Trend AnalysisEconomics & FinanceMixed Methods
Wealth Inequality Shapes Social Mobility More Than Income: New Evidence
The relationship between inequality and social mobility has been studied primarily through the lens of income. The "Great Gatsby Curve"โthe empirical regularity that countries with higher income in...
By Sean K.S. Shin
This blog summarizes research trends based on published paper abstracts. Specific numbers or findings may contain inaccuracies. For scholarly rigor, always consult the original papers cited in each post.
The relationship between inequality and social mobility has been studied primarily through the lens of income. The "Great Gatsby Curve"โthe empirical regularity that countries with higher income inequality tend to have lower intergenerational income mobilityโis among the most cited findings in economics. But income is only part of the picture. Wealthโencompassing housing, financial assets, business equity, and inheritancesโis distributed far more unequally than income and may exert a stronger influence on whether children can surpass their parents' economic position. Recent research, enabled by newly available wealth data, is beginning to fill this gap.
The Research Landscape
Wealth Inequality and Upward Mobility in the United States
Schechtl (2025), publishing in Nature Communications, provides the most direct evidence on the wealth-mobility link. Using the GEOWEALTH-US databaseโa recently published dataset of local wealth inequality estimates covering U.S. commuting zonesโcombined with upward mobility estimates from the Opportunity Insights project, the study examines whether childhood exposure to local wealth inequality is associated with later-life income mobility.
The findings are clear: local wealth inequality is negatively associated with upward income mobility. Children who grow up in commuting zones with higher wealth inequality are less likely to move up the income distribution as adults. Crucially, the study's static simulations show that wealth inequality has a stronger association with upward mobility than income inequality itselfโsuggesting that the Great Gatsby Curve may understate the relationship between inequality and immobility by focusing on income alone.
One proposed mechanism is educational: higher local wealth inequality is associated with lower educational attainment among children from low-income families. Wealthy communities may invest in high-quality schools and enrichment activities that are spatially concentrated, creating opportunity structures that are physically proximate but socially inaccessible.
The Geographic Dimension
Connor, Xie, and Jang (2025), publishing in PNAS Nexus examine how urbanization interacts with inequality and mobility. Their analysis addresses a longstanding tension: cities are engines of economic dynamism and wealth creation, but they are also sites of concentrated inequality and social stratification. The study finds that big cities fuel inequality both within and across generationsโurban wealth premiums are substantial but accrue primarily to those who already own property, while urban wage premiums have diminished for low-skill workers.
This creates a geographic trap: the places with the most economic opportunity are also the places where the cost of entry (housing, education, social networks) is highest, and where inequality makes the rungs of the social ladder furthest apart.
Cross-National Evidence on Wealth Transmission
Dewilde (2024) examines the intergenerational transmission of financial disadvantage across European countries. The study finds that rising poverty risks among working-age households have consequences that extend into retirement, creating intergenerational chains of financial vulnerability. Notably, the transmission mechanisms differ across welfare state types: in liberal welfare states (UK, Ireland), asset poverty is transmitted primarily through low homeownership rates; in continental welfare states (Germany, France), occupational pension gaps play a larger role.
Wealth and Income Stratification by Class
Gil-Hernรกndez, Salas-Rojo, and Vidal (2025) analyze wealth and income stratification across five European countries, finding that social class differences in wealth are substantially larger than social class differences in income. The wealth gap between the professional-managerial class and the working class is approximately 3โ5 times the income gap, depending on the country. This matters because wealth provides security, opportunity, and intergenerational advantage in ways that income alone does notโit funds education, buffers against unemployment, enables homeownership, and can be directly transferred to the next generation.
The GEOWEALTH-US Database
Suss, Kemeny, and Connor (2024) describe the construction of GEOWEALTH-US, the first subnational wealth inequality dataset for the United States covering 1960โ2020. The data reveal that spatial wealth inequality has increased substantially since the 1980s, with coastal metropolitan areas pulling away from the interior. This dataset enables the kind of analysis Schechtl (2025) conductsโand its creation represents a methodological advance that should generate further research.
