Among countries with the highest number of overseas Chinese on each continent, the largest Chinese diaspora community is living in Indonesia, numbering more than ten million people. Most of these people are descendants from migrants born in China, who have moved to Indonesia a long time ago. On the contrary, a large part of overseas Chinese living in Canada and Australia have arrived in these countries only during the last two decades. China as an emigration country Many Chinese people have emigrated from their home country in search of better living conditions and educational chances. The increasing number of Chinese emigrants has benefited from loosened migration policies. On the one hand, the attitude of the Chinese government towards emigration has changed significantly. Overseas Chinese are considered to be strong supporters for the overall strength of Chinese culture and international influence. On the other hand, migration policies in the United States and Canada are changing with time, expanding migration opportunities for non-European immigrants. As a result, China has become one of the world’s largest emigration countries as well as the country with the highest outflows of high net worth individuals. However, the mass emigration is causing a severe loss of homegrown talents and assets. The problem of talent and wealth outflow has raised pressing questions to the Chinese government, and a solution to this issue is yet to be determined. Popular destinations among Chinese emigrants Over the last decades, English speaking developed countries have been popular destinations for Chinese emigrants. In 2022 alone, the number of people from China naturalized as U.S. citizens had amounted to over 27,000 people, while nearly 68,000 had obtained legal permanent resident status as “green card” recipients. Among other popular immigration destinations for Chinese riches are Canada, Australia, Europe, and Singapore.

As of 2022, the European country with the most citizens of the People's Republic of China was Italy, with around 300,000 people. Spain also hosted a substantial number of Chinese nationals at roughly 193,000 people. These figures are likely to underestimate the number of people who were born in China or are of Chinese ancestry, as many of these immigrants receive the citizenship of the European country which they migrated to after living there for a period of time, and the People's Republic of China does not allow its citizens to hold dual citizenship.

This graph shows the population distribution of Chinese people living abroad in 2013 and 2023, by continent, according to official Taiwanese sources. By the end of 2023, around 2.44 million people of Chinese birth or descent who were living overseas were living in Europe. The figures of the source are in most cases higher - in some cases considerably higher - than figures published by the UN, as not only first generation migrants are included, but also their descendants.

In 2023, approximately 127.1 million people lived in Guangdong province in China. That same year, only about 3.65 million people lived in the sparsely populated highlands of Tibet. Regional differences in China China is the world’s most populous country, with an exceptional economic growth momentum. The country can be roughly divided into three regions: Western, Eastern, and Central China. Western China covers the most remote regions from the sea. It also has the highest proportion of minority population and the lowest levels of economic output. Eastern China, on the other hand, enjoys a high level of economic development and international corporations. Central China lags behind in comparison to the booming coastal regions. In order to accelerate the economic development of Western and Central Chinese regions, the PRC government has ramped up several incentive plans such as ‘Rise of Central China’ and ‘China Western Development’. Economic power of different provinces When observed individually, some provinces could stand an international comparison. Jiangxi province, for example, a medium-sized Chinese province, had a population size comparable to Argentina or Spain in 2023. That year, the GDP of Zhejiang, an eastern coastal province, even exceeded the economic output of the Netherlands. In terms of per capita annual income, the municipality of Shanghai reached a level close to that of the Czech Republik. Nevertheless, as shown by the Gini Index, China’s economic spur leaves millions of people in dust. Among the various kinds of economic inequality in China, regional or the so-called coast-inland disparity is one of the most significant. Posing as evidence for the rather large income gap in China, the poorest province Heilongjiang had a per capita income similar to that of Sri Lanka that year.

