Income segregation

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Income segregation is the separation of various classes of people based on their income. For example, certain people cannot get into country clubs because of insufficient funds. Another example of income segregation in a neighborhood would be the schools, facilities and the characteristics of a population. Income segregation can be illustrated in countries such as the United States, where racial segregation is a major cause of income inequality. [1]

Contents

Income segregation is associated with greater inequality in educational attainment between classes. [2] Income segregation is highly correlated with income inequality, racial segregation and segregation of poverty and affluence. Also, the correlation of the income segregation between schools has been documented and is an increasing trend with little or no exception. [2]

Income segregation is also dependent on other variables which are observable within society – income inequality, spatial segregation of affluence and poverty (which describes the isolation of the upper- or low-income households and other classes), and racial segregation. Also, inequality within the educational system of a given class is associated to so extend with the income segregation. [3] [2]

The importance of measuring income segregation is given by the different redistribution of outcomes across the society, uneven within different income classes. For the upper-income classes these differences can even be positive, often giving them better social and educational background or more pleasing environments in their metropolitan area. These neighborhoods can make themselves better off in comparison to lower-income ones, mostly due to public policy (and the difference among the tax base each class pays). As a result, income segregation expands because upper-income communities have these advantages and benefit from them. [2]

Metropolitan income segregation in the US grew constantly between 1970 and 2000; it was fastest in the 1980s. The growth was stronger for black families than white ones as well as the covariance of income inequality and the segregation of poverty and affluence. [4] [2]

In context

Income segregation and income inequality

Income inequality is a necessary condition for income segregation. If there were no income inequality, neighborhoods would possess the same opportunities and conditions and thus no income segregation would likely occur. However, it is important to recognize that the relationship between can be affected by many different factors and that it is not necessarily a one-to-one relationship. [5]

Based on research, income inequality itself does not create income segregation – the presence of income-correlated residential preferences, and an income-based housing market and/or housing policies is crucial. [2]

An increase in inequality in the US from 1970 to 1990 resulted in an increase in income segregation. Also, an increase in income segregation in economic school segregation is highly dependent on income inequality (as well as the role of educational policies). [4] [2]

Income segregation (as well as racial segregation) is stronger in the public educational system than in the private system, especially in primary education. This is usually explained by the neighborhood (metropolitan area) where schools are located. [6] This can be due to the fact that regardless of one's financial background, anyone can attend a public school; therefore, a broader range of people will study at a public school. The relationship between income segregation and income inequality is complex: its results can be influenced by local political, economic, and city planning agendas, which can either work for or against the fight with income segregation and income inequality. [7]

Income inequality and the Lorenz curve

The Lorenz curve was taken up by the American statistician Max Lorenz to study the income problem. In the Lorenz curve method, firstly, the number of consumer units in various income brackets and their income is evaluated. They are then divided into percentages that rank the consumer units from the lowest to the highest income. Opposite each percentage, the share of this group in national income is shown as a percentage. Finally, a table showing both consumer units and national income in percentages is drawn up, and the data is placed in a diagram. The diagrammatic expression resulting from this process is called the Lorenz curve. On this curve, the percentage of consumer units lined up on the horizontal axis from the least income to the highest income is shown cumulatively. If the percentages that different groups receive from income are marked on the diagram and the marked points are connected, a curve showing the income distribution of the economy is obtained. In the curve diagram showing this income distribution, the inequality in income distribution decreases as it approaches the line drawn by forming an angle of 45 degrees, and the inequality in income distribution increases as it gets farther away.

Income inequality and the segregation of poverty and affluence

Income inequality affects income segregation. Among low-income households the difference between incomes do not significantly vary. Thus, income inequality is generally stronger among high-income households – i.e., upper-tail income inequality. In other words, there is little or no significant impact of the income inequality on income segregation among low-income households. It means that for moderate or high-income households it is more probable that they would not be able to afford to live in the same neighborhood (on the contrary to low-income households). Thus upper-tail income inequality leads to greater segregation of affluence and not necessarily to greater segregation of poverty. [2]

Even though the segregation of the affluence is stronger, the research shows that it remains stable over the years (on the contrary to the other types). [8]

Racial differences and income segregation

Metropolitan income segregation also differs among races due to historical racial discrimination, when fewer residential options were available for black households in comparison to the white household of the same income level and wealth; then an expansion in housing options occurred in the late 20th century. This resulted in a stronger correlation between income inequality and income segregation among black families than among white families during this period. For example, studies show in the US between the 1970s and 1980s that income segregation among black families grew more than three times faster than among white families. [2]

