All publications related to earnings and working hours

Our interactive explorer shows the average full-time gross annual pay for different occupations. Find out which jobs pay the most – and least – and see how your job compares.

Earnings and employment statistics for different ethnic groups in Great Britain, using regression analysis to provide more insight into factors that affect pay.

Changes in the costs of employing labour, analysed by sector and industry. Experimental Statistics.

Use our interactive tool to find out the gender pay gap for a range of different jobs, and the percentage of men and women doing those jobs. There are breakdowns available for full- and part-time employees.

The results of statistical models that explore the relationship between mean hourly earnings and a range of independent variables, based on Annual Survey of Hours and Earnings (ASHE) 2017 provisional results data.

Distribution of earnings analyses using Annual Survey of Hours and Earnings (ASHE) provisional 2017 data and previous ASHE datasets, including differences in earnings by age, sex, region, skill-level and working pattern.

Important measures of employee earnings, using data from the Annual Survey of Hours and Earnings (ASHE). Figures are presented mainly for full-time employees, although some detail for part-time workers is also included.

The distribution of earnings of high- and low-paid jobs, earnings by selected percentiles and jobs paid below the National Minimum Wage. Compiled from the Annual Survey of Hours and Earnings (ASHE).

Differences in pay between women and men by age, region, full-time and part-time, and occupation as compiled from the Annual Survey of Hours and Earnings (ASHE). The gender pay gap is the percentage difference between men's and women’s median hourly earnings, across all jobs in the UK; it is not a measure of the difference in pay between men and women for doing the same job.

Analyses of the Average Weekly Earnings (AWE) figures, adjusted for inflation, and of wages and employment contributions underlying single-month movements in the nominal AWE.