Duration and Timing of Exposure to Neighborhood Poverty and the Risk of Adolescent Parenthood

Wodtke, Geoffrey T.

doi:10.1007/s13524-013-0219-z

Cited by 100 publications

(104 citation statements)

References 45 publications

(65 reference statements)

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“…Leventhal et al 2005). For instance, scholars often study how growing up in poor/disadvantaged neighborhoods leads to the four major risks (Duncan et al 1997;Harding 2007;Wodtke 2013;Wodtke et al 2011). Evaluating the "Moving to Opportunity" (MTO)…”

Section: Risks In Us Poverty Researchmentioning

confidence: 99%

Rethinking the Risks of Poverty: A Framework for Analyzing Prevalences and Penalties

Brady

Finnigan

Hübgen

2017

American Journal of Sociology

142

183

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may RETHINKING THE RISKS OF POVERTY: A FRAMEWORK FOR ANALYZING PREVALENCES AND PENALTIES ABSTRACTConsiderable attention focuses on the risks of poverty, defined as individual-level labor market and family characteristics more common among the poor than the non-poor. This article first develops a framework for analyzing the risks of poverty in terms of prevalences (share of the population with a risk) and penalties (increased probability of poverty associated with a risk).Comparing the four major risks (low education, single motherhood, young headship, and unemployment) across 29 rich democracies, we show there is greater variation in penalties than prevalences. Second, we apply this framework to the U.S. We show that prevalences cannot explain high U.S. poverty as the U.S. has below average prevalences. Rather, the U.S. has high poverty partly because it has the highest penalties. U.S. poverty would decline more with crossnational median penalties than cross-national median prevalences, and U.S. poverty in 2013 would actually be worse with prevalences from 1970 or 1980. Third, we analyze cross-national variation in prevalences and penalties. We find very little evidence that higher penalties discourage prevalences, or that lower penalties encourage prevalences. We also show welfare generosity significantly moderates the penalties for unemployment and low education. We conclude with three broader implications. First, a focus on risks is unlikely to provide a convincing explanation or effective strategy for poverty. Second, despite being the subject of the most research, single motherhood may be the least important of the risks. Third, for general explanations of poverty, studies based solely on the U.S. are constrained by potentially large sample selection biases. 3A prevailing and enduring feature of American poverty research has been a focus on risks. For a long time, scholars have stressed the individual-level family and labor market characteristics that are more common among the poor than the non-poor (O'Connor 2001). Recently, Sawhill (2014: 14) claims, "The ideal would be education, work, marriage, children -in that order. The achievement of these benchmarks will, in almost all cases, ensure that any children a couple decides to have are not born into poverty." Earlier in 2003, Sawhill wrote, "Those who graduate from high school, wait until marriage to have children, limit the size of their families, and work f...

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Section: Risks In Us Poverty Researchmentioning

confidence: 99%

Rethinking the Risks of Poverty: A Framework for Analyzing Prevalences and Penalties

Brady

Finnigan

Hübgen

2017

American Journal of Sociology

142

183

View full text Add to dashboard Cite

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“…The few studies that do test for interactions between neighborhood context and different measures of family socioeconomic status yield inconsistent results (e.g., Brooks-Gunn et al 1993; South and Crowder 1999; Wheaton and Clarke 2003). Furthermore, none of these studies investigate neighborhood effect moderation within a time-dependent framework that properly accounts for the dynamic coevolution of neighborhood contexts and family resources over time (Wodtke et al 2011; Wodtke 2013). …”

mentioning

confidence: 99%

Neighborhood Effect Heterogeneity by Family Income and Developmental Period

Wodtke

Harding

Elwert

2016

American Journal of Sociology

Self Cite

101

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“…Theory and previous research suggest that neighborhood effects on adolescent outcomes are likely moderated by family-level characteristics (Sharkey and Faber 2014; Wodtke et al 2016). Moreover, because both neighborhood exposures and characteristics of the family environment, like parental income, vary over time and are jointly endogenous (Wodtke 2013; Wodtke et al 2011; Wodtke et al 2016), research in this area requires new statistical tools capable of properly analyzing neighborhood effect moderation in the longitudinal setting.…”

Section: Neighborhood Effects On Teen Childbearingmentioning

confidence: 99%

Estimating Moderated Causal Effects with Time-varying Treatments and Time-varying Moderators: Structural Nested Mean Models and Regression with Residuals

Wodtke

Almirall

2017

Sociological Methodology

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Individuals differ in how they respond to a particular treatment or exposure, and social scientists are often interested in understanding how treatment effects are moderated by observed characteristics of individuals. Effect moderation occurs when individual covariates dampen or amplify the effect of some exposure. This article focuses on estimating moderated causal effects in longitudinal settings where both the treatment and effect moderator vary over time. Effect moderation is typically examined using covariate by treatment interactions in regression analyses, but in the longitudinal setting, this approach may be problematic because time-varying moderators of future treatment may be affected by prior treatment—for example, moderators may also be mediators—and naively conditioning on an outcome of treatment in a conventional regression model can lead to bias. This article introduces to sociology moderated intermediate causal effects and the structural nested mean model for analyzing effect moderation in the longitudinal setting. It discusses problems with conventional regression and presents a new approach to estimation that avoids these problems (regression-with-residuals). The method is illustrated using longitudinal data from the PSID to examine whether the effects of time-varying exposures to poor neighborhoods on the risk of adolescent childbearing are moderated by time-varying family income.

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Duration and Timing of Exposure to Neighborhood Poverty and the Risk of Adolescent Parenthood

Cited by 100 publications

References 45 publications

Rethinking the Risks of Poverty: A Framework for Analyzing Prevalences and Penalties

Rethinking the Risks of Poverty: A Framework for Analyzing Prevalences and Penalties

Neighborhood Effect Heterogeneity by Family Income and Developmental Period

Estimating Moderated Causal Effects with Time-varying Treatments and Time-varying Moderators: Structural Nested Mean Models and Regression with Residuals

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