Critical Analysis: Claims and Evidence
<
| Claim | Source | Assessment |
|---|
| Local wealth inequality predicts lower upward income mobility | Schechtl, 2025 | Supported โ well-designed study with appropriate controls |
| Wealth inequality matters more than income inequality for mobility | Schechtl, 2025 | Supported โ static simulations show stronger association |
| Big cities amplify both within- and across-generation inequality | Connor et al., 2025 | Supported โ multidisciplinary evidence |
| Financial disadvantage transmits across generations in Europe | Dewilde, 2024 | Supported โ mechanisms vary by welfare state type |
| Social class wealth gaps are 3โ5x larger than income gaps | Gil-Hernรกndez et al., 2025 | Supported โ five-country comparative data |
Open Questions
Policy implications: Should policy focus shift from income redistribution (progressive taxes, transfers) to wealth redistribution (inheritance taxes, baby bonds, universal asset-building programs)?Housing as the key mechanism: Given that housing is the largest wealth component for most families, are housing policies the most effective lever for reducing wealth-based mobility barriers?Racial wealth gaps: The racial wealth gap in the U.S. is substantially larger than the racial income gap. How does this interact with the geographic patterns identified by Schechtl and Connor et al.?Measurement: Wealth is harder to measure than income. How sensitive are the findings to measurement approaches?Where This Stands
The emerging wealth-mobility literature suggests that decades of mobility research focused on income may have been looking at the smaller part of the problem. Wealth inequalityโmore extreme, more persistent, and more directly transmissible than income inequalityโappears to be a stronger determinant of whether children can exceed their parents' economic position. The policy implications are substantial but politically challenging: interventions in wealth distribution touch property rights, inheritance norms, and housing markets in ways that income redistribution does not.
Explore related work through ORAA ResearchBrain.
๋ฉด์ฑ
์กฐํญ: ์ด ๊ฒ์๋ฌผ์ ์ ๋ณด ์ ๊ณต์ ๋ชฉ์ ์ผ๋ก ํ ์ฐ๊ตฌ ๋ํฅ ๊ฐ์์ด๋ค. ํ์ ์ฐ๊ตฌ์์ ์ธ์ฉํ๊ธฐ ์ ์ ๊ตฌ์ฒด์ ์ธ ์ฐ๊ตฌ ๊ฒฐ๊ณผ, ํต๊ณ ๋ฐ ์ฃผ์ฅ์ ์๋ณธ ๋
ผ๋ฌธ๊ณผ ๋์กฐํ์ฌ ๊ฒ์ฆํด์ผ ํ๋ค.
์ฌํ์ ์ด๋์ฑ์ ๊ฒฐ์ ํ๋ ๊ฒ์ ์๋๋ณด๋ค ๋ถ์ ๋ถํ๋ฑ: ์๋ก์ด ์ฆ๊ฑฐ
๋ถํ๋ฑ๊ณผ ์ฌํ์ ์ด๋์ฑ์ ๊ด๊ณ๋ ์ฃผ๋ก ์๋์ ๊ด์ ์์ ์ฐ๊ตฌ๋์ด ์๋ค. "์๋ํ ๊ฐ์ธ ๋น ๊ณก์ (Great Gatsby Curve)"โ์๋ ๋ถํ๋ฑ์ด ๋์ ๊ตญ๊ฐ์ผ์๋ก ์ธ๋ ๊ฐ ์๋ ์ด๋์ฑ์ด ๋ฎ์ ๊ฒฝํฅ์ด ์๋ค๋ ์ค์ฆ์ ๊ท์น์ฑโ์ ๊ฒฝ์ ํ์์ ๊ฐ์ฅ ๋ง์ด ์ธ์ฉ๋๋ ์ฐ๊ตฌ ๊ฒฐ๊ณผ ์ค ํ๋์ด๋ค. ๊ทธ๋ฌ๋ ์๋์ ์ ์ฒด ๊ทธ๋ฆผ์ ์ผ๋ถ์ ๋ถ๊ณผํ๋ค. ์ฃผํ, ๊ธ์ต ์์ฐ, ์ฌ์
์ง๋ถ, ์์ ๋ฑ์ ํฌ๊ดํ๋ ๋ถ(wealth)๋ ์๋๋ณด๋ค ํจ์ฌ ๋ ๋ถํ๋ฑํ๊ฒ ๋ถ๋ฐฐ๋์ด ์์ผ๋ฉฐ, ์๋
๊ฐ ๋ถ๋ชจ์ ๊ฒฝ์ ์ ์ง์๋ฅผ ๋ฐ์ด๋์ ์ ์๋์ง์ ๋ ๊ฐํ ์ํฅ์ ๋ฏธ์น ์ ์๋ค. ์๋กญ๊ฒ ํ์ฉ ๊ฐ๋ฅํด์ง ๋ถ ๊ด๋ จ ๋ฐ์ดํฐ๋ฅผ ๋ฐํ์ผ๋ก ํ ์ต๊ทผ ์ฐ๊ตฌ๋ค์ด ์ด ๊ณต๋ฐฑ์ ๋ฉ์ฐ๊ธฐ ์์ํ๊ณ ์๋ค.