Measurement

There are multiple options of measuring income segregation even though they are much less developed and each of them include some advantages as well as disadvantages. Many studies use dissimilarity index (unlike when measuring racial segregation) – whose possible disadvantage is the substantial loss of information. The variation of the dissimilarity index is the overall economic segregation index. This index is based on the seven variables based on the income, educational and occupational measures and out of these measures the overall economic segregation is calculated. Another possibility for measuring income segregation is the use of a ratio of the between-neighborhood variation in mean income to the total variation of income, one of the variation of this approach is a centile gap index (segregation is equal to one minus the ratio of the within-neighborhood variation in income percentile rank to the overall variation in percentile rank), Bourguignon's income inequality index or Jargowsky's Neighborhoods Sorting Index – i.e., to the square root of the ratio of the between-unit income variance to the total income variance. [9] [2]

Rank-order theory index is the ratio of within-unit income rank variation to overall income rank variation. This approach allows to measure this type of segregation even if the precise threshold of the income is unknown and we choose only based on the percentiles. [2] This index can be utilized as a way to go around the difficulty of examining the relationship between income inequality and income segregation. [5] The index varies between 0 and 1. The rank-order will be 0 if income segregation does not exist, illustrating that the income distribution in each neighborhood is identical to that of the city. [5] If the rank-order will be 1, the case will be the opposite where income segregation does exist, and neighborhoods are divided based on their income rank. [5]

Residential Income Segregation Index is one of the more precise measuring methods for summarizing the income segregation. It was developed by Richard Fry and Paul Taylor. [10] As the name indicates, it focuses on the income segregation given by the residential possibilities. [11] According to a research paper, it takes into account the highest 30 metropolitan regions for each country. The highest that the Residential Income Segregation Index can be is 200. Additionally, the residential income segregation index sums the percentage of poorer households living in a largely poorer area and the percentage of richer households living in a largely richer area. [12] The following three metropolitan regions were recorded as having the biggest degrees of income segregation: Dallas, New York and Houston. [10] This could be due to immigration as it led to increased population growth. [10] The following three metropolitan regions were recorded as having the lowest degrees of income segregation: Atlanta, Chicago and Boston. [10]

The spacial ordering index is based on the concept of spacial ordering and measurements derived from it. [13] It is a way of describing and comparing different income levels in a given neighborhood with its physical location. This should provide a map and reveal some relationships between certain locations and income levels. there are several ways to approach spacial ordering, such as the "Nearest Neighbor Spatial Ordering", or the "Monocentric Spatial Ordering". [14] Dawkins proposes his way of calculating the Spatial Ordering Index, originally derived as a ratio between the spatial Gini index [15] and the income segregation Gini index. [16] Dawkins proposes a new method of substituting these two coefficients by two "Covariance based formulas" [14] based on parameters, such as different types of Aggregate household income of a neighborhood and region, average rank and spatial rank of income of a given neighborhood. [14]

Some of these approaches require the measurement of income inequality first for which the Gini index (Gini coefficient) is most widely use. If the value of the index is equal 0, perfect equality occurs. Perfect equality is where all have the same portion. On the contrary, when the value if the index is equal to 1, perfect inequality is observed within the society. [9] Perfect inequality is where either one person or group receives the whole share of income. In other words, the higher the Gini coefficient, the higher the degree of inequality. The Gini index is an assessment of income inequality, as it summarizes the entire data set into one statistic and it is able to represent the division of income whilst considering the whole income distribution. [17] The Gini coefficient takes the Lorenz curve and the perfect equality income distribution into account. [17]

Income segregation in the US and Brazil

Income segregation in the US is a direct result of rising income inequality since the 1970s, where today the difference in income of a 90th percentile family is nearly ten-fold from a family of 10th percentile in income distribution, as opposed to a six-fold difference in 1970. [18] One of the manifestations of this phenomenon is an increase in residential income segregation, where in 1970, 66% of families lived in middle-class neighborhoods and by 2007, that number decreased to 43%. The rapid disappearance of middle-class neighborhoods is one of the indicators that middle-class itself is disappearing as well. [18] In the United States, a black household will earn 42 percent less than a white household on average. [1]

When it comes to lowering the income difference, it requires that racial segregation also gets decreased. The United States is definitely studied rigorously when it comes to the study of segregation and racial inequality. Black Americans, however, have not been included in the move towards America's economic growth. [19] In America, there is a substantial difference in unemployment between blacks and whites: to be exact, unemployment among black people is 6% compared to 3.1% among white people (the data was collected prior to the COVID-19 pandemic). [19] Another illustration of segregation in the US is the difference in median household income among black people and white people: a median black household income would be $40,258, compared to $68,145 earned by a median white household income (these figures are from 2017). [19]

