scholarly journals Income Inequality and Economic Segregation in Los Angeles from 1980 to 2010

2021 ◽  
pp. 371-387
Author(s):  
John R. Hipp ◽  
Jae Hong Kim
Keyword(s):  
Los Angeles ◽  
Income Inequality ◽  
Residential Segregation ◽  
Gini Coefficient ◽  
Metropolitan Regions ◽  
Economic Segregation ◽  
The Gini Coefficient ◽  
Time Period ◽  
The Us ◽  
Us Census

AbstractRising income inequality is a critical problem in both the global North and South. In the United States, the Gini coefficient measuring nationwide income inequality rose from 0.403 in 1980 to 0.480 in 2014 (US Census), and residential segregation by income has increasingly occurred in many metropolitan regions and is particularly reflected in the spatial separation of the wealthiest households. This chapter focuses on the change in the level of income inequality in the Los Angeles region since 1980 and how it is related to changes in residential segregation between economic groups over that same time period. We use data from the US Census collected in 1980, 1990, 2000, and 2010. We measure residential segregation between economic groups based on occupational structure, and measure ‘neighbourhoods’ using Census tracts: these are units defined by the US Census and typically average about 4,000 residents. The overall level of inequality in the region is measured at each decade point using the Gini coefficient for household income. Maps demonstrate where different socioeconomic status groups have tended to locate and how economic segregation has changed in Los Angeles over this time period. We also assess the extent to which changes in inequality are related to changes in economic segregation over the last four and a half decades.

The Problem of Income Inequality

2019 ◽  
pp. 42-44
Author(s):  
Andrew Smithers
Keyword(s):  
Income Inequality ◽  
Gini Coefficient ◽  
Living Standards ◽  
Living Standard ◽  
The Gini Coefficient ◽  
The Us ◽  
The Uk ◽  
Distribution Of Income

Living standards change in line with GDP per head only if the distribution of incomes is unchanged. If incomes become less equally distributed the living standards of most people will fall even if GDP per head is stable. The Gini Coefficient is the most widely used indicator designed to measure the distribution of income. UK inequality, on this measure, has risen since 1977, stabilized since 1987, and fallen in recent years. In the US there has been a long-term increase in income inequality. Unless this US trend for increased income inequality halts, it is quite likely that even if GDP per head rises in the US, the living standard of the average voter will fall. The recent data suggest that changes in income inequality pose less of a threat to living standards in the UK then they do to those in the US.

scholarly journals Financialization and Income Inequality in Selected European Countries, 2004–2013

e-Finanse ◽  
2017 ◽  
Vol 12 (4) ◽  
pp. 20-32
Author(s):  
Grzegorz Golebiowski ◽  
Piotr Szczepankowski ◽  
Dorota Wisniewska
Keyword(s):  
Income Inequality ◽  
Eastern Europe ◽  
Gini Coefficient ◽  
Central And Eastern Europe ◽  
Value Added ◽  
European Countries ◽  
Total Employment ◽  
The Gini Coefficient ◽  
Synthetic Indicator ◽  
The Impact

Abstract The article examines the impact of financialization on income inequality between 2004 and 2013, through a panel analysis of seven European countries. Moreover, it attempts to examine differences in the perception of the phenomenon between the selected European countries belonging to the G-7 and countries from Central and Eastern Europe. The results demonstrate the existence of individual effects, which means that the level of inequality under examination is influenced predominantly by country-specific factors. The most significant correlation is noticeable between the level of unemployment and the degree of income inequality. An increase in unemployment is accompanied by a rise in the disproportions in the level of income that individual citizens have at their disposal whereas a decrease in the unemployment level contributes to an improvement of the GINI coefficient. Simultaneously, the results confirm the existence of significant correlations between the level of the GINI coefficient and such financialization indicators as the share of employment in finance in total employment and the contribution of the financial sector to total value added creation. The most prominent dependency was discovered when a constructed synthetic indicator was adopted as an indicator of financialization. At the same time, analysis of the synthetic country financialization indicator points to a conclusion that the level of financialization is higher in European countries belonging to the G-7 (especially Great Britain) than in countries from Central and Eastern Europe.

