Decentralized Job Matching

This paper studies a decentralized job market model where firms (academic departments) propose sequentially a (unique) position to some workers (Ph.D. candidates). Successful candidates then decide whether to accept the offers, and departments whose positions remain unfilled propose to other candidates. We distinguish between several cases, depending on whether agents’ actions are simultaneous and/or irreversible (if a worker accepts an offer he is immediately matched, and both the worker and the firm to which she is matched go out of the market). For all these cases, we provide a complete characterization of the Nash equilibrium outcomes and the Subgame Perfect equilibria. While the set of Nash equilibria outcomes contain all individually rational matchings, it turns out that in most cases considered all subgame perfect equilibria yield a unique outcome, the worker-optimal matching.Two-sided matching ; job market ; subgame perfect equilibrium ; irreversibilities

Decentralized job matching

This paper studies a decentralized job market model where firms (academic departments) propose sequentially a (unique) position to some workers (Ph.D. candidates). Successful candidates then decide whether to accept the offers, and departments whose positions remain unfilled propose to other candidates. We distinguish between several cases, depending on whether agents’ actions are simultaneous and/or irreversible (if a worker accepts an offer he is immediately matched, and both the worker and the firm to which she is matched go out of the market). For all these cases, we provide a complete characterization of the Nash equilibrium outcomes and the Subgame Perfect equilibria. While the set of Nash equilibria outcomes contain all individually rational matchings, it turns out that in most cases considered all subgame perfect equilibria yield a unique outcome, the worker-optimal matching

PrivateJobMatch: A Privacy-Oriented Deferred Multi-Match Recommender System for Stable Employment

Coordination failure reduces match quality among employers and candidates in the job market, resulting in a large number of unfilled positions and/or unstable, short-term employment. Centralized job search engines provide a platform that connects directly employers with job-seekers. However, they require users to disclose a significant amount of personal data, i.e., build a user profile, in order to provide meaningful recommendations. In this paper, we present PrivateJobMatch -- a privacy-oriented deferred multi-match recommender system -- which generates stable pairings while requiring users to provide only a partial ranking of their preferences. PrivateJobMatch explores a series of adaptations of the game-theoretic Gale-Shapley deferred-acceptance algorithm which combine the flexibility of decentralized markets with the intelligence of centralized matching. We identify the shortcomings of the original algorithm when applied to a job market and propose novel solutions that rely on machine learning techniques. Experimental results on real and synthetic data confirm the benefits of the proposed algorithms across several quality measures. Over the past year, we have implemented a PrivateJobMatch prototype and deployed it in an active job market economy. Using the gathered real-user preference data, we find that the match-recommendations are superior to a typical decentralized job market---while requiring only a partial ranking of the user preferences.Comment: 45 pages, 28 figures, RecSys 201

Matching Markets with Signals

A costless signaling mechanism has been proposed as a device to improve welfare in decentralized two-sided matching markets. An example of such an environment is a job market for new Ph.D. economists. We study a market game of incomplete information between firms and workers and show that costless signaling is actually harmful in some matching markets. Specifically, if agents have very similar preferences, signaling lessens the total number of matches and the welfare of firms, as well as it affects ambiguously the welfare of workers. These results run contrary to previous findings that costless signaling facilitates match formation.Matching Markets, Signaling

Incentives in decentralized random matching markets

Decentralized markets are modeled by means of a sequential game where, starting from any matching situation, firms are randomly given the opportunity to make job offers. In this random context, we prove the existence of ordinal subgame perfect equilibria where firms act according to a list of preferences. Moreover, every such equilibrium preserves stability for a particular profile of preferences. In particular, when firms act truthfully, every outcome is stable for the true preferences. Conversely, when the initial matching is the empty matching, every stable matching can be reached as the outcome of an ordinal equilibrium play of the gameinfo:eu-repo/semantics/publishedVersio

Incentives in Decentralized Random Matching Markets

Decentralized markets are modeled by means of a sequential game where, starting from any matching situation, firms are randomly given the opportunity to make job offers. In this random context, we prove the existence of ordinal subgame perfect equilibria where firms act according to a list of preferences. Moreover, every such equilibrium preserves stability for a particular profile of preferences. In particular, when firms act truthfully, every outcome is stable for the true preferences. Conversely, when the initial matching is the empty matching, every stable matching can be reached as the outcome of an ordinal equilibrium play of the game

Decentralized Market Processes to Stable Job Matchings with Competitive Salaries

We analyze a decentralized trading process in a basic labor market where heterogeneous firms and workers meet directly and randomly, and negotiate salaries with each other over time. Firms and workers may not have a complete picture of the entire market and can thus behave myopically in the process. Our main result establishes that, starting from an arbitrary initial market state, there exists a finite sequence of successive myopic (firm-worker) pair improvements, or bilateral trades, leading to a stable matching between firms and workers with a scheme of competitive salary offers. An important implication of this result is that a general random process where every possible bilateral trade is chosen with a positive probability converges with probability one to a competitive equilibrium of the market.Decentralized market, job matching, random path, competitive salary, stability

Does search boost efficiency?

Poaching externality, arising from job-to-job turnovers, implies that a planner should allocate fewer resources to costly job creations. However, these search efforts increase competition among employers, and this could in turn internalize the externality, whereas the congestion externality requires a unit-elastic matching function

For-Profit Search Platforms

We consider optimal pricing by a profit-maximizing platform running a dynamic search and matching market. Buyers and sellers enter in cohorts over time, meet and bargain under private information. The optimal centralized mechanism, which involves posting a bid-ask spread, can be decentralized through participation fees charged by the intermediary to both sides. The sum of buyers’ and sellers’ fees equals the sum of inverse hazard rates of the marginal types and their ratio equals the ratio of buyers’ and sellers’ bargaining weights. We also show that a monopolistic intermediary in a search market may be welfare enhancing

Controlled Matching Game for Resource Allocation and User Association in WLANs

In multi-rate IEEE 802.11 WLANs, the traditional user association based on the strongest received signal and the well known anomaly of the MAC protocol can lead to overloaded Access Points (APs), and poor or heterogeneous performance. Our goal is to propose an alternative game-theoretic approach for association. We model the joint resource allocation and user association as a matching game with complementarities and peer effects consisting of selfish players solely interested in their individual throughputs. Using recent game-theoretic results we first show that various resource sharing protocols actually fall in the scope of the set of stability-inducing resource allocation schemes. The game makes an extensive use of the Nash bargaining and some of its related properties that allow to control the incentives of the players. We show that the proposed mechanism can greatly improve the efficiency of 802.11 with heterogeneous nodes and reduce the negative impact of peer effects such as its MAC anomaly. The mechanism can be implemented as a virtual connectivity management layer to achieve efficient APs-user associations without modification of the MAC layer