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The paper investigates whether loglinear models of achieved-marriage tables can validly detect underlying preferences, rather than merely reproducing outcomes caused by marginal distributions and gendered characteristics. Focusing on female hypergamy by education, it tests detection accuracy across ideal-typical data-generating processes through simulation, then evaluates how the resulting patterns relate to estimated hypergamy parameters and time dynamics.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/partner-choice-and-parameter-estimates-modelling-the-effect-of-preferences/565387/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/partner-choice-and-parameter-estimates-modelling-the-effect-of-preferences/565387.png","ImageObject",442,249,{"name":88,"@type":89},"Aurelia","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-26","2026-10-13",true,{"@type":98,"interactionType":99,"userInteractionCount":47},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What problem does the paper address in interpreting assortative mating outcomes?","Question",{"text":108,"@type":109},"It examines whether preferences can be inferred from achieved-marriage tables when outcomes are constrained by gendered characteristic distributions, competition among peers, and the agents’ own preferences. 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However, it is a complex process, and while tempting it is problematic to read preferences directly from the empirical outcomes. The mapping of preferences to outcomes in a process subject to constraints is not straightforward. Outcomes are constrained in complex ways, not least the gendered distribution of the characteristics of interest, the competition among peers for alters with the desired characteristics, and the fact that alters are agents with preferences too. Additionally, the fact that the process is dynamic, where the context changes continually, not only because of external historical reasons, but also endogenously, as the distribution of single people changes as others marry.  \nResearch on assortative mating has a long history of looking at the data, usually tables of spouse pairs classified by the characteristic of interest, and making inferences about the data generating processes in terms of homogamy preference, competition for desirable characteristics, female hypergamy preference, or relative desirability of different characteristics leading to status exchange. Earlier work tends to read directly from patterns in the tables, or simple summaries. But loglinear modelling of these tables, predominant in the literature since the 1980s, is markedly super","cbCaiqcWETSxBdeM","https://ap.wps.com/l/cbCaiqcWETSxBdeM","pdf",1466149,33,"English","# 1 Introduction\n# 2 Assortative mating and preferences\n## 2.1 Loglinear models and international comparisons\n## 2.2 The reversing gender gap in education and female hypergamy norms\n## 2.3 Research using simulation\n# 3 Four forms of assortative mating process\n# 4 Excess educational homogamy and the ESS\n## 4.1 Excess female hypergamy\n## 4.2 Log-linear models\n## 4.3 Modelling the data\n# 5 Simulations\n## 5.1 Homophily\n## 5.2 Competition\n## 5.3 Social structure\n## 5.4 Time structure\n## 5.5 Hypergamy\n# 6 Results\n## 6.1 Patterns of assortative mating\n## 6.2 Model detection of the effect of hypergamy preference\n## 6.3 Estimating the hypergamy parameter\n## 6.4 Time dynamics and a simpler homophily simulation\n# 7 Discussion and conclusion\n# A Appendix\n## A.1 Simple homophily/hypogamy simulation\n## A.2 Association models and simulations\n## A.3 Modelling ESS: fit","[{\"question\":\"What problem does the paper address in interpreting assortative mating outcomes?\",\"answer\":\"It examines whether preferences can be inferred from achieved-marriage tables when outcomes are constrained by gendered characteristic distributions, competition among peers, and the agents’ own preferences. It highlights that mapping preferences to outcomes is not straightforward.\"},{\"question\":\"Why does the paper focus on female hypergamy in education?\",\"answer\":\"It targets female hypergamy by educational attainment, motivated by contemporary interest in a reversing gender gap in education. The goal is to test whether observed hypergamy reflects true preference or mainly inequality in marginal education distributions.\"},{\"question\":\"How does the paper test whether loglinear models detect preference effects?\",\"answer\":\"It simulates ideal-typical mechanisms producing assortative mating, overlays varying levels of hypergamy preference, and then checks whether loglinear models of marriage tables can accurately detect the simulated preference effects. It also studies time dynamics via the simulations and parameter estimation.\"}]","Partner Choice and Parameter Estimates - Modelling the Effect of Preferences | PDF",1791852806]