Identifying Marriage Markets

Ugo Bolletta, Laurens Cherchye, Thomas Demuynck, Bram De Rock and Luca Merlino

No 2024-12, Working Papers ECARES from ULB -- Universite Libre de Bruxelles

Abstract: We propose a method to identify individuals’ marriage markets assuming that observed marriages are stable. We aim to learn about (the relative importance of) the individual’s observable characteristics defining these markets. First, we use a nonparametric revealed preference approach to construct inner and outer bound approximations of these markets from observed marriages. We then use machine learning to estimate arobust boundary between them (as a linear function of individual characteristics). We demonstrate the usefulness of our method using Dutch household data and quantify the trade-off between the characteristics such as age, education and wages defining individuals’ marriage markets.

Keywords: marriage market; identification; revealed preferences; machine learning; support vector machine (SVM). (search for similar items in EconPapers)
Pages: 28 p.
Date: 2024-07
New Economics Papers: this item is included in nep-big, nep-cmp and nep-dcm
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