Inequality of opportunity and household education expenditures: Evidence from panel data in China

Abstract

This paper This paper offers the first empirical evidence on the impact of inequality of opportunity on household education investment by using the by using the by using the by using the by using the by using the panel data from China Family Panel Studies (CFPS) in three in three in three in three waves (2010, 2012 and 2014). Our result suggests that inequality of opportunity has a negative effect on household education expenditures. This result is robust to robustness checks. Furthermore, the disadvantaged households (whose householders with less education, income, and rural hukou status) seem to be affected more by inequality of opportunity within the county they live in. Higher inequality of opportunity in the comparison group may reduce their incentives to investment more on education. Policy suggestions to reduce inequality of opportunity may include reducing labor market discrimination based on gender and hukou, balancing education resources to create more equal educational opportunities, and offering children education subsidies in low-income families.

Inequality of Educational Opportunities and Digital Literacy of School-Age Children In Sumatra

“…Previous literature used parametric analysis (Ferreira & Gignoux, 2013) to measure educational opportunity inequality. Educational opportunity inequality is calculated using an inter-type or ex-ante component approach (Ferreira & Gignoux, 2013),and (Song & Zhou, 2019) which uses state set variables that are exogenous variables beyond individual control. Roemer (2015), the inequality of opportunity indicates a conditional distribution of educational attainment that must be affected by variable circumstances.…”

Lower and upper bound estimates of inequality of opportunity for emerging economies

“…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.…”

The Application of Human Capital Theory and Educational Signalling Theory to Explain Parental Influences on the Chinese Population’s Social Mobility Opportunities

“…Such a circumstance helps explain why the education signalling model is important for, and included in, existing research when such project leans on the broad themes of social stratification and sociology of education. In addition, poor rural local governments, but not their richer urban counterparts, may be financially incapable of subsidising education, including compulsory education, for villagers (Song and Zhou 2019). Therefore, such socioeconomic and socioeducational arrangements stratify individuals' entitlement to life chances to a significant extent, fostering the adoption and application of EST when addressing such an education-related societal issue in contemporary China.…”