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.

Problems with storm water runoff are becoming more frequent, and the main cause is the increase of impervious cover (IC). The imperviousness increases stream peak flows, changes peak times, and so changes the flood distribution. Several policies are used to manage flows and flooding; however most have been reported to be inefficient because land owners do not have correct exposure to price incentives and risk. The main contributions of this thesis are an investigation into market mechanisms to price and allocate impervious cover allowances, while managing flood distribution. The market mechanisms are based on the electricity and gas markets which use linear programming formulations. This thesis develops three net pool market mechanisms: Det_MarketIC is a capped and deterministic market for IC, and Sto_MarketIC and Sto_MarketIC_Risk are stochastic market models with flood component penalties and risk positions representing the desired risk from the community respectively. Additionally, a gross pool market was extended under rainfall uncertainty, Gross_MarketIC. The market design is an auction system with operational constraints and bids for IC allowances from participants. The system relates physical routed flows at nodal or control points to these bids. The models clear the market by creating a demand (supply) curve for increments (reductions) in flows at specific places, and accounts for marginal changes in the expected flood damage and flood damage components. The market formulations estimate efficient allocations and prices. Decomposed prices from the market models are shown based on duality, as applied in electricity markets. The dual prices show spatial and temporal effects of flows, which impact at flooding areas. With Sto_MarketIC and Gross_MarketIC, prices account for changes in flood distribution. With Sto_MarketIC_Risk, prices also account for the risk as CVaR in flooding areas. Thus, prices increase as binding risk conditions are tightened. Finally, the net pool models are illustrated using hydrological and hydraulic simulators based on a small catchment located in Canterbury, New Zealand. Allocations and prices varied with the different models. Participants would face increasing prices in their IC allowances due to increments in flood damage.

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

Thesis advisor: M. Utku Ünver / Thesis advisor: M. Bumin Yenmez / This thesis is a collection of three essays in market design concerning designs of matching markets, affirmative action schemes, and COVID-19 testing policies. In Chapter 1, we explore the possibility of designing matching mechanisms that can accommodate non-standard choice behavior. In the standard model of matching markets, preferences over potential assignments encode participants' choice behavior. Our contribution to this literature is introducing behavioral participants to matching theory's setup. We pin down the necessary and sufficient conditions on participants' choice behavior for the existence of stable and incentive compatible matching mechanisms. Our results imply that well-functioning matching markets can be designed to adequately accommodate a plethora of non-standard (and standard) choice behaviors. We illustrate the applicability of our results by demonstrating that a simple modification in a commonly used matching mechanism enables it to accommodate non-standard choice behavior. In Chapter 2, we show that commonly used methods in reserving positions for beneficiaries of affirmative action are often inadequate in settings where affirmative action policies apply at two levels simultaneously, for instance, at university and itsdepartments. We present a comprehensive evaluation of existing procedures and formally and empirically document their shortcomings. We propose a new solution with appealing theoretical properties and quantify the benefits of adopting it using recruitment advertisement data from India. Our theoretical analysis hints at new possibilities for future work in the literature on the theory of apportionment (of parliamentary seats). Chapter 3 delves into the designs of the commonly used and advocated COVID-19 testing policies to resolve a conflict between their allocative efficiency and the ability to identify the infection rates. We present a novel comparison of various COVID-19 testing policies that allows us to pin down ordinally efficient testing policies that generate reliable estimates of infection rates while prioritizing testing of persons suspected of having the disease. / Thesis (PhD) — Boston College, 2022. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

