2017
DOI: 10.1086/693678
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Rethinking the Risks of Poverty: A Framework for Analyzing Prevalences and Penalties

Abstract: 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… Show more

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Cited by 150 publications
(207 citation statements)
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References 67 publications
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“…Because cross-level interactions are of great relevance in our models and are more straightforward in linear probability models, we followed Brady et al 2017in deciding not to estimate logistic regressions despite having a dichotomous dependent variable. Another disadvantage of logistic regression models is that they do not allow a comparison of results between models or samples (Brady et al 2017). 3 Specifically, we estimated cross-sectional linear probability models that contained organizational fixed effects.…”
Section: Methodsmentioning
confidence: 99%
“…Because cross-level interactions are of great relevance in our models and are more straightforward in linear probability models, we followed Brady et al 2017in deciding not to estimate logistic regressions despite having a dichotomous dependent variable. Another disadvantage of logistic regression models is that they do not allow a comparison of results between models or samples (Brady et al 2017). 3 Specifically, we estimated cross-sectional linear probability models that contained organizational fixed effects.…”
Section: Methodsmentioning
confidence: 99%
“…To understand the magnitude of within‐country penalties, we tested and reported the statistical significance of the family structure coefficient (cohabitating, single male, single female, single female with adults; married couple as reference category; statistical significance p < .05). Penalties have three criteria according to Brady and colleagues (). First, they are standardized to facilitate comparison across context.…”
Section: Methodsmentioning
confidence: 99%
“…As an example, for education, comparative cross-sectional analyses show that not holding a high school diploma or having some college compared to holding a high school diploma changes the probability of in-work poverty by between 4-10 percentage points (Lohmann and Crettaz 2018;Brady, Fullerton, and Moren Cross 2010). We additionally show that these relationships are more substantial for very young adults (age 18-22); this is an example of how a relatively low prevalence of specific family events at young ages, such as the transition to parenthood, are associated with very high penalties (Brady, Finnigan, and Hübgen 2017).…”
Section: Discussionmentioning
confidence: 59%