Abstract P208: The Differential Impact Of Residential Segregation On Gestational Hypertension Development Among Minority Women

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Mary D Schiff ◽  
Anthony Fabio ◽  
Tiffany Gary-Webb ◽  
Dara Mendez
Keyword(s):  
Black Women ◽  
Residential Segregation ◽  
Census Tract ◽  
Gestational Hypertension ◽  
Cardiometabolic Health ◽  
Economic Segregation ◽  
Birth Record ◽  
Child Bearing ◽  
Record Data ◽  
Us Census

Introduction: Higher levels of residential segregation have been associated with poorer cardiometabolic health profiles among women. Still, it remains unclear whether segregation may differentially impact the development of gestational hypertension (gHTN) among an ethnically-diverse cohort of pregnant women. We used birth record data from 2003-2009 and data from the 2000 US Census to determine whether racial and economic segregation are associated with gHTN among a diverse cohort of child-bearing women in the greater Philadelphia area. Methods: We quantified racial and economic segregation using sociodemographic data from the US Census and the local Getis-Ord (Gi*) spatial statistic. The Gi* produces a spatially-weighted z-score for each census tract reflecting the degree of clustering of racially-similar neighborhoods in an area relative to the surrounding Philadelphia region. We categorized each type of segregation as low (Gi*<0), moderate (Gi*0-1.96), or high (Gi*>1.96), and assigned these to each woman by her census tract of residence. Gestational hypertension was defined in the birth record data as the development of pregnancy-induced hypertension or preeclampsia. We used hierarchical generalized linear mixed effect models to obtain risk ratios and differences (per 1000 women) for the relationships between each form of residential segregation and gHTN. All models were stratified by maternal race/ethnicity, and sequentially adjusted for maternal sociodemographics, health behaviors, medical histories, and neighborhood-level characteristics. Results: Our sample consisted of 220,897 Non-Hispanic (NH) Black (26%), NH White (64%), and Hispanic (10%) women, of whom 4% developed gHTN. However, a much greater proportion of NH Black women both developed gHTN and lived in high segregation neighborhoods compared to NH Whites and Hispanics. After adjustment, NH Black women in moderate and high economic segregation areas had 16% higher risk (RR=1.16, 95% CI: 1.03-1.31) and 23% higher risk (RR=1.23, 95% CI: 1.08-1.39) of gHTN, respectively, compared to NH Black women living in low segregation areas. NH Black women in highly racially segregated neighborhoods saw an additional 9 cases of gHTN (per 1000 women) compared to NH Black women living in more racially integrated neighborhoods (RD=8.47, 95% CI: 3.14-13.80). Among NH White and Hispanic women, economic segregation was not associated with gHTN, and only marginally significant findings were observed for racial segregation. Conclusions: In our diverse sample of child-bearing women from the greater Philadelphia area, higher levels of racial and economic segregation were associated with greater risk of gHTN among NH Black women. Future work should seek to delineate the specific pathways by which neighborhoods differentially impact individual level cardiovascular health based upon race.

scholarly journals The prevalence of MS in the United States

Neurology ◽  
2019 ◽  
Vol 92 (10) ◽  
pp. e1029-e1040 ◽  
Author(s):  
Mitchell T. Wallin ◽  
William J. Culpepper ◽  
Jonathan D. Campbell ◽  
Lorene M. Nelson ◽  
Annette Langer-Gould ◽  
...  
Keyword(s):  
United States ◽  
Census Data ◽  
Adult Population ◽  
The United States ◽  
Health Claims ◽  
The North ◽  
Time Period ◽  
The Us ◽  
Group A ◽  
Us Census

ObjectiveTo generate a national multiple sclerosis (MS) prevalence estimate for the United States by applying a validated algorithm to multiple administrative health claims (AHC) datasets.MethodsA validated algorithm was applied to private, military, and public AHC datasets to identify adult cases of MS between 2008 and 2010. In each dataset, we determined the 3-year cumulative prevalence overall and stratified by age, sex, and census region. We applied insurance-specific and stratum-specific estimates to the 2010 US Census data and pooled the findings to calculate the 2010 prevalence of MS in the United States cumulated over 3 years. We also estimated the 2010 prevalence cumulated over 10 years using 2 models and extrapolated our estimate to 2017.ResultsThe estimated 2010 prevalence of MS in the US adult population cumulated over 10 years was 309.2 per 100,000 (95% confidence interval [CI] 308.1–310.1), representing 727,344 cases. During the same time period, the MS prevalence was 450.1 per 100,000 (95% CI 448.1–451.6) for women and 159.7 (95% CI 158.7–160.6) for men (female:male ratio 2.8). The estimated 2010 prevalence of MS was highest in the 55- to 64-year age group. A US north-south decreasing prevalence gradient was identified. The estimated MS prevalence is also presented for 2017.ConclusionThe estimated US national MS prevalence for 2010 is the highest reported to date and provides evidence that the north-south gradient persists. Our rigorous algorithm-based approach to estimating prevalence is efficient and has the potential to be used for other chronic neurologic conditions.

