Abstract: BACKGROUND In recent decades, patterns of transition to adulthood have undergone substantial changes, including an increase in people living solo after leaving the parental home. However, the extent to which solo living after leaving the parental home is a transitory state, quickly followed by union formation, or a relatively long-term state in the pathways to adulthood, and how long-term solo living is socially stratified are all questions that remain unanswered. OBJECTIVE To fill this gap, this study focuses on home-leaving pathways that have unfolded over a 5-year period after leaving home. It explores the association between socioeconomic background (parental education) and the long-term, solo-living, home-leaving pathways of young men and women across 29 European countries. METHODS Using European Social Survey Round 9 (2018) data, this study applies a competing trajectory analysis, which combines sequence analysis to identify home-leaving patterns with event history analysis, in order to analyse their association with parental education. RESULTS The occurrence of solo-living pathways varies considerably across Europe: both short-term and long-term solo-living pathways are the highest in Northern Europe. Long-term solo-living pathways are associated with being in education and with high levels of individual and parental education. The effect of parental education does not differ systematically across European countries and does not differ between genders.
Abstract: BACKGROUND Previous studies find that members of social networks tend to influence each other regarding the likelihood and timing of births. However, less evidence exists as to whether and how individuals actively select their network ties according to parental status. Hence, we explicitly study both the discontinuation of existing ties and formation of new ties. OBJECTIVE We study network selection regarding parenthood status based on large-scale panel data on social networks in Germany. METHODS Our analyses are based on data from waves 2 and 4 of the German Family Panel (Pairfam, up to N = 36,352 ego–alter relationships). We use a record linkage procedure to match network persons longitudinally and estimate multilevel random and fixed-effect multinomial regression models. RESULTS We find weak evidence that young children increase the likelihood that existing social network relationships are discontinued and strong evidence that young children decrease the likelihood that new network relationships are initiated. Further, we find homophily effects regarding parental status in that both childless respondents and parents who recently had a child are less likely to dissolve ties to alters with the same parental status, respectively. Among women, homophily in parenthood status also increases the likelihood of establishing a new social network relationship.
Abstract: BACKGROUND Life expectancy is a pure measure of the mortality conditions faced by a population, unaffected by that population’s age structure. The numerical value of life expectancy also has an intuitive interpretation, conditional on some assumptions, as the expected age at death of an average newborn. This intuitive interpretation gives life expectancy a broad appeal. Changes in life expectancy are also routinely used to assess mortality trends. Interpreting these changes is not straightforward as the assumptions underpinning the intuitive interpretation of life expectancy are no longer valid. This is particularly problematic during mortality ‘shocks,’ such as during wars or pandemics, when mortality changes may be sudden, temporary, and contrary to secular trends. OBJECTIVE This study aims to provide an alternative perspective on what changes in life expectancy measure that remains applicable during mortality shocks. CONCLUSIONS Returning to two different models that the period life table may represent, I show that a difference in life expectancy is typically interpreted from the synthetic cohort model as the difference in mean longevity between different birth cohorts. However, it can also be interpreted from the stationary population model as a measure of premature mortality in a death cohort. The latter, less common interpretation makes more sense for temporary declines in life expectancy induced by mortality shocks. The absolute change in life expectancy is then an age-standardized value of the average lifespan reduction for people dying during the mortality shock.
Abstract: BACKGROUND It is well-established that internal migration is selective, particularly with respect to age, educational attainment, and nativity status. However, the interplay between education and immigrants’ origin remains largely unknown. Thus, it is unclear how the educational selectivity of internal migration varies by nativity status. OBJECTIVE We establish the educational selectivity of internal migrants in 12 European countries, paying attention to variation between native and foreign-born populations born in and outside the European Union. METHODS We use microdata from the European Union Labour Force Survey (2015–2019) and run a series of multivariate binomial logistic regressions to estimate the likelihood of changing NUTS-2 region of residence by educational attainment. RESULTS Our results confirm a positive association between tertiary education and internal migration, except for in Slovenia, Greece, and the Czech Republic. On average, completing tertiary education increases the likelihood of migrating internally by close to 3 times, compared with less than 1.5 times for secondary education. In half the countries, secondary education displays either a negative or no association with internal migration. We find evidence of a strong positive selectivity of tertiary-educated foreign-born populations, who are on average twice as likely to migrate internally than the native-born with comparable education, except in Hungary, where immigrants are less likely to migrate internally. CONCLUSIONS By redistributing skills within a country, immigrants are integral to the effective functioning of labour markets.
