As of 2023, the Republic of Chad was the most culturally diverse country in Africa and worldwide. The Central African country achieved a score of **** in the cultural diversity index, followed by Cameroon and Nigeria which attained scores of **** and ****, respectively. The two countries also ranked worldwide as the second and third most culturally diverse countries. According to the index, a score of one indicates the most diverse country, while a score of zero represents the least diverse country.

Ethnic diversity is generally associated with less social capital and lower levels of trust. However, most empirical evidence for this relationship is focused on generalized trust, rather than more theoretically appropriate measures of group-based trust. This paper evaluates the relationship between ethnic diversity – at national, regional, and local levels – and the degree to which coethnics are trusted more than non-coethnics, a value I call the “coethnic trust premium.” Using public opinion data from sixteen African countries, I find that citizens of ethnically diverse states express, on average, more ethnocentric trust. However, within countries, regional ethnic diversity is actually associated with less ethnocentric trust. This same negative pattern between diversity and ethnocentric trust appears across districts and enumeration areas within Malawi. I then show, consistent with these patterns, that diversity is only detrimental to intergroup trust at the national level in the presence of ethnic group segregation. These results highlight the importance of the spatial distribution of ethnic groups on intergroup relations, and question the utility of micro-level studies of interethnic interactions for understanding macro-level group dynamics.

According to the 2021 Census, London was the most ethnically diverse region in England and Wales – 63.2% of residents identified with an ethnic minority group.

This record contains the underlying research data for the publication "People in more racially diverse neighborhoods are more prosocial" and the full-text is available from: https://ink.library.smu.edu.sg/lkcsb_research/5359Five studies tested the hypothesis that people living in more diverse neighborhoods would have more inclusive identities, and would thus be more prosocial. Study 1 found that people residing in more racially diverse metropolitan areas were more likely to tweet prosocial concepts in their everyday lives. Study 2 found that following the 2013 Boston Marathon bombings, people in more racially diverse neighborhoods were more likely to spontaneously offer help to individuals stranded by the bombings. Study 3 found that people living in more ethnically diverse countries were more likely to report having helped a stranger in the past month. Providing evidence of the underlying mechanism, Study 4 found that people living in more racially diverse neighborhoods were more likely to identify with all of humanity, which explained their greater likelihood of having helped a stranger in the past month. Finally, providing causal evidence for the relationship between neighborhood diversity and prosociality, Study 5 found that people asked to imagine that they were living in a more racially diverse neighborhood were more willing to help others in need, and this effect was mediated by a broader identity. The studies identify a novel mechanism through which exposure to diversity can influence people, and document a novel consequence of this mechanism.

The Historical Index of Ethnic Fractionalization (HIEF) dataset contains an ethnic fractionalization index for 165 countries across all continents. The dataset covers annually the period 1945-2013. The ethnic fractionalization index corresponds to the probability that two randomly drawn individuals within a country are not from the same ethnic group. The new dataset is a natural extension of previous ethnic fractionalization indices and it allows its users to compare developments in ethnic fractionalization over time. The applications of HIEF pertain to the pattern of ethnic diversity across countries and over time.

Citizens of countries with greater ethnic diversity or histories of legalized racial and ethnic discrimination such as the United States and South Africa are more likely to respond that ethnic discrimination is a significant problem in their societies. Meanwhile, those in less ethnically diverse nations such as Japan and South Korea are more likely to respond that ethnic discrimination is not a significant problem in their societies.

Ethnic Diversity and Preferences for Redistribution attempts to explain if individual's preferences for redistribution change if the ethnic diversity increases in a municipality. In this case, selected parts of the Swedish Election Studies has been matched with municipal data for the time period between 1985 and 1994, when Sweden had an active placement program of refugees. This meant that the refugees themselves were not allowed to decide where to settle, but instead they were places in municipalities which had contracts with the Swedish Integration Board (Invandrarverket). Originally the idea of the program was to direct the refugees to municipalities with good labor market conditions, but since the number of refugees arriving to Sweden were larger than expected, so in practice more or less all municipalities were a part of the program. With the placement program refugees spread more across the country, than before the program. Ethnic Diversity and Preferences for Redistribution focus primarily on refugees from nations which not were members in the OECD 1994 and Turkey.

The data comes from the Swedish Election Studies survey waves for the elections in 1982, 1985, 1988, 1991 and 1994. Primarily it consists of various background variables and variables about individual's preferences for private health care, nuclear power and social benefits. The municipal data primarily consist of various socio-economic and political variables, such as population, tax base, welfare spending and share of refugees. Some of these variables are the average of the term (1986-1988, 1989-1991, and 1992-1994).