Brazil is one the most affected countries by income inequality (as well as other economic inequalities), before it was affected by COVID-19. [20] According to research that was done during the COVID-19 pandemic, it was concluded that there is a link between higher COVID-19 mortality rates and increased inequality factors (such as income inequality and income segregation). [20] Mixed linear models and the Gini index were used in this research. [20] The Gini Index is talked about further below. It was also found that the variability of COVID-19 mortality rates got lowered as you went from the cities to the states. [20] It can be noted that even before the COVID-19 pandemic, Brazil was already being affected by socioeconomic factors that further exaggerated income inequality and income segregation already. [20]

Importance

Income segregation is an important characteristic of the community indicating possible differences among the households of different level of income. High-income classes usually possess more cultural, educational, and political benefits. Thus, a child born in a low-income family is probable to make less than the one born in high-income household. [21] It is vital to understand income segregation in order to tackle income inequality. Additionally, income segregation can result in increasing the difference in outcomes depending on whether they come from a rich or poor household. [5]

Some proposals have been made to help to reduce the income segregation, which is in the US even stronger than in the other developed countries, [6] such as the integration of disadvantaged families into the mixed-income communities. This could to some way, according to the experts, help to reduce the poverty across the generations in these disadvantaged households. [21] [3]

The economic crisis between the years 2007-2011 also had an impact on the trend of economic segregation on which precise research have not been made yet. [8]

Seeing the illustration of income segregation can be significant for multiple reasons. Firstly, it shows the economic societal differences or inequality, which largely impact social and political issues. [22] Due to the existence of income segregation, it causes separated neighborhoods to form, with wealthier individuals living in their own communities with higher incomes. [19] Income segregation can also intensify issues. These issues can be the unequal opportunities with a lower access to goods and services as well as restricted social mobility. It can also add to the marginalization of targeted groups, increasing discrimination and contributes to the amplification of stereotypes. Additionally, income segregation can slow down economic growth as there is less space for innovation and entrepreneurship due to certain groups being disadvantaged. Furthermore, higher crime rates and lowered social cohesion can result from income segregation. [23]

In conclusion, income segregation is important because it allows us to recognize and address significant issues such as inequality and discrimination. Once we are able to understand the arrangement and relevancy of income segregation, politicians will be better able to tackle issues as well as benefit those that need it.

See also

Related Research Articles

<span class="mw-page-title-main">Gini coefficient</span> Measure of inequality of a distribution

In economics, the Gini coefficient, also known as the Gini index or Gini ratio, is a measure of statistical dispersion intended to represent the income inequality, the wealth inequality, or the consumption inequality within a nation or a social group. It was developed by Italian statistician and sociologist Corrado Gini.

<span class="mw-page-title-main">Lorenz curve</span> Graphical representation of the distribution of income or of wealth

In economics, the Lorenz curve is a graphical representation of the distribution of income or of wealth. It was developed by Max O. Lorenz in 1905 for representing inequality of the wealth distribution.

<span class="mw-page-title-main">Standard of living in the United States</span> Summary of living conditions in the United States of America

The standard of living in the United States is high by the standards that most economists use, and for many decades throughout the 20th century, the United States was recognized as having the highest standard of living in the world. Per capita income is high but also less evenly distributed than in most other developed countries; as a result, the United States fares particularly well in measures of average material well being that do not place weight on equality aspects.

<span class="mw-page-title-main">Income distribution</span> How a countrys total GDP is distributed amongst its population

In economics, income distribution covers how a country's total GDP is distributed amongst its population. Economic theory and economic policy have long seen income and its distribution as a central concern. Unequal distribution of income causes economic inequality which is a concern in almost all countries around the world.

Income inequality metrics or income distribution metrics are used by social scientists to measure the distribution of income and economic inequality among the participants in a particular economy, such as that of a specific country or of the world in general. While different theories may try to explain how income inequality comes about, income inequality metrics simply provide a system of measurement used to determine the dispersion of incomes. The concept of inequality is distinct from poverty and fairness.

<span class="mw-page-title-main">Distribution of wealth</span> Spread of wealth in a society

The distribution of wealth is a comparison of the wealth of various members or groups in a society. It shows one aspect of economic inequality or economic heterogeneity.

