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The question of how social mobility affects outcomes, such as political preferences, wellbeing, and fertility, has long been of interest to sociologists. But finding answers to this question has been plagued by, on the one hand, the non-identifiability of "mobility effects" as they are usually conceived in this literature, and, on the other, the fact that these "effects" are, in reality, partial associations which may or may not represent causal relationships. We advance a different approach, drawing on a causal framework that sees the destination categories as treatments whose effects may be heterogeneous across origin categories. Our view is that most substantive hypotheses have in mind a hypothetical within-person comparison, rather than a between-person comparison. This approach is not subject to many of the problematic issues that have beset earlier attempts to formulate a model of mobility effects, and it places the study of such effects on a more reliably causal footing. We show how our approach relates to previous attempts to model mobility effects and explain how it differs both conceptually and empirically. We illustrate our approach using political preference data from the United Kingdom.

Collapses of China’s ruling dynasties were associated with explosive volcanic eruptions over the past two millennia, with the degree of influence depending on pre-existing stress in society, as suggested by a systematic analysis of eruptions and Chinese warfare.

Abstract The application of polygenic scores has transformed our ability to investigate whether and how genetic and environmental factors jointly contribute to the variation of complex traits. Modelling the complex interplay between genes and environment, however, raises serious methodological challenges. Here we illustrate the largely unrecognised impact of gene-environment dependencies on the identification of the effects of genes and their variation across environments. We show that controlling for heritable covariates in regression models that include polygenic scores as independent variables introduces endogenous selection bias when one or more of these covariates depends on unmeasured factors that also affect the outcome. This results in the problem of conditioning on a collider, which in turn leads to spurious associations and effect sizes. Using graphical and simulation methods we demonstrate that the degree of bias depends on the strength of the gene-covariate correlation and of hidden heterogeneity linking covariates with outcomes, regardless of whether the main analytic focus is mediation, confounding, or gene × covariate (commonly gene × environment) interactions. We offer potential solutions, highlighting the importance of causal inference. We also urge further caution when fitting and interpreting models with polygenic scores and non-exogenous environments or phenotypes and demonstrate how spurious associations are likely to arise, advancing our understanding of such results.

As a feature of the Fish Revolution (1400–1700), the early modern “invention” of the Grand Banks in literary and cartographical documents facilitated a massive and unprecedented extraction of cod from the waters of the north Atlantic and created the Cod/Sack trade Triangle. This overlapped with the southern Atlantic Slave, Sugar, and Tobacco Triangle to capitalise modern European and North American societies. In 1719, Pierre de Charlevoix claimed that the Grand Banks was “properly a mountain, hid under water,” and noted its cod population “seems to equal that of the grains of sand which cover this bank.” However, two centuries later in 1992, in the face of the collapse of the fishery, and fearing its extinction, a moratorium was placed on five centuries of harvesting Grand Banks cod. The invention and mining of its waters serves as a bellwether for the massive resource extractions of modernity that drive the current leviathan and “wicked problem” of global warming. The digital environmental humanities narrative of this study is parsed together from 83 pieces of Grand Banks charting from 1504 to 1833, which are juxtaposed through Humanities GIS applications with English and French cod‐catch records kept between 1675 and 1831, letters regarding Cabot's 1497 voyage, Shakespeare's The Tempest (1611) and scientific essays by De Brahms (1772) and Franklin (1786).

Background: By their nature, the impact of epidemics on mortality varies geographically, suggesting that the geographical impact of an epidemic implies a social impact. Objective: To examine the association between two measures of the social composition of a local area and age- and sex-standardised Covid-19 and other mortality in the period 1 March to 31 July 2020. The measures are how deprived an area is and what proportion of its population is non-white. Methods: Using spatial autoregressive regression we analyse geographical variation in age- and sex-standardised Covid-19 mortality among English local authorities between 1 March and 31 July 2020 in relation to measures of social composition, and we compare it with mortality from non-Covid sources in the same period, and with all-causes mortality in 2018. Results: Areas with higher social deprivation have a higher Covid-19 mortality rate, but the association is much weaker than between social deprivation and mortality rates more generally. An area's proportion non-white has a strong positive association with Covid-19 mortality, in contrast to a negative association with 2020 non-Covid and with 2018 mortality. Conclusions: Covid-19 mortality is related to the social composition of areas in different ways than current non-Covid mortality or past mortality. Contribution: The paper provides the first demonstration of the distinct distributional impact of mortality in relation to the Covid-19 virus by the social composition of areas in England.

