A European Socio-economic Classification: How we got here and where we are going More David Rose & Eric Harrison Institute for Social and Economic Research University of Essex

Eurostat Statistical Harmonisation Programme  Aims to create a common set of core units core variables and core classifications for use in European and national social statistics

ESeC  Expert Group appointed by Eurostat in January 2000  Proposals for an ESeC made in 2001 Feasibility Report (available from  This report forms the basis for the project

Form of classification Outline classification is two-level ‘nested hierarchy’ (see French PCS) The disaggregated form, Level 2, we refer to as ‘Socio- economic Groups’ (SEGs) This covers the whole population at the individual level. These SEGs cover all the various ‘other active’ and ‘inactive’ groups. These may be reallocated to ESeC classes in a variety of ways, depending on the interests of the analyst

Conceptual basis for the ESeC  Rooted in the recent theoretical work of John Goldthorpe  Employment relations and conditions are central to delineating the structure of socio-economic positions in modern societies

The Derivation of the ESeC Basic SEC Positions EMPLOYERSSELF-EMPLOYED WORKERS EMPLOYEESEXCLUDED

Dimensions of work as sources of contractual hazard Difficulty of monitoring Specificity of human assets low high

Typical elements of the Labour Contract  Short-term exchange of money for effort  Payment by the time or piece  No occupational pension or health scheme  Contract easily terminated  Low level of job security

Typical elements of the Service Relationship  Long-term exchange of service for compensation  Greater job security and employability  Salary  Incremental or similar payment systems  Occupational pension and health schemes  Greater control over the job and thus trust between employer and employee

Dimensions of work as sources of contractual hazard, forms of contract and class locations Difficulty of monitoring Specificity of human assets low high Labour contract Service relationship mixed

Possible ESeC ‘Classes’ (Level 1) 1. Large employers, higher managerial and professional occupations 2. Lower managerial and professional occupations 3. Intermediate occupations 4. Small employers and own account workers 5. Employers and self-employed in agriculture 6. Lower supervisory and lower technician occupations 7. Lower sales and lower services occupations 8. Lower technical occupations 9. Routine occupations 10. Never worked and long term unemployed

The Conceptual Derivation of ESeC Basic SEC Positions EMPLOYERSSELF-EMPLOYEDWORKERSEMPLOYEESEXCLUDED LABOUR CONTRACT Form of employment regulation SERVICE RELATIONSHIP MIXED Higher prof Lower prof/ Tech OtherAgric etc Higher prof Lower prof/ Tech OtherAgric etc Higher prof Lower prof/ Tech Other Lower SupProf /Tech ManProf Man Higher Never worked LargeSmall Super- Serv- Lower routine visory/ ices technical Technician Clerical Sales Services Clerical Sales Services Professional managerial, etc Unemp- loyed

Underlying ESeC ‘Socio-economic Groups’ (Level 2) 11.Employers (other than in agriculture) with 10+ employees 12.Farmers with full-time employees (or ‘large business’ farmers) 13.Higher managerial occupations 14.Higher professional occupations (employees) 15.Self-employed professional occupations Class 1 Large employers, higher managerial and professional occupations

Flexibility One of the advantages of a nested two-level schema such as this is that it will permit analysts to look ‘inside’ classes. This will assist them in understanding how life- chances may vary between groups with the same employment relations. For example, do higher professionals in SEGs 14 and 15 have better health outcomes when compared with higher managers in SEG 13?

Extra Socio-economic Groups Other active groups 01 Other unemployed 02 Unpaid family workers 03 National service Inactive groups 04 Retired 05 Students (full-time) 06 Children 07 Permanently sick and disabled 08 Looking after home Not classifiable 00 Occupation not given or inadequately described

Classification rules for the individual level of ESeC  Those in SEGs do not automatically collapse to any class. Individuals in these groups are re-allocated to either: a) Their ‘career typical’ (usually last ‘main’) job or b) their household class.

Household Level Rules  Also possible to re-allocate all SEGs to create a Household version of ESeC  Achieved through the concept of ‘household reference person (HRP)  Usually a given, i.e. part of survey design  But if occupational data on all HH members is available, use ‘dominance’ rules

Number of SEGs (1)  Number of SEG categories within classes to be determined by face validity, i.e. grouping together in sub-categories similar types of occupations that share similar employment relations  NB: The SEGs within this outline classification are only ones, designed to help illustrate how a possible two-level classification work.  NB: The SEGs within this outline classification are only postulated ones, designed to help illustrate how a possible two-level classification might work.

Number of SEGs (2) Therefore it is the themselves that will need to be validated. Therefore it is the classes themselves that will need to be validated. Which SEGs we then wish to recognise within each class will be largely contingent on what might be useful for the internal analysis of classes, face validity issues, etc. So SEGs only ‘exist’ to the extent that they are useful sub-divisions among those combinations of occupation and employment status that share similar employment relations.

