National population projections by age and gender are produced every two years for the UK and each of the UK constituent countries by the Office for National Statistics (ONS) on behalf of the National Statistician and the Registrars General of Scotland and Northern Ireland. Principal Projections are produced based on long-term assumptions about future fertility, mortality and migration levels, with variant projections being produced from various alternative assumptions – usually in the form of high/low variants and their combinations. National population projections provide an estimate of the future size and age structure of the population of Northern Ireland. Population projections are widely used in policy development in areas such as housing, healthcare and education.

The Health Survey Northern Ireland (HSNI) was commissioned by the Department of Health in Northern Ireland and the Central Survey Unit (CSU) of the Northern Ireland Statistics and Research Agency (NISRA) carried out the survey on their behalf. This survey series has been running on a continuous basis since April 2010 with separate modules for different policy areas included in different financial years. It covers a range of health topics that are important to the lives of people in Northern Ireland. The HSNI replaces the previous Northern Ireland Health and Social Wellbeing Survey (available under SNs 4589, 4590 and 5710).

Adult BMI, height and weight measurements, accompanying demographic and derived variables, geography, and a BMI weighting variable, are available in separate datasets for each survey year.

Further information is available from the https://www.nisra.gov.uk/health-survey-northern-ireland" title="Northern Ireland Statistics and Research Agency">Northern Ireland Statistics and Research Agency and the https://www.health-ni.gov.uk/topics/doh-statistics-and-research/health-survey-northern-ireland" title="Department of Health (Northern Ireland)">Department of Health (Northern Ireland) survey webpages.

The 2021 Northern Ireland Census marked the first time since records began where the Catholic share of the population was larger than the combined Protestant share. In 2021, over 42 percent of the population classified themselves as Catholic or from a Catholic background, in comparison with 37 percent classified as Protestant or from a Protestant background. Additionally, the share of the population with no religion (or those who did not answer) was 19 percent; larger than any individual Protestant denomination. This marks a significant shift in demographic and societal trends over the past century, as Protestants outnumbered Catholics by roughly 2:1 when Northern Ireland was established in the 1920s. Given the Catholic community's historic tendency to be in favor of a united Ireland, many look to the changing religious composition of the population when assessing the potential for Irish reunification. Religion's historical influence A major development in the history of British rule in ireland was the Plantation of Ulster in the 1600s, where much of the land in the north (historically the most rebellious region) was seized from Irish Catholics and given to Protestant settlers from Britain (predominantly Scots). This helped establish Protestant dominance in the north, created a large section of the population loyal to the British crown, and saw a distinct Ulster-Scots identity develop over time. In the 1920s, the republican movement won independence for 26 of Ireland's 32 counties, however, the six counties in Ulster with the largest Protestant populations remained part of the UK, as Northern Ireland. Following partition, structural inequalities between Northern Ireland's Protestant and Catholic communities meant that the Protestant population was generally wealthier, better educated, more politically empowered, and had better access to housing, among other advantages. In the 1960s, a civil rights movement then emerged for equal rights and status for both sides of the population, but this quickly turned violent and escalated into a the three-decade long conflict now known as the Troubles.

The Troubles was largely fought between nationalist/republican paramilitaries (mostly Catholic), unionist/loyalist paramilitaries (mostly Protestant), and British security forces (including the police). This is often described as a religious conflict, however it is more accurately described as an ethnic and political conflict, where the Catholic community generally favored Northern Ireland's reunification with the rest of the island, while the Protestant community wished to remain in the UK. Paramilitaries had a large amount of support from their respective communities in the early years of the Troubles, but this waned as the conflict progressed into the 1980s and 1990s. Demographic and societal trends influenced the religious composition of Northern Ireland's population in these decades, as the Catholic community had higher fertility rates than Protestant communities, while the growing secularism has coincided with a decline in those identifying as Protestant - the dip in those identifying as Catholic in the 1970s and 1980s was due to a protest and boycott of the Census. The Troubles came to an end in 1998, and divisions between both sides of the community have drastically fallen, although they have not disappeared completely.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)

-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method.

Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

Abstract copyright UK Data Service and data collection copyright owner.The Health Survey Northern Ireland (HSNI) was commissioned by the Department of Health in Northern Ireland and the Central Survey Unit (CSU) of the Northern Ireland Statistics and Research Agency (NISRA) carried out the survey on their behalf. This survey series has been running on a continuous basis since April 2010 with separate modules for different policy areas included in different financial years. It covers a range of health topics that are important to the lives of people in Northern Ireland. The HSNI replaces the previous Northern Ireland Health and Social Wellbeing Survey (available under SNs 4589, 4590 and 5710).Adult BMI, height and weight measurements, accompanying demographic and derived variables, geography, and a BMI weighting variable, are available in separate datasets for each survey year. Further information is available from the Northern Ireland Statistics and Research Agency and the Department of Health (Northern Ireland) survey webpages. The Health Survey Northern Ireland, 2018-2019 provides a source of information on a wide range of health issues relevant to Northern Ireland. The information collected is pursuing the development of policies aimed at improving the health and well-being of the Northern Ireland population. Main Topics: The 2018-2019 questionnaire covered to following topics:General health and conditionsRestriction of activitiesExperience of Health and Social CareVisits to hospitalGP ModuleMedicines moduleCaring responsibilitiesAntibioticsAttitudes to e-Health servicesHealth literacySocial care and social work workforceWellbeingHealth and lifestylePhysical activityDietary information - 5 a dayFood securityChild healthWarwick-Edinburgh mental wellbeing scaleGHQ12Mental healthStressLonelinessSmokingDrinkingSexual HealthReligion, ethnicity, country of birth, sexual orientationPhysical measurements Simple random sample Face-to-face interview: Computer-assisted (CAPI/CAMI)

The Health Survey Northern Ireland (HSNI) was commissioned by the Department of Health in Northern Ireland and the Central Survey Unit (CSU) of the Northern Ireland Statistics and Research Agency (NISRA) carried out the survey on their behalf. This survey series has been running on a continuous basis since April 2010 with separate modules for different policy areas included in different financial years. It covers a range of health topics that are important to the lives of people in Northern Ireland. The HSNI replaces the previous Northern Ireland Health and Social Wellbeing Survey (available under SNs 4589, 4590 and 5710).

Adult BMI, height and weight measurements, accompanying demographic and derived variables, geography, and a BMI weighting variable, are available in separate datasets for each survey year.

Further information is available from the https://www.nisra.gov.uk/health-survey-northern-ireland" title="Northern Ireland Statistics and Research Agency">Northern Ireland Statistics and Research Agency and the https://www.health-ni.gov.uk/topics/doh-statistics-and-research/health-survey-northern-ireland" title="Department of Health (Northern Ireland)">Department of Health (Northern Ireland) survey webpages.

In 2021, there were 11.6 births per 1,000 people in Northern Ireland, compared with eleven in the previous year. Between 2000 and 2008, Northern Ireland's birth rate increased from 12.8 to 14.4 but started to decline gradually until 2012 when it dropped from 13.9 to 13.3 in just one year. During this provided time period, the birth rate in Northern Ireland was highest in 1971, when it was 20.6 and was at its lowest in 2020 when there were just eleven births per 1,000 people. Falling birth rates in the UK For the United Kingdom as a whole, the birth rate fell to 10.2 births per 1,000 people in 2020, before a slight uptick to 10.4 in 2021. After a postwar peak of 18.8 births per 1,000 people in 1964, the UK birth rate fell sharply to just 11.7 by 1977. Between 1977 and 2012 the birth rate fluctuated between 11.3 and 13.9, but declined in every year between 2012 and 2020. In 2021, the UK's fertility rate (the number of births per women) fell to just 1.53, compared with 2.95 in 1964. Since 1973, the UK has fallen below the minimum replacement level fertility rate of 2.1, and without immigration would likely see its population decline in the long term. Global demographic trends The considerable decline in the UK's fertility rate in recent decades is not an isolated phenomenon. As of 2024, Africa was, at 4.12, the only continent to have a fertility rate higher than the global average of 2.31. Several countries, mainly in East Asia and Europe, have far lower fertility rates than the UK or the global average, however. South Korea provides the most dramatic example of this trend, with its fertility rate falling from 6.33 in 1960 to just 1.11 by 2020. By the 2080s, it is expected that, as Africa's fertility rate converges with the rest of the world, the global population will peak at around 10.4 billion and start to decline.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