์ฐ๊ตฌ ํํฉ
๋ฏธ๊ตญ์ ๋ถ ๋ถํ๋ฑ๊ณผ ์ํฅ ์ด๋์ฑ
Nature Communications์ ๊ฒ์ฌ๋ Schechtl(2025)์ ๋ถ์ ์ด๋์ฑ์ ์ฐ๊ด์ฑ์ ๊ดํ ๊ฐ์ฅ ์ง์ ์ ์ธ ์ฆ๊ฑฐ๋ฅผ ์ ์ํ๋ค. ์ด ์ฐ๊ตฌ๋ ๋ฏธ๊ตญ ํต๊ทผ๊ถ(commuting zones)์ ์ง์ญ๋ณ ๋ถ ๋ถํ๋ฑ ์ถ์ ์น๋ฅผ ๋ด์ ์ต๊ทผ ๊ณต๊ฐ ๋ฐ์ดํฐ์
์ธ GEOWEALTH-US ๋ฐ์ดํฐ๋ฒ ์ด์ค๋ฅผ Opportunity Insights ํ๋ก์ ํธ์ ์ํฅ ์ด๋์ฑ ์ถ์ ์น์ ๊ฒฐํฉํ์ฌ, ์๋๊ธฐ์ ์ง์ญ ๋ถ ๋ถํ๋ฑ์ ๋
ธ์ถ๋๋ ๊ฒ์ด ์ฑ์ธ๊ธฐ ์๋ ์ด๋์ฑ๊ณผ ๊ด๋ จ์ด ์๋์ง๋ฅผ ๊ฒํ ํ๋ค.
์ฐ๊ตฌ ๊ฒฐ๊ณผ๋ ๋ถ๋ช
ํ๋ค: ์ง์ญ ๋ถ ๋ถํ๋ฑ์ ์ํฅ ์๋ ์ด๋์ฑ๊ณผ ๋ถ์ ๊ด๊ณ์ ์๋ค. ๋ถ ๋ถํ๋ฑ์ด ๋์ ํต๊ทผ๊ถ์์ ์ฑ์ฅํ ์๋์ ์ฑ์ธ์ด ๋์์ ๋ ์๋ ๋ถํฌ์์ ์์๋ก ์ด๋ํ ๊ฐ๋ฅ์ฑ์ด ๋ฎ๋ค. ํนํ ์ด ์ฐ๊ตฌ์ ์ ์ ์๋ฎฌ๋ ์ด์
(static simulations)์ ๋ถ ๋ถํ๋ฑ์ด ์๋ ๋ถํ๋ฑ ์์ฒด๋ณด๋ค ์ํฅ ์ด๋์ฑ๊ณผ ๋ ๊ฐํ ์ฐ๊ด์ฑ์ ๋ณด์์ ์์ฌํ๋ฉฐ, ์ด๋ Great Gatsby Curve๊ฐ ์๋์๋ง ์ด์ ์ ๋ง์ถค์ผ๋ก์จ ๋ถํ๋ฑ๊ณผ ์ด๋์ฑ ์ ํ ๊ฐ์ ๊ด๊ณ๋ฅผ ๊ณผ์ํ๊ฐํ๊ณ ์์ ์ ์์์ ๋ํ๋ธ๋ค.
