Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/161072
Authors: 
Dupuy, Arnaud
Galichon, Alfred
Sun, Yifei
Year of Publication: 
2016
Series/Report no.: 
IZA Discussion Papers 10449
Abstract: 
In this paper, we address the problem of estimating transport surplus (a.k.a. matching affinity) in high dimensional optimal transport problems. Classical optimal transport theory species the matching affinity and determines the optimal joint distribution. In contrast, we study the inverse problem of estimating matching affinity based on the observation of the joint distribution, using an entropic regularization of the problem. To accommodate high dimensionality of the data, we propose a novel method that incorporates a nuclear norm regularization which effectively enforces a rank constraint on the affinity matrix. The lowrank matrix estimated in this way reveals the main factors which are relevant for matching.
Subjects: 
inverse optimal transport
rank-constrained estimation
bipartite matching
marriage market
JEL: 
C5
D3
Document Type: 
Working Paper

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