Thesis advisor: M. Utku Ünver / Thesis advisor: Tayfun Sönmez / This thesis is a collection of three essays in market design concerning designs of matching markets with aggregate constraints, affirmative action schemes, and investigating boundaries of simultaneous efficiency-stability relaxation for one-to-one matching mechanisms.In Chapter 1, I establish and propose a possible solution for a college housing crisis, a severe ongoing problem taking place in many countries. Every year many colleges provide housing for admitted students. However, there is no college admissions process that considers applicants’ housing needs, which often results in college housing shortages. In this chapter, I formally introduce housing quotas to the college admissions problem and solve it for centralized admissions with common dormitories. The proposed setting is inspired by college admissions where applicants apply directly to college departments, and colleges are endowed with common residence halls. Such setting has many real-life applications: hospital/residents matching in Japan (Kamada and Kojima, 2011, 2012, 2015), college admissions with scholarships in Hungary (Biró, 2012), etc. A simple example shows that there may not be a stable allocation for the proposed setting. Therefore, I construct two mechanisms that always produce some weakened versions of a stable matching: a Take-House-from-Applicant-stable and incentive compatible cumulative offer mechanism that respects improvements, and a Not-Compromised-Request-from-One-Agent-stable (stronger version of stability) cutoff minimising mechanism. Finally, I propose an integer programming solution for detecting a blocking-undominated Not-Compromised-Request-from-One-Agent-stable matching. Building on these results, I argue that presented procedures could serve as a helpful tool for solving the college housing crisis. In Chapter 2, I propose a number of solutions to resource allocation problems in an affirmative action agenda. Quotas are introduced as a way to promote members of minority groups. In addition, reserves may overlap: any candidate can belong to many minority groups, or, in other words, have more than one trait. Moreover, once selected, each candidate fills one reserve position for each of her traits, rather than just one position for one of her traits. This makes the entire decision process more transparent for applicants and allows them to potentially utilize all their traits. I extend the approach of Sönmez and Yenmez (2019) who proposed a paired-admissions choice correspondence that works under no more than two traits. In turn, I allow for any number of traits focusing on extracting the best possible agents, such that the chosen set is non-wasteful, the most diverse, and eliminates collective justified envy. Two new, lower- and upper-dominant choice rules and a class of sum-minimizing choice correspondences are introduced and characterized. In Chapter 3, I implement optimization techniques for detecting the efficient trade off between ex-post Pareto efficiency (for one side of a two-sided matching market) and ex-ante stability for small one-to-one matching markets. Neat example (Roth, 1982) proves that there is no matching mechanism that achieves both efficiency (for one side of the one-to-one matching market) and stability. As representative mechanisms I choose deferred-acceptance for stability, and top trading cycles for Pareto efficiency (both of them are strategy-proof for one side of the market). I compare performances of a randomized matching mechanism that simultaneously relaxes efficiency and stability, and a convex combination of two representative mechanisms. Results show that the constructed mechanism significantly improves efficiency and stability in comparison to mentioned convex combination of the benchmark mechanisms. / Thesis (PhD) — Boston College, 2023. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

This thesis comprises four essays in the economics of networks and market design. The common thread in all these essays is the presence of complementarities or externalities. Chapter 2 presents a unified model of networks and matching markets. We build on a contribution by Pycia (2012). We show that strong pairwise alignment of agents’ preferences is a necessary and sufficient condition for the existence of strongly stable networks and strongly stable allocations in multilateral matching markets with finite contracts. Strongly stable networks are not necessarily efficient. Although we use a demanding stability concept, strong pairwise alignment allows for complementarities and externalities. In Chapter 3, we generalise the gross substitutes and complements condition introduced by Sun and Yang (2006). Our new condition guarantees the existence of competitive equilibrium in economies with indivisible goods. Competitive equilibrium can be found using an extension of the double-track adjustment process (Sun and Yang, 2009). In this chapter, we also study contract networks (Ostrovsky, 2008). We show that chain-stable contract allocations can exist even in cyclical contractual networks, such as electricity markets, as long as they are appropriately segmented. In Chapter 4, we run a series of experiments to compare the performance of four auctions – first-price, Vickrey, Vickrey-Nearest Rule (Day and Cramton, 2008), and Reference Rule (Erdil and Klemperer, 2010). In our setting, there are two items and three bidders. Two local bidders want an item each, but the global bidder wants both items. We introduce various exposure and package-bidding treatments. We find that the first-price auction always revenue-dominates all the other auctions without any loss in efficiency, strengthening the results of Marszalec (2011). Exposure affects global bidders only in the first-price auction. In other auctions, global bidders often do not take into account the effect of their own bids on their payments. We find no evidence of threshold effects. Finally, in Chapter 5, we develop a new model of online social network formation. In this model, agents belong to many overlapping social groups. We derive analytical solutions for the macroscopic properties of the network, such as the degree distribution. We study the dynamics of homophily – the tendency of individuals to associate with those similar to themselves. We calibrate our model to Facebook data from ten American colleges.

