In 2023, there were an estimated ******* white homeless people in the United States, the most out of any ethnicity. In comparison, there were around ******* Black or African American homeless people in the U.S. How homelessness is counted The actual number of homeless individuals in the U.S. is difficult to measure. The Department of Housing and Urban Development uses point-in-time estimates, where employees and volunteers count both sheltered and unsheltered homeless people during the last 10 days of January. However, it is very likely that the actual number of homeless individuals is much higher than the estimates, which makes it difficult to say just how many homeless there are in the United States. Unsheltered homeless in the United States California is well-known in the U.S. for having a high homeless population, and Los Angeles, San Francisco, and San Diego all have high proportions of unsheltered homeless people. While in many states, the Department of Housing and Urban Development says that there are more sheltered homeless people than unsheltered, this estimate is most likely in relation to the method of estimation.

In 2023, there were about ******* homeless people estimated to be living in the United States, the highest number of homeless people recorded within the provided time period. In comparison, the second-highest number of homeless people living in the U.S. within this time period was in 2007, at *******. How is homelessness calculated? Calculating homelessness is complicated for several different reasons. For one, it is challenging to determine how many people are homeless as there is no direct definition for homelessness. Additionally, it is difficult to try and find every single homeless person that exists. Sometimes they cannot be reached, leaving people unaccounted for. In the United States, the Department of Housing and Urban Development calculates the homeless population by counting the number of people on the streets and the number of people in homeless shelters on one night each year. According to this count, Los Angeles City and New York City are the cities with the most homeless people in the United States. Homelessness in the United States Between 2022 and 2023, New Hampshire saw the highest increase in the number of homeless people. However, California was the state with the highest number of homeless people, followed by New York and Florida. The vast amount of homelessness in California is a result of multiple factors, one of them being the extreme high cost of living, as well as opposition to mandatory mental health counseling and drug addiction. However, the District of Columbia had the highest estimated rate of homelessness per 10,000 people in 2023. This was followed by New York, Vermont, and Oregon.

When analyzing the ratio of homelessness to state population, New York, Vermont, and Oregon had the highest rates in 2023. However, Washington, D.C. had an estimated ** homeless individuals per 10,000 people, which was significantly higher than any of the 50 states. Homeless people by race The U.S. Department of Housing and Urban Development performs homeless counts at the end of January each year, which includes people in both sheltered and unsheltered locations. The estimated number of homeless people increased to ******* in 2023 – the highest level since 2007. However, the true figure is likely to be much higher, as some individuals prefer to stay with family or friends - making it challenging to count the actual number of homeless people living in the country. In 2023, nearly half of the people experiencing homelessness were white, while the number of Black homeless people exceeded *******. How many veterans are homeless in America? The  number of homeless veterans in the United States has halved since 2010. The state of California, which is currently suffering a homeless crisis, accounted for the highest number of homeless veterans in 2022. There are many causes of homelessness among veterans of the U.S. military, including post-traumatic stress disorder (PTSD), substance abuse problems, and a lack of affordable housing.

The graph displays the top 15 states by an estimated number of homeless people in the United States for the year 2025. The x-axis represents U.S. states, while the y-axis shows the number of homeless individuals in each state. California has the highest homeless population with 187,084 individuals, followed by New York with 158,019, while Hawaii places last in this dataset with 11,637. This bar graph highlights significant differences across states, with some states like California and New York showing notably higher counts compared to others, indicating regional disparities in homelessness levels across the country.

The graph displays the estimated number of homeless people in the United States from 2007 to 2024. The x-axis represents the years, ranging from 2007 to 2023, while the y-axis indicates the number of homeless individuals. The estimated homeless population varies over this period, ranging from a low of 57,645 in 2014 to a high of 771,000 in 2024. From 2007 to 2013, there is a general decline in numbers from 647,258 to 590,364. In 2014, the number drops significantly to 57,645, followed by an increase to 564,708 in 2015. The data shows fluctuations in subsequent years, with another notable low of 55,283 in 2018. From 2019 onwards, the estimated number of homeless people generally increases, reaching its peak in 2024. This data highlights fluctuations in homelessness estimates over the years, with a recent upward trend in the homeless population.

