In 2023, 17.9 percent of Black people living in the United States were living below the poverty line, compared to 7.7 percent of white people. That year, the total poverty rate in the U.S. across all races and ethnicities was 11.1 percent. Poverty in the United States Single people in the United States making less than 12,880 U.S. dollars a year and families of four making less than 26,500 U.S. dollars a year are considered to be below the poverty line. Women and children are more likely to suffer from poverty, due to women staying home more often than men to take care of children, and women suffering from the gender wage gap. Not only are women and children more likely to be affected, racial minorities are as well due to the discrimination they face. Poverty data Despite being one of the wealthiest nations in the world, the United States had the third highest poverty rate out of all OECD countries in 2019. However, the United States' poverty rate has been fluctuating since 1990, but has been decreasing since 2014. The average median household income in the U.S. has remained somewhat consistent since 1990, but has recently increased since 2014 until a slight decrease in 2020, potentially due to the pandemic. The state that had the highest number of people living below the poverty line in 2020 was California.

In 2022, with more than 303,000 people, the ethnic Malay was the largest group of public assistance recipients from the Department of Social Welfare in Malaysia. The second-largest group was the Chinese Malaysian with more than 82,000 recipients of financial assistance in the same year.

Graph and download economic data for Income Before Taxes: Public Assistance, Supplemental Security Income, SNAP by Race: Black or African American (CXUWELFARELB0905M) from 1984 to 2023 about supplements, assistance, social assistance, public, SNAP, food stamps, African-American, tax, food, income, and USA.

Louisiana Poverty Rate Statistics for 2023. Analyze over 60 metrics of the Louisiana poverty database including by age, education, race, gender, work experience and more. In Louisiana, an estimated 829,565 of 4,467,616 people live in poverty, which is 18.6%. Compared to the national average of 12.6%, the poverty rate in Louisiana is 47.62% higher.

The purpose of this study was to provide an appropriate theoretical and empirical approach to concepts, measures, and methods in the study of black Americans. The questionnaire was developed over two years with input from social scientists, students, and a national advisory panel of black scholars. The final instrument is comprehensive, encompassing several broad areas related to black American life. The study explores neighborhood-community integration, services, crime and community contact, the role of religion and the church, physical and mental health, and self-esteem. It examines employment, the effects of chronic unemployment, the effects of race on the job, and interaction with family and friends. The survey includes questions about racial attitudes, race identity, group stereotypes, and race ideology. Demographic variables include education, income, occupation, and political behavior and affiliation. The sample includes 2,107 black United States citizens, 18 years of age or older. A national multistage probability sample was selected. Therefore, the sample is self-weighting and every black American household in the continental United States had an equal probability of being selected. The Murray Research Archive has available numeric file data from the study. A subset of numeric file data comprised of 500 respondents and 152 variables created specifically for use in research methodology and statistics courses is also available. Additional waves of data for this study have been collected and are available through ICPSR.

In 2022, the public assistance given to the ethnic Malay by the Malaysian Department of Social Welfare amounted to around 163 million Malaysian ringgit. The second-largest amount went to the indigenous ethnic group in Sabah, East Malaysia, with more than 53 million Malaysian ringgit in public assistance.

This dataset includes the ethnicity of applicants for Insurance Affordability Programs (IAPs) who identified their ethnicity as Hispanic with the ethnic origin as Guatemalan, Mexican/Mexican American/Chicano, Other, Puerto Rican, Salvadoran, Mixed, or Cuban, Hispanic with ethnic origin not reported, not Hispanic, or ethnicity not reported by reporting period. The ethnicity data is from the California Healthcare Eligibility, Enrollment and Retention System (CalHEERS) and includes data from applications submitted directly to CalHEERS, to Covered California, and to County Human Services Agencies through the Statewide Automated Welfare System (SAWS) eHIT interface. This dataset is part of public reporting requirements set forth by the California Welfare and Institutions Code 14102.5.

Florida Poverty Rate Statistics for 2023. Analyze over 60 metrics of the Florida poverty database including by age, education, race, gender, work experience and more. In Florida, an estimated 2,762,679 of 21,764,366 people live in poverty, which is 12.7%. Compared to the national average of 12.6%, the poverty rate in Florida is 0.79% higher.

Texas Poverty Rate Statistics for 2023. Analyze over 60 metrics of the Texas poverty database including by age, education, race, gender, work experience and more. In Texas, an estimated 4,113,641 of 29,416,679 people live in poverty, which is 14.0%. Compared to the national average of 12.6%, the poverty rate in Texas is 11.11% higher.

This statistic shows the share families that have received income-related benefits in the United Kingdom (UK) in the period from 2015 to 2018, by ethnic group of household head. In this period, 29 percent of the families with head of the family being black/African black/Caribbean or British black received some form of income-related benefit.