์ ์๋ ๋ฉ์ปค๋์ฆ ์ค ํ๋๋ ๊ต์ก๊ณผ ๊ด๋ จ๋ ๊ฒ์ด๋ค: ์ง์ญ ๋ถ ๋ถํ๋ฑ์ด ๋์์๋ก ์ ์๋ ๊ฐ์ ์๋
์ ๊ต์ก ์ฑ์ทจ๋๊ฐ ๋ฎ์์ง๋ ๊ฒ๊ณผ ๊ด๋ จ์ด ์๋ค. ๋ถ์ ํ ์ง์ญ ์ฌํ๋ ๊ณต๊ฐ์ ์ผ๋ก ์ง์ค๋ ์์ง์ ํ๊ต์ ๊ต์ก ํ๋์ ํฌ์ํ ์ ์์ผ๋ฉฐ, ์ด๋ ๋ฌผ๋ฆฌ์ ์ผ๋ก๋ ๊ฐ๊น์ง๋ง ์ฌํ์ ์ผ๋ก๋ ์ ๊ทผํ๊ธฐ ์ด๋ ค์ด ๊ธฐํ ๊ตฌ์กฐ๋ฅผ ๋ง๋ค์ด ๋ธ๋ค.
์ง๋ฆฌ์ ์ฐจ์
PNAS Nexus์ ๊ฒ์ฌ๋ Connor, Xie, Jang(2025)์ ๋์ํ๊ฐ ๋ถํ๋ฑ ๋ฐ ์ด๋์ฑ๊ณผ ์ด๋ป๊ฒ ์ํธ์์ฉํ๋์ง๋ฅผ ๊ฒํ ํ๋ค. ์ด๋ค์ ๋ถ์์ ์ค๋ซ๋์ ์ง์๋์ด ์จ ๊ธด์ฅ ๊ด๊ณ๋ฅผ ๋ค๋ฃฌ๋ค: ๋์๋ ๊ฒฝ์ ์ ์ญ๋์ฑ๊ณผ ๋ถ ์ฐฝ์ถ์ ์๋๋ ฅ์ด์ง๋ง, ๋์์ ์ง์ค๋ ๋ถํ๋ฑ๊ณผ ์ฌํ์ ๊ณ์ธตํ์ ์ฅ์์ด๊ธฐ๋ ํ๋ค. ์ด ์ฐ๊ตฌ๋ ๋๋์๊ฐ ์ธ๋ ๋ด ๋ฐ ์ธ๋ ๊ฐ ๋ถํ๋ฑ์ ๋ชจ๋ ์ฌํ์ํจ๋ค๋ ๊ฒ์ ๋ฐ๊ฒฌํ๋คโ๋์์ ๋ถ ํ๋ฆฌ๋ฏธ์(urban wealth premiums)์ ์๋นํ์ง๋ง ์ฃผ๋ก ์ด๋ฏธ ๋ถ๋์ฐ์ ์์ ํ ์ฌ๋๋ค์๊ฒ ๊ท์๋๋ ๋ฐ๋ฉด, ์ ์๋ จ ๋
ธ๋์์ ๋ํ ๋์์ ์๊ธ ํ๋ฆฌ๋ฏธ์(urban wage premiums)์ ๊ฐ์ํ์๋ค.
์ด๋ ์ง๋ฆฌ์ ํจ์ ์ ๋ง๋ค์ด ๋ธ๋ค: ๊ฒฝ์ ์ ๊ธฐํ๊ฐ ๊ฐ์ฅ ๋ง์ ๊ณณ์ด ๋์์ ์ง์
๋น์ฉ(์ฃผ๊ฑฐ, ๊ต์ก, ์ฌํ์ ๋คํธ์ํฌ)์ด ๊ฐ์ฅ ๋์ ๊ณณ์ด๊ธฐ๋ ํ๋ฉฐ, ๋ถํ๋ฑ์ผ๋ก ์ธํด ์ฌํ์ ์ฌ๋ค๋ฆฌ์ ๋ฐํ ๊ฐ ๊ฑฐ๋ฆฌ๊ฐ ๊ฐ์ฅ ๋ฉ์ด์ง๋ ๊ณณ์ด๊ธฐ๋ ํ๋ค.