This map shows the percent of population who are veterans. This pattern is shown by states, counties, and tracts. The data is from the most current American Community Survey (ACS) data from the U.S. Census Bureau. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty.The pop-up highlights the breakdown of veterans by gender.Zoom to any area in the country to see a local or regional pattern, or use one of the bookmarks to see distinct patterns of poverty through the US. Data is available for the 50 states plus Washington D.C. and Puerto Rico.The data comes from this ArcGIS Living Atlas of the World layer, which is part of a wider collection of layers that contain the most up-to-date ACS data from the Census. The layers are updated annually when the ACS releases their most current 5-year estimates. Visit the layer for more information about the data source, vintage, and download date for the data.

Analysis of ‘Natural Disasters Data Explorer’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mathurinache/natural-disasters-data-explorer on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Disasters include all geophysical, meteorological and climate events including earthquakes, volcanic activity, landslides, drought, wildfires, storms, and flooding. Decadal figures are measured as the annual average over the subsequent ten-year period.

Content

Thanks to Our World in Data, you can explore death from natural disasters by country and by date.

Acknowledgements

https://www.acacamps.org/sites/default/files/resource_library_images/naturaldisaster4.jpg" alt="Natural Disasters">

Inspiration

List of variables for inspiration: Number of deaths from drought Number of people injured from drought Number of people affected from drought Number of people left homeless from drought Number of total people affected by drought Reconstruction costs from drought Insured damages against drought Total economic damages from drought Death rates from drought Injury rates from drought Number of people affected by drought per 100,000 Homelessness rate from drought Total number of people affected by drought per 100,000 Number of deaths from earthquakes Number of people injured from earthquakes Number of people affected by earthquakes Number of people left homeless from earthquakes Number of total people affected by earthquakes Reconstruction costs from earthquakes Insured damages against earthquakes Total economic damages from earthquakes Death rates from earthquakes Injury rates from earthquakes Number of people affected by earthquakes per 100,000 Homelessness rate from earthquakes Total number of people affected by earthquakes per 100,000 Number of deaths from disasters Number of people injured from disasters Number of people affected by disasters Number of people left homeless from disasters Number of total people affected by disasters Reconstruction costs from disasters Insured damages against disasters Total economic damages from disasters Death rates from disasters Injury rates from disasters Number of people affected by disasters per 100,000 Homelessness rate from disasters Total number of people affected by disasters per 100,000 Number of deaths from volcanic activity Number of people injured from volcanic activity Number of people affected by volcanic activity Number of people left homeless from volcanic activity Number of total people affected by volcanic activity Reconstruction costs from volcanic activity Insured damages against volcanic activity Total economic damages from volcanic activity Death rates from volcanic activity Injury rates from volcanic activity Number of people affected by volcanic activity per 100,000 Homelessness rate from volcanic activity Total number of people affected by volcanic activity per 100,000 Number of deaths from floods Number of people injured from floods Number of people affected by floods Number of people left homeless from floods Number of total people affected by floods Reconstruction costs from floods Insured damages against floods Total economic damages from floods Death rates from floods Injury rates from floods Number of people affected by floods per 100,000 Homelessness rate from floods Total number of people affected by floods per 100,000 Number of deaths from mass movements Number of people injured from mass movements Number of people affected by mass movements Number of people left homeless from mass movements Number of total people affected by mass movements Reconstruction costs from mass movements Insured damages against mass movements Total economic damages from mass movements Death rates from mass movements Injury rates from mass movements Number of people affected by mass movements per 100,000 Homelessness rate from mass movements Total number of people affected by mass movements per 100,000 Number of deaths from storms Number of people injured from storms Number of people affected by storms Number of people left homeless from storms Number of total people affected by storms Reconstruction costs from storms Insured damages against storms Total economic damages from storms Death rates from storms Injury rates from storms Number of people affected by storms per 100,000 Homelessness rate from storms Total number of people affected by storms per 100,000 Number of deaths from landslides Number of people injured from landslides Number of people affected by landslides Number of people left homeless from landslides Number of total people affected by landslides Reconstruction costs from landslides Insured damages against landslides Total economic damages from landslides Death rates from landslides Injury rates from landslides Number of people affected by landslides per 100,000 Homelessness rate from landslides Total number of people affected by landslides per 100,000 Number of deaths from fog Number of people injured from fog Number of people affected by fog Number of people left homeless from fog Number of total people affected by fog Reconstruction costs from fog Insured damages against fog Total economic damages from fog Death rates from fog Injury rates from fog Number of people affected by fog per 100,000 Homelessness rate from fog Total number of people affected by fog per 100,000 Number of deaths from wildfires Number of people injured from wildfires Number of people affected by wildfires Number of people left homeless from wildfires Number of total people affected by wildfires Reconstruction costs from wildfires Insured damages against wildfires Total economic damages from wildfires Death rates from wildfires Injury rates from wildfires Number of people affected by wildfires per 100,000 Homelessness rate from wildfires Total number of people affected by wildfires per 100,000 Number of deaths from extreme temperatures Number of people injured from extreme temperatures Number of people affected by extreme temperatures Number of people left homeless from extreme temperatures Number of total people affected by extreme temperatures Reconstruction costs from extreme temperatures Insured damages against extreme temperatures Total economic damages from extreme temperatures Death rates from extreme temperatures Injury rates from extreme temperatures Number of people affected by extreme temperatures per 100,000 Homelessness rate from extreme temperatures Total number of people affected by extreme temperatures per 100,000 Number of deaths from glacial lake outbursts Number of people injured from glacial lake outbursts Number of people affected by glacial lake outbursts Number of people left homeless from glacial lake outbursts Number of total people affected by glacial lake outbursts Reconstruction costs from glacial lake outbursts Insured damages against glacial lake outbursts Total economic damages from glacial lake outbursts Death rates from glacial lake outbursts Injury rates from glacial lake outbursts Number of people affected by glacial lake outbursts per 100,000 Homelessness rate from glacial lake outbursts Total number of people affected by glacial lake outbursts per 100,000 Total economic damages from disasters as a share of GDP Total economic damages from drought as a share of GDP Total economic damages from earthquakes as a share of GDP Total economic damages from extreme temperatures as a share of GDP Total economic damages from floods as a share of GDP Total economic damages from landslides as a share of GDP Total economic damages from mass movements as a share of GDP Total economic damages from storms as a share of GDP Total economic damages from volcanic activity as a share of GDP Total economic damages from volcanic activity as a share of GDP Entity Year deaths_rate_per_100k_storm injured_rate_per_100k_storm total_affected_rate_per_100k_all_disasters

--- Original source retains full ownership of the source dataset ---

The number of people left homeless due to wildfires in 2023 amounted to 81, a considerable decrease when compared to the figures of 2022 and 2021, when 3,933 and 4,893 people lost their homes due to such disasters.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling and person

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes - Special populations: Homeless, passengers in transit (international flights), personnel on duty in hospitals, factories, institutions, and other places, employees of the National Institute of Statistics, embassies and consulates

UNIT DESCRIPTIONS: - Dwellings: Dwelling is any inhabited physical place, constructed or adapted for housing people. - Households: Household is a group of people, related or otherwise, who occupy the dwelling. - Group quarters: Collective houshold is a group of people who share the dwelling in a non-familial system, for reasons of work, health, discipline, religion, punishment, etc.

Universe

All the population in the national territory at the moment the census is carried out.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics, Ministry of Planning and Coordination, Republic of Bolivia

SAMPLE DESIGN: Systematic sample of every tenth dwelling with a random start; drawn by MPC

SAMPLE UNIT: Dwelling

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 642,368

Mode of data collection

Face-to-face [f2f]

Research instrument

A single booklet that consists of sections on geographic location, dwelling, and population (individual)

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling, census household, and population

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes - Special populations: Homeless, persons located in truck stops and in markets, passengers in transit (international flights), personnel in hospitals, factories, institutions, or other, enumerators and area supervisors, and embassies and consulates

UNIT DESCRIPTIONS: - Dwellings: A dwelling is a construction that has one or more floors covered by a roof and is constructed or adapted for the habitation of one or more persons, either permanently or temporarily. - Households: A household is made up of one or more persons, related or unrelated, who live in the same dwelling and who at least share a common budget for meals to which each person contributes in money or in kind. One person can also constitute a household. - Group quarters: A collective dwelling is inhabited by a group of persons, usually unrelated, who lie together but not as a family.

Universe

All the population in the national territory at the moment the census is carried out.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Institute of Statistics, Ministry of Planning and Coordination, Republic of Bolivia

SAMPLE DESIGN: Systematic sample of every tenth dwelling with a random start; drawn by MPC

SAMPLE UNIT: Dwelling

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 827,692

Mode of data collection

Face-to-face [f2f]

Research instrument

(1) Identification of the census form, (2) Dwelling type and occupancy, (3) Characteristics of dwellings with inhabitants who are present, (4) Individual form (all in a single booklet)

Poverty and social exclusion, social services, climate change, and the national economic situation and statistics.

Topics: 1. Poverty and social exclusion: own life satisfaction (scale); satisfaction with family life, health, job, and satisfaction with standard of living (scale); personal definition of poverty; incidence of poverty in the own country; estimated proportion of the poor in the total population; poor persons in the own residential area; estimated increase of poverty: in the residential area, in the own country, in the EU, and in the world; reasons for poverty in general; social and individual reasons for poverty; population group with the highest risk of poverty; things that are necessary to being able to afford to have a minimum acceptable standard of living (heating facility, adequate housing, a place to live with enough space and privacy, diversified meals, repairing or replacing a refrigerator or a washing machine, annual family holidays, medical care, dental care, access to banking services as well as to public transport, access to modern means of communication, to leisure and cultural activities, electricity, and running water); perceived deprivation through poverty in the own country regarding: access to decent housing, education, medical care, regular meals, bank services, modern means of communication, finding a job, starting up a business of one’s own, maintaining a network of friends and acquaintances; assessment of the financial situation of future generations and current generations compared to parent and grandparent generations; attitude towards poverty: necessity for the government to take action, too large income differences, national government should ensure the fair redistribution of wealth, higher taxes for the rich, economic growth reduces poverty automatically, poverty will always exist, income inequality is necessary for economic development; perceived tensions between population groups: rich and poor, management and workers, young and old, ethnic groups; general trust in people, in the national parliament, and the national government (scale); trust in institutions regarding poverty reduction: EU, national government, local authorities, NGOs, religious institutions, private companies, citizens; reasons for poverty in the own country: globalisation, low economic growth, pursuit of profit, global financial system, politics, immigration, inadequate national social protection system; primarily responsible body for poverty reduction; importance of the EU in the fight against poverty; prioritized policies of the national government to combat poverty; assessment of the effectiveness of public policies to reduce poverty; opinion on the amount of financial support for the poor; preference for governmental or private provision of jobs; attitude towards tuition fees; increase of taxes to support social spending; individual or governmental responsibility (welfare state) to ensure provision; attitude towards a minimum wage; optimism about the future; perceived own social exclusion; perceived difficulties to access to financial services: bank account, bank card, credit card, consumer loans, and mortgage; personal risk of over-indebtedness; attitude towards loans: interest free loans for the poor, stronger verification of borrowers by the credit institutions, easier access to start-up loans for the unemployed, free financial advice for the poor, possibility to open a basic bank account for everyone; affordable housing in the residential area; extent of homelessness in the residential area, and recent change; adequacy of the expenditures for the homeless by the national government, and the local authorities; assumed reasons for homelessness: unemployment, no affordable housing, destruction of the living space by a natural disaster, debt, illness, drug or alcohol addiction, family breakdown, loss of a close relative, mental health problems, lack of access to social services and support facilities, lack of identity papers, free choice of this life; probability to become homeless oneself; own support of homeless people: monetary donations to charities, volunteer work in a charity, help find access in emergency shelters and with job search, direct donations of clothes to homeless people, buying newspapers sold by homeless people, food donations; sufficient household income, or difficulties to make ends meet; ability to afford the heating costs, a week’s holiday once a year, and a meal with meat every second day; expected development of the financial situation of the household; assessment of the risk of potential difficulties in the next 12 months in paying: rent, mortgage, consumer loan rates, electricity bills, unexpected events, daily consumer goods; job security; difficulties in fulfilling family responsibilities because of the workload; difficulties in concentrating at work due to family commitments; necessary minimum monthly income for the own household; comparison of the monthly...

Transitional Housing Services Market size was valued at USD 100 Billion in 2023 and is projected to reach USD 342.6 Billion by 2031, growing at a CAGR of 15.2% during the forecast period 2024-2031.

Global Transitional Housing Services Market Drivers

The market drivers for the Transitional Housing Services Market can be influenced by various factors. These may include:

Increasing Homelessness Rates: The rising rates of homelessness globally are a significant market driver for transitional housing services. Factors such as economic instability, lack of affordable housing, and social issues contribute to this increasing trend. Many cities report surges in homelessness, prompting governments and NGOs to seek robust solutions. Transitional housing serves as an intermediary step, offering individuals and families temporary support while they work towards permanent housing solutions.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes (institutional) - Special populations: Homeless, boat people

UNIT DESCRIPTIONS: - Dwellings: Not available - Households: An individual or group of people who inhabit part or all of the physical or census building and usually live together and eat together from one kitchen. One kitchen means that the daily needs are managed and combined into one. - Group quarters: An institutional household includes people living in a dormitory, barracks, or insitution where everyday needs are managed by an institution or foundation. Also includes groups of 10 or more people in lodging houses or buildings.

Universe

All population, Indonesian and foreign, residing in the territorial area of Indonesia, regardless of residence status. Includes homeless, refugees, ship crews, and people in inaccessible areas. Diplomats and their families residing in Indonesia were excluded.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Statistics Indonesia

SAMPLE DESIGN: Geographically stratified systematic sample (drawn by MPC).

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 22,928,795

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires: C1 to enumerate regular households living in areas covered in the census mappling; C2 for the population living in areas not included in the mapping, such as remote areas; and L2 for the homeless, boat people, and tribes.

Various state governments in India set-up shelter homes for those stranded by the coronavirus (COVID-19) lockdown implemented in late March, 2020. The southern state of Kerala topped the list with 15,141 shelter homes in April. This was nearly 70 percent of all government camps across the country. Uttar Pradesh followed with 2,230 camps and Maharashtra ranked third during the same time period.

The country went into lockdown on March 25, 2020, the largest in the world, restricting 1.3 billion people. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

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.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Dwellings: Living quarters have been defined for census purposes as places of abode, which are structurally separate and independent. The terms separate and independent mean the following: Separate: A structure is considered separate if it is surrounded by walls, fence, etc., and is covered by roof. Independent: A structure is said to be independent if it has direct access via a public staircase, communal passageway or landing (that is, occupants can come in or go out of their living quarters without passing through someone else?s premises). In general, living quarters can be classified into two categories, that is: (i) Built or converted for living (e.g. house, flat, apartment, shophouse, makeshift hut, hotel, hostels, etc.) (ii) Not meant for living but used for this purpose on Census Day (e.g. in a building such as office, shop, barn, community hall, etc.) Living quarters built or converted for living can be further classified into housing units and collective living quarters. Housing units are classified into six main types, namely: House; Flat/apartment/condominium; Shop house, office; Room (with direct access to the outside); improvised/temporary hut; and others. House can be further classified into Detached house; and Semi-detached house. - Households: A household is made up of persons who may be related and/or persons unrelated who usually live together and make common provision for food and other essentials of living. -This group makes provision for food from part of their pooled resources and makes the same preparation for other basic need. -A household can comprise several members or may be a single member only. -Persons in a household may be related or a combination fo both. -Each living quarters is normally coccupied by a househod. However, sometimes a livng quarters may be occupied by more than one househod. This situation normally occurs in urban areas where households are forced to share a living quarters because of the shortage of accommodation. - Group quarters: Living quarters which is built or converted for living (e.g. house, flat, apartment, shophouse, makeshift hut, hotel, hostels, etc.).

Universe

In the 1991 Population and Housing Census, all persons including foreigners who were in Malaysia on Census Day were enumerated. Generally, the majority of people were found in their respective homes on August 14, 1991 and were enumerated under the normal enumeration procedures. However, a minority of the population did not fall in the above category and for the persons, special enumeration arrangements were made. The groups referred to were: (a) Guests staying in hotels, lodging houses, rest-houses, etc; (b) Persons staying in institutional living quarters such as educational, medical, charitable, religious and social welfare institutions, etc; (c) Persons in prison, detention centers and lock-ups; (d) Personnel in army/police camps and those on military patrol; (e) Orang Asli (Aborigines) in Peninsular Malaysia; (f) Wayfarers, homeless people and persons away at sea; (g) Foreign military, naval and diplomatic personnel and their families. All persons in this category were enumerated in the census with the exception of persons with diplomatic immunity who wished to be excluded.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Department of Statistics Malaysia

SAMPLE DESIGN: With 2 per cent as the sampling fraction, or a sample interval of 50, the sample was selected using the living quarters serial number starting from 1, 51, 101, 151, 201 ??. N.

SAMPLE UNIT: household

SAMPLE FRACTION: 2%

SAMPLE SIZE (person records): 347,892

Mode of data collection

Face-to-face [f2f]

Research instrument

Four types of forms were used in the 1991 Census. Document 1: Listing Book which identified the Enumeration Block and list all living quarters in each block. Document 2: The main census form which required the filling in of particulars on all listed living quarters, household and person. Document 2a: Person Form. This document was used if a household contained more than seven members. Document 3: Self-enumeration Form for Living Quarters/ Household. Document 3a: Self-enumeration Person Form. Document 4: Listing Card which assigned a control number to the living quarters.

Response rate

UNDERCOUNT: 100%

From 2017 to 2021, the share of households living under the poverty line in Venezuela has been surpassing 90 percent. In addition, more than six out of every ten households (67.97 percent) lived in extreme poverty in 2021. The overall household poverty rate in Venezuela has registered a steady growth from 2014 to 2019, after having remained relatively stable, below 40 percent, since 2005. Although poverty is widespread among the population as a whole, some groups are more vulnerable than others. That is the case of younger generations and particularly children: 98.03 percent of Venezuelans aged 15 or younger lived in poverty in 2021. An economy in disarray Venezuela, the country with the largest oil reserves in the world and whose economy has been largely dependent on oil revenues for decades, was once one of the most prosperous countries in Latin America. Today, hyperinflation and an astronomic public debt are only some of the many pressing concerns that affect the domestic economy. The socio-economic consequences of the crisis As a result of the economic recession, more than half of the population in every state in Venezuela lives in extreme poverty. This issue is particularly noteworthy in the states of Amazonas, Monagas, and Falcón, where the extreme poverty rate hovers over 80 percent. Such alarming levels of poverty, together with persistent food shortages, provoked a rapid increase in undernourishment, which was estimated at 17.9 percent between 2020 and 2022. The combination of humanitarian crisis, political turmoil and economic havoc led to the Venezuelan refugee and migrant crisis. As of 2020, more than five million Venezuelans had fled their home country, with neighboring Colombia being the main country of destination.

A multi-millionaire is defined as someone owning 10 million U.S. dollars or more. It was forecasted that there would be almost 18 thousand individuals in Australia defined as multi-millionaires by 2026. This is in line with the country’s growing economy over the years as well as the growing wealth inequality that was becoming a cause for concern in the island nation.

Distribution of the wealthy

As a rich country with plenty of natural resources and a high Human Development Index, Australia had always had a large number of high net-worth individuals or HNWIs. There were over ten thousand millionaires including a couple dozen of billionaires, with these figures expected to grow significantly over the next few years.

Income inequality

Despite the increase of wealth and economic growth, there was a concern at the level of poverty and homelessness due to the rising wealth inequality nationally. The number of homeless people living in Australia had only been increasing with more than a hundred thousand people currently without shelter. Furthermore, most of the wealth was being pushed from the country to the cities, affecting the livelihood of those living in the countryside or outback.