Abstract: BACKGROUND Socioeconomically disadvantaged groups disproportionately reported experiencing adverse circumstances resulting from the COVID-19 pandemic’s socioeconomic impacts. Overarching factors associated with differentiated risks in the United States include race and ethnicity. OBJECTIVE We aim to examine: (1) the differentiated risk of experiencing adverse circumstances by race and ethnicity in the United States and (2) the trend in adverse outcomes and racial/ethnic differences in the past two years. METHODS The study utilized 49 data cycles from the Household Pulse Survey from April 2020 to September 2022. The outcomes are adverse experiences, including loss of employment income, food scarcity, housing insecurity, and unmet needs for mental health services. The racial and ethnic groups are non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, non-Hispanic other minorities, and Hispanic. We compared weighted percentages of the total population and racial and ethnic groups reporting having experienced adverse circumstances during every data collection period. RESULTS We found that except for non-Hispanic Asians, racial and ethnic minorities were more likely to report loss of employment income, food scarcity, housing insecurity, and unmet needs for mental health services. Prevalence estimates by race/ethnicity for each cycle illustrated the persistent racial/ethnic disparities from April 2020 to the present. CONCLUSIONS The adverse socioeconomic impacts of the COVID-19 pandemic tended to be disproportionately higher for most racial and ethnic minorities compared to non-Hispanic Whites, and this trend continues.
Abstract: BACKGROUND The gravity of the Spanish flu has been often associated with inadequate health systems. However, few studies have used health data effectively in their analysis of epidemics. OBJECTIVE To analyze the role of hospitals in an Italian town during the Spanish flu and its effect on the risk of dying at home. METHODS Individual-level information from the Permission of Burials was used to evaluate the impact of the epidemic on city hospitals. A logistic model was used to estimate the odds of a home death in order to elucidate possible sociodemographic mechanisms linked to hospital saturation issues. RESULTS During the epidemic the odds of dying at home increased by 29% overall, driven especially by an increase in home deaths among the poorest social groups. However, the well-off maintained the highest odds of dying at home throughout 1918. CONCLUSIONS Hospitals facilitated the spread of the epidemic in the city and contributed to its high mortality level. The increase in the odds of dying at home for the poorest was likely associated with hospital saturation, which conversely does not appear to have affected the well-off. In fact, this social group already had very high levels of home deaths in the pre-epidemic period.
Abstract: OBJECTIVE This study has two objectives: first, to estimate the effect of adolescent fertility on high school completion for Chilean adolescents, considering selectivity due to socioeconomic background and prior academic achievement, and, second, to explore the gender differences that exist in this effect. METHODS We use propensity score weighting and regression adjustment to estimate the average treatment effect on the treated groups. We employ a rich dataset built on several administrative sources, covering a cohort of students attending publicly funded schools from 2011 to 2018. RESULTS Considering the samples of men and women separately, we find that a teenage girl who experiences adolescent fertility is 13% less likely to complete high school, whereas the corresponding probability for a teenage boy is only 3%. As compared to boys, girls who experience adolescent fertility also have higher probabilities of delayed high school graduation and dropping out of school. CONCLUSIONS Our analyses indicate that the detrimental effect of adolescent fertility on high school completion is larger for girls than boys in Chile, after taking into consideration the selectivity due to socioeconomic origin and prior academic performance.
