving the mobility of teachers, one can give them better career perspectives and so potentially attract more teachers into the profession. But in doing so, it can also hurt deprived regions in assigning more teachers with low experience to them and ultimately the students from these regions. We propose a flexible algorithm that allows to better control the movement and distribution of teachers across regions, especially deprived ones. Using the data of the French assignment of teachers in 2013, we simulate several counter factuals and show that our algorithm can accommodate a wide range of policy objectives.

This thesis consists of three independent essays on the design of matching markets, with a primary goal to understand how information interacts with matching mechanisms especially in the applications to school choice and college admissions. The first chapter compares theoretically the non-strategyproof Boston mechanism and the strategy-proof deferred acceptance mechanism when taking into account that students may face uncertainty about their own priorities when submitting preferences, one important variation from the complete information assumption. The second chapter evaluates the effectiveness of a strategy-proof mechanism when students have to submit preferences before knowing their priorities using both theory and data. The third chapter turns attention to a new mechanism that is sequentially implemented and can encourage truth-telling. Nevertheless, such implementation often faces time constraint. This chapter therefore offers an inquiry of the pros and cons of the time-constrained sequential mechanism. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished