F. Elwert - Academia.edu (original) (raw)

Papers by F. Elwert

American Journal of Sociology, 2016

Effects of disadvantaged neighborhoods on child educational outcomes likely depend on a family's ... more Effects of disadvantaged neighborhoods on child educational outcomes likely depend on a family's economic resources and the timing of neighborhood exposures during the course of child development. This study investigates how timing of exposure to disadvantaged neighborhoods during childhood versus adolescence affects high school graduation and whether these effects vary across families with different income levels. It follows 6,137 children in the PSID from childhood through adolescence and overcomes methodological problems associated with the joint endogeneity of neighborhood context and family income by adapting novel counterfactual methods-a structural nested mean model estimated via two-stage regression with residuals-for timevarying treatments and time-varying effect moderators. Results indicate that exposure to disadvantaged neighborhoods, particularly during adolescence, has a strong negative effect on high school graduation and that this negative effect is more severe for children from poor families. Spatial inequality is a central dimension of social stratification. Ever since the publication of Wilson's ð1987Þ influential treatise on urban poverty, researchers have worked to understand how concentrated neighborhood

American Sociological Review, 2011

Theory suggests that neighborhood effects depend not only on where individuals live today, but al... more 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 measures neighborhood context only once and does not account for length of residence, thereby understating the detrimental effects of long-term neighborhood disadvantage. This study investigates effects of duration of exposure to disadvantaged neighborhoods on high school graduation. It follows 4,154 children in the Panel Study of Income Dynamics, 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; thus, they capture the full impact of a lifetime of neighborhood disadvantage. We find that s...

Biometrics, Jan 29, 2014

The identification of causal peer effects (also known as social contagion or induction) from obse... more The identification of causal peer effects (also known as social contagion or induction) from observational data in social networks is challenged by two distinct sources of bias: latent homophily and unobserved confounding. In this paper, we investigate how causal peer effects of traits and behaviors can be identified using genes (or other structurally isomorphic variables) as instrumental variables (IV) in a large set of data generating models with homophily and confounding. We use directed acyclic graphs to represent these models and employ multiple IV strategies and report three main identification results. First, using a single fixed gene (or allele) as an IV will generally fail to identify peer effects if the gene affects past values of the treatment. Second, multiple fixed genes/alleles, or, more promisingly, time-varying gene expression, can identify peer effects if we instrument exclusion violations as well as the focal treatment. Third, we show that IV identification of peer...

Handbooks of Sociology and Social Research, 2013

Biometrics, Apr 1, 2014

The identification of causal peer effects (also known as social contagion or induction) from obse... more The identification of causal peer effects (also known as social contagion or induction) from observational data in social networks is challenged by two distinct sources of bias: latent homophily and unobserved confounding. In this paper, we investigate how causal peer effects of traits and behaviors can be identified using genes (or other structurally isomorphic variables) as instrumental variables (IV) in a large set of data generating models with homophily and confounding. We use directed acyclic graphs to represent these models and employ multiple IV strategies and report three main identification results. First, using a single fixed gene (or allele) as an IV will generally fail to identify peer effects if the gene affects past values of the treatment. Second, multiple fixed genes/alleles, or, more promisingly, time-varying gene expression, can identify peer effects if we instrument exclusion violations as well as the focal treatment. Third, we show that IV identification of peer effects remains possible even under multiple complications often regarded as lethal for IV identification of intra-individual effects, such as pleiotropy on observables and unobservables, homophily on past phenotype, past and ongoing homophily on genotype, inter-phenotype peer effects, population stratification, gene expression that is endogenous to past phenotype and past gene expression, and others. We apply our identification results to estimating peer effects of body mass index (BMI) among friends and spouses in the Framingham Heart Study. Results suggest a positive causal peer effect of BMI between friends.

Annual Review of Sociology, 2014

Endogenous selection bias is a central problem for causal inference. Recognizing the problem, how... more 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 ). 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.

wjh.harvard.edu

This paper contradicts the current consensus about the role of incarceration in US-European labor... more This paper contradicts the current consensus about the role of incarceration in US-European labor market performance differentials. Theoretically, I develop a more general model for the causal interrelationship between incarceration and unemployment that ...

Social Science & Medicine, 2008

The effect of death of a spouse on the mortality of the survivor (the &am... more The effect of death of a spouse on the mortality of the survivor (the "widowhood effect") is well-established. We investigated how the effect of widowhood on mortality depends on the neighborhood concentration of widowed individuals in the United States. We developed a large, nationally representative, and longitudinal dataset from Medicare claims and other data sources characterizing 200,000 elderly couples, with nine years of follow-up (1993-2002), and estimated multilevel grouped discrete-time hazard models. In neighborhoods with a low concentration of widowed individuals, widowhood increased the odds of death for men by 22% and for women by 17%, compared to 17% for men, and 15% for women in neighborhoods with a high concentration of widowed individuals. Our findings suggest that neighborhood structural contexts - that provide opportunities for interacting with others and favoring new social engagements - could be potential modifiers of the widowhood effects and as such requires more systematic consideration in future research of widowhood effects on well-being and mortality.

Palliative Medicine, 2008

We used complete Centers for Disease Control death certificate records and the Centers for Medica... more We used complete Centers for Disease Control death certificate records and the Centers for Medicare and Medicaid Services 100% Standard Analytic File for hospice claims for 2002 to examine differences in hospice utilization between African-American and white decedents living in the United States. White decedents were more likely to use hospice in the year before their death than African-American decedents (29% vs 22%). Cause-specific hospice utilization rates among women were consistently higher than among men within a given race. African-American decedents were consistently less likely to use hospice than white decedents for almost all conditions. Hospice utilization was lower among African-American than among white decedents in 31 of 40 states. The higher the overall hospice utilization in a state, the less the positive difference between white and African-American usage rates; that is, the more accepted hospice is, as measured by 'market share', the lower the racial disparity in its use. Palliative Medicine (2008); 22: 205-213

Journal of Pain and Symptom Management, 2007

Complete Center for Disease Control death certificate records and Centers for Medicare and Medica... more Complete Center for Disease Control death certificate records and Centers for Medicare and Medicaid Services 100% Standard Analytic File for hospice claims for 2002 were used to describe the whole population of hospice users and nonusers in the United States. The overall hospice utilization rate for persons 65 years and older was 28.6%. Hospice utilization varied by cause of death, and was highest for individuals with malignancies (65%), kidney disease and nephritis (55%), and Alzheimer's disease (41%). Hospice utilization was lowest for conditions leading to rapid or unexpected death, such as accidents and suicide (0%), influenza and pneumonia (3%), and sepsis (6%). Considerable geographic differences in hospice utilization existed, with hospice use higher in the South and the Southwest and lower in the Midwest and the Northeast. State-specific usage rates ranged from 8% in Alaska to 49% in Arizona. Our findings highlight opportunities for the hospice industry to provide more care, opportunities defined by diagnostic and geographic axes. J Pain Symptom Manage 2007;34:277e285. Ó

International Journal of Epidemiology, 2002

Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on d... more Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on disease occurrence, epidemiologists usually do not precisely specify what 'true effect' they want to estimate. We describe how the counterfactual theory of causation, originally developed in philosophy and statistics, can be adapted to epidemiological studies to provide precise answers to the questions 'What is a cause?', 'How should we measure effects?' and 'What effect measure should epidemiologists estimate in aetiologic studies?' We also show that the theory of counterfactuals (1) provides a general framework for designing and analysing aetiologic studies; (2) shows that we must always depend on a substitution step when estimating effects, and therefore the validity of our estimate will always depend on the validity of the substitution; (3) leads to precise definitions of effect measure, confounding, confounder, and effect-measure modification; and (4) shows why effect measures should be expected to vary across populations whenever the distribution of causal factors varies across the populations.

International Journal of Epidemiology, 2002

Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on d... more Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on disease occurrence, epidemiologists usually do not precisely specify what 'true effect' they want to estimate. We describe how the counterfactual theory of causation, originally developed in philosophy and statistics, can be adapted to epidemiological studies to provide precise answers to the questions 'What is a cause?', 'How should we measure effects?' and 'What effect measure should epidemiologists estimate in aetiologic studies?' We also show that the theory of counterfactuals (1) provides a general framework for designing and analysing aetiologic studies; (2) shows that we must always depend on a substitution step when estimating effects, and therefore the validity of our estimate will always depend on the validity of the substitution; (3) leads to precise definitions of effect measure, confounding, confounder, and effect-measure modification; and (4) shows why effect measures should be expected to vary across populations whenever the distribution of causal factors varies across the populations.

Demography, 2010

In human populations, variation in mate availability has been linked to various biological and so... more In human populations, variation in mate availability has been linked to various biological and social outcomes, but the possible effect of mate availability on health or survival has not been studied. Unbalanced sex ratios are a concern in many parts of the world, and their implications for the health and survival of the constituent individuals warrant careful investigation. We indexed mate availability with contextual sex ratios and investigated the hypothesis that the sex ratio at sexual maturity might be associated with long-term survival for men. Using two unique data sets of 7,683,462 and 4,183 men who were followed for more than 50 years, we found that men who reached their sexual maturity in an environment with higher sex ratios (i.e., higher proportions of reproductively ready men) appeared to suffer higher long-term mortality risks than those in an environment with lower sex ratios. Mate availability at sexual maturity may be linked via several biological and social mechanisms to long-term survival in men.

Demography, 2008

Increased mortality following the death of a spouse (the "widowhood effect") may be due to (1) ca... more Increased mortality following the death of a spouse (the "widowhood effect") may be due to (1) causation, (2) bias from spousal similarity (homogamy), or (3) bias from shared environmental exposures. This article proposes new tests for bias in the widowhood effect by examining husbands, wives, and ex-wives in a longitudinal sample of over 1 million elderly Americans. If the death of an ex-wife has no causal effect on the mortality of her husband, then an observed association between the mortality of an ex-wife and her husband may indicate bias, while the absence of an effect of an exwife's death on her husband's mortality would discount the possibility of homogamy bias (and also of one type of shared-exposure bias). Results from three empirical tests provide strong evidence for an effect of a current wife's death on her husband's mortality yet no statistically signifi cant evidence for an effect of an ex-wife's death on her husband's mortality. These results strengthen the causal interpretation of the widowhood effect by suggesting that the widowhood effect is not due to homogamy bias to any substantial degree.

psidonline.isr.umich.edu

This study examines how the neighborhood environments experienced over multiple generations of a ... more This study examines how the neighborhood environments experienced over multiple generations of a family influence parents' educational expectations and aspirations, children's cognitive skills, and children's health. 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. 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 show strong multigenerational neighborhood effects on outcomes related to education and cognitive skills, but no statistically significant evidence for multigenerational neighborhood effects on child health outcomes.

American Journal of Sociology, 2016

Effects of disadvantaged neighborhoods on child educational outcomes likely depend on a family's ... more Effects of disadvantaged neighborhoods on child educational outcomes likely depend on a family's economic resources and the timing of neighborhood exposures during the course of child development. This study investigates how timing of exposure to disadvantaged neighborhoods during childhood versus adolescence affects high school graduation and whether these effects vary across families with different income levels. It follows 6,137 children in the PSID from childhood through adolescence and overcomes methodological problems associated with the joint endogeneity of neighborhood context and family income by adapting novel counterfactual methods-a structural nested mean model estimated via two-stage regression with residuals-for timevarying treatments and time-varying effect moderators. Results indicate that exposure to disadvantaged neighborhoods, particularly during adolescence, has a strong negative effect on high school graduation and that this negative effect is more severe for children from poor families. Spatial inequality is a central dimension of social stratification. Ever since the publication of Wilson's ð1987Þ influential treatise on urban poverty, researchers have worked to understand how concentrated neighborhood

American Sociological Review, 2011

Theory suggests that neighborhood effects depend not only on where individuals live today, but al... more 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 measures neighborhood context only once and does not account for length of residence, thereby understating the detrimental effects of long-term neighborhood disadvantage. This study investigates effects of duration of exposure to disadvantaged neighborhoods on high school graduation. It follows 4,154 children in the Panel Study of Income Dynamics, 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; thus, they capture the full impact of a lifetime of neighborhood disadvantage. We find that s...

Biometrics, Jan 29, 2014

The identification of causal peer effects (also known as social contagion or induction) from obse... more The identification of causal peer effects (also known as social contagion or induction) from observational data in social networks is challenged by two distinct sources of bias: latent homophily and unobserved confounding. In this paper, we investigate how causal peer effects of traits and behaviors can be identified using genes (or other structurally isomorphic variables) as instrumental variables (IV) in a large set of data generating models with homophily and confounding. We use directed acyclic graphs to represent these models and employ multiple IV strategies and report three main identification results. First, using a single fixed gene (or allele) as an IV will generally fail to identify peer effects if the gene affects past values of the treatment. Second, multiple fixed genes/alleles, or, more promisingly, time-varying gene expression, can identify peer effects if we instrument exclusion violations as well as the focal treatment. Third, we show that IV identification of peer...

