Chiapas was the state in Mexico with the highest average extreme poverty rate in 2022. It was estimated that almost three out of ten people in Chiapas lived in a situation of extreme poverty. In contrast, Baja California was the state with the lowest extreme poverty rate, with 0.8 percent, well below the national average, which stood at 7.1 percent. The share of population living in poverty in Mexico amounted to 36.3 percent in 2022.

In 2021, Philadelphia, Pennsylvania was the city with the highest poverty rate of the United States' most populated cities. In this statistic, the cities are sorted by poverty rate, not population. The most populated city in 2021 according to the source was New York city - which had a poverty rate of 18 percent.

In 2023, the poverty rate of the United States was around 11.4 percent. Louisiana was the state with the highest poverty rate, at 18.9 percent. Poverty rates in the United States are higher than in many parts of the world, and minority groups are much more likely to be living in poverty when compared to white people.

Graph and download economic data for Estimated Percent of People of All Ages in Poverty for United States (PPAAUS00000A156NCEN) from 1989 to 2023 about percent, child, poverty, and USA.

Out of all 50 states, New York had the highest per-capita real gross domestic product (GDP) in 2023, at 90,730 U.S. dollars, followed closely by Massachusetts. Mississippi had the lowest per-capita real GDP, at 39,102 U.S. dollars. While not a state, the District of Columbia had a per capita GDP of more than 214,000 U.S. dollars. What is real GDP? A country’s real GDP is a measure that shows the value of the goods and services produced by an economy and is adjusted for inflation. The real GDP of a country helps economists to see the health of a country’s economy and its standard of living. Downturns in GDP growth can indicate financial difficulties, such as the financial crisis of 2008 and 2009, when the U.S. GDP decreased by 2.5 percent. The COVID-19 pandemic had a significant impact on U.S. GDP, shrinking the economy 2.8 percent. The U.S. economy rebounded in 2021, however, growing by nearly six percent. Why real GDP per capita matters Real GDP per capita takes the GDP of a country, state, or metropolitan area and divides it by the number of people in that area. Some argue that per-capita GDP is more important than the GDP of a country, as it is a good indicator of whether or not the country’s population is getting wealthier, thus increasing the standard of living in that area. The best measure of standard of living when comparing across countries is thought to be GDP per capita at purchasing power parity (PPP) which uses the prices of specific goods to compare the absolute purchasing power of a countries currency.

The McAllen-Edinburg-Mission metropolitan area in Texas was ranked first with 27.2 percent of its population living below the poverty level in 2023. Eagle Pass, Texas had the second-highest poverty rate, at 24.4 percent.

Two out of every three persons in Chiapas lived under the poverty line in 2022, making it the federal entity with the largest share of poor population in Mexico. On average, about 36 percent of the Mexican population was living in poverty that year.

Abstract

Poverty reduction via formation of community based organizations is a popular approach in regions of high socio-economic marginalization, especially in South Asia. The shortage of evidence on the impacts of such an approach is an outcome of the complexity of these projects, which almost always have a multi-sectoral design to achieve a comprehensive basket of aims. In the current research, we consider results from a rural livelihoods program in Bihar, one of India’s poorest states. Adopting a model prevalent in several Indian states, the Bihar Rural Livelihoods Project, known locally as JEEViKA, relies on mobilizing women from impoverished, socially marginalized households into Self Help Groups. Simultaneously, activities such as micro-finance and technical assistance for agricultural livelihoods are taken up by the project and routed to the beneficiaries via these institutions; these institutions also serve as a platform for women to come together and discuss a multitude of the socio-economic problems that they face. We use a retrospective survey instrument, coupled with PSM techniques to find that JEEViKA, has engendered some significant results in restructuring the debt portfolio of these households; additionally, JEEViKA has been instrumental in providing women with higher levels of empowerment, as measured by various dimensions.

In the current research, we consider a multi-sectoral approach which closely resembles the APDPIP design. We take a close look at the impacts of a rural poverty reduction program in Bihar, one of India’s poorest states. This program JEEViKA, focusses on building Self Help Groups (SHGs) of marginalized women; these groups are then federated into higher order institutions of such women at the village and local level. Cheap credit for a variety of purposes, technical assistance for various livelihood activities and encouraging awareness about various public services are the key agendas of this program. However, due to the very nature of JEEViKA’s target population, and given Bihar’s vicious income and gender inequality, the potential for impacts on women’s empowerment exists. A retrospective survey instrument, coupled with ‘Propensity Score Matching’ methods are used to estimate the impacts.

The results from the survey point out that JEEViKA has played an instrumental role in restructuring the debt portfolio of beneficiary households; households that have SHG members have a significantly lower high cost debt burden, are able to access smaller loans repeatedly and borrow more often for productive purposes, when compared to households without SHG members. Since JEEViKA works by mobilizing marginalized women into institutional platforms, such women demonstrate higher levels of empowerment, when empowerment is measured by mobility, decision making and collective action. Finally, we see some effects on the asset positions, food security and sanitation preferences of beneficiary households. It is worth pointing out here that the extent and significance of the results on debt portfolio and empowerment are robust to various matching modules and various specifications of the matched sample. The results on the other dimensions are subject to specifications or matching modules.

This brings out to the point about the timeline of these interventions and the materialization of impacts. In the context of such iterative, multi-sectoral poverty reduction approach, a well_x0002_designed research question must be able to identify the goals that a project should have achieved, given the time-line of that evaluation; the extent of such achievements are only a part of the evaluation agenda. The short review provided above provides some clues that a regular evaluation horizon of 2/3 years may be insufficient time to observe higher order effects, especially since actual benefits happen only after poor are mobilized into institutions and institutions are federated into higher-order institutions; indeed, the village-level institution, the Village Organization, which is made of 15 SHGs on an average, becomes functional 8-10 months after JEEViKA enters a village for the first time. The retrospective nature of the survey instrument also rules out any meaningful comparison of consumption or income levels between treatment and control areas.

Analysis unit

Household

Sampling procedure

The survey was administered to 10 randomly selected households from the target hamlets in all 200 project and 200 non-project villages; we can assume that had caste compositions changed significantly since 2001 in either the selected project or non-project villages, this should be reflected in the sample statistics. It is to be noted that the survey team did not have a beneficiary list for the treatment villages; thus the selection of interviewed HHs were truly random, and not a sample of beneficiary HHs only. The details on the questionnaire and selection of villages to survey are discussed at greater lengths in the Section 3 of the survey report - Data & Identification Strategy. The report is available for download under the Downloads section.

Mode of data collection

Face-to-face [f2f]

Research instrument

An identical survey instrument covering several broad areas on socio-economic indicators was administered to each of the 4000 households. The instrument had two broad modules; the general module was administered to a responsible adult (preferably HH head), and the women’s module was administered to an ever married adult woman. The general module collected economic information focused on asset ownership, debt portfolio, land holdings, savings habit and food security condition; social indicators attempting to capture changes in women’s empowerment focused on women’s mobility, decision making and networks were part of the women’s module. The demographic profile of each household was captured by an appropriate household roster and caste-religion profile; in addition, a livelihood roster was also administered. Given the retrospective nature of the study, questions on certain indicators were designed to capture the levels at end 2007, along with the current level. However for other indicators, like debt portfolio, questions for end 2007 levels were not asked since the chances for incorrect responses are considerable.

In 2021, the city of Philadelphia in Pennsylvania had the highest family poverty rate of the 25 most populated cities in the United States. The city with the next highest poverty rate was Houston, Texas.

Abstract

The objective of the survey was to produce baselines for 15 large urban centers in Kenya. The urban centers covered Nairobi, Mombasa, Naivasha, Nakuru, Malindi, Eldoret, Garissa, Embu, Kitui, Kericho, Thika, Kakamega, Kisumu, Machakos, and Nyeri. The survey covered the following issues: (a) household characteristics; (b) household economic profile; (c) housing, tenure, and rents; and (d) infrastructure services. The survey was undertaken to deepen understanding of the cities’ growth dynamics, and to identify specific challenges to quality of life for residents. The survey pays special attention to living conditions for residents of formal versus informal settlements, poor versus non-poor, and male and female headed households.

Analysis unit

Household Urban center

Kind of data

Sample survey data [ssd]

Sampling procedure

The Kenya State of the Cities Baseline Survey is aimed to produce reliable estimates of key indicators related to demographic profile, infrastructure access and economic profile for each of the 15 towns and cities based on representative samples, including representative samples of households (HHs) residing in slum and non-slum areas. For this baseline household survey, NORC used a two- or three-stage stratified cluster sampling design within each of the 15 urban centers. Our first-stage sampling frame was based on the 2009 census frame of enumeration areas. For each of the 15 towns and cities, NORC received the sampling frame of EAs from the Kenya National Bureau of Statistics (KNBS). In the first stage, NORC selected a sample of enumeration areas (PSUs). The second stage involved a random selection of households (SSUs) from each selected EA. In order to manage the field interviewing efficiently, we drew a fixed number of HHs from each selected EA, irrespective of EA size. The third stage arose in instances of very large EAs (EAs containing more than 200 households) in which EAs were divided into 2, 3 or 4 segments, from which one segment was selected randomly for household selection.

Stratification of Enumeration Areas: A few stratification factors were available for stratifying the EAs to help to achieve the survey objectives. As mentioned earlier, for this baseline survey we wanted to draw representative samples from slum and non-slum areas and also to include poor/non-poor households (HHs). For the 2009 census, depending on the location, KNBS divided the EAs into three categories: rural, urban, and peri-urban.

Although there is a clear distinction of EAs into slum and non-slum areas, it is hard to classify EAs into poor and non-poor categories. To guarantee enough representation of HHs living in slum and non-slum areas (also referred to as formal and informal areas) as well as HHs living below and above the poverty line, NORC stratified the first-stage sampling units (EAs) into strata, based on EA type (3 types) and settlement type (2 types). Given the resources available, we believe this stratification would serve our purpose as HHs living in slum and in rural areas tend to be poor. Table 1 in Appendix C of final Overview Report (provided under the Related Materials tab) presents the allocation of sampled EAs across the strata for each of the 15 cities in the baseline survey.

Sampling households is not as straightforward as the first-stage sampling of EAs, since the 2009 census frame of HHs does not exist. In the absence of a household sampling frame, NORC carried out a listing of HHs within each EA selected in the first stage. Trained listers, accompanied by local cluster guides (local residents with some form of authority in the EA), systematically listed all households in each selected EA, gathering the address, names of head of household and spouse, household description, latitude and longitude. To ensure completeness of listing data, avoid duplication and improve ease of locating households that were eventually selected for interview, listers enumerated households by chalking household identification number above the household doorway (an accepted practice for national surveys). The sampling frame of HHs produced from the listing activity was, therefore, up-to-date and included new formal and informal settlements that appeared after the 2009 census.

For adequate representativeness and to manage the interviewing task efficiently, NORC planned seven completed household interviews per EA. The final recommended sample size for the Kenya State of the Cities baseline survey is found in Table 2 in Appendix C of the final Overview Report.

Because the expected response rate was unknown prior to the start of the field period, the sampling team randomly selected ten households per enumeration area and distributed them to the interviewers working within the EA. Interviewing teams were instructed to complete at least seven interviews per EA from among the ten selected households. Interviewers were instructed to attempt at least three contacts with each selected household, approaching potential respondents on different days of the week and different times of day. Table 2 presents the final number of EAs listed per city and the final number of completed interviews per city. The table also presents the percent of planned EAs and interviews that were completed vs. planned. Please note that in several cities more interviews were completed than planned. As part of NORC's data quality plan, data collection teams were instructed to overshoot slightly the target of seven interviews per EA, if feasible, to mitigate any potential loss of cases due to poor quality or uncooperative respondents. Few cases were lost due to poor quality, therefore the target number of interviews remains over 100 percent in ten of the fifteen cities.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was developed by World Bank staff with input from stakeholders in the Kenya Municipal Program and NORC researchers and survey methodologists. The base questionnaire for the project was a 2004 World Bank survey of Nairobi slums. However, an extended iterative review process led to many changes in the questionnaire. The final version that was used for programming provided under the Related Materials tab, and in Volume II of the Overview.