New Mexico Poverty Rate Statistics for 2023. Analyze over 60 metrics of the New Mexico poverty database including by age, education, race, gender, work experience and more. In New Mexico, an estimated 364,725 of 2,072,033 people live in poverty, which is 17.6%. Compared to the national average of 12.6%, the poverty rate in New Mexico is 39.68% higher.

R Replication Flies & Data

The Moving to Opportunity (MTO) program was a randomized housing experiment administered by the United States Department of Housing and Urban Development (HUD) that gave low-income families living in high-poverty areas the chance to move to lower-poverty areas. This Restricted Access Dataset (RAD) includes data from the 3,273 adults interviewed as part of the MTO long-term evaluation and is comprised of variables analyzed for the article "Neighborhood Effects on the Long-Term Well-Being of Low-Income Adults" that was published in the journal Science on September 21, 2012. The article focused on subjective well-being, physical and mental health, social networks, neighborhoods, housing, and economic self-sufficiency. Families were tracked from the baseline survey (1994-1998) through the long-term evaluation survey fielding period (2008-2010) with the purpose of determining the effects of "neighborhood" on participating families from five United States cities. Households were randomly assigned to one of three groups: The low-poverty voucher (LPV) group (also called the experimental group) received Section 8 rental assistance certificates or vouchers that they could use only in census tracts with 1990 poverty rates below 10 percent. The families received mobility counseling and help in leasing a new unit. One year after relocating, families could use their voucher to move again if they wished, without any special constraints on location.The traditional voucher (TRV) group (also called the Section 8 group) received regular Section 8 certificates or vouchers that they could use anywhere; these families received no special mobility counseling.The control group received no certificates or vouchers through MTO, but continued to be eligible for project-based housing assistance and other social programs and services to which they would otherwise be entitled.The dataset contains all outcomes and mediators analyzed for the Science article, as well as a variety of demographic and other baseline measures that were controlled for in the analysis. Demographic information includes age, gender, race/ethnicity, employment status, and education level.

An emerging body of research has robustly found a link between immigration and preferences for redistribution. In particular, immigration has been proved to undermine native support for the welfare state (Alesina et al., 2022; Dahlberg et al., 2012; Eger, 2010; Ford, 2006; Stichnoth, 2012). This link can be interpreted within a rational resource-competition framework (since increasing the number of potential net recipients has welfare consequences). Yet different social identity theories (Hornsey, 2008; Tajfel & Turner, 1986; Turner et al., 1987) have also been invoked to stress that natives’ attitudes towards redistribution and the welfare state are grounded on ethnic/national identity as well as on related conceptions of cultural distance (Brandt et al. 2014; Chambers et al. 2013). Perceptions of cultural distance, in turn, make the overall effect of immigration on attitudes towards redistribution dependent on the characteristics of the immigrant pool —because some immigrant groups are perceived as more (or less) disserving than others (Verkuyten et al. 1996). In the European context, immigrants’ coming from Middle East and North African countries of majoritarian Muslim faith (MENAM) and their European-born descendants are known to be particularly at risk of discrimination and prejudice ( Strabac & Listhaug 2008; Strabac et al. 2014; Di Stasio et al. 2021; Polavieja et al. 2023). An important gap in the literature on redistribution and welfare nativism, however, concerns the potential role of immigrant characteristics other than cultural-religious or socioeconomic background, specifically, the role of phenotype (i.e. color or racial appearance). The importance of racial appearance as an additional source of prejudice and discrimination has been long neglected in the European context and, to our knowledge, to date no study on the impact of immigration on attitudes towards redistribution has tested whether immigrants’ physical (“racial”) appearance can influence European natives’ attitudes toward welfare deservedness. Recent field experimental research on racial discrimination in hiring has brought the question of racial discrimination to the fore by showing European employers are less likely to hire immigrant descendants with non-white phenotypes and, hence, that having “visible” phenotypes constitutes a serious barrier for the socio-economic integration of the second-generation in Europe (Polavieja et al. 2023). Building on this research, we propose an experiment to address the distinctive role of ethnicity (treatment 1) and phenotype (treatment 2) on native’s attitudes regarding welfare deservedness chauvinism (research question 1). Additionally, we test for two mediating mechanisms, welfare competition (research question 2) and disgust sensitivity (research question 3), which allows us to also contribute to the expanding literature on the neurocognitive basis of prejudice and the role of visceral emotions. To this end we draw on recent developments in cognitive psychology, political psychology and behavioral science. Our main research questions can thus be summarized as follows: Research Question 1: What is the distinctive role of immigrant-descendants’ ethnicity and phenotype as potentially different drivers of welfare chauvinism? Research Question 2: To what extent (rational) concerns about competition might help us explain welfare chauvinist responses amongst natives? Research Question 3: To what extent (irrational) disgust sensitivity can help us explain welfare chauvinism and, in particular, chauvinist responses triggered by phenotypic racism?

Poverty and low-income statistics by visible minority group, Indigenous group and immigration status, Canada and provinces.

