Structure of earnings survey 2018 (earn_ses2018)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Statistical Office of the Republic of Slovenia


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)
 



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1. Contact Top
1.1. Contact organisation

Statistical Office of the Republic of Slovenia

1.2. Contact organisation unit

Labour Market Statistics

1.5. Contact mail address

Litostrojska 54, 1000 Ljubljana


2. Statistical presentation Top
2.1. Data description

With the Structure of Earnings Survey we wish to provide insight into the structure of earnings, i.e. to present different earnings categories (earnings, bonuses, holiday bonus, paid hours, paid overtime, days of holiday leave, etc.) by different characteristic of business entities or their units (size class, activity, region, etc.) and by characteristic of employees (sex, education, occupation, etc.).

 

List of abbreviations: 
AJPES Agency of the Republic of Slovenia for Public Legal Records and Related Services
NR National Accounts
PRS Business Register
SES Structure of Earnings Survey
SRDAP Statistical Register of Employment
SURS Statistical Office of the Republic of Slovenia
ZAP/M Earnings of Persons in Paid Employment by Legal Persons; national official data on earnings

2.2. Classification system

Classifications used:

  • The Standard Classification of Activities (SKD), based on the European Classification of Economic Activities (NACE Rev. 2);
  • The Nomenclature of Territorial Units for Statistics (NUTS, level 1);
  • The Standard Classification of Institutional Sectors (SKIS);
  • The Standard Classification of Occupations, based on International Standard Classification of Occupations, (ISCO-08);
  • Classification System of Education and Training (KLASIUS), based on the International Standard Classification of Education ISCED 1997 and ISCED 2011.
2.3. Coverage - sector

Data are collected for all activities A-S.

2.4. Statistical concepts and definitions

Key variables:

  • Average annual / monthly / hourly earnings per person in paid employment by different wage categories, by different characteristics of business entities or their units and by characteristics of employees;
  • Structure of earnings;
  • Gender Pay Gap.
2.5. Statistical unit

Local kind of activity unit (LKAU).

2.6. Statistical population

The Structure of Earnings Survey covered all persons in paid employment with employment contracts working for legal or registered natural persons or their units from the mentioned sample. The survey did not cover people working under work contracts and royalty, pupils and students on practice, workers in employment promotion schemes, posted workers and labour force hired through the student employment centre.

2.7. Reference area

The whole country (Slovenia) is covered on NUTS-1 level.

2.8. Coverage - Time

In Slovenia SES data are available from SES2002 onwards. For the SES2018 the reference period are data for the year 2018.

2.9. Base period

No base period. The SES statistical survey is conducted every 4 years.


3. Statistical processing Top
3.1. Source data

Business entities (or their units) were randomly select and all employees in these business entities were observed (one stage sampling).

Sampling frame

As a basis for creating the sampling frame for SES2018, data from SRDAP and PRS were used to which data from two monthly statistical surveys – Earnings of Persons in Paid Employment by Legal Persons and Average Monthly Earnings by Registered Natural Persons – and statuses from other statistical surveys were added. In this case data from the above mentioned surveys were used only as auxiliary data in determining large units that will be sampled with certainty. In the final sampling frame 80,816 units were included.

Size classes were determined on the basis of the data on the number of employees (source: SRDAP) as well as data on labour costs (source: final accounts estimated at the level of local units). Large business entities were those with 250 and more employees or with labour costs exceeding EUR 450,000. Other business entities were divided into three size classes: medium-sized (from 50 to 249 employees), small (from 10 to 49 employees) and micro (with fewer than 10 employees). As the second and third stratification variables activity (by the Standard Classification of Activities 2008 (NACE Rev. 2)) and cohesion regions were used.

 Sample  

The final sample size for the SES2018 was 3,711 business entities or their units. Reporting units had to report data for all employees in the business entity or unit selected in the sample.

In the distribution of sample units by strata, optimum allocation by the number of employees was used, while in those strata where the calculation by optimum allocation yielded fewer than 8 units 8 units were sampled, i.e. if there were fewer than 8 units in the stratum, all units were sampled. Systematic sample selection was applied, sorting the units within each stratum by five-digit Standard Classification of Activities 2008 (NACE Rev. 2) codes and thus ensuring implicit stratification at the lowest level of activity.

