Matching markets

In this paper, we discuss a one-sided many-to-many matching model. Unlike a labor market matching model, agents may not be divided into two in our model. Moreover, unlike a roommate model, each agent is allowed to have multiple partnerships in our model. In addition, two agents may form multiple partnerships between them. We consider that each agent has a specific preference on the possible matchings. We represent a matching as a multiple graph and consider stability and efficiency of matchings of the model. We give a characterization of a matching that is stable and not Pareto dominated by any individually rational matching. Finally, we show that a direct mechanism for selecting a stable matching that is not Pareto dominated by any individually rational matching is not strategy-proof.

This study considers a school choice problem with general feasibility con-
straints. Each student belongs to a grade; and two students belonging to the
same grade are symmetric, whereas those belonging to di¤erent grades can be
asymmetric with respect to the feasibility constraint of a school. We introduce
…ve requirements of a matching and a polynomial-time algorithm to derive a
matching satisfying them. Since the algorithm is inspired by the nursery school
system of Yokohama city, we introduce the system and compare it with the
algorithm of this study.

This thesis studies some philosophical and ethical issues that economic design raises. Chapter 1 gives an overview of economic design and argues that a cross-fertilisation between philosophy and economic design is possible and insightful for both sides. Chapter 2 examines the implications of mechanism design for theories of rationality. I show that non-classical theories, such as constrained maximization and team reasoning, are at odds with the constraint of incentive compatibility. This poses a problem for non-classical theories, which proponents of these theories have not addressed to date. Chapter 3 proposes a general epistemology of economic engineering, which is motivated by a novel case study, viz. the reform of a matching market for medical practitioners. My account makes use of causal graphs to explain how models allow encoding counterfactual information about how market outcomes change if the design of the market changes. The second part of the thesis examines ethical issues. In Chapter 4, I apply tools from matching theory to gain insights into the distribution of refugees, such as among countries of the European Union. There is an ethical trade-off between the fairness of matchings and their efficiency, and I argue that in this context, fairness is the morally weightier criterion. Chapter 5 deals with the ethics of kidney exchange. Against critics, I give two arguments for the implementation of kidney exchange programmes. The first argument is that they are instrumental in meeting a moral obligation, namely to donate effectively. The second is that kidney exchange may increase the motivation for altruistic donations, because the donation of one kidney may trigger > 1 life savings. The final chapter identifies questions for future research and it closes with some thoughts about the future trajectory of economic design.

L’imaginaire de l’aviation trouve dans la presse populaire de l’entre-deux-guerres un relais efficace. L’actualité sportive et les romans-feuilletons font la part belle aux aviateurs. La rubrique de « Courrier » de la revue Midinette témoigne de l’intérêt du lectorat pour ces chevaliers du ciel. Aussi le flirt épistolaire qui s’y joue pense-t-il conjointement la conquête des cœurs et la conquête de l’air. L’aviateur est érigé en idéal masculin, un stéréotype qui est tantôt renforcé tantôt bousculé par les courriéristes. Au fil des discussions se pose en effet la question du genre de la conquête de l’air. Pour les jeunes filles, il s’agit de concilier, par le biais de la correspondance à un aviateur, deux figures a priori opposées : la midinette et l’aviatrice.

The popular press of the Interwar Period spreads a collective image of aviation. Airmen are heroes of sports pages and of dime novels. One can read the readership’s interest for aviators in Midinette’s “Courrier”. In these letters to the editor, young men and women are flirting. They use a poetics in which aircraft wings rhyme with wings of love. They hope to fly in the air and fall in love at the same time. Aviators turn out to be an ideal of manhood in the collective imaginary. This stereotype is sometimes strengthened and sometimes questionned by discussions between readers. They wonder about the gender of flying. The girls who want to receive letters from an airman try indeed to reconcile two female figures: the “midinette” and the aviatrix.

We are interested in explaining network formation by studying models in which the network structure is endogenously determined. At a basic level, a network formation problem (NFP) consists of two elements: a neighborhood structure ( or deviation structure) and a defeated relation. A neighborhood of a network is the set of all other networks that dier from the initial network by a deviation rule. A neighborhood structure is the collection of neighborhoods. A defeated relation is a binary relation over the set of all pairs of networks that are neighbors. A network is said to be stable if it defeats every network in its neighborhood. Given a neighborhood strucure there may exist a defeated relation such that all networks are defeated by some neighbor, i.e. no networks are stable. In this paper we ask, given a neighborhood structure, if we pick a defeated relation at random, what is the probability that at least one stable network will exist? First, we show that if a neighborhood is dened by diering in only one link, then the probability that at least one stable network exists converges to 1 − e −1 as the number of players in the network grows.

