Socioeconomic inequality in childhood obesity and its determinants: a Blinder–Oaxaca decomposition
Objective: Childhood obesity has become a priority health concern worldwide. Socioeconomic status is one of its main determinants. This study aimed to assess the socioeconomic inequality of obesity in children and adolescents at national and provincial ...
Roya Kelishadi +10 more
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Pseudo-Panel Decomposition of the Blinder–Oaxaca Gender Wage Gap
This article introduces a novel approach to decomposing the Blinder–Oaxaca gender wage gap using pseudo-panel data. In many developing countries, panel data are not available; however, understanding the evolution of the gender wage gap over time requires
Jhon James Mora, Diana Yaneth Herrera
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Explaining gender inequalities in overweight people: a Blinder-Oaxaca decomposition analysis in northern Sweden. [PDF]
Abstract Background Being overweight and obesity are considered serious public health concerns worldwide. At the population level, factors contributing to overweight as well as the differences in overweight between men and women in terms of prevalence or associated factors are relatively well-known. What is less known is
Yusuf FM +2 more
europepmc +5 more sources
IPV Experiences and Financial Strain Over Time: Insights from the Blinder-Oaxaca Decomposition Analysis. [PDF]
Financial strain is one hardship faced by female survivors of intimate partner violence (IPV) that is often overlooked. This paper examined the relationships between multiple forms of abuse-with a focus on economic abuse-and financial strain. Guided by stress process model, this study tested two hypotheses: (1) economic abuse is associated with ...
Lin HF, Postmus JL, Hu H, Stylianou AM.
europepmc +3 more sources
The effects of prevalence of inequalities in mental disorders between groups using Blinder- Oaxaca decomposition. [PDF]
BACKGROUND: The prevalence of inequalities in sociodemographic factors in some mental disorders (MDs) has been shown in previous reports. The aim of this study was to assess the main contributors that affected prevalence of inequalities in MDs between groups.
Veisani Y, Mohamadian F.
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The Blinder–Oaxaca Decomposition for Nonlinear Regression Models [PDF]
In this article, a general Blinder–Oaxaca decomposition for nonlinear models is derived, which allows the difference in an outcome variable between two groups to be decomposed into several components. We show how, using nldecompose, this general decomposition can be applied to different models with discrete and limited dependent variables.
Mathias Sinning +2 more
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Workplace discrimination continues to at least be perceived as a problem by faculty and staff in higher education. The current study extends the academic literature in this area by exploring the possibility of gender discrimination in the wages of ...
Steven B. Caudill +3 more
doaj +1 more source
Blinder-Oaxaca Decomposition for Tobit Models [PDF]
In this paper, a decomposition method for Tobit-models is derived, which allows the differences in observed outcome variables between two groups to be decomposed into a part that is explained by differences in observed characteristics and a part attributable to differences in the estimated coefficients.
Bauer, Thomas, Sinning, Mathias
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Explaining Racial Inequality in Food Security in Columbus, Ohio: A Blinder-Oaxaca Decomposition Analysis. [PDF]
Food insecurity is a leading public health challenge in the United States. In Columbus, Ohio, as in many American cities, there exists a great disparity between Black and White households in relation to food insecurity. This study investigates the degree to which this gap can be attributed to differences in food shopping behavior, neighborhood ...
Koh K +4 more
europepmc +4 more sources
The Blinder–Oaxaca Decomposition for Linear Regression Models [PDF]
The counterfactual decomposition technique popularized by Blinder (1973, Journal of Human Resources, 436–455) and Oaxaca (1973, International Economic Review, 693–709) is widely used to study mean outcome differences between groups. For example, the technique is often used to analyze wage gaps by sex or race.
Jann, Ben, Jann, Ben
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