How to Find and Use Statistics on Education, How to Find and Use Statistics on Education, Skills & EmploymentSkills & Employment

Emma Charnock - Regional Observatory Manager

Adam Crockett – Senior Economic Analyst

The Regional Intelligence Unit (RIU)

The Team has the cross-cutting theme of providing support to NWDA colleagues and regional partners. This is achieved by:

• Data & Analysis• Monitoring & Benchmarking Data • Consultations/Small Scale Surveys• Commission Research • Economic Assessment • Briefings on Research/Policy

www.nwriu.co.uk • Helping to disseminate and widen access to data and intelligence

Education Data

• Department for Children, Schools & Families (DCSF) http://www.dcsf.gov.uk

• Examples – GCSE & A Level results, class sizes, key stage performance

• Search by Key Word or Subject Category

• Data available at different geographies

Education - Example

• Proportion of children who receive at least 5 GCSEs graded A* to C

CAUTION:

• Data often ‘lags’ real time

Source:

• Important to source the data correctly – Acknowledges the data supplier and helps you to re trace your steps!

• Title of Dataset, Year and Provider

Skills Data

• Office for National Statistics (ONS) www.statistics.gov.uk

• NOMIS www.nomisweb.co.uk

• Search using the Wizard or Advanced Query

• Examples – NVQ Qualifications, by working age population, economically active or those in employment, also splits by age group

Skills Data - Example

• Proportion of working age people who have no qualifications

CAUTION:

• Unfortunately constrained by the options available in the public domain

• The smaller the sample the more unreliable the data

• Some data is available on request

Skills Data – Other Sources

• Connexions and NEET data

• LSC http://www.lsc.gov.uk/regions/NorthWest/

• NESS 2007 Northwest Summary Report: http://www.lsc.gov.uk/regions/NorthWest/Aboutus/National+Employer+Skills+Survey+2007.htm

• Analyse NESS Data: http://researchtools.lsc.gov.uk/ness/home/home.asp

• HESA – Higher Educational Statistical Agency

• RIU Pocket Databank

Labour Market Data - definitions

• Employment rate – the proportion of a population that are in employment

- anyone who does at least one hour’s paid work

• Unemployment rate – generally use the ILO definition- those who haven’t got a job but would like a job as a the proportion of the labour

force

• Economic inactivity- Economically active persons are those, who are either in employment or

unemployed, the remainder of the population are economically inactive.

Labour Market Data - sources

• The Annual Population Survey (APS) - NOMIS- Easy to use with comprehensive coverage- 6-9 months old

• Labour Market Statistics - ONS - Very timely but most data is only available at a regional level- Less user friendly and time consuming for comparison

• Job seekers allowance - NOMIS and ONS- Timely proxy of unemployment at low geographical levels- Doesn’t capture all unemployment

Unemployment data Example

• The latest unemployment rates in Liverpool and Manchester now and a year ago

Points to consider:

• Due to small samples, unemployment is unavailable for some small districts

• Estimates of large groups or areas are robust

• The data is considerably lagged – latest data Sept 2008!

Labour Market Statistics - example

• Collecting the most timely JSA data and unemployment figures at a regional level

Points to consider:

• This is very timely

• Geographical disaggregation is poor

• The data not user friendly

Labour Market Data – points to consider

• Robust data- Confidence levels- Small samples- Timely data is often based off smaller samples – less robust- Look at proxies, JSA often used as a timely robust proxy

for unemployment

• Disaggregation- Can get employment data split by gender, occupation,

ethnicity, age, disability, self employment, full time, part time- Can mix these but need to be mindful of confidence levels- May need to use a high level of geography

Key Messages

• Finding data can be a mine field - building up your confidence re what is available and how to use it

• Time lags

• Data not reliable or available at lower levels e.g. geographies or ethnicity

• Remember: Source data correctly & save the raw data

ANY QUESTIONS?