Purpose:

Investigate the causal link between the ethnic diversity in a society and its inhabitants´ preferences for redistribution.

The COVID-19 pandemic, which began in China in late 2019, and subsequently spread across the world during the first several months of 2020, has had a dramatic impact on all facets of life. At the same time, it has not manifested in the same way in every nation. Some countries experienced a large initial spike in cases and deaths, followed by a rapid decline, whereas others had relatively low rates of both outcomes throughout the first half of 2020. The United States experienced a unique pattern of the virus, with a large initial spike, followed by a moderate decline in cases, followed by second and then third spikes. In addition, research has shown that in the United States the severity of the pandemic has been associated with poverty and access to health care services. This study was designed to examine whether the course of the pandemic has been uniform across America, and if not how it differed, particularly with respect to poverty. Results of a random intercept multilevel mixture model revealed that the pandemic followed four distinct paths in the country. The least ethnically diverse (85.1% white population) and most rural (82.8% rural residents) counties had the lowest death rates (0.06/1000) and the weakest link between deaths due to COVID-19 and poverty (b = 0.03). In contrast, counties with the highest proportion of urban residents (100%), greatest ethnic diversity (48.2% nonwhite), and highest population density (751.4 people per square mile) had the highest COVID-19 death rates (0.33/1000), and strongest relationship between the COVID-19 death rate and poverty (b = 46.21). Given these findings, American policy makers need to consider developing responses to future pandemics that account for local characteristics. These responses must take special account of pandemic responses among people of color, who suffered the highest death rates in the nation.

This paper examines such counter-territorialization strategies among ethnic minorities of the Lao People’s Democratic Republic. With a single-party regime that is often qualified as“authoritarian” (e.g.Jönsson, 2002; Stuart-Fox, 2005), Laos is also one the most ethnically diverse countries of Southeast Asia

This graph shows the population of the U.S. by race and ethnic group from 2000 to 2023. In 2023, there were around 21.39 million people of Asian origin living in the United States. A ranking of the most spoken languages across the world can be accessed here. U.S. populationCurrently, the white population makes up the vast majority of the United States’ population, accounting for some 252.07 million people in 2023. This ethnicity group contributes to the highest share of the population in every region, but is especially noticeable in the Midwestern region. The Black or African American resident population totaled 45.76 million people in the same year. The overall population in the United States is expected to increase annually from 2022, with the 320.92 million people in 2015 expected to rise to 341.69 million people by 2027. Thus, population densities have also increased, totaling 36.3 inhabitants per square kilometer as of 2021. Despite being one of the most populous countries in the world, following China and India, the United States is not even among the top 150 most densely populated countries due to its large land mass. Monaco is the most densely populated country in the world and has a population density of 24,621.5 inhabitants per square kilometer as of 2021. As population numbers in the U.S. continues to grow, the Hispanic population has also seen a similar trend from 35.7 million inhabitants in the country in 2000 to some 62.65 million inhabitants in 2021. This growing population group is a significant source of population growth in the country due to both high immigration and birth rates. The United States is one of the most racially diverse countries in the world.

The project generated several key findings, in line with the original project themes: 1) The project demonstrates that ethnic diversity alone does not appear to be a key driver of Brexit support, despite much of the public/political narrative in the area. Instead, we demonstrate that it is patterns of segregation which determine when diversity drove Brexit support. Thus, how increasing ethnic diversity of society appears to trigger tensions is in more segregated forms. Where diverse communities are integrated relations actually appear to improve. 2) The project uniquely demonstrates that residential segregation is a significant negative driver of mental health among ethnic minority groups in the UK. Mental health policy in the UK acknowledges that ethnic minorities often suffer worse mental health than their majority group counterparts. This work demonstrates that community characteristics need to be considered in mental health policy; in particular, how patterns of residential segregation are a key determinant of minority group mental health. 3) We demonstrate that, as expected, the ethnic mix of a community is a strong predictor of patterns of interethnic harassment. However, we also demonstrate that, even controlling for this, how residentially segregated an area is a stronger and consistent predictor of greater harassment. This will help societies better identify potential drivers of harassment and areas where focus should be on minimising hate crime. 4) The project demonstrates the key role sites of youth engagement can play in building positive intergroup relations among young people. In particular, their efficacy for overcoming key obstacles to integration such as residential segregation.

