Federal Department of Home Affairs FDHA

Federal Statistical Office FSO

Division Economy

Section Wages and Working Conditions

Espace de l'Europe 10, CH-2010 Neuchâtel

The Swiss Earnings Structure Survey (SESS) exists since 1994 and is carried out every 2 years. Its variables (thereafter called “Swiss variables”) are not yet fully harmonised with those defined in COM-MISSION REGULATION (EC) No 1738/2005 (“Eurostat variables”).

For the first time, Switzerland delivered to Eurostat the two datasets EARNINGS_SES_A_A4 and EARNINGS_SES_B_A4, which are based on the transformed “Swiss variables” in order to approximate to the “Eurostat variables” at best possible. Some aspects of this quality report, due to lack of experience with the “Eurostat variables”, refer to the “Swiss variables” (e.g. relevance; timeliness; accessibility and clarity).

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Sampling methodology: A stratified two-stage random sample

The basis for sampling was the Swiss Business and Enterprise Register. The universe for sampling were all enterprises active in August 2010 on the territory of Switzerland, ranging from NACE Rev.2 section B to S and further including NACE Rev.2 division 2 (NACE Rev.2 division 2 is only for national purposes and is not on the datasets EARNINGS_SES_A_A4 and EARNINGS_SES_B_A4 delivered to Eurostat). In the private sector, the minimum size of the enterprise is 3 upward. In the public sector, there is no minimum size.

The survey did not take into account apprentices, trainees, home workers, persons paid solely on a commission basis, persons whose professional activities take place mainly abroad and persons who earn a reduced wage due to occupational disability. The wage data of subcontracted workers had to be delivered by their employment agencies.

In the private sector the SESS is based on a random sample at two levels: The first level concerns the stratified enterprises, while the second level concerns the employees in the enterprises. Enterprises are stratified according to three criteria: enterprise size (3 classes), economic branch (39 ag-gregations of NACE Rev.2 divisions) and geographical entity (7 major regions, 7 cantons and 1 city).

In total the SESS stratification includes more than 1600 cells (strata). While for some strata the selection of the enterprises is exhaustive (this is always the case for enterprise size larger than 49, but not exclusively), for the majority of strata enterprises are sampled by random selection.
In the federal and cantonal public sectors the survey is exhaustive for enterprises and administrations at the first, but not necessarily at the second stage. In the public sector at communal level, sampling is again based on a two-stage stratified random sample: the communes and the employ-ments (one employee can have multiple employments). The stratification at the commune level is based on commune size (4 categories) and geographical entity (7 major regions). In total the SESS stratification of the communes results in 27 strata; for the biggest size class (communes with more than 800 employees), the samples at the first stage are exhaustive, while for the rest of the strata communes were selected according to random sampling.

The number of salary records of a sampled enterprise or public administration to be delivered depends on the size of the responding unit. Enterprises with fewer than 20 employees have to provide all salaries. For the size class 20 to 49 employees one out of two is to be reported, while in the size class 49+, at least one out of three is expected.

Sampling of the employees has to be done by the responding units themselves, according to princi-ples of random selection.

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The Swiss Earnings Structure Survey 2010 was produced by 11 permanent statworkers (6 of them with a university education), assisted by 21 temporary employed statworkers, who were carefully trained and supervised.

Production process comprises dispatching the questionnaires, counselling enterprises in case of questions; validation of the returned questionnaires and electronic data-files and, in case of doubts, calling back for clarification; furthermore reminding tardy enterprises; and finally entering the data to the provisional database.

The completeness of the returned questionnaires was at first checked by eyes.

The plausibility of the data was then checked by means of electronic tools, after entering the data in the data-capturing system. The plausibility checks generally were not constraining, but rather “warnings”; that means, besides of some impossible categories, the warnings could, after verification, be ignored.

Once the data were definitively cleared, the attribution of the final weights was accomplished by specialised scientific staff. After further checking the final database (“Swiss variables”) was set up.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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The main users of the Swiss Earnings Structure Survey (SESS) are government bodies, trade unions and employers’ associations, international organisations, courts, researchers, mass media and the general public.