As of 2023, the bulk of the Chinese population was aged between 25 and 59 years, amounting to around half of the population. A breakdown of the population by broad age groups reveals that around 61.3 percent of the total population was in working age between 16 and 59 years in 2023. Age cohorts below 25 years were considerably smaller, although there was a slight growth trend in recent years. Population development in China Population development in China over the past decades has been strongly influenced by political and economic factors. After a time of high fertility rates during the Maoist regime, China introduced birth-control measures in the 1970s, including the so-called one-child policy. The fertility rate dropped accordingly from around six children per woman in the 1960s to below two at the end of the 20th century. At the same time, life expectancy increased consistently. In the face of a rapidly aging society, the government gradually lifted the one-child policy after 2012, finally arriving at a three-child policy in 2021. However, like in most other developed countries nowadays, people in China are reluctant to have more than one or two children due to high costs of living and education, as well as changed social norms and private values. China’s top-heavy age pyramid The above-mentioned developments are clearly reflected in the Chinese age pyramid. The age cohorts between 30 and 39 years are the last two larger age cohorts. The cohorts between 15 and 24, which now enter childbearing age, are decisively smaller, which will have a negative effect on the number of births in the coming decade. When looking at a gender distribution of the population pyramid, a considerable gender gap among the younger age cohorts becomes visible, leaving even less room for growth in birth figures.

According to latest figures, the Chinese population decreased by 1.39 million to around 1.408 billion people in 2024. After decades of rapid growth, China arrived at the turning point of its demographic development in 2022, which was earlier than expected. The annual population decrease is estimated to remain at moderate levels until around 2030 but to accelerate thereafter. Population development in China China had for a long time been the country with the largest population worldwide, but according to UN estimates, it has been overtaken by India in 2023. As the population in India is still growing, the country is very likely to remain being home of the largest population on earth in the near future. Due to several mechanisms put into place by the Chinese government as well as changing circumstances in the working and social environment of the Chinese people, population growth has subsided over the past decades, displaying an annual population growth rate of -0.1 percent in 2024. Nevertheless, compared to the world population in total, China held a share of about 18 percent of the overall global population in 2022. China's aging population In terms of demographic developments, the birth control efforts of the Chinese government had considerable effects on the demographic pyramid in China. Upon closer examination of the age distribution, a clear trend of an aging population becomes visible. In order to curb the negative effects of an aging population, the Chinese government abolished the one-child policy in 2015, which had been in effect since 1979, and introduced a three-child policy in May 2021. However, many Chinese parents nowadays are reluctant to have a second or third child, as is the case in most of the developed countries in the world. The number of births in China varied in the years following the abolishment of the one-child policy, but did not increase considerably. Among the reasons most prominent for parents not having more children are the rising living costs and costs for child care, growing work pressure, a growing trend towards self-realization and individualism, and changing social behaviors.

Abstract

China Living Standards Survey (CLSS) consists of one household survey and one community (village) survey, conducted in Hebei and Liaoning Provinces (northern and northeast China) in July 1995 and July 1997 respectively. Five villages from each three sample counties of each province were selected (six were selected in Liaoyang County of Liaoning Province because of administrative area change). About 880 farm households were selected from total thirty-one sample villages for the household survey. The same thirty-one villages formed the samples of community survey. This document provides information on the content of different questionnaires, the survey design and implementation, data processing activities, and the different available data sets.

Geographic coverage

The China Living Standards Survey (CLSS) was conducted only in Hebei and Liaoning Provinces (northern and northeast China).

Kind of data

Sample survey data [ssd]

Sampling procedure

The CLSS sample is not a rigorous random sample drawn from a well-defined population. Instead it is only a rough approximation of the rural population in Hebei and Liaoning provinces in Northeastern China. The reason for this is that part of the motivation for the survey was to compare the current conditions with conditions that existed in Hebei and Liaoning in the 1930’s. Because of this, three counties in Hebei and three counties in Liaoning were selected as "primary sampling units" because data had been collected from those six counties by the Japanese occupation government in the 1930’s. Within each of these six counties (xian) five villages (cun) were selected, for an overall total of 30 villages (in fact, an administrative change in one village led to 31 villages being selected). In each county a "main village" was selected that was in fact a village that had been surveyed in the 1930s. Because of the interest in these villages 50 households were selected from each of these six villages (one for each of the six counties). In addition, four other villages were selected in each county. These other villages were not drawn randomly but were selected so as to "represent" variation within the county. Within each of these villages 20 households were selected for interviews. Thus the intended sample size was 780 households, 130 from each county.