๋ถ ์ด์ ์ ๊ดํ ๊ตญ๊ฐ ๊ฐ ๋น๊ต ์ฆ๊ฑฐ
Dewilde(2024)๋ ์ ๋ฝ ์ฌ๋ฌ ๊ตญ๊ฐ์ ๊ฑธ์ณ ์ธ๋ ๊ฐ ๊ธ์ต์ ๋ถ์ด์ต์ ์ ๋ฌ์ ๊ฒํ ํ๋ค. ์ด ์ฐ๊ตฌ๋ ๊ทผ๋ก ์ฐ๋ น ๊ฐ๊ตฌ์ ๋น๊ณค ์ํ ์ฆ๊ฐ๊ฐ ๋
ธํ๊น์ง ์ด์ด์ง๋ ๊ฒฐ๊ณผ๋ฅผ ๋ณ์ผ๋ฉฐ, ์ธ๋์ ๊ฑธ์น ๊ธ์ต์ ์ทจ์ฝ์ฑ์ ์ฐ์๋ฅผ ๋ง๋ค์ด ๋ธ๋ค๋ ๊ฒ์ ๋ฐ๊ฒฌํ๋ค. ์ฃผ๋ชฉํ ๋งํ๊ฒ๋, ์ ๋ฌ ๋ฉ์ปค๋์ฆ์ ๋ณต์ง๊ตญ๊ฐ ์ ํ์ ๋ฐ๋ผ ์ฐจ์ด๋ฅผ ๋ณด์ธ๋ค: ์์ ์ฃผ์์ ๋ณต์ง๊ตญ๊ฐ(์๊ตญ, ์์ผ๋๋)์์๋ ์์ฐ ๋น๊ณค์ด ์ฃผ๋ก ๋ฎ์ ์๊ฐ ๋ณด์ ์จ์ ํตํด ์ ๋ฌ๋๋ ๋ฐ๋ฉด, ๋๋ฅํ ๋ณต์ง๊ตญ๊ฐ(๋
์ผ, ํ๋์ค)์์๋ ์ง์ญ ์ฐ๊ธ(occupational pension)์ ๊ฒฉ์ฐจ๊ฐ ๋ ํฐ ์ญํ ์ ํ๋ค.
๊ณ์ธต๋ณ ๋ถ์ ์๋ ๊ณ์ธตํ
Gil-Hernรกndez, Salas-Rojo, Vidal(2025)์ ์ ๋ฝ 5๊ฐ๊ตญ์ ๋ถ์ ์๋ ๊ณ์ธตํ๋ฅผ ๋ถ์ํ์ฌ, ๋ถ์์์ ์ฌํ๊ณ๊ธ ๊ฒฉ์ฐจ๊ฐ ์๋์์์ ์ฌํ๊ณ๊ธ ๊ฒฉ์ฐจ๋ณด๋ค ์ค์ง์ ์ผ๋ก ๋ ํฌ๋ค๋ ์ฌ์ค์ ๋ฐ๊ฒฌํ์๋ค. ์ ๋ฌธ์งยท๊ด๋ฆฌ์ง ๊ณ๊ธ๊ณผ ๋
ธ๋์ ๊ณ๊ธ ์ฌ์ด์ ๋ถ ๊ฒฉ์ฐจ๋ ๊ตญ๊ฐ์ ๋ฐ๋ผ ์๋ ๊ฒฉ์ฐจ์ ์ฝ 3~5๋ฐฐ์ ๋ฌํ๋ค. ์ด๊ฒ์ด ์ค์ํ ์ด์ ๋ ๋ถ๊ฐ ์๋๋ง์ผ๋ก๋ ์ ๊ณตํ ์ ์๋ ๋ฐฉ์์ผ๋ก ์์ , ๊ธฐํ, ์ธ๋ ๊ฐ ์ด์ ์ ์ ๊ณตํ๊ธฐ ๋๋ฌธ์ด๋คโ๋ถ๋ ๊ต์ก์ ๋ท๋ฐ์นจํ๊ณ , ์ค์
์ ๋ํ ์์ถฉ ์ญํ ์ ํ๋ฉฐ, ์ฃผํ ์์ ๋ฅผ ๊ฐ๋ฅํ๊ฒ ํ๊ณ , ๋ค์ ์ธ๋์ ์ง์ ์ด์ ๋ ์ ์๋ค.