Abstract This paper proposes a reform for school allocation procedures in order to help integration policies reach their objective. For this purpose, we suggest the use of a natural two-step mechanism. The (equitable) first step is introduced as an adaptation of the deferred-acceptance algorithm designed by Gale and Shapley (1962), when students are divided into two groups. The (efficient) second step captures the idea of exchanging places inherent to Gale's Top Trading Cycle.

This paper introduces τ-fairness as a compromise solution reconciling Pareto efficiency and equity in School Choice Problems. We show that, by considering a weak notion of equity that we refer to as λ-equity, it is possible to contribute positively to solve an open debate, originated by the efficiency-equity trade-off of the schooling problem. We also suggest a slight modification to some allocative procedures recently introduced in the United States to compute τ-fair allocations and provide support for this (possible) reformulation.

We examine network members’ collaboration preferences between and within academic and commercial organizations that are members of a UK-based Knowledge Transfer Network. By introducing conjoint analysis to innovation studies, we provide insights into the relative importance of various task and partner characteristics of potential collaborations in determining preferences. Research funding is found to be the most important predictor of network members’ preferences to collaborate, but its effect is moderated by firm size, prior experience and the goal of the collaboration. We suggest that the desire to control and diminish both behavioural and outcome uncertainty explains these moderating effects.

"We present a two-sided matching framework to investigate the entry-level marketing assistant professor job market. Under this framework, candidates’ and departments’ decisions to mutually choose one another are driven by the matching value produced by the pair, which is in turn determined by observable department brand cues and candidates’ human brand cues such as field of research, research productivity, and ranking status. Our results suggest that matches between candidates and faculty trained in the same field do not always generate the highest matching value. Candidates’ publications in top marketing journals enhance their likelihood of matching with research-oriented hiring departments,
and this effect is moderated by their field of research. In general, the ranking status of candidates boosts their chance of being matched with research-oriented hiring departments. However, this effect differs across fields, and it also interacts with candidates’ own research productivity. In particular, publications by candidates from top-ranked degree-granting departments are taken as three to four times more valuable by research-oriented hiring departments. Our work extends the current research on the marketing job market and, most importantly, quantifies and compares the significance of various human brand cues in influencing mutual choices in the job market."

A key property of overlay networks is the overlay nodes’ ability to establish connections (or be matched) to other nodes by preference, based on some suitability metric related to, e.g., the node’s distance, interests, recommendations, transaction history or available resources. When there are no preference cycles among the nodes, a stable  matching exists in which nodes have maximized individual satisfaction, due to their choices, however no such guarantees are currently being given in the generic case. In this work, we employ the notion of node satisfaction to suggest a novel modeling for matching problems, suitable for overlay networks. We start by presenting a simple, yet powerful, distributed algorithm that solves the many-to-many matching problem with preferences. It achieves that by using local information and aggregate satisfaction as an optimization metric, while providing a guaranteed convergence and approximation ratio. Subsequently, we show how to extend the algorithm in order to support and adapt to changes in the nodes’ connectivity and preferences. In addition, we provide a detailed experimental study that focuses on the levels of achieved satisfaction, as well as convergence and reconvergence speed.

An important function of overlay networks is the facilitation
of connection, interaction and resource sharing between peers. The peers may maintain some private notion of how a “desirable” peer should look like and they share their bounded resources with peers that they prefer better than others. Recent research proposed that this problem can be modeled and studied analytically as a many-to-many matching problem with preferences. The solutions suggested by the latter proposal guarantee both algorithmic convergence and stabilization,  however they address static networks with specific properties, where no node joining or leaving is considered. In this paper we present an adaptive, distributed algorithm for the many-to-many matching problem with preferences that works over any network, provides a guaranteed approximation for the total satisfaction in the network and guarantees convergence. In addition, we provide a detailed experimental study of the algorithm that focuses on the levels of achieved satisfaction as well as convergence and reconvergence speed. Finally, we improve, both for static and dynamic networks, the previous known approximation ratio.

A key property of overlay networks, that is going to play an important part in future networking solutions, is the peers' ability to establish connections with other peers based on some suitability metric related to e.g. the node's distance, interests, recommendations, transaction history or available resources. Each node may choose individually an appropriate metric and try to connect or be matched with the available peers that it considers best. When there are no preference cycles among the peers, it has been proven that a stable matching exists, where peers have maximized the individual satisfaction gleaned of their choices. However, no such guarantees are currently being given for the cases where cycles may exist and known methods may not be able to resolve ¿oscillations¿ in preference-based connectivity and reach stability. In this work we employ the use of node satisfaction to move beyond classic stable matchings and towards the overlay network context. We present a simple yet powerful distributed algorithm that uses aggregate satisfaction as an optimization metric. The algorithm is a generalization of an approximation one-to-one matching algorithm, into the many-to-many case. We prove that the total satisfaction achieved by our algorithm is a constant factor approximation of the maximum total satisfaction in the network, depending also on the maximum number of possible connections of a peer in the overlay.

