Abstract
AbstractWe develop a method which assumes that marital preferences are characterized either by the scalar-valued measure proposed by Liu and Lu, or by the matrix-valued generalized Liu–Lu measure. The new method transforms an observed contingency table into a counterfactual table while preserving its (generalized) Liu–Lu value. After exploring some analytical properties of the new method, we illustrate its application by decomposing changes in the prevalence of homogamy in the US between 1980 and 2010. We perform this decomposition with two alternative transformation methods as well where both methods capture preferences differently from Liu and Lu. Finally, we use survey evidence to support our claim that out of the three considered methods, the new transformation method is the most suitable for identifying the role of marital preferences at shaping marriage patterns. These data are also in favor of measuring assortativity in preferences à la Liu and Lu.
Highlights
Measuring the effect of changing marital preferences on the changing marital patterns is in the center of interest of many demographers, economists, and sociologists
The examples include the following: (i) controlling for marital preferences by the aggregate marriage matching function derived by Choo and Siow (2006); (ii) applying the iterative proportional fitting (IPF) algorithm developed by Stephan and Deming (1940) and generalized by Sinkhorn (1967); (iii) keeping a similarity coefficient fixed, e.g., the correlation between the couples’ trait [e.g., Kremer (1997), Fernandez et al (2005)]
The typical question addressed is how the marriage patterns would have changed in the absence of change in the education levels of men and women
Summary
Measuring the effect of changing marital preferences on the changing marital patterns is in the center of interest of many demographers, economists, and sociologists. This task is challenging because the observed equilibrium outcome in the marriage market depends on marital preferences and on the structural availability of prospective partners with different traits as well as the interplay between preferences and availability (Kalmijn 1998).. What would be the share of educationally homogamous couples like in our society today if the education levels of young men and women were the same as in an older generation?. Our work facilitates method selection for those researchers who would like to study changing marriage patterns by analyzing contingency tables
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