How to Find and Use Statistics on Education, Skills

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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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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

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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

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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

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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

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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

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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/Na
  tionalEmployerSkillsSurvey2007.htm
• Analyse NESS Data http//researchtools.lsc.gov.uk
  /ness/home/home.asp
• HESA Higher Educational Statistical Agency
• RIU Pocket Databank

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Labour Market Data - definitions

• Employment rate the proportion of a population
  that are in employment
• - anyone who does at least one hours paid work
• Unemployment rate generally use the ILO
  definition
• - those who havent 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.

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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
• Doesnt capture all unemployment

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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!

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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

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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

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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?