The Theil index is a statistic primarily used to measure economic inequality and other economic phenomena, though it has also been used to measure racial segregation.

The Hoover index, also known as the Robin Hood index or the Schutz index, is a measure of income inequality. It is equal to the percentage of the total population's income that would have to be redistributed to make all the incomes equal.

The African-American middle class consists of African-Americans who have middle-class status within the American class structure. It is a societal level within the African-American community that primarily began to develop in the early 1960s, when the ongoing Civil Rights Movement led to the outlawing of de jure racial segregation. The African American middle class exists throughout the United States, particularly in the Northeast and in the South, with the largest contiguous majority black middle-class neighborhoods being in the Washington, DC suburbs in Maryland. The African American middle class is also prevalent in the Atlanta, Charlotte, Houston, Dallas, New York, San Antonio and Chicago areas.

In economics, personal income refers to the total earnings of an individual from various sources such as wages, investment ventures, and other sources of income. It encompasses all the products and money received by an individual.

<span class="mw-page-title-main">Affluence in the United States</span> Economical and financial advantage

Affluence refers to an individual's or household's economical and financial advantage in comparison to others. It may be assessed through either income or wealth.

<span class="mw-page-title-main">Income inequality in the United States</span> National income inequality

Income inequality has fluctuated considerably in the United States since measurements began around 1915, moving in an arc between peaks in the 1920s and 2000s, with a 30-year period of relatively lower inequality between 1950 and 1980.

<span class="mw-page-title-main">Wealth inequality in the United States</span>

The inequality of wealth has substantially increased in the United States in recent decades. Wealth commonly includes the values of any homes, automobiles, personal valuables, businesses, savings, and investments, as well as any associated debts.

Residential segregation is the physical separation of two or more groups into different neighborhoods—a form of segregation that "sorts population groups into various neighborhood contexts and shapes the living environment at the neighborhood level". While it has traditionally been associated with racial segregation, it generally refers to the separation of populations based on some criteria.

In the United States, housing segregation is the practice of denying African Americans and other minority groups equal access to housing through the process of misinformation, denial of realty and financing services, and racial steering. Housing policy in the United States has influenced housing segregation trends throughout history. Key legislation include the National Housing Act of 1934, the G.I. Bill, and the Fair Housing Act. Factors such as socioeconomic status, spatial assimilation, and immigration contribute to perpetuating housing segregation. The effects of housing segregation include relocation, unequal living standards, and poverty. However, there have been initiatives to combat housing segregation, such as the Section 8 housing program.

<span class="mw-page-title-main">Housing inequality</span>

Housing inequality is a disparity in the quality of housing in a society which is a form of economic inequality. The right to housing is recognized by many national constitutions, and the lack of adequate housing can have adverse consequences for an individual or a family. The term may apply regionally, temporally or culturally. Housing inequality is directly related to racial, social, income and wealth inequality. It is often the result of market forces, discrimination and segregation.

In the United States, racial inequality refers to the social inequality and advantages and disparities that affect different races. These can also be seen as a result of historic oppression, inequality of inheritance, or racism and prejudice, especially against minority groups.

Structural inequality occurs when the fabric of organizations, institutions, governments or social networks contains an embedded cultural, linguistic, economic, religious/belief, physical or identity based bias which provides advantages for some members and marginalizes or produces disadvantages for other members. This can involve, personal agency, freedom of expression, property rights, freedom of association, religious freedom,social status, or unequal access to health care, housing, education, physical, cultural, social, religious or political belief, financial resources or other social opportunities. Structural inequality is believed to be an embedded part of all known cultural groups. The global history of slavery, serfdom, indentured servitude and other forms of coerced cultural or government mandated labour or economic exploitation that marginalizes individuals and the subsequent suppression of human rights are key factors defining structural inequality. In particular the history of oppression of the Jewish people, as victims of historic and ongoing antisemitism that dates back to their slavery under the Pharaohs offer an example of the historic nature and wide variance of structural inequality.

Sean F. Reardon is an American sociologist who currently serves as the Endowed Professor of Poverty and Inequality in Education at the Stanford Graduate School of Education, where he also is a member of the Steering Committee of the Center for Education Policy Analysis (CEPA). Reardon is an Elected Fellow to the American Academy of Arts & Sciences.

