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Social Indicators Research
Published in: Social Indicators Research 1/2022

09-02-2022 | Original Research

Examining the Relationship Between Intergenerational Upward Mobility and Inequality: Evidence from Panel Data

Author: Lijie Song

Published in: Social Indicators Research | Issue 1/2022

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Abstract

The relationship between intergenerational mobility and inequality is widely explored but yet to reach conclusive results. The convention is to provide descriptive analysis with data of several developed countries, termed as the Great Gatsby Curve (GGC). This paper constructs a panel data containing a wide range of modern societies to replicate and extend the GGC with alternative measures. Through investigations, this study confirms that inequality skews the intergenerational upward mobility. Ceteris paribus, every one percent increase in inequality measured by top 10% income share will decrease the upward mobility by about 5 percent on average. On the other hand, every one percent increase in the bottom 50% income share contributes to 12 percent increase in the upward mobility. In comparison, it implies that it is not only the degree but also the structure of the inequality, that matters for the intergenerational mobility. The increase in the income share held by the bottom earners prompts the overall upward mobility with much greater and more meaningful magnitude. Besides, economic development benefits to the overall upward mobility.
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Appendix
Available only for authorised users
Footnotes
1
See OECD report at OECD2016-Income-Inequality-Update.pdf.
 
2
The Gini coefficients are estimated by the World Bank. See at Poverty and Equity DataBank (worldbank.org).
 
3
See also Narayan et al. (2018) for a review.
 
4
See more detailed information at the end of Sect. 3.2.
 
5
The convention to gauge IGE in the extant literature is to regress the log father’s earnings in relates to log child’s earnings. More recent researches consider a rank-rank specification that rank both generations among their cohorts and obtain the rank-rank estimates, which is argued to be more stable and less biased (Chetty et al., 2014; Dahl & Deleire, 2008).
 
6
Data collection for the WVS-7 survey round will be completed in December 2021. Data and all related survey documentation will be made available at the WVS web-site in free access in a series of public data releases: in July 2020, in July 2021 and in January 2022. See http://​www.​worldvaluessurve​y.​org/​WVSEventsShow.​jsp?​ID=​413.
 
7
Five countries and districts are removed for cause of a lack of inequality data available, including Adora, Taiwan, etc.
 
8
The data can be downloaded at World Bank website, see https://​databathnk.​worldbank.​org/​home.​aspx.
 
10
See summary statistics of IUM by counties in Table 5 in the Appendix.
 
11
We thank the anonymous reviewers for pointing out this issue.
 
12
Pre-tax national income share held by a given percentile group. Pre-tax national income is the sum of all pre-tax personal income flows accruing to the owners of the production factors, labor and capital, before taking into account the operation of the tax/transfer system, but after taking into account the operation of pension system. The central difference between personal factor income and pre-tax income is the treatment of pensions, which are counted on a contribution basis by factor income and on a distribution basis by pre-tax income. The population is comprised of individuals over age 20. The Pre-tax national income is defined as pre-tax labor income [total pre-tax income ranking] + pre-tax capital income [total pre-tax income ranking].
 
14
The results with inequality measured by top 10% income share and bottom 50% income share are reported in Sect. 5, and the result with Gini coefficient is also estimated and reported in Table 6 in the Appendix.
 
15
Estimates with inequality proxied by Gini coefficient is also reported as supplementary, see in Table 6 in the Appendix.
 
16
The approach used for the construction of the panel departs from the Age-Period-Cohort analysis in that it aggregates the macro-level variable of interest from the proper and targeted cohorts (age groups) (see Yang & Land, 2006 and Chauvel & Hamilton, 2013 for instance). The selection rules for age intervals, however, still need to be addressed with caution. We thank an anonymous reviewer for the advice.
 
17
The data used for the instruments are from the World Bank Dataset, which can be retrieved at World Development Indicators | DataBank (worldbank.org). See detailed definition and summary statistics of these instruments in Table 10 in the Appendix.
 
18
Inequality and per capita are measured by top10t-1, lgdpt-1 and averages over top10t-1 to top10t-5, lgdpt-1 to lgdpt-5 accordingly. See similar timing convention in Berg et al. (2018) for instance.
 
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Metadata
Title
Examining the Relationship Between Intergenerational Upward Mobility and Inequality: Evidence from Panel Data
Author
Lijie Song
Publication date
09-02-2022
Publisher
Springer Netherlands
Published in
Social Indicators Research / Issue 1/2022
Print ISSN: 0303-8300
Electronic ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-022-02891-z

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