ESSnet on the harmonisation and implementation of a European socio- economic classification Workpackage 2 – Expertise of the basic variables ___________________ Francesca Gallo Istat- Department for socio-economic statistics

Objectives and expected results of the ESSnet on ESeC 1 - Prepare a prototype of a European Socio- economic Classification exclusively based on core variables 2 - Improve comparability of the components of the classification 3 - Study the possibility of providing more precise results from the LFS with additional variables already available in this survey

Workpackage 2 – Expertise on the basic variables Objectives focus on the quality of the main (target and not target) variables used to build the prototypes with a particular attention on Isco08 Deliverables – First report on the quality of the core variables involved in the ESeC Prototype and on some other variables which are interesting to build a second level (like supervision) → in 12 months time – Recommendations on Isco08 → in 24 months time – General recommendations for the implementation of other variables in the final ESeC → in 24 months time

- Status in employment (target variable)  Self-employed  Employee with a permanent job or work contract of unlimited duration  Employee with temporary job/work contract of limited duration - Occupation in employment both 2-digit (target variable) and more than 2-digit (not target variable) - Economic sector in employment (target variable)  Agriculture, hunting and forestry; fishing and operation of fish hatcheries and fish farms  Industry, including energy  Construction  Wholesale and retail trade, repair of motor vehicles and household goods, hotels and restaurants; transport and communications  Financial, real-estate, renting and business activities  Other service activities - Supervisory responsibilities The main (target and not target) variables we would give priority 1 in the quality analysis

Quality dimension to evaluate Quality DimensionDefinition 1. Relevancedegree to which statistics meet current and potential users ’ needs 2. Accuracy the closeness of estimates to the exact or true values 3. Timeliness and punctuality The length of time between its availability and the event or phenomenon it describes; time lag between the date of the release of the data and the target date (the date by which the data should have been delivered) 4. Accessibility and clarity Refer to the physical conditions in which users can obtain data and whether data are accompanied with appropriate metadata, illustrations such as graphs and maps 5. Coherence statistics originating from different sources convey coherent messages 6. Comparability extent to which differences between statistics are attributed to differences between the true values of the statistical characteristic

How to document the ‘Coherence’ dimension for the selected variables (see for instance occupation) CountriesNumber of employed by occupation (1st digit, 2nd digit, 3rd digit Isco08) EU-silcLFS Country_1 Occ_silc Occ_LFS Occ_silc Occ_LFS …… Country_i Occ_silc Occ_LFS Country_N The two estimates should lay within the confidence limits

Important differences could stem from an accuracy problem To understand it better  check quality reports and if differences remain unexplained  ask extra information to MS

Differences could be due to measurement errors, like the survey instrument, the respondents, the interviewers … It will be interesting to understand the source of non sampling errors for EuSilc and LFS results trying for instance to answer questions like:  Do Eusilc and LFS use the same interviewers for data collection?  Are they trained in the same way?  Are they responsible for the coding?  Are they provided with the same software? But also  How much is the proxy rate?

4. How to document the ‘Comparability’ dimension - Time comparability - Analyse time series of the variables in the 3 selected surveys (LFS, EuSilc, AES) A specific analysis will be performed for Isco08

- Time comparability for occupation - Major group - Isco Unit groups Isco88Isco08 I- Managers3331 II- Professionals5592 III- Technicians and associate professionals7384 IV- Clerical support workers2329 V- Service and sales workers2340 VI- Skilled agricultural, forestry and fishery workers1718 VII- Craft and related trades workers7066 VIII- Plant and machine operators and assemblers7040 IX- Elementary occupations2533 X- Armed forces occupations13 Total BUT WE DON’T KNOW THE IMPACT IN TERM OF NUMBER OF EMPLOYED

If we analyse the MG distribution across we are not able to conclude if the changes are due to: - real change of the labour market; - different allocation of occupation according to Isco88 or Isco Group %

- We would like to ask MS if  they can provide double coding in 2010 or 2011 LFS or  they can analyse the longitudinal subsample of individual who didn't change job and was interviewed and coded in 2010 with ISCO 88 and in 2011 with ISCO08 To estimate the impact of Isco08 in term of number of employed - Time comparability for occupation -

- Comparability over space - A matrix summarising by country the possible sources of lack of comparability relative to a specified standard (Isco08) Check quality reports and, if necessary, elaborate a questionnaire for NSI on how the questions and the derivation of the variables are done in each country