2019
DOI: 10.1111/cwe.12266
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Inequality of Opportunity in China's Labor Earnings: The Gender Dimension

Abstract: This paper investigates the inequality of opportunity in China's labor earnings, defined as the component of inequality determined by personal circumstances that lie beyond the control of an individual, of which gender is one, as opposed to the component determined by personal efforts. Using the Survey of Women's Social Status in China (2010), we measure the share of inequality of opportunity in the total inequality of individual labor earnings for people aged 26–55 years, and separately for six birth cohorts … Show more

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Cited by 25 publications
(18 citation statements)
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References 46 publications
(33 reference statements)
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“…First, if households smooth consumption its distribution is less unequal than the distribution of income. Additionally, assuming transitory fluctuations to be more strongly reflected in the outcome distribution Y t than the smoothed distribution M t , we would expect relative IOp in consumption expenditures to 17 Due to differences in the underlying data, we refrain from comparing our results to other IOp estimates in the relevant countries: See for example, Brock et al (2016), Brunori et al (2019a) Ferreira and Gignoux (2011), Ferreira et al (2018, Golley et al (2019), Piraino (2015), Song and Zhou (2019), Juárez Wendelspiess Chávez (2015), Zhang and Eriksson (2010). These differences pertain to reference periods, the considered outcomes of interest, the detail of available circumstance characteristics, sample selection criteria, estimation methods, as well as inequality indices.…”
Section: Datamentioning
confidence: 97%
“…First, if households smooth consumption its distribution is less unequal than the distribution of income. Additionally, assuming transitory fluctuations to be more strongly reflected in the outcome distribution Y t than the smoothed distribution M t , we would expect relative IOp in consumption expenditures to 17 Due to differences in the underlying data, we refrain from comparing our results to other IOp estimates in the relevant countries: See for example, Brock et al (2016), Brunori et al (2019a) Ferreira and Gignoux (2011), Ferreira et al (2018, Golley et al (2019), Piraino (2015), Song and Zhou (2019), Juárez Wendelspiess Chávez (2015), Zhang and Eriksson (2010). These differences pertain to reference periods, the considered outcomes of interest, the detail of available circumstance characteristics, sample selection criteria, estimation methods, as well as inequality indices.…”
Section: Datamentioning
confidence: 97%
“…Importantly, the gender gap in education has largely been eliminated. But barriers for women remain and, according to some studies, may have in increased in recent years (World Economic Forum 2018;Golley, Zhou, and Wang 2019;Qin 2019). Women face discrimination in hiring, promotion, and pay once they enter the workforce.…”
Section: Interventions For Excluded Groupsmentioning
confidence: 99%
“…Relatively well-off households will be able to provide their children with an education to give them the skills and capacity to compete in the labour market in the future. If there is strong inequality of opportunity, income inequality could deteriorate over generations (Golley et al 2019;UN ESCAP 2017). Policies that aim at reducing inequality of opportunity will help alleviate income inequality and its negative impact when societies are increasingly faced with the rise of robotics and AI.…”
Section: Automation and Income Inequality And The Policy Responsementioning
confidence: 99%