Historical chart and dataset showing U.S. population growth rate by year from 1961 to 2023.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within New Jersey. The dataset can be utilized to gain insights into gender-based income distribution within the New Jersey population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within New Jersey, among individuals aged 15 years and older with income, there were 3.32 million men and 3.31 million women in the workforce. Among them, 1.92 million men were engaged in full-time, year-round employment, while 1.46 million women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 5.61% fell within the income range of under $24,999, while 8.12% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 41.39% of men in full-time roles earned incomes exceeding $100,000, while 28.39% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

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 New Jersey median household income by race. You can refer the same here

Introduction

The 2023 mid-year estimate (MYE) is the current official estimate of the population for local authorities in England and Wales. Estimates are produced annually by the Office for National Statistics (ONS) and the 2023 MYE was published on 15 July 2024.

Comparison to previous MYE data

The previous MYE series (for the period 2012-2020) starts with the 2011 census estimate. Each subsequent year’s population is calculated by adding estimates of births, deaths and migration to the previous year’s population. The 2021 MYE represents a break in this series as it uses the 2021 census as its base.

The ONS revised the 2012-2020 MYE series to bring it in line with the 2021 MYE, so that comparisons could be made between between this series and the previous series. The values plotted on the chart are the revised values of the previously published estimates for 2011 to 2022, together with the estimates for 2023.

Key Points

• London’s mid-2023 population was 8.945 million
• London’s population increased by 76,300 persons compared to the previous mid-year value
• Components of change were as follows:
• 105,100 births and 53,500 deaths (natural change of 51,600)
• Net domestic migration was an outflow of 129,200
• Net international migration was an inflow of 154,100

Population Change

London’s 2023 population was 8,945,310. The first chart below shows the 2023 MYE in the context of previous estimates. There is an uptick after a temporary decrease in population which we attribute to the COVID-19 pandemic.

https://cdn.datapress.cloud/london/img/dataset/763802e7-af17-4b77-995d-44c494fb68af/2025-06-09T20%3A56%3A29/666cd938678c5361c953cb608e532416.webp" width="1152" alt="Embedded Image" />

Components of Change

Births, deaths and migration form the components of population change.

The 2023 MYE value for births was 4% lower than that in 2022, and for deaths 3% higher. The consequent value for natural change (births - deaths) was 10% lower than in 2022.

At -129,000, the value for domestic migration (migration within the UK) was nearly 3% higher than the 2022 value, so still significantly lower than the peak net outflow during the COVID-19 pandemic of -186,000. An outflow of domestic migrants from London is normal and this has been the case each year for the last two decades. This flow is partly because many international in-migrants initially settle in London before moving out to other parts of the UK. The second move in this sequence is counted as a domestic migration.

There has been a marked change in immigration since 2021. This can be attributed to the end of free movement for EU nationals, easing of travel restrictions following the COVID 19 pandemic, and the war in Ukraine. At over 150,000, the 2023 MYE value for London’s net international migration was more than 18% higher than 2022, and represents a considerable increase from 78,000 in 2021.

https://cdn.datapress.cloud/london/img/dataset/763802e7-af17-4b77-995d-44c494fb68af/2025-06-09T20%3A56%3A29/cb537d44954e11f7f7b7e2189ae74629.webp" width="1152" alt="Embedded Image" />

Age structure of the population

https://cdn.datapress.cloud/london/img/dataset/763802e7-af17-4b77-995d-44c494fb68af/2025-06-09T20%3A56%3A29/6d4cf55b96888dbc3aacfc1de5c664ec.webp" width="1152" alt="Embedded Image" />

Future Updates

The release of the next mid-year estimates is expected in July 2025.

The full ONS mid-year population estimates release and back series can be found on the ONS website: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates.

For information relating to London’s population see the demography pages of the London Datastore: https://data.london.gov.uk/demography/ or email demography@london.gov.uk.

An in-depth review of the available evidence for population change in London since the start of the coronavirus pandemic has been produced by GLA Demography: https://data.london.gov.uk/dataset/population-change-in-london-during-the-pandemic.

Historical chart and dataset showing total population for Bangladesh by year from 1950 to 2025.

Annual population estimates as of July 1st, by census metropolitan area and census agglomeration, single year of age, five-year age group and gender, based on the Standard Geographical Classification (SGC) 2021.

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Historical chart and dataset showing U.S. birth rate by year from 1950 to 2025.

A dataset listing Montana cities by population for 2024.