The project has generated several other impacts related to the project themes of social capital/social cohesion and mental health, as relates to the Covid-19 pandemic: 1) The paper explores the potential impact of the Covid-19 pandemic on people’s perceptions of cohesion in their local communities; particularly for vulnerable groups/communities, such as ethnic minorities or those living in highly deprived neighbourhoods. To this end, we examine both trends over time in overall levels of cohesion as well as patterns of positive and negative changes experienced by individuals using nationally representative data from Understanding Society Study. We test whether rates of positive-/negative-change in cohesion over the pandemic-period differed across socio-demographic groups and neighbourhood characteristics. These trends are then compared to patterns of positive-/negative-change over time experienced in earlier periods to test whether the pandemic was uniquely harmful. We show that the overall levels of social cohesion are lower in June 2020 compared to all of the examined pre-pandemic periods. The decline of perceived-cohesion is particularly high in the most deprived communities, among certain ethnic minority groups and among the lower-skilled. Our findings suggest that the pandemic put higher strain on social-resources among vulnerable groups and communities, who also experienced more negative changes in other areas of life. 2) The study examines the impact of coronavirus-related restrictions on mental health among American adults, and how this relationship varies as a function of time and two measures of vulnerability (preexisting physical symptoms and job insecurity). We draw on data from two waves of Corona Impact Survey, which were fielded in late April and early of May 2020. Multilevel models were used to analyze the hierarchically nested data. Experiencing coronavirus disease-2019 restrictions significantly raise mental distress. This association is stronger for individuals with preexisting health conditions and those who worry about job prospects. These findings hold with the inclusion of region-wave covariates (number of deaths, wave dummy and aggregate measure of restrictions). Finally, there is a cross-level interaction: the restriction-distress connection is more pronounced in the second wave of data. Our research indicates that people who are more physically and/or financially vulnerable suffer more from the imposed restrictions, i.e. ‘social isolation’. The mental health impact of coronavirus pandemic is not constant but conditional on the level of vulnerability.

Rising ethnic diversity across countries is becoming a highly-charged issue. This is leading to intense academic, policy, and public debate, amid concerns that diversity may pose a threat to social cohesion. Within these debates, residential communities are increasingly seen as key sites across which both fractures may emerge, but also where opportunities for building cohesion exist. In light of this, research showing diverse communities weaken cohesion is worrying. Yet, there is a potentially key omission from this work: the role of residential segregation. While studies largely focus on the size of ethnic groups in an area they rarely explore whether the level of segregation in the area matters; that is, how (un)evenly ethnic groups are spread across it. This project aims to advance our understanding of the role segregation plays for cohesion alongside diversity; in particular, exploring what occurs at the intersection of the two: is it only in 'diverse and segregated' areas (where groups tend to live in separate neighbourhoods) in which cohesion is threatened? Can 'diverse and integrated' areas actually build more cohesion? We posit that how segregated a community is may form a 'missing link', helping to explain when diversity may build or undermine cohesion.

This project draws on an interdisciplinary framework (geography, demography, and developmental fields); marshals longitudinal panel/cohort data linked to multiple censuses; applies advanced statistical methods; and measures multiple inter-ethnic, intra-community and wider cohesion outcomes and mechanisms. Through this it will conduct the most complete investigation to date into how both diversity and segregation across communities affects cohesion, among majority and minority young people and adults, contemporaneously and across their lives. This will include:

*Performing some of the first robust 'causal' tests of how changes in community diversity and segregation affect cohesion over time, including asking: what happens to residents' cohesion when the levels of diversity and segregation in their communities change around them? Does moving into/out of communities with different levels of diversity and segregation affect peoples' cohesion?

*Producing crucial insights into processes of residential selection in the diversity-segregation-cohesion relationship, including: do levels of diversity and segregation affect beliefs and decisions to move into/out of certain communities? How far are such decisions driven by inter-ethnic attitudes? Or, are they driven instead by processes such as life cycle or disadvantage?

*Exploring the role of communities in young people's cohesion, asking: does community diversity and segregation affect youth cohesion? What role do familial attitudes, schools environments, and civic activities, play in youth cohesion, and can these domains help understand the pathways through which communities impact young people? And, do the levels of diversity and segregation in the communities we grow up in exert enduring impacts on cohesion over people's lives?

*Investigating how diversity and segregation across communities affect both minority and majority groups. For example: do minority-group residents respond in the same way as majority-group residents when they are more or less segregated from one another? How does the size of, and level of segregation from, other ethnic minority groups affect minority residents' cohesion? In particular, what occurs when newly-arrived immigrant-groups increasingly live among more established minority groups?

Through partnering with the Ministry of Housing, Communities and Local Government and building an advisory panel of experts and key youth and community stakeholders, this project will contribute to academic debates while engaging in high-impact knowledge exchange, generating a crucial evidence-base for practical policy solutions to directly feed into the government's developing integration strategy.