This statistic shows the share of United States citizens by their opinion on the welfare of animals in zoos in 2016, by ethnicity. During the survey, 24 percent of Hispanic respondents stated that they think most zoo animals are treated very well.

Corpus Christi, Texas Poverty Rate Statistics for 2023. Analyze over 60 metrics of the Corpus Christi, Texas poverty database including by age, education, race, gender, work experience and more. In Corpus Christi, Texas, an estimated 53,623 of 310,235 people live in poverty, which is 17.3%. Compared to the national average of 12.6%, the poverty rate in Corpus Christi is 37.3% higher.

This dataset includes race/ethnicity of newly Medi-Cal eligible individuals who identified their race/ethnicity as Hispanic, White, Other Asian or Pacific Islander, Black, Chinese, Filipino, Vietnamese, Asian Indian, Korean, Alaskan Native or American Indian, Japanese, Cambodian, Samoan, Laotian, Hawaiian, Guamanian, Amerasian, or Other, by reporting period. The race/ethnicity data is from the Medi-Cal Eligibility Data System (MEDS) and includes eligible individuals without prior Medi-Cal Eligibility. This dataset is part of the public reporting requirements set forth in California Welfare and Institutions Code 14102.5.

This project sought to investigate a possible relationship between sentencing guidelines and family structure in the United States. The research team developed three research modules that employed a variety of data sources and approaches to understand family destabilization and community distress, which cannot be observed directly. These three research modules were used to discover causal relationships between male withdrawal from productive spheres of the economy and resulting changes in the community and families. The research modules approached the issue of sentencing guidelines and family structure by studying: (1) the flow of inmates into prison (Module A), (2) the role of and issues related to sentencing reform (Module B), and family disruption in a single state (Module C). Module A utilized the Uniform Crime Reporting (UCR) Program data for 1984 and 1993 (Parts 1 and 2), the 1984 and 1993 National Correctional Reporting Program (NCRP) data (Parts 3-6), the Urban Institute's 1980 and 1990 Underclass Database (UDB) (Part 7), the 1985 and 1994 National Longitudinal Survey on Youth (NLSY) (Parts 8 and 9), and county population, social, and economic data from the Current Population Survey, County Business Patterns, and United States Vital Statistics (Parts 10-12). The focus of this module was the relationship between family instability, as measured by female-headed families, and three societal characteristics, namely underclass measures in county of residence, individual characteristics, and flows of inmates. Module B examined the effects of statewide incarceration and sentencing changes on marriage markets and family structure. Module B utilized data from the Current Population Survey for 1985 and 1994 (Part 12) and the United States Statistical Abstracts (Part 13), as well as state-level data (Parts 14 and 15) to measure the Darity-Myers sex ratio and expected welfare income. The relationship between these two factors and family structure, sentencing guidelines, and minimum sentences for drug-related crimes was then measured. Module C used data collected from inmates entering the Minnesota prison system in 1997 and 1998 (Part 16), information from the 1990 Census (Part 17), and the Minnesota Crime Survey (Part 18) to assess any connections between incarceration and family structure. Module C focused on a single state with sentencing guidelines with the goal of understanding how sentencing reforms and the impacts of the local community factors affect inmate family structure. The researchers wanted to know if the aspects of locations that lose marriageable males to prison were more important than individual inmate characteristics with respect to the probability that someone will be imprisoned and leave behind dependent children. Variables in Parts 1 and 2 document arrests by race for arson, assault, auto theft, burglary, drugs, homicide, larceny, manslaughter, rape, robbery, sexual assault, and weapons. Variables in Parts 3 and 4 document prison admissions, while variables in Parts 5 and 6 document prison releases. Variables in Part 7 include the number of households on public assistance, education and income levels of residents by race, labor force participation by race, unemployment by race, percentage of population of different races, poverty rate by race, men in the military by race, and marriage pool by race. Variables in Parts 8 and 9 include age, county, education, employment status, family income, marital status, race, residence type, sex, and state. Part 10 provides county population data. Part 11 contains two different state identifiers. Variables in Part 12 describe mortality data and welfare data. Part 13 contains data from the United States Statistical Abstracts, including welfare and poverty variables. Variables in Parts 14 and 15 include number of children, age, education, family type, gender, head of household, marital status, race, religion, and state. Variables in Part 16 cover admission date, admission type, age, county, education, language, length of sentence, marital status, military status, sentence, sex, state, and ZIP code. Part 17 contains demographic data by Minnesota ZIP code, such as age categories, race, divorces, number of children, home ownership, and unemployment. Part 18 includes Minnesota crime data as well as some demographic variables, such as race, education, and poverty ratio.

Harris County, Texas Poverty Rate Statistics for 2023. Analyze over 60 metrics of the Harris County, Texas poverty database including by age, education, race, gender, work experience and more. 16.5% Poverty Rate in Harris County, Texas