Abstract

The Cox’s Bazar Panel Survey (CBPS) was completed in August 2019, through a partnership between the Yale Macmillan Center Program on Refugees, Forced Displacement, and Humanitarian Responses (Yale Macmillan PRFDHR), the Gender & Adolescence: Global Evidence (GAGE) program, the Poverty and Equity Global Practice of the World Bank and the State and Peacebuilding Fund (SPF) administered by the World Bank. It is a representative survey of the post-2017 population of displaced Rohingya and households in host communities in the Cox’s Bazar district in Bangladesh.

The high-frequency phone tracking (HFT) surveys were built to maintain communication with baseline respondents while collecting rapid data on key welfare indicators on labor, basic needs and education. Three rounds of the HFT have been completed between 2020-2021, which have been used to produce welfare updates on the host and Rohingya population residing in Cox's Bazar, Bangladesh, particularly amidst the COVID-19 crisis.

The tracking surveys collected information across three broad welfare dimensions: labor, access to basic needs and education status of school-aged children. Round 1 collected information on labor and access to basic needs only; the module on education was added Round 2 onwards.

Geographic coverage

Cox's Bazar district and some parts of Bandarban district.

Analysis unit

Households and individuals

Universe

a) Rohingya population living in camps and b) host population within Cox's Bazar and Bandarban district.

Kind of data

Sample survey data [ssd]

Sampling procedure

The CBPS study has a total sample size of 5,020 households (HHs), divided among three strata covering Rohingya refugees in camps and host communities in Cox’s Bazar district and some adjacent regions of Bandarban district. The CBPS HFT attempted to follow the full baseline sample of 5,020 household in each round, with no alterations or additions made to the sampling design. The baseline sampling strategy is detailed below. The three strata are defined as:
i. Rohingya refugees in camps ii. High exposure hosts: hosts within 15 km (3-hour walking distance) of camps iii. Low exposure hosts: hosts at more than 15 km (3-hour walking distance) from camps (In the datasets, the 'settlement_type' and 'stratum' variables identify the different levels at which the sample is representative)

Defining the camp strata: A two-step data collection on Rohingya refugee prevalence within host communities (i.e., outside of camps) confirmed that prevalence in host communities was low, and that this was the case not only for newer Rohingya displaced, but for the older cohort of displaced, as well. This pattern of refugee prevalence supported having one stratum for the Rohingya displaced living in camps. The sampling strategy for the CBPS therefore focused on generating representative estimates for the camp based Rohingya population in Cox’s Bazar district.

Defining the host strata: For hosts, the sampling strategy was designed to account for the differential implications of a camp-based concentration of close to a million Rohingya displaced for different areas of Cox’s Bazar. To distinguish between host communities that are differentially affected by the arrival of the Rohingya, the CBPS sampling strategy used a threshold of three hours’ walking time from a campsite to define two survey strata: (i) host communities with potentially high exposure (HE) to the displaced Rohingya, and (ii) host communities with potentially low exposure (LE).

Sampling frame: The camp sample uses the Needs and Population Monitoring Round 12 (NPM12) data from the International Organization for Migration as the sampling frame. For the host sample, a combination of the 2011 population census, Admin 4 shapefiles from the Bureau of Statistics and publicly available Google Earth imagery and OpenStreetMaps were used to develop a sampling frame.

Stages of sample selection: For camps, NPM12 divided all camps into 1,954 majhee blocks.1 200 blocks were randomly selected using a probability proportional to the size of the camp. A full listing was carried out in each selected camp block.

For hosts, a two-stage sampling strategy was followed. The first stage of selection was done at the mauza level by strata. A random sample of 66 mauzas was drawn from a frame of 286 mauzas using probability proportional to size. Based on census population size, each mauza was divided into segments of roughly 100-150 households. The second stage selected three segments from each selected mauza with equal probability of selection.

Listing and replacements: Within each selected PSU in camps (blocks) and hosts (mauza-segments), all households (100-150 on average) were listed. Of listed households, 13 households were selected at random for interview, with an additional replacement list of 5 households. More information on the sampling strategy and process can be found on the published working paper titled “Data Triangulation Strategies to Design a Representative Household Survey of Hosts and Rohingya Displaced in Cox’s Bazar, Bangladesh”.

Sampling deviation

While the original sampling strategy was designed to be representative of all camp-based Rohingya displaced, campsites with older Rohingya displaced refused to participate in the listing due to other political sensitivities. This refusal was maintained despite many attempts. Since the older Rohingya displaced were not a separate stratum, a decision was made to drop these households from the survey. Therefore, the attained sample does not contain registered refugees from the two camps – Kutupalong RC and Nayapara RC.

