Matching Multidimensional Types: Theory and Application
Veli Safak

TL;DR
This paper extends Becker's scalar matching model to multidimensional types, establishing new sorting patterns and complementarities, and applies the framework to analyze health and education correlations among U.S. households.
Contribution
It introduces multidimensional generalizations of sorting concepts, identifies conditions for optimal sorting patterns, and links theory with observed aggregate attributes in empirical data.
Findings
Weak positive association between health and education among spouses
Attraction effects influence household insurance risk
Multidimensional sorting patterns explain observed attribute correlations
Abstract
Becker (1973) presents a bilateral matching model in which scalar types describe agents. For this framework, he establishes the conditions under which positive sorting between agents' attributes is the unique market outcome. Becker's celebrated sorting result has been applied to address many economic questions. However, recent empirical studies in the fields of health, household, and labor economics suggest that agents have multiple outcome-relevant attributes. In this paper, I study a matching model with multidimensional types. I offer multidimensional generalizations of concordance and supermodularity to construct three multidimensional sorting patterns and two classes of multidimensional complementarities. For each of these sorting patterns, I identify the sufficient conditions which guarantee its optimality. In practice, we observe sorting patterns between observed attributes that…
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Taxonomy
TopicsGender, Labor, and Family Dynamics · Financial Literacy, Pension, Retirement Analysis · Income, Poverty, and Inequality