The future electricity grid is likely to be increasingly complex and uncertain due to the introduction of new technologies in the grid, the increased use of control and communication infrastructure, and the uncertain political climate. In recent years, the transactive energy market framework has emerged as the key framework for future electricity market design in the electricity grid. However, most of the work done in this area has focused on developing retail level transactive energy markets. There seems to be an underlying assumption that wholesale electricity markets are ready to support any retail market design. In this dissertation, we focus on designing wholesale electricity markets that can better support transactive retail market. On the highest level, this dissertation contributes towards developing tools and models for future electricity market designs. A particular focus is placed on the relationship between wholesale markets and investment planning. Part I of this dissertation uses relatively simple models and case studies to evaluate key impediments to flexible transmission operation. In doing so, we identify several potential areas of concern in wholesale market designs: 1. There is a lack of consideration of demand flexibility both in the long-run and in the short-run 2. There is a disconnect between operational practices and investment planning 3. There is a need to rethink forward markets to better manage resource adequacy under long-term uncertainties 4. There is a need for more robust modeling tools for wholesale market design In Part II and Part III of this dissertation, we make use of mathematical decomposition and agent-based simulations to tackle these concerns. Part II of this dissertation uses Benders Decomposition and Lagrangian Decomposition to spatially and temporally decompose a power system and operation problem with active participation of flexible loads. In doing so, we are able to not only improve the computational efficiency of the problem, but also gain various insights on market structure and pricing. In particular, the decomposition suggests the need for a coordinated investment market and forward energy market to bridge the disconnect between operational practices and investment planning. Part III of this dissertation combines agent-based modeling with state-machine based modeling to test various spot, forward, and investment market designs, including the coordinated investment market and forward energy market proposed in Part II of this dissertation. In addition, we test a forward energy market design where 75% of load is required to be purchased in a 2-year-ahead forward market and various transmission cost recovery strategies. We demonstrate how the different market designs result in different investment decisions, winners, and losers. The market insights lead to further policy recommendations and open questions. Overall, this dissertation takes initial steps towards demonstrating how mathematical decomposition and agent-based simulations can be used as part of a larger market design toolbox to gain insights into different market designs and rules for the future electricity grid. In addition, this dissertation identifies market design ideas for further studies, particularly in the design of forward markets and investment cost recovery mechanisms.

Cette thèse s'intéresse à plusieurs aspects des marchés de gros de l'électricité. L'achat et vente d'électricité se négocient sur les marchés à terme et sur le marché day-ahead. Sur ce dernier se pratique un type d'enchère très spécifique, où les enchères des acteurs prennent la forme de fonctions d'offre et de demande. Chapitre 2 prend comme point de départ un résultat de Zachmann et von Hirschhausen (2008) qui constatent une réponse asymétrique du prix de gros de l'électricité en Allemagne au changement du prix des permis d'émission négociable ( EUA ). Cependant, en contradiction avec les résultats existants, il est démontré que l'asymétrie a disparu suite à la publication d'un rapport d'enquête par l'autorité de la concurrence. Chapitre 3 porte sur l'interaction des marchés à terme et day-ahead dans un jeu d'oligopole répété. L'effet du marché à terme sur la stabilité des collusions est étudié dans le cas où les stratégies sur le marché spot prennent la forme des fonctions d'offre. Il est démontré que la simple existence d'un marché à terme peut élargir l'intervalle des valeurs du facteur d'actualisation pour lesquelles la collusion est soutenable. Chapitre 4 examine si une réaction asymétrique au changement du prix du C02 est également présente dans les fonctions d'offre du marché d'électricité day-ahead. À cette fin, les outils de l'analyse des données fonctionnelles sont adoptés et appliquées à des données des enchères. Chapitre 5 développe un test pour l'auto-corrélation dans un panel d'observations fonctionnelles. Une simulation Monte-Carlo montre une bonne puissance du test dans des échantillons de taille habituellement utilisé dans la recherche appliquée. / This thesis addresses aspects of interacting markets in electricity wholesale. Electricity is traded in forward markets and in day-ahead auctions, which implement a very specifie market design. The bids of market participants take the fonn of supply and demand functions. Chapter 2 builds upon a finding of Zachmann and von Hirschhausen (2008) who report an asymmetric response of electricity wholesale prices for Gennany to changes in the price of EV Emission Allowances (EVA). ln contrast to the fonner contribution, it is shown that the asymmetry disappeared in response to a report on investigations by the competition authority. Chapter 3 addresses the interaction offorward markets and day-ahead auctions in a repeated oligopoly game. The effect offorward trading on the sustainability of collusion is studied for the case that spot market strategies take the fonn of supply functions. It is shown that the existence of forward markets enlarges the range of discount factors for which collusion can be sustained. Chapter 4 examines if an asymmetric reaction to EVA prices can also be found in the supply functions from the day-ahead market. To this end, tools from the field of functionaJ data analysis are adopted and applied to observed bids from the day-ahead auction. Chapter 5 develops a test for autocorrelation in functional panel data. Asymptotic nonnality of the statistic is proved, and Monte-Carlo simulation sho\l good power of the test in sample sizes which frequently prevail in applied research.

