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Decomposition of the changes in the share of homogamous couples with a specific education level and the share of all educationally homogamous couples between 2001 and 2011 in Hungary. Notes: The decomposition uses census data for Hungary from 2001 and 2011 in combination with the dating data. Changes in the aggregate and the education level-specific measures of prevalence of homogamy are decomposed by the Oaxaca-Blinder decomposition scheme. It works as follows with factors being preferences (determined by the estimates for P RP=S and P RP=S ) and availability of potential partners with given education levels (determined by the gender-specific educational distributions) and observations from time 0 and 1:f (a 1 , p 1 ) − f (a 0 , p 0 ) = f * (a 0 , p 1 ) − f (a 0 , p 0 ) due to D preferences
Source publication
We study changes in educational homogamy in the US and four European countries over the decade covering the Great Recession. The marital preferences identified point to the widening of the social gap between different educational groups since these preferences have increased the inclination of the individuals to match with others of similar educati...
Contexts in source publication
Context 1
... robustness check confirms the main finding of the benchmark decomposition: the changes in the marital preferences over the partners' education levels and getting married at all made educational homogamy more prevalent. This is apparent from the aggregate results presented by Figure 9, where the dark bar is in the positive range. ...
Context 2
... if one disregarded the kind of adjustment along the extensive margin that is due to the changing share of the voluntary singles, then the above four percentage points effect would be estimated to be negligible (see the hardly visible striped bar in Figure 9 corresponding to the aggregate value). ...
Citations
... (M7) GS-approach, where matching is made by the Gale-Shapley matching algorithm, while the nonstructural factor, i.e., the aggregate marital preferences over a single dimensional trait is kept fixed with the unchanged gender-specific and education level-specific distributions of the reservation points. It was proposed and applied by Naszodi and Mendonca (2022), who used the search criteria on a dating site as a proxy for the reservation points. ...
Measuring the extent to which educational marital homophily differs in two consecutive generations is challenging when the educational distributions of marriageable men and women are also generation-specific. We propose a set of criteria that indicators may have to satisfy to be considered as suitable measures of homophily. One of our analytical criteria is on the robustness to the number of educational categories. Another analytical criterion defined by us is on the association between intergenerational mobility and homophily. A third criterion is empirical and concerns the identified historical trend of homophily, a comprehensive aspect of inequality, in the US between 1960 and 2015. While the ordinal Liu--Lu-indicator and the cardinal indicator constructed with the Naszodi--Mendonca method satisfy all three criteria, most indices commonly applied in the literature do not. Our analysis sheds light on the link between the violation of certain criteria and the sensitivity of the historical trend of homophily obtained in the empirical assortative mating literature.
... As to the major source of risk, the literature finds inequality of various forms to positively associated with the degree of segmentation of the marriage market and to negatively associ-ated with social cohesion. For instance, Naszodi and Mendonca (2022) present evidence that the growing inequality of opportunity to find a job in the 2000s in the US -as well as in the European countries (France, Hungary and Portugal) they analyze -coincided with the rise in inclination to choose a partner from one's own education group. In particular, during the Great Recession, the employment prospects of people with low education level have worsened relative to the highly educated individuals. ...
... At the same time, educational inter-marriages have typically became less desired in 2010 relative to 2000 in all the countries analyzed. Naszodi and Mendonca (2022) identify the employment gap-marital preferences association with time series data as well: they find Americans' stated marital preferences over spousal education monitored by surveys to have had a more than 70% correlation with the employment gap between highly educated and low educated workers between 1990 and 2017. ...
https://doi.org/10.48550/arXiv.2303.05515
In this paper, we identify two different sets of problems. The first covers the problems that the iterative proportional fitting (IPF) algorithm was developed to solve. These concern completing a population table by using a sample. The other set concerns constructing a counterfactual population table with the purpose of comparing two populations. The IPF is commonly applied by social scientists to solve problems not only in the first set, but also in the second one. We show that while it is legitimate to use the IPF for the first set of problems, it is not the right tool to address the problems of the second kind. We promote an alternative of the IPF, the NM-method (see https://en.wikipedia.org/wiki/NM-method), for solving problems in the second set. We provide both theoretical and empirical comparisons of these methods.
Europeans are, on average, better educated and live healthier, longer and more prosperous lives today than at any point in the past. However, this view on average achievements obscures large disparities, both within and between European countries. The income of the richest 20 % of households in Europe is on average 5 times higher than that of the poorest 20 %, and up to 8 times higher in some Member States. Most indicators of well-being display a social gradient according to education level, occupation, income and social status. The Great Recession has reinforced existing socio-economic divides. Vulnerable groups – those with low education levels, the unemployed and individuals with a migrant experience – have largely borne the brunt of the resulting economic downturn and austerity programmes. Southern European countries were hit particularly hard. Growing disparities on multiple socio-economic dimensions have contributed to a sense of unfairness and discontent in Europe. Recent data show that 38 % of Europeans do not believe that they are treated fairly and 41 % do not agree that they have enjoyed equal opportunities in life. Fairness is a subjective phenomenon, but the far-reaching consequences of perceptions of unfairness warrant a closer look at its drivers and underlying dynamics. The present report analyses some of the most pertinent dimensions of fairness in relation to the agenda for a fair, inclusive and social European Union (EU). Chapter 2 describes Europeans’ perceptions of fairness and how they vary across countries and socio-economic groups. The chapter also discusses how perceptions of fairness relate to the functioning of society and to individual wellbeing. Chapter 3 presents some stylised facts on income inequality for the whole EU before, during and after the Great Recession. The dynamics of income inequality are shown for the entire income distribution as well as for different income sources in the EU as a whole, but also for three macro-regions. Chapter 4 discusses inequality of opportunity – a key structural inequality in society – through the study of persistence of educational attainment levels across generations. The analysis goes beyond most existing evidence by considering persistence across three generations rather than only two. The second part of the chapter explores individual perceptions of social mobility and beliefs about equality of opportunity. After the examination of inequality of outcomes and opportunities in Europe, Chapter 5 provides some perspectives and evidence on welfare state arrangements and tax-benefit systems: the distributional impacts of tax reforms, individual tax evasion behaviour, corporate tax avoidance behaviour and aspects of social protection in changing labour markets. Chapter 6 concludes this report.