The host sample covers six out of eight upazilas in Cox’s Bazar District (Chakaria, Cox’s Bazar Sadar, Pekua, Ramu, Teknaf, and Ukhia upazilas) and one upazila in Bandarban District (Naikhongchhori upazila). The two upazilas not covered within the sample are the islands of Kutubdia and Maheshkhali.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The R1 tracking questionnaire was developed as a lean version of the questionnaire implemented during the CBPS baseline. The R2 and R3 questionnaires retained certain aspects of the R1 questionnaire, but also added more detailed questions on aspects such as food security (in consultation with UN-WFP) and credit-seeking and coping behavior based on findings observed in previous rounds and dynamic research needs within the COVID-19 crisis.

One questionnaire was developed per round of data collection with modules containing household level questions on access to basic needs, credit-seeking behavior, access to health services, vaccinations and individual level questions on labor market status. Any adult, knowledgeable member of the confirmed sample household were eligible to answer the household modules. The labor module was only permitted if the respondent reached was any one of the 2-3 selected adults within the household who had completed the baseline adult questionnaires.

Questionnaires were developed in English and translated into Bengali. The translations to Bengali were thoroughly reviewed by the World Bank team’s local consultants to ensure quality. Pretesting and piloting were done using the Bengali questionnaires.

All questionnaires and modules in English are provided as external resources.

Cleaning operations

Data was collected through computer-assisted telephone interviews via SurveyCTO, an ODK-based platform. Maintenance of correct questionnaire flow was ensured through in-built skips and logic checks within the programmed questionnaire.

No manual data corrections were made on submitted interviews by the data processing team. Interviews flagged as needing field corrections due to mistaken entries were re-submitted by enumerators upon strict evaluation by the project team upon close review of the concerns raised and filtered by the program automatically before closing of data collection in each round.

In addition to logic checks within the survey program itself, extensive data consistency checks and quality indicators were developed by the WB team to monitor data quality during survey implementation. Field debriefs were held frequently during the piloting phase and first week of data collection, and once a week in latter weeks to provide feedback to enumerators and gain clarity on data quality concerns.

Post data collection, structural and consistency checks have been conducted on each round dataset and in-between datasets from different rounds.

Response rate

The response rates at household level for each round of the CBPS HFT, based on the baseline sample of 5,020 and disaggregated at stratum-level are: Round 1: Overall - 67%; Camps - 54%; High exposure: 71%; Low exposure: 72% Round 2: Overall - 72%; Camps - 63%; High exposure: 81%; Low exposure: 80% Round 3: Overall - 68%; Camps - 55%; High exposure: 81%; Low exposure: 80%

*Note that the Round 1 tracking exercise was a joint-effort between the Yale Y-Rise team and the WB team. The Yale team contacted and surveyed a randomly selected 25% of baseline households, while the WB team completed the remaining 75%. The Round 1 dataset contains data on this segment of the sample only as the welfare surveys implemented by the teams were different.

As of July 2024, Nigeria's population was estimated at around 229.5 million. Between 1965 and 2024, the number of people living in Nigeria increased at an average rate of over two percent. In 2024, the population grew by 2.42 percent compared to the previous year. Nigeria is the most populous country in Africa. By extension, the African continent records the highest growth rate in the world. Africa's most populous country Nigeria was the most populous country in Africa as of 2023. As of 2022, Lagos held the distinction of being Nigeria's biggest urban center, a status it also retained as the largest city across all of sub-Saharan Africa. The city boasted an excess of 17.5 million residents. Notably, Lagos assumed the pivotal roles of the nation's primary financial hub, cultural epicenter, and educational nucleus. Furthermore, Lagos was one of the largest urban agglomerations in the world. Nigeria's youthful population In Nigeria, a significant 50 percent of the populace is under the age of 19. The most prominent age bracket is constituted by those up to four years old: comprising 8.3 percent of men and eight percent of women as of 2021. Nigeria boasts one of the world's most youthful populations. On a broader scale, both within Africa and internationally, Niger maintains the lowest median age record. Nigeria secures the 20th position in global rankings. Furthermore, the life expectancy in Nigeria is an average of 62 years old. However, this is different between men and women. The main causes of death have been neonatal disorders, malaria, and diarrheal diseases.

Number and percentage of live births, by month of birth, 1991 to most recent year.