GEOWEALTH-US ๋ฐ์ดํฐ๋ฒ ์ด์ค
Suss, Kemeny, Connor(2024)๋ 1960~2020๋
์ ํฌ๊ดํ๋ ๋ฏธ๊ตญ ์ต์ด์ ์ง์ญ๋ณ ๋ถ ๋ถํ๋ฑ ๋ฐ์ดํฐ์
์ธ GEOWEALTH-US์ ๊ตฌ์ถ ๊ณผ์ ์ ์์ ํ๋ค. ์ด ๋ฐ์ดํฐ๋ 1980๋
๋ ์ดํ ๊ณต๊ฐ์ ๋ถ ๋ถํ๋ฑ์ด ์ค์ง์ ์ผ๋ก ์ฆ๊ฐํ์์ผ๋ฉฐ, ํด์ ๋๋์๊ถ์ด ๋ด๋ฅ ์ง์ญ์ ์์ ๋๊ฐ๊ณ ์์์ ๋ณด์ฌ์ค๋ค. ์ด ๋ฐ์ดํฐ์
์ Schechtl(2025)์ด ์ํํ ๊ฒ๊ณผ ๊ฐ์ ๋ถ์์ ๊ฐ๋ฅํ๊ฒ ํ๋ฉฐ, ๊ทธ ๊ตฌ์ถ ์์ฒด๊ฐ ์ถ๊ฐ์ ์ธ ์ฐ๊ตฌ๋ฅผ ์ด์งํ ๋ฐฉ๋ฒ๋ก ์ ์ง์ ์ ์๋ฏธํ๋ค.
๋นํ์ ๋ถ์: ์ฃผ์ฅ๊ณผ ๊ทผ๊ฑฐ
<
| ์ฃผ์ฅ | ์ถ์ฒ | ํ๊ฐ |
|---|
| ์ง์ญ ๋ด ๋ถ ๋ถํ๋ฑ์ ๋ ๋ฎ์ ์ํฅ ์๋ ์ด๋์ฑ์ ์์ธกํ๋ค | Schechtl, 2025 | ์ง์ง๋จ โ ์ ์ ํ ํต์ ๋ณ์๋ฅผ ๊ฐ์ถ ์ ์ค๊ณ๋ ์ฐ๊ตฌ |
| ์ด๋์ฑ์ ์์ด ๋ถ ๋ถํ๋ฑ์ด ์๋ ๋ถํ๋ฑ๋ณด๋ค ๋ ์ค์ํ๋ค | Schechtl, 2025 | ์ง์ง๋จ โ ์ ์ ์๋ฎฌ๋ ์ด์
์ด ๋ ๊ฐํ ์ฐ๊ด์ฑ์ ๋ณด์ฌ์ค |
| ๋๋์๋ ์ธ๋ ๋ด ๋ฐ ์ธ๋ ๊ฐ ๋ถํ๋ฑ์ ๋ชจ๋ ์ฌํ์ํจ๋ค | Connor et al., 2025 | ์ง์ง๋จ โ ๋คํ์ ์ ๊ทผ๊ฑฐ |
| ์ฌ์ ์ ๋ถ์ด์ต์ ์ ๋ฝ ์ ์ญ์์ ์ธ๋ ๊ฐ ์ ๋ฌ๋๋ค | Dewilde, 2024 | ์ง์ง๋จ โ ๋ฉ์ปค๋์ฆ์ ๋ณต์ง๊ตญ๊ฐ ์ ํ์ ๋ฐ๋ผ ๋ค์ํจ |
| ์ฌํ๊ณ๊ธ ๊ฐ ๋ถ ๊ฒฉ์ฐจ๋ ์๋ ๊ฒฉ์ฐจ๋ณด๋ค 3~5๋ฐฐ ๋ ํฌ๋ค | Gil-Hernรกndez et al., 2025 | ์ง์ง๋จ โ 5๊ฐ๊ตญ ๋น๊ต ๋ฐ์ดํฐ |
๋ฏธํด๊ฒฐ ๊ณผ์
์ ์ฑ
์ ํจ์: ์ ์ฑ
์ ์ด์ ์ด ์๋ ์ฌ๋ถ๋ฐฐ(๋์ง์ธ, ์ด์ ์ง์ถ)์์ ๋ถ ์ฌ๋ถ๋ฐฐ(์์์ธ, ๋ฒ ์ด๋น ๋ณธ๋, ๋ณดํธ์ ์์ฐ ํ์ฑ ํ๋ก๊ทธ๋จ)๋ก ์ ํ๋์ด์ผ ํ๋๊ฐ?ํต์ฌ ๋ฉ์ปค๋์ฆ์ผ๋ก์์ ์ฃผ๊ฑฐ: ๋๋ถ๋ถ์ ๊ฐ๊ตฌ์์ ์ฃผ๊ฑฐ๊ฐ ๊ฐ์ฅ ํฐ ๋ถ์ ๊ตฌ์ฑ ์์์์ ๊ฐ์ํ ๋, ๋ถ์ ๊ธฐ๋ฐํ ์ด๋์ฑ ์ฅ๋ฒฝ์ ์ค์ด๋ ๋ฐ ์ฃผ๊ฑฐ ์ ์ฑ
์ด ๊ฐ์ฅ ํจ๊ณผ์ ์ธ ์๋จ์ธ๊ฐ?์ธ์ข
๊ฐ ๋ถ ๊ฒฉ์ฐจ: ๋ฏธ๊ตญ์ ์ธ์ข
๊ฐ ๋ถ ๊ฒฉ์ฐจ๋ ์ธ์ข
๊ฐ ์๋ ๊ฒฉ์ฐจ๋ณด๋ค ์ค์ง์ ์ผ๋ก ๋ ํฌ๋ค. ์ด๊ฒ์ด Schechtl๊ณผ Connor et al.์ด ๊ท๋ช
