Analysis of real earnings: June 2017

This article presents two analyses of the average weekly earnings (AWE) figures, which are published in the UK Labour Market statistical bulletin. These analyses are updated every month. The first section describes real AWE, which is AWE deflated by the Consumer Prices Index including owner occupiers’ housing costs (CPIH). The second section analyses single month movements in the nominal AWE.

Please note that improvements to the methodology for the estimation of earnings of employees of small businesses in the AWE series have been implemented in the June release. Consequently, this has impacted all real earnings estimates back to 2005, which have been subject to a review of the seasonal adjustment process.

The figures show the recent movements in real AWE (whole economy). This is calculated as nominal unadjusted AWE, divided by the CPIH. This series is calculated for regular pay (excluding bonuses, excluding arrears) and total pay (including bonuses, excluding arrears) at the whole economy level and then seasonally adjusted. The data in Figures 1 and 2 are levels of real and nominal AWE, shown on a monthly basis, with an index of 2015 equals 100. Figure 3 shows 3-month average year-on-year increases in these derived indices. The data are available in dataset EARN01, together with estimates of real AWE at 2015 prices.

Comparing the 3 months to April 2017 with the same period in 2016, real AWE (total pay) fell by 0.4%, compared with an increase of 0.1% in the 3 months to March 2017. This is the first 3-month average year-on-year decrease seen in real AWE (total pay) since the 3 months to September 2014. Nominal AWE (total pay) grew by 2.1% in the 3 months to April 2017, while the CPIH increased by 2.6% in the year to April 2017 (from 2.3% in March 2017). In the same 3-month period, real AWE (regular pay) fell by 0.6%, compared with a decrease of 0.4% in the 3 months to March 2017. The nominal AWE (regular pay) rose by 1.7% in the 3 months to April 2017.

The wages and employment contributions underlying the latest AWE data are available on our website in the EARN02 dataset each month. The “employment contribution”, shown in these figures, changes if the relative proportion of employment in the 24 industrial headings changes, but will not necessarily change if total employment increases. Employment contributions were significantly negative in 2009 and 2010, largely caused by a shift away from employment in financial and insurance activities, which are relatively highly paid industries.

Figures 4 and 5 summarise the recent figures.

Employment contributions were positive 0.2% for both total and regular pay in April 2017.