Unlike county and village selection, the selection of households within each village was done according to standard sample selection procedures. In each village, a list of all households in the village was obtained from village leaders. An "interval" was calculated as the number of the households in the village divided by the number of households desired for the sample (50 for main villages and 20 for other villages). For the list of households, a random number was drawn between 1 and the interval number. This was used as a starting point. The interval was then added to this number to get a second number, then the interval was added to this second number to get a third number, and so on. The set of numbers produced were the numbers used to select the households, in terms of their order on the list.

In fact, the number of households in the sample is 785, as opposed to 780. Most of this difference is due to a village in which 24 households were interviewed, as opposed to the goal of 20 households

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire

The household questionnaire contains sections that collect data on household demographic structure, education, housing conditions, land, agricultural management, household non-agricultural business, household expenditures, gifts, remittances and other income sources, and saving and loans. For some sections (general household information, schooling, housing, gift-exchange, remittance, other income, and credit and savings) the individual designated by the household members as the household head provided responses. For some other sections (farm land, agricultural management, family-run non-farm business, and household consumption expenditure) a member identified as the most knowledgeable provided responses. Identification codes for respondents of different sections indicate who provided the information. In sections where the information collected pertains to individuals (employment), whenever possible, each member of the household was asked to respond for himself or herself, except that parents were allowed to respond for younger children. Therefore, in the case of the employment section it is possible that the information was not provided by the relevant person; variables in this section indicate when this is true.

The household questionnaire was completed in a one-time interview in the summer of 1995. The survey was designed so that more sensitive issues such as credit and savings were discussed near the end. The content of each section is briefly described below.

Section 0 SURVEY INFORMATION

This section mainly summarizes the results of the survey visits. The following information was entered into the computer: whether the survey and the data entry were completed, codes of supervisor’s brief comments on interviewer, data entry operator, and related revising suggestion (e.g., 1. good, 2. revise at office, and 3. re-interview needed). Information about the date of interview, the names of interviewer, supervisor, data enterer, and detail notes of interviewer and supervisor were not entered into the computer.

Section 1 GENERAL HOUSEHOLD INFORMATION

1A HOUSEHOLD STRUCTURE 1B INFORMATION ABOUT THE HOUSEHOLD MEMBERS’ PARENTS 1C INFORMATION ABOUT THE CHILDREN WHO ARE NOT LIVING IN HOME

Section 1A lists the personal id code, sex, relationship to the household head, ethnic group, type of resident permit (agricultural [nongye], non-agricultural [fei nongye], or no resident permit), date of birth, marital status of all people who spent the previous night in that household and for household members who are temporarily away from home. The household head is listed first and receives the personal id code 1. Household members were defined to include “all the people who normally live and eat their meals together in this dwelling.” Those who were absent more than nine of the last twelve months were excluded, except for the head of household. For individuals who are married and whose spouse resides in the household, the personal id number of the spouse is noted. By doing so, information on the spouse can be collected by appropriately merging information from the section 1A and other parts of the survey.

Section 1B collects information on the parents of all household members. For individuals whose parents reside in the household, parents’ personal id numbers are noted, and information can be obtained by appropriately merging information from other parts of the survey. For individuals whose parents do not reside in the household, information is recorded on whether each parent is alive, as well as their schooling and occupation.

Section 1C collects information for children of household members who are not living in home. Children who have died are not included. The information on the name, sex, types of resident permit, age, education level, education cost, reasons not living in home, current living place, and type of job of each such child is recorded.

Section 2 SCHOOLING

In Section 2, information about literacy and numeracy, school attendance, completion, and current enrollment for all household members of preschool age and older. The interpretation of pre-school age appears to have varied, with the result that while education information is available for some children of pre-school age, not all pre-school children were included in this section. But for ages 6 and above information is available for nearly all individuals, so in essence the data on schooling can be said to apply all persons 6 age and above. For those who were enrolled in school at the time of the survey, information was also collected on school attendance, expenses, and scholarships. If applicable, information on serving as an apprentice, technical or professional training was also collected.

