The Combinatorial Assignment Problem: Approximate Competitive Equilibrium from Equal Incomes

By Eric Budish. Journal of Political Economy, 2010

1,077 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/f70f810b4fcc0e0a2358d2cbafac958c8ed61ab1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Fuhito Kojima
2. Nisarg Shah
3. Eric Budish
4. Lars Ehlers
5. Yeon-Koo Che
6. Benjamin Plaut
7. Tim Roughgarden
8. Yuichiro Kamada

In Management Science and Operations Research

1. Fuhito Kojima
2. Nisarg Shah
3. Eric Budish
4. Lars Ehlers
5. Benjamin Plaut
6. Tim Roughgarden
7. Yeon-Koo Che
8. Yuichiro Kamada

Citations in the corpus

• Matching, Allocation, and Exchange of Discrete Resources (2009, neutral): “Budish (2009) endogenized competitive prices and bidding using a direct mechanism.”
• Efficient Matching under Distributional Constraints: Theory and Applications (2015, background): “A classical resource allocation problem with multi-unit demand has attracted renewed attention in the context of practical course allocation at business schools as studied by Sönmez and Ünver (2010), Budish and Cantillon (2010), and Budish (2010). Initiated by Roth, Sönmez, and Ünver (2004, 2005, 20”
• Almost Envy-Freeness with General Valuations (2017, methodology): “The Wharton School at the University of Pennsylvania now uses a theoretically grounded mechanism titled Course Match to fairly allocate courses among MBA students, which has led to demonstrably higher satisfaction and perceived fairness among students [7, 8].”
• Fair Public Decision Making (2016, background): “Unfortunately, envy-freeness cannot always be guaranteed, and therefore its relaxations have been focused on [11, 14, 26, 30].”
• School choice with controlled choice constraints: Hard bounds versus soft bounds (2011, methodology): “In Appendix A, we provide a simpler and more intuitive algorithm for finding such an assignment that we call the deferred acceptance algorithm with fixed type allotments ( DAAFTA ) We also show how DAAFTA followed by SEA works in Appendix A”
• Designing Random Allocation Mechanisms: Theory and Applications (2013, background): “(18)See Sönmez and Ünver (2008) and Budish and Cantillon (2009). (19)Budish (2009) proposes a mechanism that adapts CEEI to multi-unit assignment in a di erent way.”
• The Core of the Participatory Budgeting Problem (2016, background): “Though these as well as public good markets are truthful in the Bayesian sense in the large market limit [2, 4, 1], we seek dominant strategy truthful mechanisms, which are non-trivial to design for public good markets even in the large market limit.”
• The Unreasonable Fairness of Maximum Nash Welfare (2016, positive): “Our quest for fairer algorithms is part of the growing body of work on practical applications of computational fair division [Budish 2011; Ghodsi et al. 2011; Aleksandrov et al. 2015; Procaccia and Wang 2014; Kurokawa et al. 2015].”