Coupling couples with copulas: analysis of assortative matching on risk attitude

TL;DR

This paper introduces a novel copula-based bivariate panel ordinal model to analyze assortative matching on risk attitudes within married couples, revealing positive dependence and evidence of assimilation over time.

Contribution

The study develops a new copula-based modeling approach for ordinal data and applies it to couple risk attitudes, providing novel insights into assortative matching and its evolution.

Findings

Positive dependence in risk attitudes within couples

Evidence of increasing assortative matching over marriage duration

Rejection of risk-sharing based matching theories

Abstract

We investigate patterns of assortative matching on risk attitude, using self-reported (ordinal) data on risk attitudes for males and females within married couples, from the German Socio-Economic Panel over the period 2004-2012. We apply a novel copula-based bivariate panel ordinal model. Estimation is in two steps: firstly, a copula-based Markov model is used to relate the marginal distribution of the response in different time periods, separately for males and females; secondly, another copula is used to couple the males' and females' conditional (on the past) distributions. We find positive dependence, both in the middle of the distribution, and in the joint tails, and we interpret this as positive assortative matching (PAM). Hence we reject standard assortative matching theories based on risk-sharing assumptions, and favour models based on alternative assumptions such as the ability of agents to control income risk. We also find evidence of "assimilation"; that is, PAM appearing to increase with years of marriage.