From KISS to TASS Modeling: A Preliminary Analysis of the Segregation Model Incorporated with Spatial Data on Chicago

2015 ◽  
Vol 16 (4) ◽  
pp. 553-573 ◽  
Author(s):  
GAKU ITO ◽  
SUSUMU YAMAKAGE
Keyword(s):  
Residential Segregation ◽  
Spatial Data ◽  
Demographic Data ◽  
Theoretical Models ◽  
Agent Based Modeling ◽  
Agent Based Models ◽  
Agent Based ◽  
The Us ◽  
Us Census ◽  
The City

AbstractThe ‘keep it simple, stupid’ slogan, or the KISS principle has been the basic guideline in agent-based modeling (ABM). While the KISS principle or parsimony is vital in modeling attempts, conventional agent-based models remain abstract and are rarely incorporated or validated with empirical data, leaving the links between theoretical models and empirical phenomena rather loose. This article reexamines the KISS principle and discusses the recent modeling attempts that incorporate and validate agent-based models with spatial (geo-referenced) data, moving beyond the KISS principle. This article also provides a working example of such time and space specified (TASS) agent-based models that incorporates Schelling's (1971) classic model of residential segregation with detailed geo-referenced demographic data on the city of Chicago derived from the US Census 2010.

THE GINI COEFFICIENT'S APPLICATION TO GENERAL COMPLEX NETWORKS

2005 ◽  
Vol 08 (01) ◽  
pp. 159-167 ◽  
Author(s):  
HAI-BO HU ◽  
LIN WANG
Keyword(s):  
Income Inequality ◽  
Complex Networks ◽  
Network Structure ◽  
Gini Coefficient ◽  
Scale Free ◽  
The Gini Coefficient ◽  
Scale Free Networks ◽  
General Complex

The Gini coefficient, which was originally used in microeconomics to describe income inequality, is introduced into the research of general complex networks as a metric on the heterogeneity of network structure. Some parameters such as degree exponent and degree-rank exponent were already defined in the case of scale-free networks also as a metric on the heterogeneity. In scale-free networks, the Gini coefficient is proved to be equivalent to the parameters mentioned above, and moreover, a classification of infinite scale-free networks is given according to the value of the Gini coefficient.

scholarly journals Income Inequality and Noncash Food Assistance Program in Central Java Province

2021 ◽  
Vol 16 (2) ◽  
Author(s):  
Yusuf Munandar
Keyword(s):  
Income Inequality ◽  
Gini Coefficient ◽  
Rural Areas ◽  
Food Assistance ◽  
Population Increase ◽  
Assistance Program ◽  
Central Java ◽  
The Gini Coefficient ◽  
Central Java Province

One measure of income inequality that is often used is the Gini Coefficient. In Central Java Province, the income inequality in March 2019 was increasing compared to income inequality in September 2018. To reduce this income inequality, the government is focusing on increasing government spending in the field of social assistance, including Non-Cash Food Assistance (Bantuan Pangan Non Tunai/BPNT). Thus, this study aims to calculate and obtain a reduction in the Gini Coefficient as a result of the implementation of the BPNT program in the Central Java Province of Indonesia. This study uses the Counter Factual Analysis (CFA) method and the March 2019 Susenas data. This study concludes that the implementation of the BPNT program in 2019 is quite effective in reducing the level of income inequality in the Central Java Province of Indonesia, which is able to reduce the Gini Coefficient of Central Java Province by -1.20%. The implementation of the BPNT program was able to make the expenditure of the lower class population increase faster than the expenditure of upper and middle class population. The implementation of the BPNT program changes the map of the income inequality level of 35 districts/cities in the Central Java Province of Indonesia but does not change the map of the level of income inequality between urban and rural areas in the Central Java Province of Indonesia. In addition, the implementation of the BPNT program in the Central Java Province of Indonesia has not been able to change the category of income inequality in the Central Java Province of Indonesia, namely that it remains in the moderate category. This study recommends improvements in terms of the target recipients of BPNT, the quality of the human resources of the companions, the time for receiving assistance, the quality of rice, and the readiness of e-warong in 35 districts/cities in the Province of Central Java, Indonesia.

scholarly journals Energy transition and social justice: Do renewable energy levies have an impact on income distribution and energy poverty?