<span class="mw-page-title-main">The Elephant Curve</span> Graph showing unequal income growth

The Elephant Curve, also known as the Lakner-Milanovic graph or the global growth incidence curve, is a graph that illustrates the unequal distribution of income growth for individuals belonging to different income groups. The original graph was published in 2013 and illustrates the change in income growth that occurred from 1988 to 2008. The x axis of the graph shows the percentiles of the global income distribution. The y axis shows the cumulative growth rate percentage of income. The main conclusion that can be drawn from the graph is that the global top 1% experienced around a 60% increase in income, whereas the income of the global middle increased 70 to 80%.

References

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  2. 1 2 3 4 5 6 7 8 9 10 11 Reardon, Sean F. (July 2010). "Income Inequality and Income Segregation" (PDF). American Journal of Sociology.
  3. 1 2 Owens, Ann; Reardon, Sean F.; Jencks, Christopher (1 August 2016). "Income Segregation Between Schools and School Districts". American Educational Research Journal. 53 (4): 1159–1197. doi: 10.3102/0002831216652722 . ISSN   0002-8312.
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  6. 1 2 Stiglitz, Joseph E; Jay K. Rosengard (2015). Economics of the public sector (Fourth ed.). New York. ISBN   978-0-393-92522-7. OCLC   909815898.{{cite book}}: CS1 maint: location missing publisher (link)
  7. ↑ Urban Socio-Economic Segregation and Income Inequality: A Global Perspective. The Urban Book Series. 2021. doi:10.1007/978-3-030-64569-4. ISBN   978-3-030-64568-7. S2CID   234879684.
  8. 1 2 Logan, John R.; Foster, Andrew; Xu, Hongwei; Zhang, Wenquan (1 October 2020). "Income Segregation: Up or Down, and for Whom?". Demography. 57 (5): 1951–1974. doi: 10.1007/s13524-020-00917-0 . ISSN   1533-7790. PMC   7606787 . PMID   32935300.
  9. 1 2 Reardon, Sean F. (September 2011). "Measures of Income Segregation" (PDF). Stanford University.
  10. 1 2 3 4 Seckan, Bakary (30 October 2012). "The rise of residential segregation by income in the United States". The Journalist's Resource. Retrieved 25 April 2023.
  11. ↑ Bischoff, Kendra (16 October 2013). Residential Segregation by Income, 1970-2009 (PDF) (Report).
  12. ↑ Taylor, Paul (1 August 2012). "The Rise of Residential Segregation by Income". PewResearchCenter.
  13. ↑ Kelejian, H. H.; Robinson, D. P. Robinson (1992). "Spatial Autocorrelation: A New Computationally SimpleTest with an Application to Per Capita County Police Expenditures". Regional Science and Urban Economics. 22: 317–333. doi:10.1016/0166-0462(92)90032-V.
  14. 1 2 3 Dawkins, Casey J. (2007). "Space and the Measurement of Income Segregation". Journal of Regional Science. 47 (2): 255–272. Bibcode:2007JRegS..47..255D. doi:10.1111/j.1467-9787.2007.00508.x. S2CID   154562258.
  15. ↑ Working paper princeton.edu 2012 [ dead link ]
  16. ↑ A Gini measure of Economic Segregation University of Verona
  17. 1 2 Bureau, US Census. "Gini Index". Census.gov. Retrieved 27 April 2023.
  18. 1 2 "Income Segregation Maps - Stanford Center on Poverty and Inequality".
  19. 1 2 3 4 "Segregation Has Gotten Worse, Not Better, and It's Fueling the Wealth Gap Between Black and White Americans". Time. 19 June 2020. Retrieved 27 April 2023.
  20. 1 2 3 4 5 Sousa Filho, J. Firmino de; Silva, Uriel M.; Lima, Larissa L.; Paiva, Aureliano S. S.; Santos, Gervásio F.; Andrade, Roberto F. S.; Gouveia, Nelson; Silveira, Ismael H.; de Lima Friche, Amélia A.; Barreto, Maurício L.; Caiaffa, Waleska Teixeira (2022). "Association of urban inequality and income segregation with COVID-19 mortality in Brazil". PLOS ONE. 17 (11): e0277441. Bibcode:2022PLoSO..1777441S. doi: 10.1371/journal.pone.0277441 . ISSN   1932-6203. PMC   9665357 . PMID   36378655.
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  23. ↑ Krammer, Sorin M. S.; Lashitew, Addisu A.; Doh, Jonathan P.; Bapuji, Hari (1 March 2023). "Income inequality, social cohesion, and crime against businesses: Evidence from a global sample of firms". Journal of International Business Studies. 54 (2): 385–400. doi:10.1057/s41267-022-00535-5. ISSN   1478-6990. PMC   9187503 . PMID   35729969.
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