# Online Housing Market

arXiv: https://arxiv.org/abs/2501.15916 · HTML: https://mlsanity.com/paper/2501.15916/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 58 references that are in the map.
- First posted on arXiv 27 Jan 2025.

## Builds on (most cited first, 12 of 12)

- [Online Fair Division: analysing a Food Bank problem](https://mlsanity.com/paper/1502.07571/) (2015)
- [Online Fair Division: A Survey](https://mlsanity.com/paper/1911.09488/) (2019)
- [Online Nash Social Welfare Maximization with Predictions](https://mlsanity.com/paper/2008.03564/) (2020)
- [Proportionally Fair Online Allocation of Public Goods with Predictions](https://mlsanity.com/paper/2209.15305/) (2022)
- [Matchings with Group Fairness Constraints: Online and Offline Algorithms](https://mlsanity.com/paper/2105.09522/) (2021)
- [Online Stochastic Matching, Poisson Arrivals, and the Natural Linear Program](https://mlsanity.com/paper/2103.13024/) (2021)
- [Class Fairness in Online Matching](https://mlsanity.com/paper/2203.03751/) (2022)
- [Strategyproof Multi-Item Exchange Under Single-Minded Dichotomous Preferences](https://mlsanity.com/paper/1905.10778/) (2019)
- [Strategy-proofness, Envy-freeness and Pareto efficiency in Online Fair Division with Additive Utilities](https://mlsanity.com/paper/2006.15900/) (2020)
- [Efficient Reallocation under Additive and Responsive Preferences](https://mlsanity.com/paper/1604.01091/) (2016)
- [The Temporary Exchange Problem](https://mlsanity.com/paper/1807.05514/) (2018)
- [Online 2-stage Stable Matching](https://mlsanity.com/paper/2207.02057/) (2022)

## Abstract (arXiv)

This paper studies an online variant of the celebrated housing market problem, where each agent has a single house and seeks to exchange it for another based on her preferences. In this online setting, agents may arrive and depart at any time, meaning that not all agents are present on the housing market simultaneously. I extend the well known serial dictatorship and Gale s top trading cycle mechanisms to this online scenario, aiming to retain their desirable properties such as Pareto efficiency, individual rationality, and strategy proofness. These extensions also seek to prevent agents from strategically delaying their arrival or advancing their departure. I demonstrate that achieving all of these properties simultaneously is impossible in the online context, and I present several variants that achieve different subsets of these properties.