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How to Find and Use Statistics on Education, Skills & Employment Emma Charnock - Regional Observatory Manager Adam Crockett – Senior Economic Analyst.

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Presentation on theme: "How to Find and Use Statistics on Education, Skills & Employment Emma Charnock - Regional Observatory Manager Adam Crockett – Senior Economic Analyst."— Presentation transcript:

1 How to Find and Use Statistics on Education, Skills & Employment Emma Charnock - Regional Observatory Manager Adam Crockett – Senior Economic Analyst

2 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

3 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

4 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

5 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

6 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

7 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/Nati onal+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

8 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.

9 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

10 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!

11 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

12 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

13 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?


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