Modelling Union Dissolution: A Global Comparative Review of Quantitative Approaches (2001–2025)

Research on union dissolution has expanded considerably over the past two decades, yet evidence remains fragmented across regions, methodological traditions, data systems and union types, particularly outside North America and Western Europe. This study provides a global comparative synthesis of quantitative research on union dissolution, by identifying the dominant statistical approaches, examining their distribution across world regions, and determining which predictors are most frequently analysed in relation to union dissolution. It also highlights methodological and geographical imbalances that limit cross-national comparability and the cumulative development of demographic knowledge. The review covers 174 peer-reviewed articles published between 2001 and 2025, comprising 312 statistical models from 45 countries and four African regions. Models were classified according to methodological approach, union type and categories of explanatory variables. The findings show that discrete-time event history models and Cox regression dominate empirical research in the field. Despite the growing demographic relevance of non-marital partnerships, cohabiting couples remain substantially underrepresented in empirical analyses. Across regions, the most frequently examined predictors include demographic, socioeconomic, child-related, family-background and socio-psychological factors, reflecting both common patterns and region-specific determinants of union dissolution. The study concludes that, despite its increasing scope, the literature on union dissolution remains methodologically and geographically uneven. Limited access to timely longitudinal data continues to hinder the development of comparable evidence and the broader application of advanced statistical methods in many regions. By synthesising more than two decades of quantitative research, this paper provides a methodological synthesis of quantitative approaches to union dissolution across diverse demographic and institutional contexts, while identifying prevailing modelling practices, regional research gaps and key predictor domains.