It is often pointed out that conclusions about intergenerational (parent–child) mobility can differ depending on whether we base them on studies of class or income. We analyze empirically the degree of overlap in income and social mobility; we demonstrate mathematically the nature of their relationship; and we show, using simulations, how intergenerational income correlations relate to relative social mobility rates. Analyzing Swedish longitudinal register data on the incomes and occupations of over 300,000 parent–child pairs, we find that social mobility accounts for up to 49 percent of the observed intergenerational income correlations. This figure is somewhat greater for a fine-graded micro-class classification than a five-class schema and somewhat greater for women than men. There is a positive relationship between intergenerational social fluidity and income correlations, but it is relatively weak. Our empirical results, and our simulations verify that the overlap between income mobility and social mobility leaves ample room for the two indicators to move in different directions over time or show diverse patterns across countries. We explain the circumstances in which income and social mobility will change together or co-vary positively and the circumstances in which they will diverge.

We consider the problem of bias arising from conditioning on a post-outcome collider. We illustrate this with reference to Elwert and Winship (2014) but we go beyond their study to investigate the extent to which inverse probability weighting might offer solutions. We use linear models to derive expressions for the bias arising in different kinds of post-outcome confounding, and we show the specific situations in which inverse probability weighting will allow us to obtain estimates that are consistent or, if not consistent, less biased than those obtained via ordinary least squares regression.

Background: Conventional studies of intergenerational social reproduction are based on a retrospective design, sampling adults and linking their status to that of their parents. This approach yields conditional estimates of intergenerational relationships. Recent studies have taken a prospective approach, following a birth cohort forward to examine how it is socially reproduced. This permits the estimation of relationships of social reproduction that do not condition on the existence of at least one child. Objective: We examine whether the relationship between conditional and unconditional estimates found for the United States and Great Britain also holds for a diverse range of European countries. Methods: We examine educational reproduction among men and women born 1930-1950 in 12 countries using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) and compare unconditional and conditional estimates. Results: We find striking similarities in the relationship between unconditional and conditional estimates throughout Europe. Among women, the difference between conditional and unconditional estimates generally increased with education. Women with more education were less likely to reproduce themselves educationally because they were less likely to marry. The educational gradient, in terms of the probability of having a child who attained a tertiary degree, was more pronounced in the South and East of Europe than in the North and West. Conclusions: The gap between conditional and unconditional estimates indicates that the more common retrospective approach tends to overstate the extent of educational reproduction. Contribution: This is the first comparative study adopting a prospective approach to intergenerational social reproduction.

Many commentators have seen the growing gap in earnings and income between those with a college education and those without as a major cause of increasing inequality in the United States and elsewhere. In this article we investigate the extent to which increasing the educational attainment of the US population might ameliorate inequality. We use data from NLSY79 and carry out a three-level decomposition of total inequality into within-person, between-person and between-education parts. We find that the between-education contribution to inequality is small, even when we consider only adjusted inequality that omits the within-person component. We carry out a number of simulations to gauge the likely impact on inequality of changes in the distribution of education and of a narrowing of the differences in average incomes between those with different levels of education. We find that any feasible educational policy is likely to have only a minor impact on income inequality.

The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects. This might lead us to find heterogeneous effects when the true effect is homogenous, or to wrongly estimate not only the magnitude but also the sign of heterogeneous effects. We apply a test for the robustness of heterogeneous causal effects in the face of varying degrees and patterns of selection bias, and we illustrate our arguments and our method using National Longitudinal Survey of Youth 1979 (NLSY79) data.