Section 3 EMPLOYMENT

3A GENERAL INFORMATION 3B MAJOR NON-FARM JOB IN 1994 3C THE SECOND NON-FARM JOB IN 1994 3D OTHER EMPLOYMENT ACTIVITIES IN 1994 3E SEARCHING FOR NON-FARM JOB 3F PROCESS FOR GETTING MAJOR NON-FARM JOB 3G CORVEE LABOR

All individuals age thirteen and above were asked to respond to the employment activity questions in Section 3. Section 3A collects general information on farm and non-farm employment, such as whether or not the household member worked on household own farm in 1994, when was the last year the member worked on own farm if he/she did not work in 1994, work days and hours during busy season, occupation and sector codes of the major, second, and third non-farm jobs, work days and total income of these non-farm jobs. There is a variable which indicates whether or not the individual responded for himself or herself.

Sections 3B and 3C collect detailed information on the major and the second non-farm job. Information includes number of months worked and which month in 1994 the member worked on these jobs, average works days (or hours) per month (per day), total number of years worked for these jobs by the end of 1994, different components of income, type of employment contracts. Information on employer’s ownership type and location was also collected.

Section 3D collects information on average hours spent doing chores and housework at home every day during non-busy and busy season. The chores refer to cooking, laundry, cleaning, shopping, cutting woods, as well as small-scale farm yard animals raising, for example, pigs or chickens. Large-scale animal

Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.

China is a vast and diverse country and population density in different regions varies greatly. In 2023, the estimated population density of the administrative area of Shanghai municipality reached about 3,922 inhabitants per square kilometer, whereas statistically only around three people were living on one square kilometer in Tibet. Population distribution in China China's population is unevenly distributed across the country: while most people are living in the southeastern half of the country, the northwestern half – which includes the provinces and autonomous regions of Tibet, Xinjiang, Qinghai, Gansu, and Inner Mongolia – is only sparsely populated. Even the inhabitants of a single province might be unequally distributed within its borders. This is significantly influenced by the geography of each region, and is especially the case in the Guangdong, Fujian, or Sichuan provinces due to their mountain ranges. The Chinese provinces with the largest absolute population size are Guangdong in the south, Shandong in the east and Henan in Central China. Urbanization and city population Urbanization is one of the main factors which have been reshaping China over the last four decades. However, when comparing the size of cities and urban population density, one has to bear in mind that data often refers to the administrative area of cities or urban units, which might be much larger than the contiguous built-up area of that city. The administrative area of Beijing municipality, for example, includes large rural districts, where only around 200 inhabitants are living per square kilometer on average, while roughly 20,000 residents per square kilometer are living in the two central city districts. This is the main reason for the huge difference in population density between the four Chinese municipalities Beijing, Tianjin, Shanghai, and Chongqing shown in many population statistics.

The total population in China was estimated at 1409.7 million people in 2023, according to the latest census figures and projections from Trading Economics. This dataset provides - China Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

China Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 11.600 % in 2021. This records a decrease from the previous number of 11.900 % for 2020. China Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 15.100 % from Dec 1990 (Median) to 2021, with 19 observations. The data reached an all-time high of 19.500 % in 2010 and a record low of 8.900 % in 1990. China Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Chart and table of population level and growth rate for the Shanghai, China metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

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: Not identified - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes (collective households)

UNIT DESCRIPTIONS: - Dwellings: Not applicable - Households: Households can be classified into two types: domestic and institutional. Individuals who live in the same place mostly due to family relationships are counted as a domestic household. Singles who live alone are counted as a domestic household. Individuals who live in the same domestic household should be registered as one household only, regardless of the type of working places and the type of household registrations (agricultural or non-agricultural), and whether they have the formal household registrations. - Group quarters: Unknown

Universe

All individuals who have Chinese nationality and reside in China

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Bureau of Statistics

SAMPLE DESIGN: Stratified cluster design

SAMPLE UNIT: Households

SAMPLE FRACTION: 1%

SAMPLE SIZE (person records): 11,835,947

Mode of data collection

Face-to-face [f2f]

Research instrument

A single questionnaire for regular and collective households.