Abstract: BACKGROUND Previous research posits that racial reclassification, or response shift, may confound measures of racial earnings inequality. However, this claim has not been systematically tested. OBJECTIVE We measure racial response shift in Brazil and examine its impact on white-to-nonwhite earnings inequality between survey waves over ten years at nine-month intervals. METHODS We use individual-level linked data from the 2002–2012 Monthly Employment Survey, involving Brazil's six largest metropolitan areas (n = 400,046). We describe the level and pattern of racial reclassification across time and by income rank. We then decompose racial inequality into two components (income and population ratios) to examine the impact of racial response shift on estimates of racial inequality and to construct analytic counterfactuals. RESULTS Results reveal that 16% of our sample shifted their racial responses between survey waves. Nonetheless, we show that this level of response shift had no substantial impact on estimates of income inequality. We explain the counterintuitive results by demonstrating how bidirectional racial classification flows – lightening and darkening – countervail each other due to their similar income profiles and racial reclassification rates.
Abstract: BACKGROUND Italy’s life expectancy at age 65 is one of the highest in Europe, but its disability-free life expectancy (DFLE) is not so high. To understand this diverging pattern of longevity and health it is essential to consider indicators accounting for both mortality and morbidity, and to analyse the gender, social, and geographical inequities characterising them. OBJECTIVE The aim is to quantify the gender, social, and geographical inequalities in DFLE among Italian older adults and analyse the age-specific contribution of mortality and morbidity to those inequalities. METHODS This study draws on census-linked mortality data and disability prevalence for the years 2012–2014. DFLE at age 65 in Italian regions is computed by gender and educational attainment using the Sullivan method. Age-specific mortality–morbidity contributions to the gender and educational gaps in DFLE are calculated using the stepwise decomposition method. RESULTS Although at the national level older women and men share similar DFLE, these estimates hide important geographical and social inequalities. Women’s health disadvantage completely outweighs their life expectancy advantage, resulting in lower DFLE. Educational inequalities in health are far more dramatic than those in mortality and the disadvantage in DFLE accumulates over education and region of residence. CONCLUSIONS In Italy notable differences in DFLE are found between genders and between educational groups, suggesting the need for better health policies aimed at reducing inequalities.
Abstract: BACKGROUND Research shows that children’s social background influences the extent to which they experience educational disadvantages when their parents separate. However, while some studies find larger separation penalties for children from lower social backgrounds than for children from higher backgrounds, other studies find the opposite. The present study builds on this research by examining heterogeneous parental separation effects by parental education for lower (mid-secondary) and higher (higher-secondary) educational thresholds. METHODS Analyses are based on a sample of children (and their siblings) born in the 1970s and 1960s (N = 6,855 children), drawn from the German Life History Study. A series of linear probability models are estimated; additional analyses include sibling-fixed-effects models. RESULTS No separation disadvantages for children from higher status backgrounds were found, for either outcome. Children from lower educational backgrounds had fewer chances of completing mid-secondary education; this was true to a lesser extent for higher-secondary education. Sibling fixed effects show the same pattern but also indicate that results may be partly due to unobserved family characteristics.
Abstract: BACKGROUND Timely, accurate, and precise demographic estimates at various levels of geography are crucial for planning, policymaking, and analysis. In the United States, data from the decennial census and annual American Community Survey (ACS) serve as the main sources for subnational demographic estimates. While estimates derived from these sources are widely regarded as accurate, their timeliness is limited and variability sizable for small geographic units like towns and neighborhoods. OBJECTIVE This paper investigates the potential for using nonrepresentative consumer trace data assembled by commercial vendors to produce valid and timely estimates. We focus on data purchased from Data Axle, which contains the names and addresses of over 150 million Americans annually. METHODS We identify the predictors of over- and undercounts of households as measured with consumer trace data and compare a range of calibration approaches to assess the extent to which systematic errors in the data can be adjusted for over time. We also demonstrate the utility of the data for predicting contemporaneous (nowcasting) tract-level household counts in the 2020 Decennial Census. RESULTS We find that adjusted counts at the county, ZIP Code Tabulation Areas (ZCTA), and tract levels deviate from ACS survey-based estimates by an amount roughly equivalent to the ACS margins of error. Machine-learning methods perform best for calibration of county- and tract-level data. The estimates are stable over time and across regions of the country. We also find that when doing nowcasts, incorporating Data Axle estimates improved prediction bias relative to using the most recent ACS five-year estimates alone.
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