Several labor markets, including the job market for new Ph.D. economists, have recently developed formal signaling mechanisms. We show that such mechanisms are harmful for some environments. While signals transmit previously unavailable information, they also facilitate information asymmetry that leads to coordination failures. In particular, we consider a two-sided matching game of incomplete information between firms and workers. Each worker has either the same "typical" known preferences with probability close to one or "atypical" idiosyncratic preferences with the complementary probability close to zero. Firms have known preferences over workers. We show that under some technical condition if at least three firms are responsive to some worker signal, the introduction of signaling strictly decreases the expected number of matches.

—Next generation networks are designed to improve connectivity and capacity, adding to the current range of available services and expanding their reachability. For these systems to work, they need to be compatible with legacy technologies in addition to making use of (limited) available spectrum resources. This is one of the reasons why spectrum sharing has been at the forefront of the list of enablers for such systems. From federal-commercial sharing to finding opportunities in millimeter-wave spectrum, we have witnessed the formulation of multiple approaches to making spectrum sharing happen. Existing work on spectrum sharing is wide ranging and includes technical as well as market-based approaches. The study of spectrum markets is of particular interest, as it merges a market approach with the technical limitations inherent to electromagnetic spectrum. In this manner, spectrum markets settings have called for different definitions of spectrum-related resources as a means to increase market thickness and thus improve the opportunities for market success. In a similar vein, we find proposals of network models which aim at adapting technical definitions of spectrum resources, such as those that are the product of virtualization. In this work, we adopt a market perspective for spectrum sharing within the context of more comprehensive network definitions such as those envisioned for next generation networks. To this end, we explore matching market concepts and middleman theory in order to shed light on factors that may impact the performance and, ultimately, the success of spectrum markets.

The purpose of this paper is to use what learned from the literature for presenting a proposal of redesign of the entry-level of the Academic Job Market in Italy. The matching researchers/Universities is currently obtained through local contests and it suffers inefficiencies caused by its decentralized structure. The first step of the study was to create a unique centralized procedure of matching based on a researchers-proposing deferred-acceptance algorithm that cleverly solve the first three issues. On the other hand, the question of merit – established as the possibility that non-deserving candidates will be hired instead of more qualified ones - represents a new challenge in the practice of market design. It has been treated as a misrepresentation of the Universities' preferences due to an agency problem between the institutions – that express propensities in regulations – and committees – who practically have to realize the list of candidates using their judgments in line with the institutions' guidelines – into the decision process. A misalignment of interests between the two agents causes the false declaration of Universities' preferences and the outcomes of the matching procedure result to be not stable (Roth and Sotomayor 1992; Roth 2008). I formalize the agency problem in the study of the Universities' decision process in order to analyze the players' behaviors and relations for working out a set of rules to control it. I propose a solution at this problem by splitting into two steps the process of building up the Universities’ list of preferences and controlling it.

We consider a two-sided many-to-one matching model where universities offer scholarships to students. We show that every stable matching rule is manipulable by a university via destroying and predonating endowments under a fairly wide class of scholarship rules. We also show that the student-and university-optimal matching rules are non-manipulable under the class of scholarship rule, where the universities give some of their endowments only to their most preferred student as scholarship. Furthermore, we show that the set of Nash equilibria of the destruction game and the set of stable matchings may be disjoint. We also show that there exists a stable allocation which is manipulable by a university via destroying as well as via predonating endowments whenever the scholarships are determined endogenously in the model.

This paper proposes a reform for school allocation procedures in order to help integration policies reach their objective. For this purpose, we suggest the use of a natural two-step mechanism. The (equitable) first step is introduced as an adaptation of the deferred-acceptance algorithm designed by Gale and Shapley (1962), when students are divided into two groups. The (efficient) second step captures the idea of exchanging places inherent to Gale's Top Trading Cycle. This latter step could be useful for Municipal School Boards when implementing some integration policies.

Being argumentative in nature and referring to Oaxaca Decomposition for the purpose of defining the main drivers of rental flats and houses, be new, old, repaired, or unrepaired, together with applying difference in difference method to evaluate the effectiveness of policy, this paper calls into the question of how to inaugurate a country-specific two-sided matching algorithm for rental house allocation based on the empirical results. Model 3 is built on time series data to evaluate the policy implementation by Azerbaijani government to provide households with financial aid. Based on Blinder-Oaxaca Decomposition, the main findings of the study manifest that for the repaired and unrepaired houses, the price discrimination is mainly explained by the room number while this is area of the houses per meter square that explains the price gap between old and new flats. The Difference in Difference model signifies that the increase in the amount of mortgage loans from 50.000 AZN to 150.000 AZN declined demand more than increase in supply. Additionally, study offers 2 Matching Algorithm and Mechanism Design for the allocation of rental houses with existing tenants and newcomers in addition to tenants and owners without initial endowments through YRMH-IGYT in two-sided matching markets.