Changing Fortunes: An analysis of the dynamics of income inequality in US metropolitan areas Article Swipe
Alicia Cavanaugh
,
Sébastien Breau
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.7202/1083640ar
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.7202/1083640ar
Income inequality has increased significantly in OECD countries over the last few decades. Rising inequality has been particularly pronounced in the United States, especially so in metropolitan areas. During this time, the increasingly uneven distribution of income reflects the pulling away of high-income earners, as well as increased returns to skilled workers. This study uses IPUMS data to build a novel dataset for 226 MSAs over the 1980 to 2010 period. Results suggest that education has had the strongest impact on rising inequality across US metropolitan areas. Our findings also suggest that supply-side factors such as racial segregation and the size of the immigrant population are likewise positively linked with greater inequality.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7202/1083640ar
- https://www.erudit.org/fr/revues/cjrs/2019-v42-n1-cjrs06538/1083640ar.pdf
- OA Status
- bronze
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3215363428
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3215363428Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.7202/1083640arDigital Object Identifier
- Title
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Changing Fortunes: An analysis of the dynamics of income inequality in US metropolitan areasWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-11-10Full publication date if available
- Authors
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Alicia Cavanaugh, Sébastien BreauList of authors in order
- Landing page
-
https://doi.org/10.7202/1083640arPublisher landing page
- PDF URL
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https://www.erudit.org/fr/revues/cjrs/2019-v42-n1-cjrs06538/1083640ar.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
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https://www.erudit.org/fr/revues/cjrs/2019-v42-n1-cjrs06538/1083640ar.pdfDirect OA link when available
- Concepts
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Metropolitan area, Inequality, Economic inequality, Demographic economics, Economics, Income distribution, Income inequality metrics, Distribution (mathematics), Population, Development economics, Geography, Sociology, Demography, Mathematical analysis, Mathematics, ArchaeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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51Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.During | 28 |
| abstract_inverted_index.Income | 0 |
| abstract_inverted_index.Rising | 13 |
| abstract_inverted_index.United | 21 |
| abstract_inverted_index.across | 83 |
| abstract_inverted_index.areas. | 27, 86 |
| abstract_inverted_index.impact | 79 |
| abstract_inverted_index.income | 36 |
| abstract_inverted_index.linked | 108 |
| abstract_inverted_index.racial | 96 |
| abstract_inverted_index.rising | 81 |
| abstract_inverted_index.uneven | 33 |
| abstract_inverted_index.Results | 71 |
| abstract_inverted_index.States, | 22 |
| abstract_inverted_index.dataset | 61 |
| abstract_inverted_index.factors | 93 |
| abstract_inverted_index.greater | 110 |
| abstract_inverted_index.period. | 70 |
| abstract_inverted_index.pulling | 39 |
| abstract_inverted_index.returns | 48 |
| abstract_inverted_index.skilled | 50 |
| abstract_inverted_index.suggest | 72, 90 |
| abstract_inverted_index.decades. | 12 |
| abstract_inverted_index.earners, | 43 |
| abstract_inverted_index.findings | 88 |
| abstract_inverted_index.likewise | 106 |
| abstract_inverted_index.reflects | 37 |
| abstract_inverted_index.workers. | 51 |
| abstract_inverted_index.countries | 7 |
| abstract_inverted_index.education | 74 |
| abstract_inverted_index.immigrant | 103 |
| abstract_inverted_index.increased | 3, 47 |
| abstract_inverted_index.strongest | 78 |
| abstract_inverted_index.especially | 23 |
| abstract_inverted_index.inequality | 1, 14, 82 |
| abstract_inverted_index.population | 104 |
| abstract_inverted_index.positively | 107 |
| abstract_inverted_index.pronounced | 18 |
| abstract_inverted_index.high-income | 42 |
| abstract_inverted_index.inequality. | 111 |
| abstract_inverted_index.segregation | 97 |
| abstract_inverted_index.supply-side | 92 |
| abstract_inverted_index.distribution | 34 |
| abstract_inverted_index.increasingly | 32 |
| abstract_inverted_index.metropolitan | 26, 85 |
| abstract_inverted_index.particularly | 17 |
| abstract_inverted_index.significantly | 4 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/1 |
| sustainable_development_goals[0].score | 0.6800000071525574 |
| sustainable_development_goals[0].display_name | No poverty |
| citation_normalized_percentile.value | 0.24787661 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |