The median annual earnings for full-time employees in the United Kingdom was approximately 37,430 British pounds in 2024, compared with 34,963 pounds in the previous year. At the start of the provided time period, in 1999, the average full-time salary in the UK was 17,803 pounds per year, with median earnings exceeding 20,000 pounds per year in 2002, and 30,000 by 2019. Wages continue to grow faster than inflation in 2024 Between November 2021 and July 2023 inflation was higher than wage growth in the UK, with wages still outpacing inflation as of April 2024. At the peak of the recent wave of high inflation in October 2022, the CPI inflation rate reached a 41-year-high of 11.1 percent, wages were growing much slower at 6.1 percent. Since that peak, inflation remained persistently high for several months, only dropping below double figures in April 2023, when inflation was 8.7 percent, down from 10.1 percent in the previous month. For 2023 as a whole, the average annual rate of inflation was 7.3 percent but is forecast to fall to 2.2 percent in 2024, and 1.5 percent in 2025. Highest and lowest-paid occupations As of 2023, the highest-paid occupation in the UK was that of Chief Executives and Senior Officials, who had an average weekly pay of approximately, 1,576 pounds. By contrast, the lowest-paid occupation that year was that of retail cashiers, and check-out operators, who earned approximately 383 pounds a week. For industry sectors as a whole, people who worked full-time in the electricity, gas, steam and air conditioning supply sector had the highest average earnings, at 955 pounds a week, compared with 505 pounds a week in the accommodation and food services sector, the lowest average earnings in 2023.

Wages in the United Kingdom decreased to 711 GBP/Week in January from 712 GBP/Week in December of 2024. This dataset provides - United Kingdom Average Weekly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Average weekly earnings, UK, monthly.

Abstract copyright UK Data Service and data collection copyright owner.

The New Earnings Survey is almost certainly the most detailed and comprehensive earnings series anywhere in the world. It is a one in a hundred sample survey of employees in Britain, giving information on aspects of earnings and employment based on a week in April each year. The NES enquiry is conducted by the Department of Employment under the provisions of the Statistics of Trade Act (1947). Under the terms of this Act, data so obtained and relating solely to any individual may not be released into the public domain. All the data described here are in a form that ensures that there is no disclosure of individual information. They have been processed into a minimally aggregated form approved by the Department of Employment: any data record released relates to an aggregate of not less than three individuals.
Main Topics:
The dataset consists of fourteen separate extract data files from the original New Earnings Survey files held by the Department of Employment. Each extract file had been constructed to allow investigation of a particular aspect of the data contained in the Survey, as follows:
AGG01 National Collective Agreements
AGG02 Manual Skill Differentials
AGG03 Regional Implications
AGG04 Age implications
AGG05 Dispersion of Pay within Occupations
AGG06 Shiftwork
AGG07 Pay in relation to hours worked
AGG08 Public/Private Sector Pay Movements
AGG09 White Collar Pay Movements
AGG10 Sex Differentials
AGG11 Incentive Pay and Payment Schemes
AGG12 Incentive Payment Schemes and Age
AGG14 Pay in Relation to Size of Company and Plant
AGG15 Pay in Relation to Company Size and Region
Eight of the aggregate files (numbers 2,3,4,5,7,8,9 and 10) relate to dimensions recorded in the Survey in each year and comprise 13 annual files, one for each year 1970-1982. A further two aggregate files (numbers 1 and 6) contain 10 annual files for the years 1973-1982 inclusive, omitting the years 1970-1972, AGG01, due to the introduction of new occupations codes in 1973, and AGG06 due to the lack of shift pay premium prior to 1973. The remaining four files (numbers 11,12,14 and 15) relate to a single year only and are based on the special question included in that year.

The United Kingdom's economy grew by 0.9 percent in 2024, after a growth rate of 0.4 percent in 2023, 4.8 percent in 2022, 8.6 percent in 2021, and a record 10.3 percent fall in 2020. During the provided time period, the biggest annual fall in gross domestic product before 2020 occurred in 2009, when the UK economy contracted by 4.6 percent at the height of the global financial crisis of the late 2000s. Before 2021, the year with the highest annual GDP growth rate was 1973, when the UK economy grew by 6.5 percent. UK economy growing but GDP per capita falling In 2022, the UK's GDP per capita amounted to approximately 37,371 pounds, with this falling to 37,028 pounds in 2023, and 36,977 pounds in 2024. While the UK economy as a whole grew during this time, the UK's population grew at a faster rate, resulting in the negative growth in GDP per capita. This suggests the UK economy's struggles with productivity are not only stagnating, but getting worse. The relatively poor economic performance of the UK in recent years has not gone unnoticed by the electorate, with the economy consistently seen as the most important issue for voters since 2022. Recent shocks to UK economy In the second quarter of 2020, the UK economy shrank by a record 20.3 percent at the height of the COVID-19 pandemic. Although there was a relatively swift economic recovery initially, the economy has struggled to grow much beyond its pre-pandemic size, and was only around 3.1 percent larger in December 2024, when compared with December 2019. Although the labor market has generally been quite resilient during this time, a long twenty-month period between 2021 and 2023 saw prices rise faster than wages, and inflation surge to a high of 11.1 percent in October 2022.