The power balance of an electrical power system is crucial to the quality of the delivered electricity as well as the security of supply. In a scenario where Swedish nuclear power plants are being phased out and replaced by renewable energy sources new constraints are added to the power balance equation since the production of many renewable energy sources, such as wind and solar power, are intermittent by nature. This leads to a situation where the currently available regulating power might have difficulties to manage the increasing frequency fluctuations in the power grid. One possible solution to the problem is to build gas turbines for the purpose of peak power generation capacity. An alternative option would be to increase customer flexibility; that is Demand Response. This master thesis investigates how the market for Demand Respond can be designed and which potential Demand Response volumes different policy programs might release. This is done through a mixed approach. Firstly, a scientific review of previously documented Demand Response experiences compares and categorizes different Demand Response programs in a typology based on the parameters cost, volume and feasibility. Subsequently an interview series with different market agents, predominantly through interviews with the Swedish energy intensive industry, identifies the existing Demand Response potential in Sweden and offers the paradigm needed to transfer the results to a future hypothetical situation. The typology of Demand Response programs and estimation of the future industrial Demand Response potential in Sweden are the main new knowledge contributions of this master thesis. The scope however is limited to the Swedish market geographically and focuses on the time horizon 2020-2050. It is also assumed that only existing technologies are likely to be implemented on a large scale over the given time horizon. The results of this master thesis suggest that a Real Time Pricing model would realize the largest potential of Demand Response and to a relatively low cost. This solution however requires actions and further development of both the pricing model and in technology. Firstly, all market agents must have free access to real time price information, something that is lacking today. Secondly, a smart grid with hourly meters is required. If policymakers consider security of supply to be more important than a low system cost, Direct Control or a continuation of the Strategic Reserve is to be preferred according to the conclusions of this report. Previous studies have placed the existing potential for industrial Demand Response in Sweden between 600 and 900 MW. This report suggests that the available volume is in the upper region of the mentioned interval already today and has potential to rise significantly in the future as industries become more aware of the concept and the transmission grid is becoming more flexible. Another driving force for increased Demand Response volumes are the increased price fluctuations which are expected as a consequence of a greater share of renewable energy sources. For the future Demand Response potential, a cost perspective is introduced and a distinction between different response durations is made. More specifically the results indicate that the potential industrial Demand Response volume will be about 1,500 MW in 2030, given a response duration time of 4 h and a spot price on 2,000 SEK/MWh. If 1,500 MW of peak generation capacity could be avoided through active Demand Side Management, it would reduce the system cost with about 350 Million SEK annually. Consequently, there is a business case for Demand Response and the issue is likely to be subject to further investigation and discussion in the future. On the long term however industrial Demand Response must be compared with other flexibility options, e.g. as import/export or energy storages but also residential Demand Response, and is in such case likely to be outcompeted due to its relatively high variable cost of providing capacity.

Diplomová práce se zabývá analýzou mezinárodního úspěchu společnosti Starbucks. Příčiny tohoto bezprecedentního úspěchu jsou nejprve detekovány ve vnějších faktorech a v odvětví samotném. Následuje pozorování strategických kroků společnosti od založení až po mezinárodní expanzi a podrobná deskripce interních praktik společnosti. V analytické části je pak vymezen a aplikován model, který byl vyvinut na Bocconské univerzitě v Miláně. Jednotlivé předpoklady modelu jsou porovnávány s postupem společnosti Starbucks. Vyhodnocením shodností a odlišností reality a modelu se pak dochází k závěrům, které vysvětlují příčiny extrémně pozitivních výsledků společnosti Starbucks a její schopnosti přeměnit stagnující neatraktivní odvětví na lukrativní obor s vysokými maržemi.