A description of the modelling methods used for age and sex structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00646

Projected indicators included are derived from the published 2018-based subnational population projections for England, Wales, Scotland and Northern Ireland up to the year 2043. The indicators are the projected percentage of the population aged 65 years and over, 85 years and over, 0 to 15 years, 16 to 64 years, 16 years to State Pension age, State Pension age and over, median age and the Old Age Dependency Ratio (the number of people of State Pension age per 1000 of those aged 16 years to below State Pension age).

This dataset has been produced by the Ageing Analysis Team for inclusion in the subnational ageing tool, which was published on July 20, 2020 (see link in Related datasets). The tool is interactive, and users can compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu.

Note on data sources: England, Wales, Scotland and Northern Ireland independently publish subnational population projections and the data available here are a compilation of these datasets. The ONS publish national level data for the UK, England, Wales and England & Wales, which has been included. National level data for Scotland and Northern Ireland have been taken from their subnational population projections datasets.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.


Bespoke methods used to produce datasets for specific individual countries are available through the WorldPop Open Population Repository (WOPR) link below. These are 100m resolution gridded population estimates using customized methods ("bottom-up" and/or "top-down") developed for the latest data available from each country. They can also be visualised and explored through the woprVision App.
The remaining datasets in the links below are produced using the "top-down" method, with either the unconstrained or constrained top-down disaggregation method used. Please make sure you read the Top-down estimation modelling overview page to decide on which datasets best meet your needs. Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 3 and 30 arc-seconds (approximately 100m and 1km at the equator, respectively):

- Unconstrained individual countries 2000-2020 ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020.
- Unconstrained individual countries 2000-2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019)
-Unconstrained individual countries 2000-2020 UN adjusted ( 1km resolution ): Consistent 1km resolution population count datasets created using unconstrained top-down methods for all countries of the World for each year 2000-2020 and adjusted to match United Nations national population estimates (UN 2019).
-Unconstrained global mosaics 2000-2020 ( 1km resolution ): Mosaiced 1km resolution versions of the "Unconstrained individual countries 2000-2020" datasets.
-Constrained individual countries 2020 ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020.
-Constrained individual countries 2020 UN adjusted ( 100m resolution ): Consistent 100m resolution population count datasets created using constrained top-down methods for all countries of the World for 2020 and adjusted to match United Nations national population estimates (UN 2019).

Older datasets produced for specific individual countries and continents, using a set of tailored geospatial inputs and differing "top-down" methods and time periods are still available for download here: Individual countries and Whole Continent.

Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00645

The total population in Ireland was forecast to continuously increase between 2024 and 2029 by in total 0.3 million people (+5.54 percent). After the tenth consecutive increasing year, the total population is estimated to reach 5.72 million people and therefore a new peak in 2029. Notably, the total population was continuously increasing over the past years.According to the International Monetary Fund, the total population of a country consists of all persons falling within the scope of the census.Find more statistics on other topics about Ireland with key insights such as the gross domestic product per capita, the average inflation rate, and the budget balance in relation to the gross domestic product.

Projected indicators included are derived from the published 2018-based subnational population projections for England, Wales, Scotland and Northern Ireland up to the year 2043. The indicators are the projected sex ratio for those aged 65 years and over and the projected sex ratio for those aged 85 years and over. A sex ratio shows the number of males in the population for every 100 females.

This dataset has been produced by the Ageing Analysis Team for inclusion in the subnational ageing tool, which was published on July 20, 2020 (see link in Related datasets). The tool is interactive, and users can compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu.

