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Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

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Page 1: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS dataMerle Paats

Leading Statistician from the Social Statistics Department, Estonia

Page 2: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• The comparison between the ESeC simplified classes and ESeC full classes.• To compare the usage of ESeC based on LFS and EU-SILC data.

The purpose

Page 3: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• The aim of the survey is to get an overview of the labour market situation.• ES conducted the first LFS at the beginning of 1995.• The survey is conducted continuously since 2000.• The Estonian LFS is based on the definitions devised by the ILO and EUROSTAT regulations.

Estonian LFS

Page 4: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• The aim of the survey is to obtain comparative and reliable statistics on income distribution, living conditions and social exclusion.• ES runs the survey since 2004.• The Estonian EU-SILC is based on the EUROSTAT regulations.

Estonian EU-SILC

Page 5: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

Required information

ISCO88, 3 digit ISCO88, 4 digit

Yes Yes

For ref. period, for the inactive number of direct subordinates in the last job

For ref. period yes, for the inactive no

Number of direct subordinates

Number of direct subordinates

Information about reference week or about last job.

Page 6: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• For assigning the ESeC values the SPSS Syntax developed by Institute for Social and Economic Research was used. • Number of employees is included in information about job during of reference week. For the information about the last job, the number of direct subordinates was used:

– Sole proprietor – 0 employees

– Employer with employee(s) – number of direct subordinates • The number of direct subordinates for supervisor status was used. The person with at least 3 direct subordinates was coded into the supervisor group.

Problems with implementing ESeC

Page 7: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• The code 613 - Crop and animal producers – was missing in the syntax of ESeC Simplified classes. It was coded into class number “5” according the table of “Class matrix for EuroESeC”.• The combined classification of ISCO-88 and ISCO-88 for European Union purposes is used in Estonia.

Problems with implementing ESeC

Page 8: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• The difference is not very big between using of the ESeC simplified classes and ESeC full classes: 94% of persons fall in the same class and 6% of the persons fall to different classes.• The difference is higher in following Esec classes:

– Small employers and self-employed (agriculture)– Lower technical– Lower mgrs/professionals, higher

supervisory/technicians

Results

Page 9: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

Results

Freq. Perc. Freq. Perc. Freq. Perc.Large employers, higher mgrs/professionals 721 6 709 6 12 0.1Lower mgrs/professionals, higher supervisory/technicians 1272 11 1102 9 170 1.4Intermediate occupations 494 4 526 4 32 0.3Small employers and self-employed (non-agriculture) 221 2 240 2 19 0.2Small employers and self-employed (agriculture) 153 1 418 3 265 2.2Lower supervisors and technicians 139 1 68 1 71 0.6Lower sales and service 918 8 976 8 58 0.5Lower technical 1627 14 1438 12 189 1.6Routine 2688 22 2756 23 68 0.6Never worked 3812 32 3812 32 0 0Total 12045 100 12045 100 0 0

Full ESeC Simply ESeC Difference

Page 10: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• Small employers and self-employed (agriculture):– When using the simplified ESeC 17% of them fall into class of lower

technical occupations and 3% of them fall in the class of routine occupations. Actually they are self-employed without employees.

• Lower technical– When using the simplified ESeC 18% of them fall into class of small

employers and self-employed in agriculture. Actually they are employees or non-paid family workers.

• Lower mgrs/professionals, higher supervisory/technicians– When using the simplified ESeC 13% of them fall into class of small

employers and self-employed. Actually they are managers of small enterprises.

• The simplified ESeC is based on the occupation only and it is thus impossible to consider the employment status.

Results

Page 11: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

The more problematic occupations are:• Managers of small enterprises (131):

– ESeC full classes they fall into the class of large employers, higher mgrs/professionals; lower mgrs/professionals, higher supervisory/technicians or small employers and self-employed (non-agriculture) according to employment status, number of employees and supervisor status.

– ESeC simplified classes they fall into the class of small employers and self-employed (non-agriculture).

• Skilled agricultural workers (611, 612, 613):– ESeC full classes they fall mostly (70%) into the class of lower

technical occupations or small employers and self-employed (agriculture) (30%).

– ESeC simplified classes they fall into the class of small employers and self-employed (agriculture)

Results

Page 12: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• Forestry and fishery workers (614, 615):– ESeC full classes they mostly fall into the class of lower technical

occupations (55%) or small employers and self-employed (agriculture) (31%).

– ESeC simplified classes they fall into the class of lower technical occupations.

• In general, the problems occur with recoding of 6% of persons.

Results

Page 13: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• ESeC simplified classification was used for comparison of EU-SILC and LFS data• The distribution of ESeC classes was similar in the LFS and EU-SILC• The differences between surveys were a result of different survey methodology – LFS includes all working-age population (15 – 74) and EU-SILC includes all persons older than 15.

EU-SILC and LFS

Page 14: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

EU-SILC and LFSDiff.

Freq. Perc. Freq. Perc.Large employers, higher mgrs/professionals 721 6 962 7 1Lower mgrs/professionals, higher supervisory/technicians 1272 11 1533 10 1Intermediate occupations 494 4 731 5 1Small employers and self-employed (non-agriculture) 221 2 412 3 1Small employers and self-employed (agriculture) 153 1 315 2 1Lower supervisors and technicians 139 1 106 1 0Lower sales and service 918 8 1721 12 4Lower technical 1627 14 1851 13 1Routine 2688 22 3116 21 1Never worked 3812 32 3858 26 6Total 12045 100 14605 100 0

EU-SILC LFS

Page 15: Application of ESeC in Estonian Social Surveys based on EU-SILC and LFS data Merle Paats Leading Statistician from the Social Statistics Department, Estonia

July, 2006 ESeC

• For assigning the ESeC values the full ESeC classification should be used – for this purpose the several questions should be added.• For earlier years, it is possible to use the simplified Esec classification.• For comparison with earlier years the Esec classes on higher level should be used.

Conclusion