BackgroundMigrant and ethnic minority groups are often assumed to have poor health relative to the majority population. Few countries have the capacity to study a key indicator, mortality, by ethnicity and country of birth. We hypothesized at least 10% differences in mortality by ethnic group in Scotland that would not be wholly attenuated by adjustment for socio-economic factors or country of birth.Methods and findingsWe linked the Scottish 2001 Census to mortality data (2001–2013) in 4.62 million people (91% of estimated population), calculating age-adjusted mortality rate ratios (RRs; multiplied by 100 as percentages) with 95% confidence intervals (CIs) for 13 ethnic groups, with the White Scottish group as reference (ethnic group classification follows the Scottish 2001 Census). The Scottish Index of Multiple Deprivation, education status, and household tenure were socio-economic status (SES) confounding variables and born in the UK or Republic of Ireland (UK/RoI) an interacting and confounding variable. Smoking and diabetes data were from a primary care sub-sample (about 53,000 people). Males and females in most minority groups had lower age-adjusted mortality RRs than the White Scottish group. The 95% CIs provided good evidence that the RR was more than 10% lower in the following ethnic groups: Other White British (72.3 [95% CI 64.2, 81.3] in males and 75.2 [68.0, 83.2] in females); Other White (80.8 [72.8, 89.8] in males and 76.2 [68.6, 84.7] in females); Indian (62.6 [51.6, 76.0] in males and 60.7 [50.4, 73.1] in females); Pakistani (66.1 [57.4, 76.2] in males and 73.8 [63.7, 85.5] in females); Bangladeshi males (50.7 [32.5, 79.1]); Caribbean females (57.5 [38.5, 85.9]); and Chinese (52.2 [43.7, 62.5] in males and 65.8 [55.3, 78.2] in females). The differences were diminished but not eliminated after adjusting for UK/RoI birth and SES variables. A mortality advantage was evident in all 12 minority groups for those born abroad, but in only 6/12 male groups and 5/12 female groups of those born in the UK/RoI. In the primary care sub-sample, after adjustment for age, UK/RoI born, SES, smoking, and diabetes, the RR was not lower in Indian males (114.7 [95% CI 78.3, 167.9]) and Pakistani females (103.9 [73.9, 145.9]) than in White Scottish males and females, respectively. The main limitations were the inability to include deaths abroad and the small number of deaths in some ethnic minority groups, especially for people born in the UK/RoI.ConclusionsThere was relatively low mortality for many ethnic minority groups compared to the White Scottish majority. The mortality advantage was less clear in UK/RoI-born minority group offspring than in immigrants. These differences need explaining, and health-related behaviours seem important. Similar analyses are required internationally to fulfil agreed goals for monitoring, understanding, and improving health in ethnically diverse societies and to apply to health policy, especially on health inequalities and inequities.

Despite comprising of a smaller share of the U.S. population than African Americans or Hispanics, the most represented non-white U.S. CEOs were of an Asian background. They made up 55 percent of CEO positions at Fortune 500 and S&P 500 companies in 2024. By comparison, 11 percent of CEOs at the time were African American. The rise of environmental, social, and corporate governance (ESG) Investments in ESG have risen dramatically over last few years. In November 2023 there were approximately 480 billion U.S. dollars in ESG ETF assets worldwide, compared to 16 billion U.S. dollars in 2015. ESG measures were put in place to encourage companies to act responsibly, with the leading reason for ESG investing stated to be brand and reputation according to managers and asset owners. Gender diversity With the general acceptance of ESG in larger companies, there has still been a significant employment gap of women working in senior positions. For example, the share of women working as a partner or principal at EY, one of the largest accounting firms in the world, was just only 28 percent in 2023.

The value of multiculturalism and diversity has long been greatest merit for Georgia. The issues of migrations, its difficulties and objections pose formidable challenges country has to deal with for centuries. For many years already effective and coherent attitude towards this subject have helped greatly to establish divers and liberalistic society.

At the same time Georgia also is a country with a high rate of emigrants. Nowadays, because of country’s harsh economic condition, many people tend to leave Georgia to settle in more developed and economically advanced countries. Where they hope to lead easier live, get better education and healthcare and change the living condition for themselves and their families.

In the following article we will give a brief description of countries migration policy and history, as well as conditions and ways of human coexistence, that forms interesting, complex and multiple society. Notwithstanding the obstacles, that regularly attends this subject, Georgian government attempts to find right way out of the problem. The government and the citizens understand that further development and independence of the country necessarily requires the consideration of multi-ethnic values. Subsequently, Georgia is an ethnically diverse country, where people of different ethnicity and nationality live peacefully side by side, work together, trade, demonstrate their individual and unique historical and ethnic customs and traditions, try to preserve their cultural heritage and develop.