Handbooks of Sociology and Social Research, 2013

Biometrics, Apr 1, 2014

The identification of causal peer effects (also known as social contagion or induction) from obse... more The identification of causal peer effects (also known as social contagion or induction) from observational data in social networks is challenged by two distinct sources of bias: latent homophily and unobserved confounding. In this paper, we investigate how causal peer effects of traits and behaviors can be identified using genes (or other structurally isomorphic variables) as instrumental variables (IV) in a large set of data generating models with homophily and confounding. We use directed acyclic graphs to represent these models and employ multiple IV strategies and report three main identification results. First, using a single fixed gene (or allele) as an IV will generally fail to identify peer effects if the gene affects past values of the treatment. Second, multiple fixed genes/alleles, or, more promisingly, time-varying gene expression, can identify peer effects if we instrument exclusion violations as well as the focal treatment. Third, we show that IV identification of peer effects remains possible even under multiple complications often regarded as lethal for IV identification of intra-individual effects, such as pleiotropy on observables and unobservables, homophily on past phenotype, past and ongoing homophily on genotype, inter-phenotype peer effects, population stratification, gene expression that is endogenous to past phenotype and past gene expression, and others. We apply our identification results to estimating peer effects of body mass index (BMI) among friends and spouses in the Framingham Heart Study. Results suggest a positive causal peer effect of BMI between friends.

Annual Review of Sociology, 2014

Endogenous selection bias is a central problem for causal inference. Recognizing the problem, how... more 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 ). 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.

wjh.harvard.edu

This paper contradicts the current consensus about the role of incarceration in US-European labor... more This paper contradicts the current consensus about the role of incarceration in US-European labor market performance differentials. Theoretically, I develop a more general model for the causal interrelationship between incarceration and unemployment that ...

Social Science & Medicine, 2008

The effect of death of a spouse on the mortality of the survivor (the &am... more The effect of death of a spouse on the mortality of the survivor (the "widowhood effect") is well-established. We investigated how the effect of widowhood on mortality depends on the neighborhood concentration of widowed individuals in the United States. We developed a large, nationally representative, and longitudinal dataset from Medicare claims and other data sources characterizing 200,000 elderly couples, with nine years of follow-up (1993-2002), and estimated multilevel grouped discrete-time hazard models. In neighborhoods with a low concentration of widowed individuals, widowhood increased the odds of death for men by 22% and for women by 17%, compared to 17% for men, and 15% for women in neighborhoods with a high concentration of widowed individuals. Our findings suggest that neighborhood structural contexts - that provide opportunities for interacting with others and favoring new social engagements - could be potential modifiers of the widowhood effects and as such requires more systematic consideration in future research of widowhood effects on well-being and mortality.

Palliative Medicine, 2008

We used complete Centers for Disease Control death certificate records and the Centers for Medica... more We used complete Centers for Disease Control death certificate records and the Centers for Medicare and Medicaid Services 100% Standard Analytic File for hospice claims for 2002 to examine differences in hospice utilization between African-American and white decedents living in the United States. White decedents were more likely to use hospice in the year before their death than African-American decedents (29% vs 22%). Cause-specific hospice utilization rates among women were consistently higher than among men within a given race. African-American decedents were consistently less likely to use hospice than white decedents for almost all conditions. Hospice utilization was lower among African-American than among white decedents in 31 of 40 states. The higher the overall hospice utilization in a state, the less the positive difference between white and African-American usage rates; that is, the more accepted hospice is, as measured by 'market share', the lower the racial disparity in its use. Palliative Medicine (2008); 22: 205-213

Journal of Pain and Symptom Management, 2007

Complete Center for Disease Control death certificate records and Centers for Medicare and Medica... more Complete Center for Disease Control death certificate records and Centers for Medicare and Medicaid Services 100% Standard Analytic File for hospice claims for 2002 were used to describe the whole population of hospice users and nonusers in the United States. The overall hospice utilization rate for persons 65 years and older was 28.6%. Hospice utilization varied by cause of death, and was highest for individuals with malignancies (65%), kidney disease and nephritis (55%), and Alzheimer's disease (41%). Hospice utilization was lowest for conditions leading to rapid or unexpected death, such as accidents and suicide (0%), influenza and pneumonia (3%), and sepsis (6%). Considerable geographic differences in hospice utilization existed, with hospice use higher in the South and the Southwest and lower in the Midwest and the Northeast. State-specific usage rates ranged from 8% in Alaska to 49% in Arizona. Our findings highlight opportunities for the hospice industry to provide more care, opportunities defined by diagnostic and geographic axes. J Pain Symptom Manage 2007;34:277e285. Ó

