Monthly Wages and Salaries Survey

This bulletin contains the latest estimates of labour market statistics (including employment, unemployment and economic inactivity) for the United Kingdom.

Excel spreadsheets containing estimates of labour market statistics are available here. These spreadsheets contain historic estimates going back as far as comparable data exists for each time series.

Average weekly earnings by industry (Monthly Wages and Salaries Survey).

Claimant count revisions triangle.

This dataset contains Average Weekly Earnings (AWE) series. The AWE is the ONS's headline measure of short-term earnings growth. The data is derived from the Monthly Wages & Salaries Survey, a survey of employers.

This dataset contains the main labour market statistics data series. All of the series in this dataset are available in spreadsheet format from the labour market data tables. In this dataset Labour Force Survey (LFS) estimates are shown for the mid-month of the three-month average time periods. For example, estimates for January to March 2012 are shown as "February 2012", estimates for February to April 2012 are shown as "March 2012", etc.

This video summarises the key messages in the latest labour market release.

Comparing December 2012 - February 2013, with the previous three months, there was a rise in the number of unemployed people, a fall in the number of people “not in the labour force”, or economically inactive, and little change in the number of people in work

Average weekly earnings by sector (Monthly Wages & Salaries Survey).

Average Weekly Earnings (AWE), seasonally adjusted. This spreadsheet includes the headline estimates of earnings growth based on the Monthly Wages and Salaries Survey.

Labour productivity. This table is updated in January, April, July and October.

This dataset contains the main labour market statistics data series. All of the series in this dataset are available in spreadsheet format from the labour market data tables. In this dataset Labour Force Survey (LFS) estimates are shown for the mid-month of the three-month average time periods. For example, estimates for January to March 2012 are shown as "February 2012", estimates for February to April 2012 are shown as "March 2012", etc.

Labour productivity statistics in terms of output per worker, output per job and output per hour worked for the whole economy and a range of industries. The release also presents unit labour cost estimates, regional productivity estimates and experimental market sector productivity estimates.

Zip file of Excel spreadsheets containing revisions triangles for the main labour productivity variables: Whole economy output per worker, annual percentage change

This is a short video looking at Labour Productivity up to the fourth quarter of 2012.

This video summarises the key messages in the latest labour market release.

Average weekly earnings excluding bonus payments rose by 1.2% comparing November 2012 to January 2013 with the same period a year earlier

Labour market statistics summary data tables. This document contains the tables which appear in the pdf version of the Labour Market Statistical Bulletin.

Average Weekly Earnings (AWE), seasonally adjusted. This spreadsheet includes the headline estimates of earnings growth based on the Monthly Wages and Salaries Survey.

Claimant count revisions triangle.

A list of those receiving pre-release access to labour market statistics is available here.

Also known as Labour Costs Index (LCI). Measures changes in the average labour costs per hour worked. Labour costs include wages and salaries as well as employer social contributions, maternity, paternity and sick pay and benefits in kind.

This dataset contains Average Weekly Earnings (AWE) series. The AWE is the ONS's headline measure of short-term earnings growth. The data is derived from the Monthly Wages & Salaries Survey, a survey of employers.

Excel spreadsheets containing estimates of labour market statistics are available here. These spreadsheets contain historic estimates going back as far as comparable data exists for each time series.

While employment increased there was a 14,000 fall in the number of people unemployed.