Intergenerational mobility across Australia and the stability of regional estimates

Deutscher, Nathan; Mazumder, Bhashkar

doi:10.1016/j.labeco.2020.101861

Cited by 48 publications

(59 citation statements)

References 25 publications

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“…This is a conclusion that would be in line with Bradbury et al (2015), and the other comparisons in Table 1. Murray et al (2018) and Connolly, Corak and Haeck (2019) offer results based on similar age cohorts, as do Deutscher and Mazumder (2019) and Corak (2019) using somewhat older cohorts. This later pair of studies is almost exactly comparable, as both use administrative data associated with the income tax system with similarly defined income measures 3 .…”

Section: What Is the ‘Right’ Set Of Comparisons?mentioning

confidence: 86%

“…But this raises a puzzle that might pull us back from the earlier conclusion that roughly one‐quarter of inequality is passed on between generations, Deutscher and Mazumder (2019) suggesting a significantly lower value for the intergenerational elasticity than Murray et al (2018).…”

Section: What Are the ‘Right’ Statistics?mentioning

confidence: 93%

“…This later pair of studies is almost exactly comparable, as both use administrative data associated with the income tax system with similarly defined income measures 3 . Deutscher and Mazumder (2019) estimate the Australian intergenerational elasticity to be 0.185, while Corak (2019) finds 0.201, with the standard errors in both studies being so small as to suggest that the difference is statistically significant even if there is not a big economic significance between them.…”

Section: What Is the ‘Right’ Set Of Comparisons?mentioning

confidence: 99%

“…Like Murray et al (2018), Deutscher and Mazumder (2019) use parents and children who have been directly linked, and they also use an analytical sample and income definitions comparable to Chetty et al (2014), but they estimate the intergenerational income elasticity to be 0.185, and offer a much tighter confidence interval, the standard error being 0.001. The difference is that this study uses administrative records from the tax system, offering a sample of 1.025 million parent–child pairs, representing close to the population of children born between 1978 and 1982, and with the children being in their early 30s when their adult incomes are measured, a bit older but not much different than Murray et al (2018).…”

Section: What Are the ‘Right’ Statistics?mentioning

confidence: 99%

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Intergenerational Mobility: What Do We Care About? What Should We Care About?

Corak¹

2020

Australian Economic Review

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Inequality threatens intergenerational income mobility, but different types of inequality threaten mobility in different ways, raising distinct policy challenges. This is why empirical researchers should be agnostic in the choice of statistics they use to measure intergenerational mobility. I argue that Australia is on the whole characterised by a good deal of intergenerational mobility, but that a full picture requires judicious international comparisons across different dimensions of mobility citizens care about, mobility not just of incomes, but also of position and direction, particularly the scope for upward mobility.

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Section: What Is the ‘Right’ Set Of Comparisons?mentioning

confidence: 86%

Section: What Are the ‘Right’ Statistics?mentioning

confidence: 93%

Section: What Is the ‘Right’ Set Of Comparisons?mentioning

confidence: 99%

Section: What Are the ‘Right’ Statistics?mentioning

confidence: 99%

See 2 more Smart Citations

Intergenerational Mobility: What Do We Care About? What Should We Care About?

Corak¹

2020

Australian Economic Review

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“…Recent studies (Deutscher and Mazumder 2019) have alerted us to the possibility of using tax data to study intergenerational mobility. However, the use of tax data has its problems.…”

Section: Challenge Ii: Data Gapsmentioning

confidence: 99%

Intergenerational Mobility Research: Current Challenges and Future Directions

Mooi‐Reci¹

2020

Australian Economic Review

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This article discusses major challenges facing intergenerational mobility research in three main domains: (1) the (dis)connection between theory and empirical applications; (2) data gaps; and (3) measurement concerns. In doing so, it highlights theoretical and empirical extensions to better describe, explain and predict complex intergenerational transmission processes in the light of new and rapid administrative data linkages, more mature survey data and other forms of big data. The article concludes with future directions for research.

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A lost land of opportunity? The geography of intergenerational educational mobility in China

Hong,

Gruijters

2024

Population Space and Place

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Despite the significant political, economic and geographical diversity in China, there is limited research on spatial differences in intergenerational mobility in China. This research aims to fill this gap by exploring the spatial and temporal dimensions of intergenerational educational mobility in China. The data used for the analysis is the 2010–2018 China Family Panel Studies (CFPS), a nationally representative longitudinal general social survey. The analysis incorporates both relative and absolute mobility measures to provide a comprehensive description of intergenerational educational mobility. The results reveal substantial regional differences in intergenerational educational mobility across various economic zones in China, with a rising geographic inequality over time. The southwest and northeast regions stand out as the areas where the educational prospects of the young generation have become not only bleaker but dependent more on their parents. Additionally, this study presents the first education Great Gatsby Curve for China, highlighting the strong relationship between intergenerational mobility and education inequality at the regional level, particularly after China's market reform. The findings highlight the need for regionally targeted policies and levelling up agendas to promote educational opportunities in low‐mobility regions.

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Intergenerational mobility across Australia and the stability of regional estimates

Cited by 48 publications

References 25 publications

Intergenerational Mobility: What Do We Care About? What Should We Care About?

Intergenerational Mobility: What Do We Care About? What Should We Care About?

Intergenerational Mobility Research: Current Challenges and Future Directions

A lost land of opportunity? The geography of intergenerational educational mobility in China

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