This statistic shows the ratio of house prices to household income in the United Kingdom from 1976 to 2016. In 1976 the ratio of house prices to household income was 2.64. This has risen to 4.54 in 2016. The lowest ratio at any point in this statistic was 2.23 in 1996.

Abstract copyright UK Data Service and data collection copyright owner.

The 1970 British Cohort Study (BCS70) is a longitudinal birth cohort study, following a nationally representative sample of over 17,000 people born in England, Scotland and Wales in a single week of 1970. Cohort members have been surveyed throughout their childhood and adult lives, mapping their individual trajectories and creating a unique resource for researchers. It is one of very few longitudinal studies following people of this generation anywhere in the world.

Since 1970, cohort members have been surveyed at ages 5, 10, 16, 26, 30, 34, 38, 42, 46, and 51. Featuring a range of objective measures and rich self-reported data, BCS70 covers an incredible amount of ground and can be used in research on many topics. Evidence from BCS70 has illuminated important issues for our society across five decades. Key findings include how reading for pleasure matters for children's cognitive development, why grammar schools have not reduced social inequalities, and how childhood experiences can impact on mental health in mid-life. Every day researchers from across the scientific community are using this important study to make new connections and discoveries.

BCS70 is run by the Centre for Longitudinal Studies (CLS), a research centre in the UCL Institute of Education, which is part of University College London. The content of BCS70 studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from BCS70 that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets
Secure Access versions of BCS70 have more restrictive access conditions than versions available under the standard End User Licence (EUL).

SN 9115 - 1970 British Cohort Study: Sweeps 1-11, 1970-2024: Secure Access currently includes sensitive survey data from Sweep 10 and 11, as well as Activity Histories data.

Researchers applying for access to the Secure Access BCS70 datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the BCS70 Series Access web page).

Latest edition information
For the third edition (March 2025), sensitive data from the Sweep 11, age 51 survey have been added.

Main Topics:

The study currently includes restricted files containing sensitive data for the following:

• sweep 10: details of any children of the respondent, born alive but since died and not already recorded in the person grids
• sweep 10: details of any pregnancies which resulted in a still-birth, miscarriage or termination (female respondents only)
• up to sweep 10: employment history data of respondents, including more detailed SIC and SOC codes than available under EUL
• sweep 11 data files on benefits, debts, employment, housing, pregnancies, regular income, savings, and a core sweep 11 data file that also covers health and emigration.

Abstract copyright UK Data Service and data collection copyright owner.

The Family Expenditure Survey (FES), which closed in 2001, was a continuous survey with an annual sample of around 10,000 households. They provided information on household and personal incomes, certain payments that recurred regularly (e.g. rent, gas and electricity bills, telephone accounts, insurances, season tickets and hire purchase payments), and maintained a detailed expenditure record for 14 consecutive days.

The original purpose of the FES was to provide information on spending patterns for the United Kingdom Retail Price Index (RPI). The survey was a cost-efficient way of collecting a variety of related data that the government departments required to correlate with income and expenditure at the household, tax unit and person levels. The annual FES began in 1957 (with an earlier large scale survey conducted in 1953/54) and was one of the first Department of Employment (DE) systems to be computerised in the early 1960s. The UKDA holds FES data from 1961-2001. The Northern Ireland Family Expenditure Survey (NIFES), which ran from 1967-1998, was identical to the UK FES and therefore used the same questionnaires and documentation. However, starting in 1988, a voluntary question on religious denomination was asked of those aged 16 and over in Northern Ireland. The UKDA holds NIFES data from 1968-1998, under GN 33240.

Significant FES developments over time include:

• 1968: the survey was extended to include a sample drawn from the Northern Ireland FES and a new computer system was introduced which was used until 1985
• 1986: DE and the Office of Population Censuses and Surveys (OPCS) converted the FES into a new database system using the SIR package
• 1989: the Central Statistical Office (CSO) took over responsibility for the survey
• 1994: in April, computerised personal interviewing was introduced using lap-top computers, the database system changed to INGRES and the survey changed from a calendar year to financial year basis
• 1996: in April, OPCS and CSO were amalgamated into the Office for National Statistics (ONS), who assumed responsibility for the FES
• 1998: from April onwards information from expenditure diaries kept by children aged 7 to 15 was included in data, and grossing factors were made available on the database

From 2001, the both the FES and the National Food Survey (NFS) (held at the UKDA under GN 33071) were completely replaced by a new survey, the Expenditure and Food Survey (EFS). Prior to the advent of the EFS, there had previously been considerable overlap between the FES and NFS, with both surveys asking respondents to keep a diary of expenditure. Thus, the 2000-2001 FES was the final one in the series. The design of the new EFS was based on the previous FES; further background to its development may be found in the 1999-2000 and 2000-2001 Family Spending reports. From 2008, the EFS became the Living Costs and Food Survey (LCF) (see under GN 33334).


Main Topics:
Household Schedule:
This schedule was taken at the main interview. Information for most of the questions was obtained from the head of household or housewife, but certain questions of a more individual character were put to every spender aged 15 or over (or 16 or over from 1973 onwards). Until the introduction of the community charge, information on rateable value and rate poundage was obtained from the appropriate local authority, as was information on whether the address was within a smokeless zone. Information was collected about the household, the sex and age of each member, and also details about the type and size of the household accommodation. The main part of the questionnaire related to expenditure both of a household and individual nature, but the questions were mainly confined to expenses of a recurring nature, e.g.:

• Household: housing costs, payment to Gas and Electricity Boards or companies, telephone charges, licences and television rental
• Individual: motor vehicles, season tickets for transport, life and accident insurances, payments through a bank, instalments, refund of expenses by employer, expenditure claimed by self-employed persons as business expenses for tax purposes, welfare foods, education grants and fees

Income Schedule:
Data were collected for each household spender. The schedule was concerned with income, national insurance contributions and income tax. Income of a child not classed as a spender was obtained from one or other of his parents and entered on the parent's questionnaire. Information collected included: employment status and recent absences from work, earnings of an employee, self-employed earnings, National Insurance contributions, pensions and other regular allowances, occasional benefits - social security benefits and other...

Affordability ratios calculated by dividing house prices by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

United Kingdom UK: GDP: Net Current Transfer from Abroad data was reported at -24,349.000 GBP mn in 2016. This records an increase from the previous number of -24,699.000 GBP mn for 2015. United Kingdom UK: GDP: Net Current Transfer from Abroad data is updated yearly, averaging -4,642.299 GBP mn from Dec 1970 (Median) to 2016, with 36 observations. The data reached an all-time high of 522.682 GBP mn in 1986 and a record low of -26,863.000 GBP mn in 2013. United Kingdom UK: GDP: Net Current Transfer from Abroad data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Gross Domestic Product: Nominal. Current transfers comprise transfers of income between residents of the reporting country and the rest of the world that carry no provisions for repayment. Net current transfers from abroad is equal to the unrequited transfers of income from nonresidents to residents minus the unrequited transfers from residents to nonresidents. Data are in current local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ;

United Kingdom UK: GDP: GNI per Capita data was reported at 30,358.815 GBP in 2017. This records an increase from the previous number of 29,217.036 GBP for 2016. United Kingdom UK: GDP: GNI per Capita data is updated yearly, averaging 12,892.396 GBP from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 30,358.815 GBP in 2017 and a record low of 1,042.209 GBP in 1970. United Kingdom UK: GDP: GNI per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Gross Domestic Product: Nominal. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ;

Abstract copyright UK Data Service and data collection copyright owner.

The Northern Ireland Family Expenditure Survey (NIFES) was conducted in Northern Ireland from 1967-1998, and was the counterpart to the Family Expenditure Survey (FES), which was conducted annually in Great Britain from 1957-2001 (see under GN 33057). The FES/NIFES provided reliable data on expenditure and income in relation to household characteristics. The results of the survey show how expenditure patterns of different kinds of households vary, and the extent to which individual members of a household contribute to the household income. Although originally commissioned to provide expenditure details for the calculation of weights for the Retail Price Index, the FES/NIFES collected much additional information was also collected on the characteristics of co-operating households and the incomes of their members. It thus became a multi-purpose survey, and provided a unique fund of important economic and social data.

From 1968 the Great Britain FES incorporated a sample drawn from the NIFES to become the UK FES. The FES was replaced in 2001 by a new survey series, the Expenditure and Food Survey (EFS) (see under GN 33334), covering the whole of the UK. The EFS is an amalgamation of the previous National Food Survey (NFS) (see under GN 33071) and UK FES.


Main Topics:
Household Schedule:
This schedule was taken at the main interview. Information for most of the questions was obtained from the head of household or housewife, but certain questions of a more individual character were put to every spender aged 15 or over (or 16 or over from 1973 onwards). Until the introduction of the community charge, information on rateable value and rate poundage was obtained from the appropriate local authority, as was information on whether the address was within a smokeless zone. Information was collected about the household, the sex and age of each member, and also details about the type and size of the household accommodation. The main part of the questionnaire related to expenditure both of a household and individual nature, but the questions were mainly confined to expenses of a recurring nature, e.g.:

• Household: housing costs, payment to Gas and Electricity Boards and companies, telephone charges, licences and television rental
• Individual: motor vehicles, season tickets for transport, life and accident insurances, payments through a bank, instalments, refund of expenses by employer, expenditure claimed by self-employed persons as business expenses for tax purposes, welfare foods, education grants and fees

Income Schedule:
Data were collected for each household spender. Apart from page 1, the schedule was concerned with income, National Insurance contributions and income tax. Income of a child not classed as a spender was obtained from one or other of his parents and entered on the parent's questionnaire. Information collected included: employment status and recent absences from work, earnings of an employee, self-employed earnings, National Insurance contributions, pensions and other regular allowances, occasional benefits - social security benefits and other types, investment income, miscellaneous earnings of a 'once-only' character, tax paid directly to Inland Revenue or refunded, income of a child.

Diary Records
Each diary covered fourteen days. Each household member aged 15 or over (or 16 or over from 1973 onwards) was asked to record all expenditure made during the 14 days.

The NIFES was identical to the UK FES and therefore used the same questionnaires and documentation. However, starting in 1988, a voluntary question on religious denomination was asked of those aged 16 and over in Northern Ireland.

United Kingdom UK: GDP: 2010 Price: USD: Gross National Income data was reported at 2,711.810 USD bn in 2016. This records an increase from the previous number of 2,655.347 USD bn for 2015. United Kingdom UK: GDP: 2010 Price: USD: Gross National Income data is updated yearly, averaging 1,662.701 USD bn from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 2,711.810 USD bn in 2016 and a record low of 994.237 USD bn in 1970. United Kingdom UK: GDP: 2010 Price: USD: Gross National Income data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Gross Domestic Product: Real. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2010 U.S. dollars.; ; World Bank national accounts data, and OECD National Accounts data files.; Gap-filled total;

United Kingdom UK: GDP: USD: Net Income from Abroad data was reported at -31.229 USD bn in 2016. This records an increase from the previous number of -39.334 USD bn for 2015. United Kingdom UK: GDP: USD: Net Income from Abroad data is updated yearly, averaging -358.819 USD mn from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 59.316 USD bn in 2005 and a record low of -39.334 USD bn in 2015. United Kingdom UK: GDP: USD: Net Income from Abroad data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Gross Domestic Product: Nominal. Net income includes the net labor income and net property and entrepreneurial income components of the SNA. Labor income covers compensation of employees paid to nonresident workers. Property and entrepreneurial income covers investment income from the ownership of foreign financial claims (interest, dividends, rent, etc.) and nonfinancial property income (patents, copyrights, etc.). Data are in current U.S. dollars.; ; World Bank national accounts data, and OECD National Accounts data files.; ;

This deposit contains three do files which were constructed as part of the project “Intergenerational income mobility: Gender, Partnerships and Poverty in the UK”, UKRI grant number ES/P007899/1. The aim of the do files is to convert partnership, fertility, and labour market activity information provided with the age 46 wave of the British Cohort Study (BCS70) into monthly panel format. There are separate do files to do this for each of the three aspects.

This important new work looks to fill an 'evidence deficit' within the literature on intergenerational economic mobility by investigating intergenerational income mobility for two groups who are often overlooked in existing research: women and the poorest in society. To do this, the research will make two methodological advancements to previous work: First, moving to focus on the family unit in the second generation and total family resources rather than individual labour market earnings and second, looking across adulthood to observe partnership, fertility and poverty dynamics rather than a point-in-time static view of these important factors.

Specifically it will ask four research questions:

1) What is the relationship between family incomes of parents in childhood and family incomes of daughters throughout adulthood? The majority of previous studies of intergenerational income mobility have focused on the relationship between parents' income in childhood and sons' prime-age labour market earnings. Women have therefore been consistently disregarded due to difficulties observing prime-age labour market earnings for women. This is because women often exit the labour market for fertility reasons, and the timing of this exit and the duration of the spell out of the labour market are related to both parental childhood income and current labour market earnings. This means that previous studies that have focused on employed women only are not representative of the entire population of women. By combining our two advancements, considering total family income and looking across adulthood for women, we can minimise these issues. The life course approach enables us to observe average resources across a long window of time, dealing with issues of temporary labour market withdrawal, while the use of total family income gives the most complete picture of resources available to the family unit including partner's earnings and income from other sources, including benefits.

2) What role do partnerships and assortative mating play in this process across the life course? The shift to focusing on the whole family unit emphasises the importance of partnerships including when they occur and breakdown and who people partner with in terms of education and current labour market earnings. Previous research on intergenerational income mobility in the UK has suggested an important role for who people partner with but has been limited to only focusing on those in partnerships. This work will advance our understanding of partnership dynamics by looking across adulthood at both those in partnerships and at the importance of family breakdown and lone parenthood in this relationship.

3) What is the extent of intergenerational poverty in the UK, and does this persist through adulthood? The previous focus on individuals' labour market earnings has often neglected to consider intergenerational income mobility for the poorest in society: those without labour market earnings for lengthy periods of time who rely on other income from transfers and benefits. The shift in focus to total family resources and the life course approach will allow us to assess whether those who grew up in poor households are more likely to experience persistent poverty themselves in adulthood.

4) What is the role of early skills, education and labour market experiences, including job tenure and progression, in driving these newly estimated relationships? Finally our proposed work will consider the potential mechanisms for these new estimates of intergenerational income mobility for women and the poorest in society for the first time and expand our understanding of potential mechanisms for men. While our previous work showed the importance of early skills and education in transmitting inequality across generations for males, this new work will also consider the role of labour market experiences including job tenure and promotions as part of the process.

A dataset, 1970-2009, containing equivalently defined variables for the British Household Panel Study (BHPS), the Household Income and Labour Dynamics in Australia (HILDA), the Korea Labor and Income Panel Study (KLIPS) (new this year), the Panel Study of Income Dynamics (PSID), the Russia Longitudinal Monitoring Survey (RLMS-HSE) (new this year), the Swiss Household Panel (SHP), the Canadian Survey of Labour and Income Dynamics (SLID), and the German Socio-Economic Panel (SOEP). The data are designed to allow cross-national researchers not experienced in panel data analysis to access a simplified version of these panels, while providing experienced panel data users with guidelines for formulating equivalent variables across countries. The CNEF permit researchers to track yearly changes in the health and economic well-being of older people relative to younger people in the study countries. The equivalent file provides a set of constructed variables (for example pre- and post-government income and United States and international household equivalence weights) that are not directly available on the original surveys. Since the Cross-National Equivalent File 1970-2009 can be merged with the original surveys, PSID-CNEF users can easily incorporate these constructed variables into current analyses. The most recent release of the Equivalent File includes: * BHPS data from 1991 to 2005 on over 21,000 individuals and approximately 6,000 households. * GSOEP data from 1984 to 2007 on over 20,000 individuals and approximately 6,000 households in Germany. * HILDA data from 2001 to 2006 on over 19,000 individuals and 7,000 households. * PSID data from 1980 to 2005 on over 33,000 individuals and approximately 7,000 households. * SHP data from 1999 to 2006 on 12,900 individuals and 5,000 households. * SLID data from 1993 to 2006 on over 95,000 individuals and approximately 32,000 households. With one exception, the CNEF country data are available on CD-ROM from Cornell University for a fee. The Canadian SLID data are not distributed on the CD but are available to CNEF registered researchers through special arrangements with Statistics Canada. Complete instructions for obtaining CNEF data may be accessed on the project website. * Dates of Study: 1980-2007 * Study Features: International, Longitudinal * Sample Size: ** BHPS: 21,000+ ** PSID: 33,000+ ** SLID: 95,000+ ** GSOEP: 20,000+ ** HILDA: 19,000+ ** SHP: 12,900+ NACDA link: http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/00145/detail

United Kingdom UK: BOP: Current Account: Primary Income: Receipts data was reported at 225.882 USD bn in 2017. This records an increase from the previous number of 185.927 USD bn for 2016. United Kingdom UK: BOP: Current Account: Primary Income: Receipts data is updated yearly, averaging 136.335 USD bn from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 620.835 USD bn in 2007 and a record low of 3.586 USD bn in 1970. United Kingdom UK: BOP: Current Account: Primary Income: Receipts data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Balance of Payments: Current Account. Primary income receipts refer to employee compensation paid to resident workers working abroad and investment income (receipts on direct investment, portfolio investment, other investments, and receipts on reserve assets). Data are in current U.S. dollars.; ; International Monetary Fund, Balance of Payments Statistics Yearbook and data files.; Sum; Note: Data are based on the sixth edition of the IMF's Balance of Payments Manual (BPM6) and are only available from 2005 onwards.

Selection of time series of different scientific publications and of publication of the official statistics:

EUROSTAT, European Statistical Office OECD: Organisation for Economic Cooperation and Development; ONS: Office for National Statistics, England; SCB: Statistiska Centralbyran, Sweden; Federal Statistical Office, Wiesbaden. Deutschland; WHO: World Health Organization.

The UK's median gender pay gap has substantially reduced from 36.4% in the 1970s to around 18%, yet it remains one of the highest in the EU and OECD. Previously attributed to differences in education and work experience, this explanation is outdated as women now frequently outpace men in education and are less likely to leave the workforce. However, women still earn about 10% less than men, even with similar work and qualifications. Research has shifted focus from productivity differences to the potential role of employer wage-setting practices. This research suggests that women's negotiating power may be undermined by familial responsibilities, leading to lower mobility in the job market and consequently lower wages. The study will explore how employer wage-setting power and job-to-job mobility contribute to the gender pay gap, aiming to inform effective policies.

The collection contains a set of syntax files used to construct an alternative employment concentration index that takes into account commuting costs. The files are based on the Stata language and use the Business Structure Dataset and the UK Longitudinal Household Study to derive the index.

The median gender pay gap has declined dramatically in the UK from 36.4% in the 1970 (O'Reilly, Smith et al. 2015) to around 18% in the most recent data (ONS 2018). Still, by international standards the pay gap is high: the UK has the fourth largest gender pay gap in the EU and the eighth largest of OECD countries (OECD 2019). Researchers and policy makers have focused on gender differences in education and labour market experience as the likely drivers of the pay gap. However, today these explanations no longer stand up to scrutiny. Women are on average better educated than men and they are much less likely to withdraw from the labour market for long periods of time. Nevertheless, women earn on average about 10% less than men even when they work full-time and have similar education and labour market experience. While explanations focusing on women's potential lower productivity as the cause of the gender pay gap have been thoroughly investigated and found inadequate, there is less evidence on the role played by employers. This research will contribute to addressing this gap. The standard economic model of the labour market assumes that wages are determined by the market and that individual employers cannot choose the wages they offer to their employees. A different model assumes that for a variety of reasons competition is not perfect and employers have some discretion over the wages they offer. This wage setting power is likely to be weaker when workers are mobile. Mobile workers will leave an employer offering wages below the market rate. However, if workers are relatively immobile, employers can exploit this 'immobility' by offering them lower wages. If women are more constrained by family responsibilities in the types of jobs that they will take-up or in the amount of time and effort they can devote to job search, they will generally be more immobile and thus at a disadvantage. Women's family responsibilities might be ultimately responsible for the gender pay gap but not because they limit their productivity but rather because they reduce their bargaining power with firms. This research project will examine the role of employer wage-setting power in driving the gender pay gap in two ways. First, using data from the UK's largest longitudinal study, it will investigate the extent to which job-to-job mobility patterns differ between men and women, and whether any differences can explain the observed gender gap in pay progression. Second, it will develop an index of employer wage-setting power based on geographical location, industry and cost of travel and test whether the index can explain gender differences in pay progression. Tackling the gender pay gap is a widely shared goal among policy makers, political parties, women's groups, trade-unions and employer organizations. A better understanding of the factors driving the gap is essential to design effective policies. For example, in April 2017, the UK government has mandated large employers report annually on the pay gap in their organization. If women's lower productivity is to blame for the gender pay gap, such legislation is likely to be ineffective and even counterproductive. On the other hand, mandatory reporting is likely to be more effective if employers' stronger wage-setting power is a significant factor behind the pay gap. More generally, if employers enjoy significant wage setting power relative to some of their employees, this has implications for legislation on anti-discrimination, the minimum wage, trade-unions and family policy.