Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/161072 
Erscheinungsjahr: 
2016
Schriftenreihe/Nr.: 
IZA Discussion Papers No. 10449
Verlag: 
Institute of Labor Economics (IZA), Bonn
Zusammenfassung: 
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.
Schlagwörter: 
inverse optimal transport
rank-constrained estimation
bipartite matching
marriage market
JEL: 
C5
D3
Dokumentart: 
Working Paper

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