The geography of intergenerational mobility — Danish evidence

Eriksen, Jesper; Munk, Martin D.

doi:10.1016/j.econlet.2020.109024

Cited by 22 publications

(12 citation statements)

References 8 publications

(12 reference statements)

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“…Specifically, we use estimates for the United States (Chetty et al 2014), Canada (Corak 2019), Italy (Acciari, Polo and Violante 2019) and Denmark (Eriksen and Munk 2020). While these studies cover a smaller subset of the measures discussed here, they provide a useful point of comparison.…”

Section: An Illustration -Relationships Between Mobility Metrics In Practicementioning

confidence: 99%

Measuring Intergenerational Income Mobility: A Synthesis of Approaches

Deutscher¹,

Mazumder²

2021

SSRN Journal

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The literature on intergenerational income mobility uses a diverse set of measures and there is limited knowledge about whether these measures provide similar information and yield similar conclusions. We provide a framework to highlight the key concepts and properties of the different estimators. We then show how these measures relate to one another empirically. Our main analysis uses income tax data from Australia to produce a comprehensive set of empirical estimates for each of 19 different mobility measures at both the national and regional level. We supplement this analysis with other data that uses either within or between country variation in mobility measures. A key finding is that there is a clear distinction between relative and absolute measures both conceptually and empirically. A region may be high with respect to absolute mobility but could be low with respect to relative mobility. However, within broad categories, the different mobility measures tend to be highly correlated. For rank-based estimators, we highlight the importance of how the choice of the distribution used for calculating ranks can play a critical role in determining its properties as well as affect empirical findings. These patterns of results are important for policy makers whose local economy might fare well according to some mobility indicators but not others. * This article was prepared for the Journal of Economic Literature and is under review. We thank Steven Durlauf for helpful guidance and anonymous reviewers for their comments. We also thank Francisco Ferreira and Markus Jäntti for helpful comments and participants at the workshop on Aging, Family and Social Insurance in Solstrand, Norway and the ZEW Workshop on Social Mobility and Economic Performance for their feedback, and Aastha Rajan for excellent research assistance. This research uses data from the Australian Taxation Office. All findings, opinions and conclusions are those of the authors and do not necessarily represent the views of the Australian Government or any of its agencies. The views expressed here do not reflect those of the Federal Reserve Bank of Chicago or the Federal Reserve system or the Australian Treasury. The research plan was approved by the Australian National University Human Ethics Committee, protocol number 2017/832.

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Section: An Illustration -Relationships Between Mobility Metrics In Practicementioning

confidence: 99%

Measuring Intergenerational Income Mobility: A Synthesis of Approaches

Deutscher¹,

Mazumder²

2021

SSRN Journal

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“…In contrast, estimate that achievement gaps between the top and bottom quarters of the SES distribution have remained remarkably constant. Their and Corak (2020) for Canada, Fan, Yi, and Zhang (2021) for China, Eriksen and Munk (2020) for Denmark, Bell, Blundell, and Machin (2022) for England, Dodin et al (2021) for Germany, Güell et al (2018) and Acciari, Polo, and Violante (2019) for Italy, Bütikofer, Dalla-Zuanna, and Salvanes (2018) and Risa (2019) for Norway, Llaneras, Medina, and Costas (2020) for Spain, Heidrich (2017), Brandén (2019) and Nybom and Stuhler (2021) for Sweden, and Aydemir and Yazici (2019) for Turkey.…”

Section: Economic Inequality and Educational Inequality Over Timementioning

confidence: 99%

Educational Inequality

Blanden¹,

Doepke²,

Stuhler³

2022

Preprint

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This chapter provides new evidence on educational inequality and reviews the literature on the causes and consequences of unequal education. We document large achievement gaps between children from different socioeconomic backgrounds, show how patterns of educational inequality vary across countries, time, and generations, and establish a link between educational inequality and social mobility. We interpret this evidence from the perspective of economic models of skill acquisition and investment in human capital. The models account for different channels underlying unequal education and highlight how endogenous responses in parents' and children's educational investments generate a close link between economic inequality and educational inequality. Given concerns over the extended school closures during the Covid-19 pandemic, we also summarize early evidence on the impact of the pandemic on children's education and on possible long-run repercussions for educational inequality.

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“…An influential literature studies within-country variation in intergenerational income mobility (see e.g., Chetty et al, 2020;Deutscher and Mazumder, 2019;Eriksen and Munk, 2020;Guell et al, 2018, for recent examples). This literature claims to find that there are powerful neighborhood effects, but it does not identify their source.…”

Section: Is Zip Code Destiny?mentioning

confidence: 99%

Lessons from Denmark About Inequality and Social Mobility

Heckman

Landersø

2021

SSRN Journal

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Many American policy analysts point to Denmark as a model welfare state with low levels of income inequality and high levels of income mobility across generations. It has in place many social policies now advocated for adoption in the U.S. Despite generous Danish social policies, family influence on important child outcomes in Denmark is about as strong as it is in the United States. More advantaged families are better able to access, utilize, and influence universally available programs. Purposive sorting by levels of family advantage create neighborhood effects. Powerful forces not easily mitigated by Danish-style welfare state programs operate in both countries.

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The geography of intergenerational mobility — Danish evidence

Cited by 22 publications

References 8 publications

Measuring Intergenerational Income Mobility: A Synthesis of Approaches

Measuring Intergenerational Income Mobility: A Synthesis of Approaches

Educational Inequality

Lessons from Denmark About Inequality and Social Mobility

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