In 2024, there were around 719 million male inhabitants and 689 million female inhabitants living in China, amounting to around 1.41 billion people in total. China's total population decreased for the first time in decades in 2022, and population decline is expected to accelerate in the upcoming years. Birth control in China From the beginning of the 1970s on, having many children was no longer encouraged in mainland China. The one-child policy was then introduced in 1979 to control the total size of the Chinese population. According to the one-child policy, a married couple was only allowed to have one child. With the time, modifications were added to the policy, for example parents living in rural areas were allowed to have a second child if the first was a daughter, and most ethnic minorities were excepted from the policy. Population ageing The birth control led to a decreasing birth rate in China and a more skewed gender ratio of new births due to boy preference. Since the negative economic and social effects of an aging population were more and more felt in China, the one-child policy was considered an obstacle for the country’s further economic development. Since 2014, the one-child policy has been gradually relaxed and fully eliminated at the end of 2015. However, many young Chinese people are not willing to have more children due to high costs of raising a child, especially in urban areas.

In 2024, about 943.5 million people lived in urban regions in China and 464.8 million in rural. That year, the country had a total population of approximately 1.41 billion people. As of 2024, China was the second most populous country in the world. Urbanization in China Urbanization refers to the process by which people move from rural to urban areas and how a society adapts to the population shift. It is usually seen as a driving force in economic growth, accompanied by industrialization, modernization and the spread of education. Urbanization levels tend to be higher in industrial countries, whereas the degree of urbanization in developing countries remains relatively low. According to World Bank, a mere 19.4 percent of the Chinese population had been living in urban areas in 1980. Since then, China’s urban population has skyrocketed. By 2024, about 67 percent of the Chinese population lived in urban areas. Regional urbanization rates In the last decades, urbanization has progressed greatly in every region of China. Even in most of the more remote Chinese provinces, the urbanization rate surpassed 50 percent in recent years. However, the most urbanized areas are still to be found in the coastal eastern and southern regions of China. The population of Shanghai, the largest city in China and the world’s seventh largest city ranged at around 24 million people in 2023. China’s urban areas are characterized by a developing middle class. Per capita disposable income of Chinese urban households has more than doubled between 2010 and 2020. The emerging middle class is expected to become a significant driver for the continuing growth of the Chinese economy.

Chart and table of population level and growth rate for the Beijing, China metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

About this dataset

Context

The dataset tabulates the population of Lisle by race. It includes the population of Lisle across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Lisle across relevant racial categories.

Key observations

The percent distribution of Lisle population by race (across all racial categories recognized by the U.S. Census Bureau): 71.53% are white, 4.43% are Black or African American, 16.29% are Asian, 2.12% are some other race and 5.62% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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: This column displays the racial categories (excluding ethnicity) for the Lisle
• Population: The population of the racial category (excluding ethnicity) in the Lisle is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Lisle total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Lisle Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of Lisle by race. It includes the distribution of the Non-Hispanic population of Lisle across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of Lisle across relevant racial categories.

Key observations

Of the Non-Hispanic population in Lisle, the largest racial group is White alone with a population of 16,023 (74.21% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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: This column displays the racial categories (for Non-Hispanic) for the Lisle
• Population: The population of the racial category (for Non-Hispanic) in the Lisle is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Lisle total Non-Hispanic population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Lisle Population by Race & Ethnicity. You can refer the same here

Iceland Number of Immigrants: China data was reported at 95.000 Person in 2017. This records an increase from the previous number of 79.000 Person for 2016. Iceland Number of Immigrants: China data is updated yearly, averaging 45.000 Person from Dec 1986 (Median) to 2017, with 32 observations. The data reached an all-time high of 432.000 Person in 2005 and a record low of 2.000 Person in 1986. Iceland Number of Immigrants: China data remains active status in CEIC and is reported by Statistics Iceland . The data is categorized under Global Database’s Iceland – Table IS.G006: Number of Immigrants.

About this dataset

Context

The dataset tabulates the population of Troy by race. It includes the population of Troy across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Troy across relevant racial categories.

Key observations

The percent distribution of Troy population by race (across all racial categories recognized by the U.S. Census Bureau): 64.56% are white, 4.02% are Black or African American, 0.19% are American Indian and Alaska Native, 25.98% are Asian, 0.01% are Native Hawaiian and other Pacific Islander, 1.22% are some other race and 4.03% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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: This column displays the racial categories (excluding ethnicity) for the Troy
• Population: The population of the racial category (excluding ethnicity) in the Troy is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Troy total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Troy Population by Race & Ethnicity. You can refer the same here