ํ ์ง๋ฆฌ์ ํจํด๊ณผ ์ด๋ป๊ฒ ์ํธ์์ฉํ๋๊ฐ?์ธก์ : ๋ถ๋ ์๋๋ณด๋ค ์ธก์ ํ๊ธฐ ์ด๋ ต๋ค. ์ฐ๊ตฌ ๊ฒฐ๊ณผ๋ค์ ์ธก์ ๋ฐฉ์์ ์ผ๋ง๋ ๋ฏผ๊ฐํ๊ฐ?ํ์ฌ์ ์์น
๋ถ-์ด๋์ฑ์ ๊ดํ ์ ํฅ ์ฐ๊ตฌ ๋ฌธํ์ ์์ญ ๋
๊ฐ ์๋์ ์ด์ ์ ๋ง์ถฐ์จ ์ด๋์ฑ ์ฐ๊ตฌ๊ฐ ๋ฌธ์ ์ ๋ ์์ ๋ถ๋ถ๋ง์ ๋ฐ๋ผ๋ณด๊ณ ์์์ ์ ์์์ ์์ฌํ๋ค. ๋ถ ๋ถํ๋ฑโ์๋ ๋ถํ๋ฑ๋ณด๋ค ๋ ๊ทน๋จ์ ์ด๊ณ , ๋ ์ง์์ ์ด๋ฉฐ, ๋ ์ง์ ์ ์ผ๋ก ์ ๋ฌ ๊ฐ๋ฅํโ์ ์๋
๊ฐ ๋ถ๋ชจ์ ๊ฒฝ์ ์ ์ง์๋ฅผ ๋์ด์ค ์ ์๋์ง ์ฌ๋ถ๋ฅผ ๊ฒฐ์ ํ๋ ๋ ๊ฐ๋ ฅํ ์์ธ์ผ๋ก ๋ณด์ธ๋ค. ์ ์ฑ
์ ํจ์๋ ์ค์ง์ ์ด์ง๋ง ์ ์น์ ์ผ๋ก ๋์ ์ ์ด๋ค. ๋ถ ๋ถ๋ฐฐ์ ๋ํ ๊ฐ์
์ ์๋ ์ฌ๋ถ๋ฐฐ์๋ ๋ฌ๋ฆฌ ์ฌ์ฐ๊ถ, ์์ ๊ท๋ฒ, ์ฃผํ ์์ฅ์ ๊ฑด๋๋ฆฌ๊ธฐ ๋๋ฌธ์ด๋ค.
๊ด๋ จ ์ฐ๊ตฌ๋ ORAA ResearchBrain์ ํตํด ํ์ํ ์ ์๋ค.
References (5)
[1] Schechtl, M. (2025). The association between childhood exposure to local wealth inequality and intergenerational income mobility in the United States. Nature Communications, 16.
[2] Connor, D. S., Xie, S., & Jang, J. (2025). Big cities fuel inequality within and across generations. PNAS Nexus, 4(1), pgae587.
[3] Dewilde, C. (2024). The intergenerational transmission of financial disadvantage across Europe. Social Policy & Administration, 59(2).
[4] Gil-Hernรกndez, C. J., Salas-Rojo, P., & Vidal, G. (2025). Wealth and Income Stratification by Social Class in Five European Countries. Social Indicators Research.
[5] Suss, J., Kemeny, T., & Connor, D. S. (2024). GEOWEALTH-US: Spatial wealth inequality data for the United States, 1960โ2020. Scientific Data, 11, 308.