Because in the case of the selected sampling plan it cannot be controlled for how many employees the unit will report data, it was decided to include control in the software application for reporting. If the business entities reported data for too low number of employees (according to data from SRDAP), the person reporting the data was warned.



Annexes:
3.1_Frame-Sample_SES2018_Slovenia
3.2. Frequency of data collection

Data are collected every 4 years.

3.3. Data collection

For the Structure of Earnings Survey existing sources and data from the questionnaire (in Slovene language only) sent to the business entities selected in the sampleare used;  the data from the questionnaire are collected by AJPES by a web questionnaire.

 

Variable number in the EU Regulation

Variable name

How was the information collected

Question number in the survey questionnaire or formula

1

Information about the local unit to which the sampled employees are attached

 

 

1.1

Geographical location of the local unit (NUTS-1)

For national purposes data collected on NUTS-3 level - PRS

 

1.2

Size of the business entity to which the local unit belongs

PRS, SRDAP

 

1.3

Principal economic activity of the local unit (NACE Rev. 2)

PRS

 

1.4

Form of economic and financial control

PRS

 

1.5

Collective pay agreement

ZAP/M

 

1.6

Total number of employees in the local unit in the reference month (optional)

SRDAP

 

1.7

Affiliation of the local unit to a group of business entities (optional)

Data were not collected

 

2

Information on individual characteristics of each employee in the sample relating to the reference month

 

 

2.1

Sex

SRDAP

 

2.2

Age

SRDAP

 

2.3

Occupation (ISCO-08)

SRDAP

 

2.4

Management or supervisory position (optional)

Data were not collected

 

2.5

Highest successfully completed level of education and training (ISCED 97)

SRDAP

 

2.6

Length of service in the business entity

Included in the questionnaire

2

2.7

Contractual working time (full-time or part-time)

SRDAP

 

2.7.1

Share of a full-timer’s normal hours

SRDAP

 

2.8

Type of employment contract

SRDAP

 

2.9

Citizenship (optional)

Data were not collected

 

3

Information on working periods for each employee in the sample

 

 

3.1

Number of weeks in the reference year to which the gross annual earnings relate

Included in the questionnaire

13

3.2

Number of hours paid during the reference month

Included in the questionnaire and calculated

7, 9

3.2.1

Number of overtime hours paid in the reference month

Included in the questionnaire

8

3.3

Annual days of holiday leave

Included in the questionnaire

16

3.4

Other annual days of paid absence (optional)

Data were not collected

 

4

Information on earnings for each employee in the sample

 

 

4.1

Gross annual earnings in the reference year

Included in the questionnaire and calculated

10, 12, 15, 17, 18, 19

4.1.1

Annual bonuses and allowances not paid in each pay period

Included in the questionnaire and calculated

11, 15

4.1.2

Annual payments in kind (optional)

Data were not collected

17, 18, 19

4.2

Gross earnings in the reference month

Included in the questionnaire and calculated

3, 6

4.2.1

Earnings related to overtime

Included in the questionnaire

4

4.2.2

Special payments for shift work

Included in the questionnaire

5

4.2.3

Compulsory social contributions and taxes paid by the employer on behalf of the employee (optional)

Data were not collected

 

4.2.3.1.

Compulsory social-security contributions (optional)

Data were not collected

 

4.2.3.2.

Taxes (optional)

Data were not collected

 

4.3

Average gross hourly earnings in the reference month

Included in the questionnaire and calculated

Calculated from 3, 6, 7, 9

5

Grossing-up factors

 

 

5.1

Grossing-up factor for the local unit

 

 

5.2

Grossing-up factor for the employees

 

 

 

The responding units were notified with a circular letter about being included in the sample, which was sent to them by mail or by post where mail was unknown. The circular letter contained the general information about the survey and obligation by Law of Statistics to fill the questionnaire and for which variables data are already collected from the existing sources. The guidelines and definitions were published on internet sites of SURS and AJPES.

The questionnaire was open for filling it in on 15 May 2019. The deadline for filling in the questionnaire was set to 7 June 2019, but the final deadline was then change to 3 July 2019. After the deadline non–responded business entities were notified by mail. In July and August 2019 just non-responded key-responders were contacted to send the data. The data collection ended in October 2019. 

