Endogenous selection bias is a central problem for causal inference. Recognizing the problem, however, can be difficult in practice. This article introduces a purely graphical way of characterizing endogenous selection bias and of understanding its consequences (Hernán et al. 2004). We use causal graphs (direct acyclic graphs, or DAGs) to highlight that endogenous selection bias stems from conditioning (e.g., controlling, stratifying, or selecting) on a so-called collider variable, i.e., a variable that is itself caused by two other variables, one that is (or is associated with) the treatment and another that is (or is associated with) the outcome. Endogenous selection bias can result from direct conditioning on the outcome variable, a post-outcome variable, a post-treatment variable, and even a pre-treatment variable. We highlight the difference between endogenous selection bias, common-cause confounding, and overcontrol bias and discuss numerous examples from social stratification, cultural sociology, social network analysis, political sociology, social demography, and the sociology of education.

This study examines how the neighborhood environments experienced over multiple generations of a family influence children’s cognitive ability. Building on recent research showing strong continuity in neighborhood environments across generations of family members, we argue for a revised perspective on “neighborhood effects” that considers the ways in which the neighborhood environment in one generation may have a lingering impact on the next generation. To specify such multigenerational effects is not simply a theoretical problem, but poses considerable methodological challenges. Instead of traditional regression techniques that may obscure multigenerational effects of neighborhood disadvantage, we utilize newly developed methods designed to generate unbiased treatment effects when treatments and confounders vary over time. The results confirm a powerful link between neighborhoods and cognitive ability that extends across generations. Being raised in a high-poverty neighborhood in one generation has a substantial negative effect on child cognitive ability in the next generation. A family’s exposure to neighborhood poverty across two consecutive generations reduces child cognitive ability by more than half a standard deviation. A formal sensitivity analysis suggests that results are robust to unobserved selection bias.

Theory suggests that neighborhood effects depend not only on where individuals live today, but also on where they lived in the past. Previous research, however, usually measured neighborhood context only once and did not account for length of residence, thereby understating the detrimental effects of long-term neighborhood disadvantage. This study investigates the effects of duration of exposure to disadvantaged neighborhoods on high school graduation. It follows 4,154 children in the PSID, measuring neighborhood context once per year from age 1 to 17. The analysis overcomes the problem of dynamic neighborhood selection by adapting novel methods of causal inference for time-varying treatments. In contrast to previous analyses, these methods do not “control away” the effect of neighborhood context operating indirectly through time-varying characteristics of the family, and thus they capture the full impact of a lifetime of neighborhood disadvantage. We find that sustained exposure to disadvantaged neighborhoods has a severe impact on high school graduation that is considerably larger than effects reported in prior research. Growing up in the most (compared to the least) disadvantaged quintile of neighborhoods is estimated to reduce the probability of graduation from 96% to 76% for black children, and from 95% to 87% for nonblack children.

Objectives We investigate the effect of spousal bereavement on mortality, and we extend prior work by documenting cause-specific bereavement effects by the causes of death both of the pre-decedent spouse and the bereaved survivor. Methods We examined a nationally representative cohort of 373,189 elderly married couples in the United States, followed from 1993 to 2002, using competing-risk and Cox models. Covariates included the baseline health of both spouses. Results In both men and women, there is significant variation in the effect of widowhood on mortality as a function of the causes of death of both spouses. The death of a spouse due to almost all causes, including various cancers, infections, and cardiovascular diseases, increases the mortality of the surviving spouse, albeit to varying degrees. Conversely, the death of a spouse increases survivor’s cause-specific mortality for almost all causes, including cancers, infections, and cardiovascular diseases, albeit to varying degrees. Conclusions The effect of widowhood on mortality varies substantially by the causes of death of both spouses, suggesting that the widowhood effect is not restricted to one aspect of human biology.