2021 ◽  
Author(s):  
Jan Priesmann ◽  
Saskia Spiegelburg ◽  
Reinhard Madlener ◽  
Aaron Praktiknjo
Keyword(s):  
Social Justice ◽  
Income Inequality ◽  
Low Income ◽  
Gini Coefficient ◽  
Electricity Consumption ◽  
Energy Transition ◽  
Relative Increase ◽  
Energy Poverty ◽  
The Gini Coefficient ◽  
Ex Post

Abstract Energy systems are decidedly the largest emitters of greenhouse gases. Therefore, transitioning them from fossil to renewable systems is a top priority for societies committed to reducing greenhouse gas emissions. However, such transitions involve substantial costs. In many cases, these costs are proportionally passed on to final energy consumers through levies on their electricity consumption. In our paper, we investigate the impacts of renewable support levies on social justice or, more specifically, on income inequality. For our study, we chose Germany where inflation-adjusted electricity prices for private households increased substantially because of such a levy for renewables. We base our analyses on representative household panel data with over 40,000 households from 2003 to 2018. Our results indicate that indiscriminate renewable support levies on electricity consumption increase income inequality and energy poverty. For our case in 2018, renewable support levies alone led to a relative increase of ~0.23% of the Gini coefficient and ~11.31% of the high cost low income (HCLI) energy poverty indicator measuring energy poverty intensity. Based on our findings, we propose a reform of the renewable support levy and analyze three options: (1) the abolition of the levy, (2) levies which are income-progressive proportionally to the income taxes, and (3) a high and flat levy in conjunction with an income-degressive compensation payment. Our ex-post analyses for 2018 indicate that a reformed levy system would have slightly decreased overall income inequality with relative decreases of ~0.23%, ~0.32%, and ~0.59% of the Gini coefficient for options (1), (2), and (3), respectively. But more importantly, such a system would have substantially decreased energy poverty by ~11.31%, ~30.45%, and ~31.45% for the HCLI energy poverty indicator for options (1), (2), and (3), respectively.

scholarly journals A Meta-Analysis of the Association between Income Inequality and Intergenerational Mobility

2019 ◽  
Vol 5 ◽  
pp. 237802311988128 ◽  
Author(s):  
Ernesto F. L. Amaral ◽  
Shih-Keng Yen ◽  
Sharron Xuanren Wang-Goodman
Keyword(s):  
Income Inequality ◽  
Gini Coefficient ◽  
Intergenerational Mobility ◽  
Meta Analysis ◽  
The United States ◽  
Income Share ◽  
Income Elasticities ◽  
Great Gatsby ◽  
The Gini Coefficient ◽  
Over Time

We provide an overview of associations between income inequality and intergenerational mobility in the United States, Canada, and eight European countries. We analyze whether this correlation is observed across and within countries over time. We investigate Great Gatsby curves and perform metaregression analyses based on several papers on this topic. Results suggest that countries with high levels of inequality tend to have lower levels of mobility. Intergenerational income elasticities have stronger associations with the Gini coefficient compared to associations with the top 1 percent income share. Once models are controlled for methodological variables, country indicators, and paper indicators, correlations of mobility with the Gini coefficient lose significance but not with the top 1 percent income share. This result is an indication that recent increases in inequality at the top of the distribution might be negatively affecting mobility on a greater magnitude compared to variations across the income distribution.

T‐Communities: Pedestrian Street Networks and Residential Segregation in Chicago, Los Angeles, and New York

2004 ◽  
Vol 4 (3) ◽  
pp. 295-321 ◽  
Author(s):  
Rick Grannis
Keyword(s):  
New York ◽  
Los Angeles ◽  
Residential Segregation ◽  
Metropolitan Areas ◽  
Racial Variation ◽  
Metropolitan Regions ◽  
Street Networks ◽  
Households With Children ◽  
Block Groups ◽  
Pedestrian Street

In this article, I build on Grannis' (1998) analysis and examine the entire metropolitan regions of the three most populous U.S. Primary Metropolitan Statistical Areas (PMSAs). I find that t‐communities, communities defined by their internal access via pedestrian streets, powerfully account for the racial patterning of households in all three metropolitan areas. Racial variation occurs between t‐communities not within them, even when both distances between block groups or, in the case of households with children, racial variation between elementary schools is accounted for. While Grannis (1998) examined how similar t‐communities connected by pedestrian streets were to each other, this study examines how internally homogeneous t‐communities themselves are. Further, this study's analysis of households with children finds that they have settled in such a way as to assure a racially homogeneous t‐community more than a racially homogeneous school. By analyzing the entire metropolitan areas of PMSAs in different regions, this study also discovered very large t‐communities, hundreds of times larger than a typical t‐community, in which pedestrian streets no longer have an important influence.

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