Quarterly Earnings Statistics

1. Quarterly Earnings Statistics Kieran Walsh Senior Statistician Labour Market and Earnings Analysis

2. Outline of Presentation 1. Data collection 2. Primary indicators 3. Additional indicators

3. Quarterly earnings data collection • Historically multiple earnings surveys • Covered different sectors (public sector, industry, building, distributive trade, financial services) but not comprehensive • Different methods and coverage • No all sectors estimation possible • Earnings hours and employment costs survey (EHECS) initiated in 2005 – initially covered industry and finance • In Q1 2008 extended to all sectors of the economy

4. Quarterly earnings data collection contd. • EHECS collects information on the following main elements from enterprises with 3+ employees: • Regular earnings • Irregular earnings • Other labour costs • Paid hours • Employment • Broken down full time/part time and 3 occupational groups • Aggregate level information collected

5. Quarterly earnings data collection contd. • Data collected from all enterprises with 50 or more employees • Sample of smaller enterprises • High burden survey – done according to Labour Costs Survey framework (detailed) – no separate LCS required • In 2009/2010 a number of steps taken to reduce burden • Reduced sample • Reduced form for smaller enterprises • Done so as to maintain key outputs • Improved timeliness as a result

6. Quarterly earnings statistics – key indicators – weekly earnings

7. Quarterly earnings statistics – key indicators – weekly earnings • Average weekly earnings overall down over the period • Private sector steadily down during 2008/9 – fluctuating in 2010 • Public sector up in 2008, fluctuated 2009 (excluding pension levy effect), down in 2010 following pay cut • By size class all fluctuating but no major pattern

8. Quarterly earnings statistics – key indicators – hourly earnings

9. Quarterly earnings statistics – key indicators – hourly earnings • Paid hours have been cut most notably in private sector and smaller enterprises • As such some of cuts in weekly earnings not replicated in hourly earnings • Most notable shift in hourly earnings in public sector where pay cut shifted level down in 2010

10. Interpretation issues • Refers to remaining enterprises and employees • Some queries regarding loss in earnings for people who used to work in Construction – cannot be estimated from this source • Composition effects – difficult to estimate without high burden on respondent enterprises – would require very detailed occupation, experience etc. information • Trends not unidirectional – e.g. reduction occur in some periods and not others

11. Supplementary analysis • Looked at wage bill changes among enterprises who were available in both periods • Enterprises cut/increase wage bill in 3 ways • Employment • Paid hours • Hourly earnings • Used data for Q3 2008 and Q3 2009 – period of greatest employment loss • Showed that 65% of all enterprises cut their wage bill by more than 2% • 68% small enterprises, 57% large enterprises

12. Supplementary analysis from EHECS Percentage of enterprises reducing their wage bill and components of the wage bill, by components changed, Quarter 3 2008 to Quarter 3 2009 54% 12% 13% 20% 9% 4% 4% 3% 37% 29%

13. Supplementary analysis • Many enterprises cut more than one of the components • Employment most frequent (more than half of enterprises cut their wage bill with an employment reduction as part of it) • Paid hours next most frequent (37%) • Hourly earnings least frequent (29%) and hourly earnings (standardised actually increased 1% over the period) • Varied greatly across sectors • Compositional effect also looked at with available information – no significant compositional effect identified