Note on data sources: England, Wales, Scotland and Northern Ireland independently publish subnational population projections and the data available here are a compilation of these datasets. The ONS publish national level data for the UK, England, Wales and England & Wales, which has been included. National level data for Scotland and Northern Ireland have been taken from their subnational population projections datasets.

4,9 (Rate) in 2018.

Background
The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.

Longitudinal data
The LFS retains each sample household for five consecutive quarters, with a fifth of the sample replaced each quarter. The main survey was designed to produce cross-sectional data, but the data on each individual have now been linked together to provide longitudinal information. The longitudinal data comprise two types of linked datasets, created using the weighting method to adjust for non-response bias. The two-quarter datasets link data from two consecutive waves, while the five-quarter datasets link across a whole year (for example January 2010 to March 2011 inclusive) and contain data from all five waves. A full series of longitudinal data has been produced, going back to winter 1992. Linking together records to create a longitudinal dimension can, for example, provide information on gross flows over time between different labour force categories (employed, unemployed and economically inactive). This will provide detail about people who have moved between the categories. Also, longitudinal information is useful in monitoring the effects of government policies and can be used to follow the subsequent activities and circumstances of people affected by specific policy initiatives, and to compare them with other groups in the population. There are however methodological problems which could distort the data resulting from this longitudinal linking. The ONS continues to research these issues and advises that the presentation of results should be carefully considered, and warnings should be included with outputs where necessary.

New reweighting policy
Following the new reweighting policy ONS has reviewed the latest population estimates made available during 2019 and have decided not to carry out a 2019 LFS and APS reweighting exercise. Therefore, the next reweighting exercise will take place in 2020. These will incorporate the 2019 Sub-National Population Projection data (published in May 2020) and 2019 Mid-Year Estimates (published in June 2020). It is expected that reweighted Labour Market aggregates and microdata will be published towards the end of 2020/early 2021.

LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned. However, volumes are updated periodically by ONS, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.

Additional data derived from the QLFS
The Archive also holds further QLFS series: End User Licence (EUL) quarterly data; Secure Access datasets; household datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.

Variables DISEA and LNGLST
Dataset A08 (Labour market status of disabled people) which ONS suspended due to an apparent discontinuity between April to June 2017 and July to September 2017 is now available. As a result of this apparent discontinuity and the inconclusive investigations at this stage, comparisons should be made with caution between April to June 2017 and subsequent time periods. However users should note that the estimates are not seasonally adjusted, so some of the change between quarters could be due to seasonality. Further recommendations on historical comparisons of the estimates will be given in November 2018 when ONS are due to publish estimates for July to September 2018.

An article explaining the quality assurance investigations that have been conducted so far is available on the ONS Methodology webpage. For any queries about Dataset A08 please email Labour.Market@ons.gov.uk.

Occupation data for 2021 and 2022 data files

The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/articles/revisionofmiscodedoccupationaldataintheonslabourforcesurveyuk/january2021toseptember2022" style="background-color: rgb(255, 255, 255);">Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.

2022 Weighting

The population totals used for the latest LFS estimates use projected growth rates from Real Time Information (RTI) data for UK, EU and non-EU populations based on 2021 patterns. The total population used for the LFS therefore does not take into account any changes in migration, birth rates, death rates, and so on since June 2021, and hence levels estimates may be under- or over-estimating the true values and should be used with caution. Estimates of rates will, however, be robust.

Latest edition information

For the third edition (February 2025), the data file was resupplied with the 2024 weighting variable included (LGWT24).

Abstract copyright UK Data Service and data collection copyright owner.The Annual Population Survey (APS) is a major survey series, which aims to provide data that can produce reliable estimates at the local authority level. Key topics covered in the survey include education, employment, health and ethnicity. The APS comprises key variables from the Labour Force Survey (LFS), all its associated LFS boosts and the APS boost. The APS aims to provide enhanced annual data for England, covering a target sample of at least 510 economically active persons for each Unitary Authority (UA)/Local Authority District (LAD) and at least 450 in each Greater London Borough. In combination with local LFS boost samples, the survey provides estimates for a range of indicators down to Local Education Authority (LEA) level across the United Kingdom.For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.Occupation data for 2021 and 2022The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. The affected datasets have now been updated. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022APS Well-Being DatasetsFrom 2012-2015, the ONS published separate APS datasets aimed at providing initial estimates of subjective well-being, based on the Integrated Household Survey. In 2015 these were discontinued. A separate set of well-being variables and a corresponding weighting variable have been added to the April-March APS person datasets from A11M12 onwards. Further information on the transition can be found in the Personal well-being in the UK: 2015 to 2016 article on the ONS website.APS disability variablesOver time, there have been some updates to disability variables in the APS. An article explaining the quality assurance investigations on these variables that have been conducted so far is available on the ONS Methodology webpage. End User Licence and Secure Access APS dataUsers should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to: age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family nationality and country of origin geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district health: including main health problem, and current and past health problems education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from system variables: including week number when interview took place and number of households at address The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. Latest Edition InformationFor the fourth edition (October 2019), a new version of the data file was deposited, including the 2018 weighting variable and the Northern Ireland boost sample. Main Topics:Topics covered include: household composition and relationships, housing tenure, nationality, ethnicity and residential history, employment and training (including government schemes), workplace and location, job hunting, educational background and qualifications. Many of the variables included in the survey are the same as those in the LFS. Multi-stage stratified random sample Face-to-face interview Telephone interview 2017 2018 ACADEMIC ACHIEVEMENT ADULT EDUCATION AGE APPLICATION FOR EMP... APPOINTMENT TO JOB ATTITUDES BONUS PAYMENTS COHABITATION COMMUTING CONDITIONS OF EMPLO... DEBILITATIVE ILLNESS DEGREES DISABILITIES Demography population ECONOMIC ACTIVITY EDUCATIONAL BACKGROUND EDUCATIONAL COURSES EMPLOYEES EMPLOYER SPONSORED ... EMPLOYMENT EMPLOYMENT HISTORY EMPLOYMENT PROGRAMMES EMPLOYMENT SERVICES ETHNIC GROUPS FAMILY BENEFITS FIELDS OF STUDY FULL TIME EMPLOYMENT FURNISHED ACCOMMODA... GENDER HEADS OF HOUSEHOLD HIGHER EDUCATION HOME BASED WORK HOME OWNERSHIP HOURS OF WORK HOUSEHOLDS HOUSING HOUSING BENEFITS HOUSING TENURE INCOME INDUSTRIES JOB CHANGING JOB HUNTING JOB SEEKER S ALLOWANCE LANDLORDS LONGTERM UNEMPLOYMENT Labour and employment MANAGERS MARITAL STATUS MATERNITY BENEFITS NATIONAL IDENTITY NATIONALITY OCCUPATIONAL TRAINING OCCUPATIONS OLD AGE BENEFITS OVERTIME PART TIME COURSES PART TIME EMPLOYMENT PLACE OF BIRTH PLACE OF RESIDENCE PRIVATE SECTOR PUBLIC SECTOR QUALIFICATIONS RECREATIONAL EDUCATION RECRUITMENT REDUNDANCY REDUNDANCY PAY RELIGIOUS AFFILIATION RENTED ACCOMMODATION RESIDENTIAL MOBILITY SELF EMPLOYED SICK LEAVE SICK PAY SICKNESS AND DISABI... SOCIAL HOUSING SOCIAL SECURITY BEN... SOCIO ECONOMIC STATUS STATE RETIREMENT PE... SUBSIDIARY EMPLOYMENT SUPERVISORS SUPERVISORY STATUS TAX RELIEF TEMPORARY EMPLOYMENT TERMINATION OF SERVICE TIED HOUSING TRAINING TRAINING COURSES TRAVELLING TIME UNEMPLOYED UNEMPLOYMENT UNEMPLOYMENT BENEFITS UNFURNISHED ACCOMMO... UNWAGED WORKERS WAGES WELL BEING HEALTH WELL BEING SOCIETY WELSH LANGUAGE WORKING CONDITIONS WORKPLACE vital statistics an...

Abstract

The Future of Business Survey is a new source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the monthly survey - a partnership between Facebook, OECD, and The World Bank - provides a timely pulse on the economic environment in which businesses operate and who those businesses are to help inform decision-making at all levels and to deliver insights that can help businesses grow. The Future of Business Survey provides a perspective from newer and long-standing digitalized businesses and provides a unique window into a new mobilized economy.

Policymakers, researchers and businesses share a common interest in the environment in which SMEs operate, as well their outlook on the future, not least because young and innovative SMEs in particular are often an important source of considerable economic and employment growth. Better insights and timely information about SMEs improve our understanding of economic trends, and can provide new insights that can further stimulate and help these businesses grow.

To help provide these insights, Facebook, OECD and The World Bank have collaborated to develop a monthly survey that attempts to improve our understanding of SMEs in a timely and forward-looking manner. The three organizations share a desire to create new ways to hear from businesses and help them succeed in the emerging digitally-connected economy. The shared goal is to help policymakers, researchers, and businesses better understand business sentiment, and to leverage a digital platform to provide a unique source of information to complement existing indicators.

With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

Geographic coverage

Argentina Australia Belgium Brazil Canada Colombia Egypt France Germany Ghana India Indonesia Ireland Israel Italy Kenya Mexico Nigeria Pakistan Philippines (the) Poland Portugal Russian Federation (the) South Africa Spain Taiwan Turkey United Kingdom of Great Britain and Northern Ireland (the) United States of America (the) Viet Nam

Analysis unit

The study describes small and medium-sized enterprises.

Universe

The target population consists of SMEs that have an active Facebook business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

Kind of data

Sample survey data [ssd]

Sampling procedure

Twice a year in over 97 countries, the Facebook Survey Team sends the Future of Business to admins and owners of Facebook-designated small business pages. When we share data from this survey, we anonymize responses to all survey questions and only share country-level data publicly. To achieve better representation of the broader small business population, we also weight our results based on known characteristics of the Facebook Page admin population.

A random sample of firms, representing the target population in each country, is selected to respond to the Future of Business Survey each month.

Mode of data collection

Internet [int]

Research instrument

The survey includes questions about perceptions of current and future economic activity, challenges, business characteristics and strategy. Custom modules include questions related to regulation, access to finance, digital payments, and digital skills. The full questionnaire is available for download.

Response rate

Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.

Note: Response rates are calculated as the number of respondents who completed the survey divided by the total number of SMEs invited.

Sampling error estimates

Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:

Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.

Other factors beyond sampling error that contribute to such potential differences are frame or coverage error (sampling frame of page owners does not include all relevant businesses but also may include individuals that don't represent businesses), and nonresponse error.

Note that the sample is meant to reflect the population of businesses on Facebook, not the population of small businesses in general. This group of digitized SMEs is itself a community worthy of deeper consideration and of considerable policy interest. However, care should be taken when extrapolating to the population of SMEs in general. Moreover, future work should evaluate the external validity of the sample. Particularly, respondents should be compared to the broader population of SMEs on Facebook, and the economy as a whole.

3,7 (Rate) in 2018.

There are two sets of data exploring people's attitudes in Northern Ireland towards different types of Brexit and their possible consequences on political stability and peace. The survey data is a representative sample of 1,012 people from across Northern Ireland were interviewed by Ipsos-MORI in face-to-face computer-assisted interviews between 9 February and 12 March 2018. A two-stage sampling design was used, with random selection of geographic sampling points and quotas set for each sampling point based on the latest socio-demographic census estimates to ensure that the respondents were statistically representative of the Northern Ireland population regarding traits such as age, gender, religion of origin, geographical location, and social class. The deliberative forum data studies 48 people from across Northern Ireland took part in a deliberative forum in which they received expert presentations and discussed the possible impact on Northern Ireland of the UK’s exit from the EU. This deliberative forum took place on 10 February 2018 at the Clayton Hotel in Belfast. Ipsos MORI recruited the 48 participants to be broadly representative of the Northern Ireland population in their socio-demographic backgrounds and geographic residences. Importantly, the sample was broadly balanced between those who had voted Leave and those who had voted Remain in the 2016 referendum. The participants’ roundtable discussions in the morning and afternoon were recorded and transcribed. Participants also completed questionnaires, from which survey data are provided.

A follow up survey experiment was conducted in 2019 to test the effect of imagined dialogue on inter-group attitudes. In the first wave (March-April 2019), the experimental treatment involved participants engaging in an imagined conversation about a controversial political issue with someone holding the opposite view; participants randomly assigned to the control condition were asked to imagine having a conversation about a benign non-political issue with someone holding an opposite political viewpoint. The survey experiment was conducted using representative samples in three political contexts: Northern Ireland (unionists/nationalists; N = 1,263), Great Britain (Remainers/Leavers; N = 1,879), and the USA (pro-life/pro-choice; N = 1,217). A second wave of the experiment (June-July 2019) used the same design but addressed partisan divisions rather than divisions over political issues in Northern Ireland (SF/DUP supporters; N = 806), Great Britain (Conservative/Labour supporters; N = 839) and the USA (Democrats/Republicans; N = 836).

Peace and stability in any society is dependent upon citizen acceptance of the legitimacy of political and legal arrangements, and particularly so in Northern Ireland where peaceful politics is a recent outcome of a long and difficult 'peace process'. Knowing the likely level and intensity of perceived illegitimacy (non-acceptability) of different possible border arrangements after the UK leaves the EU would provide policy makers with crucial evidence when evaluating the relative merits of different border options, particularly with respect to the criteria of political sustainability and likely impact on peace and stability in Northern Ireland. With Northern Ireland's politicians engaged in political campaigning in an Assembly election and likely impending inter-party talks to re-establish a power sharing executive, it is arguably particularly important that there is a systematic reporting of the considered views of citizens on this crucial issue of the UK's exit from the EU. We conduct two "deliberative democracy" exercises which allow Northern Ireland citizens the space and relevant information to consider the challenging issue of Brexit and the border. Once they have become informed about the issues and reflected upon them, we ask the citizens to put forward their own views. We are focused on answering the following questions. How difficult would it be for Catholics/nationalists to accept a policed North/South border and what level of protest would they condone? How difficult would it be for Protestants/unionists to accept a policed East/West border and what level of protest would they condone? We seek to provide policy makers with evidence-based answers to the these questions. This evidence will prove to be especially useful when policy makers are considering the likely implications of the post-Brexit border for peace and stability in Northern Ireland. We generate a report which summarises our key findings and presents our key evidence. We also produce a short animated film which gets across to the viewer in a dramatic, simple and exciting way our key findings. We engage enthusiastically in submissions to the key committees, bodies and specific politicians who have responsibility for negotiating the UK exit from the EU. We contribute to their work by highlighting the likely implications, for peace and stability in Northern...

Abstract copyright UK Data Service and data collection copyright owner.

The Continuous Household Survey (CHS) is one of the largest continuous surveys carried out in Northern Ireland. The survey is designed, conducted and analysed by the Central Survey Unit of the Northern Ireland Statistics and Research Agency (NISRA). It is based on a sample of the general population resident in private households and has been running since 1983. The Survey is designed to provide a regular source of information on a wide range of social and economic issues relevant to Northern Ireland. The CHS is an important source of information in Northern Ireland and is used by many Government departments and Agencies. Regular clients include the Departments of Enterprise, Trade and Investment, Culture Arts and Leisure, Regional Developments, Environment, Education, Employment and Learning and NISRA.

Further information about the series, including methodology, may be found on the NISRA Central Survey Unit (CSU) Continuous Household Survey web pages.

The main topics covered in the survey include demographic, personal, family and household information, religion, mobile phone/internet access, education, adult health, smoking, drinking, employment, tourism, culture, languages, arts and leisure activities, environment, and benefits. There were also questions asked at a household level on tenure, internet and care access, domestic tourism, children sports, arts, play facilities, education, travel to school, and environmental issues and actions taken.