The questionnaire’s topical coverage is indicated by the titles of its nine modules: 1. Demographics and household composition 2. Security of housing, land and tenure 3. Housing and settlement profile 4. Economic profile 5. Infrastructure services 6. Health 7. Household enterprises7 8. Civil participation and respondent tracking

Response rate

The completion rate is reported as the number of households that successfully completed an interview over the total number of households selected for the EA. These are shown by city in Table 5 in Appendix C of the final Overview Report, and have an average rate of 68.66 percent, with variation from 66 to 74 percent (aside from Nairobi at 61.47 percent and Machakos at 56 percent). As described earlier, ten households were selected per EA if the EA contained more than 10 households. For EAs where fewer than ten households were selected for interviews, all households were selected. In some EAs, more than ten households were selected due to a central office error.

United States CSI: Government Economic Policy: Poor Job data was reported at 31.000 % in May 2018. This records an increase from the previous number of 28.000 % for Apr 2018. United States CSI: Government Economic Policy: Poor Job data is updated monthly, averaging 29.000 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 57.000 % in Oct 2011 and a record low of 6.000 % in Feb 1999. United States CSI: Government Economic Policy: Poor Job data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The question was: As to the economic policy of the government -- I mean steps taken to fight inflation or unemployment -- would you say the government is going a good job, only fair, or a poor job?

The system of social indicators for the Federal Republic of Germany - developed in its original version as part of the SPES project under the direction of Wolfgang Zapf - provides quantitative information on levels, distributions and changes in quality of life, social progress and social change in Germany from 1950 to 2013, i.e. over a period of more than sixty years. With the approximately 400 objective and subjective indicators that the indicator system comprises in total, it claims to measure welfare and quality of life in Germany in a differentiated way across various areas of life and to observe them over time. In addition to the indicators for 13 areas of life, including income, education and health, a selection of cross-cutting global welfare measures were also included in the dashboard, i.e. general welfare indicators such as life satisfaction, social isolation or the Human Development Index. Based on available data from official statistics and survey data, time series were compiled for all indicators, ideally with annual values from 1950 to 2013. Around 90 of the indicators were marked as "key indicators" in order to highlight central dimensions of welfare and quality of life across the various areas of life. The further development and expansion, regular maintenance and updating as well as the provision of the data of the system of social indicators for the Federal Republic of Germany have been among the tasks of the Center for Social Indicator Research, which is based at GESIS, since 1987. For a detailed description of the system of social indicators for the Federal Republic of Germany, see the study description under "Other documents".
The data on the area of life ´Income and Income Distribution´ is composed as follows:

Level and growth: Net national income (net national product) per inhabitant in constant prices (in euros), growth of the net national product per inhabitant, ratio of household income in old/new federal states (SOEP). Inequality in the income dimension: concentration of net income (EVS), concentration of net income (SOEP), share of income of the poorest 20% of the population, share of income of the richest 10% of the population. Poverty in the income dimension: Poverty rate for relative poverty - overall/West/East specific 40% poverty threshold (EVS), poverty rate for relative poverty - overall/West/East specific 40% poverty threshold (SOEP), poverty rate for relative poverty - overall /West/East specific 50% poverty threshold (EVS), poverty rate for relative poverty - overall/West/East specific 60% poverty threshold (SOEP), poverty rate for relative poverty - overall/West/East specific 60% poverty threshold (EVS), Poverty Gap Ratio. Performance adequacy of income: multiple of factor income (EVS), multiple of labor income (EVS), multiple of labor income (SOEP). Assessment of income: satisfaction with household income (SOEP), concern about one´s own economic situation, importance of income. Poverty in the consumption dimension: poverty rate for consumption poverty - 50% line (EVS), poverty rate for consumption poverty - 60% line (EVS). Inequality in the consumption dimension: Concentration of consumer spending (EVS).

This survey represents the thoughts of the U.S. population concerning the income gap between the rich and the poor in 2012. In 2012, 65 percent of the respondents thought that the income gap between the rich and the poor in the United States has gotten larger in the past ten years. The number of ultra high net worth individuals in each region worldwide can be accessed here.

Abstract copyright UK Data Service and data collection copyright owner.