Long lasting practise shows how crucial the tolerance is for harmonious life of the society. To respect different religious beliefs and particular habits is a guarantee for developing civic consciousness and take the constructive step forward. Consequently, joining the European family to preserve human rights and became honourable member of that family is the main target for Georgian people.

Completion of a survey of dermatoglyphic variables for all ethnic groups in an ethnically diverse country like China is a huge research project, and an achievement that anthropological and dermatoglyphic scholars in the country could once only dream of. However, through the endeavors of scientists in China over the last 30 years, the dream has become reality. This paper reports the results of a comprehensive analysis of dermatoglyphics from all ethnic groups in China. Using cluster analysis and principal component analysis of dermatoglyphics, it has been found that Chinese populations can be generally divided into a southern group and a northern group. Furthermore, there has been considerable debate about the origins of many Chinese populations and about proper assignment of these peoples to larger ethnic groups. In this paper, we suggest that dermatoglyphic data can inform these debates by helping to classify a Chinese population as a northern or southern group, using selected reference populations and quantitative methods. This study is the first to assemble and investigate dermatoglyphics from all 56 Chinese ethnic groups. It is fortunate that data on population dermatoglyphics, a field of physical anthropology, have now been collected for all 56 Chinese ethnic groups, because intermarriage between individuals from different Chinese ethnic groups occurs more frequently in recent times, making population dermatoglyphic research an ever more challenging field of inquiry.

About this dataset

Context

The dataset presents the median household income across different racial categories in Hill Country Village. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Hill Country Village population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 77.50% of the total residents in Hill Country Village. Notably, the median household income for White households is $223,276. Interestingly, despite the White population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $270,229. This reveals that, while Whites may be the most numerous in Hill Country Village, Two or More Races households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/hill-country-village-tx-median-household-income-by-race.jpeg" alt="Hill Country Village median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Hill Country Village.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hill Country Village median household income by race. You can refer the same here

This paper will explore whether teachers’ multicultural ideology, soft skills (transversal capacities), national pride and identity, and intergroup contact, controlled by other variables, are related to their multicultural attitudes. This objective is developed and estimated from correlation analysis and using the method of ordinary least squares, to verify how multicultural ideology, national pride and identity, soft skills, and intergroup contact, controlled for some sociodemographic variables, generate effects on the multicultural attitudes of teaching in a Colombian higher education institution with high-quality accreditation. The findings revealed that soft skills and multicultural ideology positively influenced teachers’ multicultural attitudes, while intergroup contact with different ethnic groups showed a negative correlation. The analysis used primary data collected from 199 professors at the institution, which operates in a culturally diverse, multi-campus context within an emerging country characterized by very low national pride.

Ethnic-racial classification criteria are widely recognized to vary according to historical, cultural and political contexts. In Brazil, the strong influence of individual socio-economic factors on race/colour self-classification is well known. With the expansion of genomic technologies, the use of genomic ancestry has been suggested as a substitute for classification procedures such as self-declaring race, as if they represented the same concept. We investigated the association between genomic ancestry, the racial composition of census tracts and individual socioeconomic factors and self-declared race/colour in a cohort of 15,105 Brazilians. Results show that the probability of self-declaring as black or brown increases according to the proportion of African ancestry and varies widely among cities. In Porto Alegre, where most of the population is white, with every 10% increase in the proportion of African ancestry, the odds of self-declaring as black increased 14 times (95%CI 6.08–32.81). In Salvador, where most of the population is black or brown, that increase was of 3.98 times (95%CI 2.96–5.35). The racial composition of the area of residence was also associated with the probability of self-declaring as black or brown. Every 10% increase in the proportion of black and brown inhabitants in the residential census tract increased the odds of self-declaring as black by 1.33 times (95%CI 1.24–1.42). Ancestry alone does not explain self-declared race/colour. An emphasis on multiple situational contexts (both individual and collective) provides a more comprehensive framework for the study of the predictors of self-declared race/colour, a highly relevant construct in many different scenarios, such as public policy, sociology and medicine.

About this dataset

Context

The dataset presents the median household income across different racial categories in Town And Country. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Town And Country population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 82.80% of the total residents in Town And Country. Notably, the median household income for White households is $207,167. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $270,229. This reveals that, while Whites may be the most numerous in Town And Country, Asian households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/town-and-country-mo-median-household-income-by-race.jpeg" alt="Town And Country median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Town And Country.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Town And Country median household income by race. You can refer the same here

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics