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Correlation of Rankings in Matching Markets
R\'emi Castera, Patrick Loiseau, Bary S. R. Pradelski
https://arxiv.org/abs/2512.05304 https://arxiv.org/pdf/2512.05304 https://arxiv.org/html/2512.05304
arXiv:2512.05304v1 Announce Type: new
Abstract: We study the role of correlation in matching markets, where multiple decision-makers simultaneously face selection problems from the same pool of candidates. We propose a model in which a candidate's priority scores across different decision-makers exhibit varying levels of correlation dependent on the candidate's sociodemographic group. Such differential correlation can arise in school choice due to the varying prevalence of selection criteria, in college admissions due to test-optional policies, or due to algorithmic monoculture, that is, when decision-makers rely on the same algorithms and data sets to evaluate candidates. We show that higher correlation for one of the groups generally improves the outcome for all groups, leading to higher efficiency. However, students from a given group are more likely to remain unmatched as their own correlation level increases. This implies that it is advantageous to belong to a low-correlation group. Finally, we extend the tie-breaking literature to multiple priority classes and intermediate levels of correlation. Overall, our results point to differential correlation as a previously overlooked systemic source of group inequalities in school, university, and job admissions.
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Beyond Revenue and Welfare: Counterfactual Analysis of Spectrum Auctions with Application to Canada's 3800MHz Allocation
Sara Jalili Shani, Kris Joseph, Michael B. McNally, James R. Wright
https://arxiv.org/abs/2512.08106 https://arxiv.org/pdf/2512.08106 https://arxiv.org/html/2512.08106
arXiv:2512.08106v1 Announce Type: new
Abstract: Spectrum auctions are the primary mechanism through which governments allocate scarce radio frequencies, with outcomes that shape competition, coverage, and innovation in telecommunications markets. While traditional models of spectrum auctions often rely on strong equilibrium assumptions, we take a more parsimonious approach by modeling bidders as myopic and straightforward: in each round, firms simply demand the bundle that maximizes their utility given current prices. Despite its simplicity, this model proves effective in predicting the outcomes of Canada's 2023 auction of 3800 MHz spectrum licenses. Using detailed round-by-round bidding data, we estimate bidders' valuations through a linear programming framework and validate that our model reproduces key features of the observed allocation and price evolution. We then use these estimated valuations to simulate a counterfactual auction under an alternative mechanism that incentivizes deployment in rural and remote regions, aligning with one of the key objectives set out in the Canadian Telecommunications Act. The results show that the proposed mechanism substantially improves population coverage in underserved areas. These findings demonstrate that a behavioral model with minimal assumptions is sufficient to generate reliable counterfactual predictions, making it a practical tool for policymakers to evaluate how alternative auction designs may influence future outcomes. In particular, our study demonstrates a method for counterfactual mechanism design, providing a framework to evaluate how alternative auction rules could advance policy goals such as equitable deployment across Canada.
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Zero Carbon V2X Tariffs for Non-Domestic Customers
Elisheva S Shamash, Zhong Fan
https://arxiv.org/abs/2512.07308 https://arxiv.org/pdf/2512.07308 https://arxiv.org/html/2512.07308
arXiv:2512.07308v1 Announce Type: new
Abstract: With the aim of meeting the worlds net-zero objectives, electricity trading through contractual agreements is becoming increasingly relevant in global and local energy markets. We develop contracts enabling efficient energy trading using Vehicle to Everything technology which can be applied to regulate energy markets and reduce costs and carbon emissions by using electric vehicles with bidirectional batteries to store energy during offpeak hours for export during peak hours. We introduce a contract based on the VCG mechanism which enables fleets of electric vehicles to export electricity to the grid efficiently throughout the day, where each electric vehicle has its energy consumption and exporting schedules and costs.
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