This inquiry into the views of the year 2000 held by the younger generation took place under the auspices of the European Coordination Centre for Research and Documentation in the Social Sciences, established at Vienna, which was founded by UNESCO and which is a division of the International Social Science Council at Paris. The technical coordination was in the hands of the International Peace Research Institute, Oslo, under the direction of Johan Galtung.
The objective of the inquiry was to examine attitudes of people in the age group 15 - 40 years towards various aspects of the future, with particular reference to war, peace and disarmament. The great attractiveness of such an inquiry lies in comparing the results of countries with very different political and philosophical backgrounds. Eleven countries are covered by this study.
Main Topics:
Attitudinal/Behavioural Questions
Respondent's future-consciousness is assessed in terms of his thinking about the future of the world and of his country, his perception of the year 2000 as the near or distant future, his talking, seeing, hearing and reading about the future. Respondent predictions: what he considers will be the main differences between life today and life in the year 2000 (particularly what he feels would be the best and worst things that could happen). Employing a 9-point scale (i.e. 'best' - 'worst' possible life) the respondent is requested to indicate where he would place himself: a) at the present time, b) five years ago, c) five years from now, d) in the year 2000. Using the same procedure he is asked to assess future trends of his country and of the world.
More specifically, the respondent is asked to predict social trends in his country covering topics such as: happiness and work satisfaction, leisure, unemployment, religion, kinship and marriage, material wealth, spiritual contentment, sexual freedom, mental illness, use of narcotics and drugs, crime, social differentiation, the role of women, the role of young people, city dwelling and manual work. It is recorded whether, in most cases, the respondent's hopes coincide with his predictions.
Respondent predictions of the possibilities of science in the year 2000 are ascertained. Namely, whether it will be possible: to predetermine the sex and major personality feature of one's child, to cure dangerous diseases (e.g. cancer), to predetermine the weather, to travel to other planets. The respondent is again asked to state whether his hopes coincide with his predictions.
War, armament and disarmament: respondent assessments of world trends in this area are recorded. In addition, he is asked to assess the probable effects of a third world war on his native country, and to state his opinion on how such a war is most likely to break out (i.e. by accident, by extension of a limited conflict or by one big power attacking another big power). Any value, goal or ideal the respondent believes could justify a war with nuclear weapons/without nuclear weapons is noted. A list of 25 ideas on how world peace might be obtained is included and respondents are asked to state whether they agree or disagree with each statement (e.g. 'to obtain peace, hunger and poverty must be abolished all over the world', 'to obtain peace, we must have general and complete disarmament as soon as possible', etc.). Information also includes whether the respondent thinks that peace can be realised by the year 2000 and whether he believes he can contribute anything himself to the realisation of this proposal; what he believes is most likely to happen in the relations between capitalist and socialist countries, between rich and poor countries and between different races. Finally, respondent's knowledge of the membership of NATO and the Warsaw Pact is tested.
Opinion is ascertained on a number of items tapping the personality of the respondent (e.g. dogmatism). Social satisfaction of the respondent is measured in regard to income, job, influence on public affairs, living in his country, whether the respondent believes he has control over his future and, if so, how he feels he should direct this future. He is also asked to comparatively evaluate certain activities and views of the younger and older generations.
Background Variables
Age, sex, marital status, education, occupational details, work satisfaction (ideal occupation is noted), personal monthly income quartile, satisfaction with income received, occupation of head of household (where different), total monthly income quartile of household, household composition, area of residence (i.e. density of population, geographical region - where available), whether respondent practises religion or considers himself to be a `believer', parental household composition, father's occupational details, whether mother worked outside the home, area of childhood residence...

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 the third quarter of 2024, the top ten percent of earners in the United States held over 67 percent of total wealth. This is fairly consistent with the second quarter of 2024. Comparatively, the wealth of the bottom 50 percent of earners has been slowly increasing since the start of the 2010s, though remains low. Wealth distribution in the United States by generation can be found here.

Maternal and early malnutrition have negative health and developmental impacts over the life-course. Consequently, early nutrition support can provide significant benefits into later life, provided the later life contexts allow. This study examines the limits of siloed investments in nutrition and illustrates how ignoring life-course contextual constraints limits human development benefits and exacerbates inequality, particularly in fragile contexts. This case study focuses on Burkina Faso, a country with high rates of early malnutrition and a fragile state. We modelled the impact of scaling up 10 nutrition interventions to 80% coverage for a single year cohort on stunting, nationally and sub-nationally, using the Lives Saved Tool (LiST), and the consequent impact on earnings, without and with a complementary cash-transfer in later life. The impact on earnings was modelled utilising the well-established pathway between early nutrition, years of completed schooling and, consequent adult earnings. Productivity returns were estimated as the present value of increased income over individuals’ working lives, then compared to estimates of the present value of providing the cost of nutrition interventions and cash-transfers. The cost benefit ratio at the national level for scaled nutrition alone is 1:1. Sub-nationally the worst-off region yields the lowest ratio < 0.2 for every dollar spent. The combination of nutrition and cash-transfers national cost benefit is 1:12, still with regional variation but with great improvement in the poorest region. This study shows that early nutrition support alone may not be enough to address inequality and may add to state fragility. Taking a life-course perspective when priority-setting in contexts with multiple constraints on development can help to identify interventions that maximizing returns, without worsening inequality.

In 2023, the around 11.1 percent of the population was living below the national poverty line in the United States. Poverty in the United StatesAs shown in the statistic above, the poverty rate among all people living in the United States has shifted within the last 15 years. The United Nations Educational, Scientific and Cultural Organization (UNESCO) defines poverty as follows: “Absolute poverty measures poverty in relation to the amount of money necessary to meet basic needs such as food, clothing, and shelter. The concept of absolute poverty is not concerned with broader quality of life issues or with the overall level of inequality in society.” The poverty rate in the United States varies widely across different ethnic groups. American Indians and Alaska Natives are the ethnic group with the most people living in poverty in 2022, with about 25 percent of the population earning an income below the poverty line. In comparison to that, only 8.6 percent of the White (non-Hispanic) population and the Asian population were living below the poverty line in 2022. Children are one of the most poverty endangered population groups in the U.S. between 1990 and 2022. Child poverty peaked in 1993 with 22.7 percent of children living in poverty in that year in the United States. Between 2000 and 2010, the child poverty rate in the United States was increasing every year; however,this rate was down to 15 percent in 2022. The number of people living in poverty in the U.S. varies from state to state. Compared to California, where about 4.44 million people were living in poverty in 2022, the state of Minnesota had about 429,000 people living in poverty.

Out of all OECD countries, Cost Rica had the highest poverty rate as of 2022, at over 20 percent. The country with the second highest poverty rate was the United States, with 18 percent. On the other end of the scale, Czechia had the lowest poverty rate at 6.4 percent, followed by Denmark.

The significance of the OECD

The OECD, or the Organisation for Economic Co-operation and Development, was founded in 1948 and is made up of 38 member countries. It seeks to improve the economic and social well-being of countries and their populations. The OECD looks at issues that impact people’s everyday lives and proposes policies that can help to improve the quality of life.

Poverty in the United States

In 2022, there were nearly 38 million people living below the poverty line in the U.S.. About one fourth of the Native American population lived in poverty in 2022, the most out of any ethnicity. In addition, the rate was higher among young women than young men. It is clear that poverty in the United States is a complex, multi-faceted issue that affects millions of people and is even more complex to solve.

In the first quarter of 2024, almost two-thirds percent of the total wealth in the United States was owned by the top 10 percent of earners. In comparison, the lowest 50 percent of earners only owned 2.5 percent of the total wealth. Income inequality in the U.S. Despite the idea that the United States is a country where hard work and pulling yourself up by your bootstraps will inevitably lead to success, this is often not the case. In 2023, 7.4 percent of U.S. households had an annual income under 15,000 U.S. dollars. With such a small percentage of people in the United States owning such a vast majority of the country’s wealth, the gap between the rich and poor in America remains stark. The top one percent The United States follows closely behind China as the country with the most billionaires in the world. Elon Musk alone held around 219 billion U.S. dollars in 2022. Over the past 50 years, the CEO-to-worker compensation ratio has exploded, causing the gap between rich and poor to grow, with some economists theorizing that this gap is the largest it has been since right before the Great Depression.