Criterion validation of ESeC (1) Initial work based on previously created and validated measure in the UK – the NS-SEC. Also drawing on previous European research developing measures of comparative social structure, for example the Comparative Analysis of Social Mobility in Industrial Societies (CASMIN) project.

Criterion validation of ESeC (2) Given the broad similarities of market economies and occupational and industrial structures across the EU, we can expect that employment relations will also be similar. Thus, it is reasonable to begin by creating an ESeC derivation matrix with cell values based on UK employment relations data. These data were collected in the 1996/97 winter quarter of the LFS.

Constructing ESeC In order for an ESeC to be in line with our theoretical model, at a minimum we require measures of: In order for an ESeC to be fully operationalized in line with our theoretical model, at a minimum we require measures of:occupation, status in employment, labour market position and (in some cases) enterprise size. In many countries a measure of farm size may also be necessary

Occupation Measured by ISCO88 (COM) at (up to) 4 digits or a national occupational classification similar to it. Exception is France, but has a Table des Correspondances between the Catégories Socioprofessionnelles (CSP) and ISCO88(COM). ISCO88(COM) is a core variable for the Eurostat harmonisation programme and so is the obvious measure of occupation to use for ESeC.

Status in Employment All classifications distinguish between employers, the self-employed (own account workers) and employees. The EU harmonised variable is ICSE-93. ICSE-93: 1. Employees 2. Employers 3. Own account workers 4. Members of producers’ co-operatives 5. Contributing family workers 6. Workers not classifiable by status

Labour market position It is necessary to distinguish more than activity status. Our theoretical model requires us to identify employers by size and between managers (by size of enterprise or preferably managerial level), supervisors and other employees. Managerial status will be dependent on allocation to Sub-major Groups 12 and 13 of ISCO88(COM). Thus, labour market position involves a combination of ICSE-93, enterprise size and supervisory status.

Number of employees The size cut-off for enterprise size in the non- agricultural sector varies across the national SECs and across datasets: 1-9, 10+; 1-24, 25+; 1-49, 50+ or combinations of these. However, since ISCO88(COM) is the harmonised occupational classification, then the initial simple rule for ESeC will need to be that employed by ISCO for managers and employers – 1-9 and 10+.

Example illustration of parts of the ESeC derivation matrix Employment status ISCO OUG Self-emp 10+ Self-emp <10 Self-emp none Manager 10+ Manager <10 Super- visor Employee 12xx111xx113xxx 13xxx441442X221xx 3xxx xx yyy xx xxxxx225333

ESeC in a world of incomplete information  Some data sets may not contain all the elements required to create ESeC in the prescribed manner.  ECHP: (2 digits ISCO or less – anonymity)  ESS: French occupations 2 digits French occupations 2 digits Norwegian self-employed no occupation code Norwegian self-employed no occupation code

Reduced ESeC However, it would also be possible to produce a ‘reduced’ form of ESeC for use where data on establishment size is missing. The reduced form could be derived in essentially the same way as the full form of ESeC, except that (ignoring the agricultural sector again) the employment status variable would only have five categories: 1.Self-employed with employees; 2.Self-employed with no employees; 3.Manager 4.Supervisor 5.Employee The ESeC category for self-employed with employees and for managers would be based on the category for each occupation. The ESeC category for self-employed with employees and for managers would be based on the modal employment status category for each occupation.

Simplified ESeC The simplified form of ESeC would be for data sets in which only information on occupation (i.e. on 4 digit ISCO OUG) is available. The primary rule would be that occupations (OUGs) are allocated to the ESeC category for ‘other employees’, except where these are in a minority within that occupation. In these cases the ESeC category of the modal occupation by employment status combination would be used. Hence, for example, if within a particular OUG supervisory status predominates, then the ESeC value for supervisors in that OUG will apply. In these cases the ESeC category of the modal occupation by employment status combination would be used. Hence, for example, if within a particular OUG supervisory status predominates, then the ESeC value for supervisors in that OUG will apply.

Using Fewer ISCO Digits  Datasets do not always code occupation to four digits – often three or two  We can construct matrices for every combination of occupation and extra information, i.e.  4 digit full, reduced, simplified  3 digit full, reduced, simplified  2 digit full, reduced, simplified

Timetable of Work  Create derivation matrices: done  Matrices + report to partners, NSIs, Eurostat and experts for responses - done  Statistical Compendium – being undertaken  Validation studies – in progress, reporting November 2005  Validation conference – January 2006  ESeC User Guide – Spring 2006  NSIs’ Workshop – Summer 2006

Request for Assistance/Participation  We want feedback from existing and potential users of socio-economic classifications  Matrices and syntax available:  Contact or