From end of October 2019 to February 2020 data were analysed and some double checking with responding units were done. In March 2020 the data were weighted and basic tables were made. Through period from April until June 2020 other tables were produced and checked. First Release was published on 18 June 2020 as a provisional data. Final data was published on 30 June 2020, with detailed data in the SISTAT database. On the same day data were put in Eurostat's standard scheme and sent to Eurostat via Edamis.

3.4. Data validation

Data collected with the questionnaire were validated trough set of logic controls. First logic control was built in application of data collection where mistakes were hard or soft (colored in red or yellow). Data could not be transferred with hard mistakes while for soft mistakes their values must be double-checked.

3.5. Data compilation

Data from the questionnaire and administrative data are compiled into the ORACLE database using SID (statistical ID) number of employee and PIN number of local kind of activity unit.

3.6. Adjustment

Due to national specific earnings system data are adjusted to be in line with the regulation's requirements. For the same reason separated tables with data for 1+ employee and 10+ employees were also prepared.


4. Quality management Top
4.1. Quality assurance

Key quality indicators are calculated regularly.

4.2. Quality management - assessment

Standard quality report is prepared for every SES survey.


5. Relevance Top
5.1. Relevance - User Needs

The main SES users are the Institute of Macroeconomic Analyses and Development, the Bank of Slovenia, the Ministry of Labour, Family, Social Affairs and Equal Opportunities, the Ministry of Finance, the Chamber of Commerce and Industry, the Employers' Association of Slovenia and trade unions. Important users are also units within the Statistical Office of the Republic of Slovenia (SURS). Other users of survey results are various research institutes, domestic and foreign companies, students and the media.

The most important national users are the Ministry of Labour, Family, Social Affairs and and Equal Opportunities (The International Cooperation and European Affairs Service), the Institute of Macroeconomic Analyses and Development and the Employers' Association of Slovenia.

Major foreign users of survey data are Eurostat, the European Central Bank, the International Monetary Fund and the International Labour Organisation. SES data also represent basis for many researchers dealing with earnings statistics.

From SES2014 onwards anonymised data for Slovenia are also available on CD-ROM for researchers, prepared by Eurostat.

5.2. Relevance - User Satisfaction

Structural data on earnings, including Gender Pay Gap, are one of the top data on earnings which are interesting not just for experts but also for general public. In general users are satisfied with data offered but two main weaknesses were mentioned; information on structure of earnings should be available more often than every four years (problem is solved by annual estimations, especially with annual Gender Pay Gap) and data availability which is almost one and half year after the reference period (for domestic users) or almost two years (for international comparison). For SES2018 final data were published T+18 months (for SES2014 T+24 months).

There is user service on the level of NSI. At least once per 1.5 year Statistical Advisory Committee is held, where main and other users can express their needs. Key users are treated individually on request.

5.3. Completeness

In the SES the articles of the EU Regulation regarding SES are fully implemented. Because holiday bonus and payments in kind (including payments for meal and for travel from/to work) are not part of the earnings system in Slovenia they are for Eurostat included in the earnings data but shown separately in national tables.

5.3.1. Data completeness - rate

100%


6. Accuracy and reliability Top
6.1. Accuracy - overall

Accuracy is described in 6.2 to 6.6.

6.2. Sampling error

See 6.2.1.

6.2.1. Sampling error - indicators

In the tables from 1 to 5 sampling errors are shown in percentage for variables 4.2 (Gross earnings in the reference month) and 4.3 (Average gross hourly earnings in the reference month) for different individual breakdowns.

Coefficients of variations are calculated for business entities with 1 and more employees and for all activities A-S.



Annexes:
6.2.1_Sampling errors_SES2018_Slovenia
6.3. Non-sampling error

See 6.3.1. - 6.3.5.

6.3.1. Coverage error

See 6.3.1.1. and 6.3.1.2.

6.3.1.1. Over-coverage - rate

For SES2018 there are no difference between the reference and the study population. For national purposes for business entities and employees in activities A and S data were also collected and published. Moreover also data for business entities with less than 10 employees were included.

On total there was 1.7% of over-coverage among business entities and 2.7% among employees. Higher % of overcoverage in activities K and L is because in those two activites all ineligible units are small units with very high weights.

There were some responses from units which were not in the sample but they were in the frame. Under-coverage was not detected.