International Journal of Epidemiology, 2002

Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on d... more Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on disease occurrence, epidemiologists usually do not precisely specify what 'true effect' they want to estimate. We describe how the counterfactual theory of causation, originally developed in philosophy and statistics, can be adapted to epidemiological studies to provide precise answers to the questions 'What is a cause?', 'How should we measure effects?' and 'What effect measure should epidemiologists estimate in aetiologic studies?' We also show that the theory of counterfactuals (1) provides a general framework for designing and analysing aetiologic studies; (2) shows that we must always depend on a substitution step when estimating effects, and therefore the validity of our estimate will always depend on the validity of the substitution; (3) leads to precise definitions of effect measure, confounding, confounder, and effect-measure modification; and (4) shows why effect measures should be expected to vary across populations whenever the distribution of causal factors varies across the populations.

International Journal of Epidemiology, 2002

Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on d... more Although one goal of aetiologic epidemiology is to estimate 'the true effect' of an exposure on disease occurrence, epidemiologists usually do not precisely specify what 'true effect' they want to estimate. We describe how the counterfactual theory of causation, originally developed in philosophy and statistics, can be adapted to epidemiological studies to provide precise answers to the questions 'What is a cause?', 'How should we measure effects?' and 'What effect measure should epidemiologists estimate in aetiologic studies?' We also show that the theory of counterfactuals (1) provides a general framework for designing and analysing aetiologic studies; (2) shows that we must always depend on a substitution step when estimating effects, and therefore the validity of our estimate will always depend on the validity of the substitution; (3) leads to precise definitions of effect measure, confounding, confounder, and effect-measure modification; and (4) shows why effect measures should be expected to vary across populations whenever the distribution of causal factors varies across the populations.

Demography, 2010

In human populations, variation in mate availability has been linked to various biological and so... more In human populations, variation in mate availability has been linked to various biological and social outcomes, but the possible effect of mate availability on health or survival has not been studied. Unbalanced sex ratios are a concern in many parts of the world, and their implications for the health and survival of the constituent individuals warrant careful investigation. We indexed mate availability with contextual sex ratios and investigated the hypothesis that the sex ratio at sexual maturity might be associated with long-term survival for men. Using two unique data sets of 7,683,462 and 4,183 men who were followed for more than 50 years, we found that men who reached their sexual maturity in an environment with higher sex ratios (i.e., higher proportions of reproductively ready men) appeared to suffer higher long-term mortality risks than those in an environment with lower sex ratios. Mate availability at sexual maturity may be linked via several biological and social mechanisms to long-term survival in men.

Demography, 2008

Increased mortality following the death of a spouse (the "widowhood effect") may be due to (1) ca... more Increased mortality following the death of a spouse (the "widowhood effect") may be due to (1) causation, (2) bias from spousal similarity (homogamy), or (3) bias from shared environmental exposures. This article proposes new tests for bias in the widowhood effect by examining husbands, wives, and ex-wives in a longitudinal sample of over 1 million elderly Americans. If the death of an ex-wife has no causal effect on the mortality of her husband, then an observed association between the mortality of an ex-wife and her husband may indicate bias, while the absence of an effect of an exwife's death on her husband's mortality would discount the possibility of homogamy bias (and also of one type of shared-exposure bias). Results from three empirical tests provide strong evidence for an effect of a current wife's death on her husband's mortality yet no statistically signifi cant evidence for an effect of an ex-wife's death on her husband's mortality. These results strengthen the causal interpretation of the widowhood effect by suggesting that the widowhood effect is not due to homogamy bias to any substantial degree.

psidonline.isr.umich.edu

This study examines how the neighborhood environments experienced over multiple generations of a ... more This study examines how the neighborhood environments experienced over multiple generations of a family influence parents' educational expectations and aspirations, children's cognitive skills, and children's health. 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. 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 show strong multigenerational neighborhood effects on outcomes related to education and cognitive skills, but no statistically significant evidence for multigenerational neighborhood effects on child health outcomes.