6.3.1.2. Common units - proportion

Not applicable.

6.3.2. Measurement error

Data were collected electronically by AJPES. Every question in the questionnaire contains the definition of what must be included in and excluded from the data. Methodology and definitions were published on SURS and AJPES internet sites. First logic control was built in application of data collection where mistakes were hard or soft (colored in red or yellow). Data could not be transferred with hard mistakes. Mistakes are described in the following table. In case of unit non-response reporting units were notified to send the data.

All hard mistakes detected through the system of logical controls were corrected by the companies themselves. Where a lot of soft mistakes occurred companies were contacted and data were double checked. Variables from existing sources were not controlled; they have their own checking system. Data from existing sources were put through code list to check possible miscoding.

6.3.3. Non response error

See  6.3.3.1. and 6.3.3.2.

6.3.3.1. Unit non-response - rate

The overall unit response rate was 85.7%. Response rate concerning employees was 90.9%. In the sample key-responders were selected which represent units from which respond is necessary to obtain the sample quality. In case of unit non-response re-weighting was used.



Annexes:
6.3.3.1_Non-response rates_SES2018_Slovenia
6.3.3.2. Item non-response - rate

For mandatory variables, including ‘Gross earnings in the reference month'; variable (4.2), data were expected while filling in the electronic questionnaire. This variable was not included in the logic control as hard mistake, because it is possible for employee not to have been paid in October. Missing data were checked at the business entities and corrected if necessary. No imputation was performed in case of item non-response.

6.3.4. Processing error

See 6.3.4.1.

6.3.4.1. Imputation - rate

Most of the mandatory variables (those collected with the questionnaire) were included in the logic control and mostly of them were treated as hard mistakes in case of item non-response. Also the questionnaire could not be delivered if these variables were not filled in correctly. For those variables no imputation were performed, just statistical editing. For other mandatory variables missing values were found out in the latter stage of data analysing and imputation were performed. Overall imputation and editing rates were 3.0% and 4.0%, respectively.



Annexes:
6.3.4.1_Imputation and editing rates_SES2018_Slovenia
6.3.5. Model assumption error

No models were used.

6.4. Seasonal adjustment

Not applicable.

6.5. Data revision - policy

See link.



Annexes:
General Methodological Explanations – REVISION OF STATISTICAL DATA
6.6. Data revision - practice

Provisional data were published on 18 June 2020 and final detailed data were published on 30 June 2020.

6.6.1. Data revision - average size

No differences between provisional and final data.


7. Timeliness and punctuality Top
7.1. Timeliness

Provisional data were published on 18 June 2020 and final detailed data were published on 30 June 2020. Final data were sent to Eurostat on 30 June 2020 which is 18 months after the reference period as it is stated in the EU regulation.

7.1.1. Time lag - first result

First results (provisional data) were published on 18 June 2020 which is 17.5 months after the reference period.



Annexes:
First Release: Earnings (by the Structure of Earnings Survey), Slovenia, 2018
7.1.2. Time lag - final result

Final results were published on 30 June 2020 which is 18 months after the reference period.



Annexes:
Final data: Earnings (by the Structure of Earnings Survey), detailed data, Slovenia, 2018
7.2. Punctuality

Data were published as planned.

7.2.1. Punctuality - delivery and publication

0 days.


8. Coherence and comparability Top
8.1. Comparability - geographical

SES2018 data were collected for Slovenia as total in accordance with EU regulations.

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable.

8.2. Comparability - over time

In comparison with previous SES almost all methods were the same. There were small changes in data collection regarding more logic controls.

SES2018 data were collected in accordance with EU regulations with some exceptions listed below:

  • Also business entities with less than 10 employees were included because of national purposes. In Slovenia there are many small business entities; for SES2018 85.2% of all business entities, which represents 21.1% employees.
  • Apprentices were excluded due to negligible phenomena and because units would face a problem filling the data.
  • By the regulation payments paid by employer at a reduced rate are to be excluded. In Slovenia there are a lot of payments at a reduced rate because all sickness leave which is paid by employer (up to 30 days) is paid at a reduced rate (except in case of injuries at work). Therefore data on monthly and annual earnings were collected separately for total and payments at a reduced rate. For EU purposes payments at a reduced rate were deduct from total payments (the same procedure was applied for paid hours and paid hours at a reduced rate).
  • Holiday bonus in Slovenia is not treated as earning component. In tables for Eurostat holiday bonus was included but for national purposes holiday bonus was excluded from annual earnings data and shown separately.
  • Wages in kind in Slovenia are not treated as earnings component though wages in kind in Slovenia represent high share in total costs because of payments for costs for meals and payments for travel between home and work. In Slovenia all employees are entitled for costs for meals and most of employees are entitled to receive payments for travel between home and work (e.g. as cash payments, bus or train tickets). In tables for Eurostat payments in kind were included but for national purposes payments in kind were excluded from annual earnings data and were shown separately.
8.2.1. Length of comparable time series

In Slovenia SES is carried out every four years from 2002 onwards with no major changes.

8.3. Coherence - cross domain

Some variables, which were available from Tax Administration (annual wages, holiday bonus) were double checked.

8.4. Coherence - sub annual and annual statistics

Not applicable.

8.5. Coherence - National Accounts

In some activities there are lower average annual wages and salaries per employee in SES2018 compared to NA data because in Slovenia in wages and salaries per employee in NA data also some payments are included which are not parts of earnings system (e.g. retirement bonus, jubilee rewards). Data on holiday bonus and payments in kind (including payments for costs for meals and payments for travel to/from work) are also not part of earnings system in Slovenia but were collected and included in SES2018 Eurostat tables but excluded for national purposes. In the attached table holiday bonus and payments in kind are included in SES2018 data.

There reasons for the major differences between both surveys among earnings and employees by activities are from the fact that some groups of business entities or employees are included in NA but not in SES; unpaid family members in activity A and business entities without employees in activity L. The difference in activity S is because of relatively high non-response rate. Data on employees for this activity are published as less precise estimate – use with caution.



Annexes:
8.5_Coherence-National Accounts_SES2018_Slovenia
8.6. Coherence - internal

All variables containing earnings and paid hours data were checked with results from existing statistical earnings surveys.


9. Accessibility and clarity Top
9.1. Dissemination format - News release

According to the SURS publishing policy, data were first published in First Release (18 June 2020) as provisional data, including explanations and short methodology.



Annexes:
First Release: Earnings (by the Structure of Earnings Survey), Slovenia, 2018
9.2. Dissemination format - Publications

More detailed results were published on 30 June 2020 in statistical database SISTAT.



Annexes:
Final data: Earnings (by the Structure of Earnings Survey), detailed data, Slovenia, 2018
9.3. Dissemination format - online database

See link.



Annexes:
SiStat Database
9.3.1. Data tables - consultations

In case of special data inquiry special tables are made.

9.4. Dissemination format - microdata access

Individual data are also available in the safe room at SURS and from SES2014 onwards also on Eurostat's CD-ROM for researchers.

9.5. Dissemination format - other

No results were send to the reporting units, only on their explicit request.

9.6. Documentation on methodology

See link.



Annexes:
SES2018 Methodological Explanations
9.7. Quality management - documentation

See link.



Annexes:
Quality Reports
9.7.1. Metadata completeness - rate

All metadata elements are in the Methodological Explanations for SES2018.

9.7.2. Metadata - consultations

No information on the event.


10. Cost and Burden Top

There were additional costs for SURS because of additional logic control and additional individual data protection both implemented in the electronic questionnaire. There is always burden on units selected in the sample, because data on earnings and paid hours are collected with the questionnaire. All other data are collected from the existing sources (see item 3.3.).


11. Confidentiality Top
11.1. Confidentiality - policy

SURS treats all data of all our reporting units (households, persons and enterprises) confidential according to our National Statistics Act, other laws and internal acts. The dissemination of the data must not allow any identification of a reporting unit or disclosure of sensitive data, therefore the data are protected in accordance with the rules of statistical disclosure control. The access to the data is enabled only for the employees, who need the access due to the nature of their work.

For more see link.



Annexes:
Statistical confidentiality
11.2. Confidentiality - data treatment

Microdata are available only in the secure room or via remote access. All direct identifiers are removed from microdata sets and all outputs are checked by SURS' methodologists to prevent any identification of the unit or disclosure of sensitive data.


12. Comment Top

No comment.


Related metadata Top


Annexes Top