The main needs of the users in Switzerland consist in knowledge about earnings according to economic activity, region, level of qualification required by the job, gender, age, citizenship, level of education, occupation, managerial position, length of stay in the enterprise, collective pay agreement and marital status.

Usually users want to know the medians, sometimes also the quartiles and sometimes the arithmetic means. In addition they are often interested in the distribution of wage classes, the proportions of wage components, and finally the comparability of earnings in specific settings of variables across the years.

No specific survey about the satisfaction of users has been conducted. Based on some direct feed-back we have obtained, we assume that their needs are largely being met.

Users’ inquiries that cannot be answered mainly concern earnings according to a very detailed level of disaggregation (either concerning economic activity or regionalisation), often coupled with a combination of too many variables. From the general public there is sometimes a demand concerning earnings in specific professions, which cannot be satisfied.

Users generally made no statements concerning lacking or redundant variables. In a few cases it was regretted that information about the total length of professional experience is lacking.

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The measures of precision in the attached document Sampling errors were calculated in accordance with the sampling design – taking into account both the first and second stage.

All monetary estimators are expressed in the national currency, i.e. Swiss francs (CHF).

Monthly earnings relate to the variable B42, hourly earnings to B43.

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Over-coverage:

No over-coverage does exist.

Under-coverage:

Economic Activity:

The Datasets EARNINGS_SES_A_A4 and EARNINGS_SES_B_A4 delivered to Eurostat cover NACE Rev.2 sections B to S, including O.

Slight under-coverage does exist for NACE Rev.2 division 94: In fact, public churches as employers, mainly belonging to NACE Rev.2 division 94, were covered by the sample, but in the end were not kept in the database, due to inconsistencies between delivered salaries and employees according to the Business and Enterprise Register. In this register they account for 0.38% of the total reference population, while for division 94 (NACE Rev.2) they account for 28%. No action for weight-correction was undertaken in this regard.

Size of enterprises:

No under-coverage regarding the regulation.

Sampling covers enterprises from staff number three upwards, according to the Business and Enterprise Register (“staff”, because the Business and Enterprise Register actually informs only about number of persons working in the enterprise, regardless whether they are proprietors or employees).

Answering enterprises with fewer than three employees in the reference month were kept in the data-set.

With the goal of covering the employees of the whole economy (NACE Rev.2 sections B to S) there is an estimated under-coverage of around 1-2% due to the fact of not sampling the smallest enterprises with fewer than three staff. (Estimation source: Business and Enterprise Register)

Specific categories of employees:

Regarding the COMMISSION REGULATION (EC) No 1738/2005, there is under-coverage concerning the following categories of employees, which in 2010 still were excluded from the Swiss Earnings Structure Survey:

• apprentices
• trainees
• home workers
• employees whose salaries cannot be put in relation to a corresponding working time (flat-rate earnings)

Apprentices account for about 6% for under-coverage in relation to the reference population. (Source: http://www.bfs.admin.ch/bfs/portal/de/index/themen/15/17/blank/01.indicator.401206.4081.html) For the other categories no reliable information is available to quantify the resulting under-coverage.

There is concern about a possible under-coverage of top-earning managers. Indeed it was noticed that their earning data often figure in separate payrolls with restricted access; thus it is possible that such categories may sometimes not have been delivered. Nevertheless, the influence of this possible under-coverage should be quite limited. Simulations doubling the weights (B52) of observations with B41 greater than 1 million Swiss francs show a global increase of 0.6% for annual earnings and of around 0.2% for monthly and hourly earnings.

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The Swiss Earnings Structure Survey starting in 1994, with respect to some variables, does not fully correspond to COMMISSION REGULATION (EC) No 1738/2005. Therefore, the datasets EARNINGS_SES_A_A4 and EARNINGS_SES_B_A4 delivered to Eurostat had partly to be computed. In this context, there are some measurement or processing problems (see table below).

Gross unit response rate:

Concerning the total of NACE Rev.2 sections B-S, the gross unit response rate is 79% for the private sector and 80% for the public sector.

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Generally speaking, one possible source of potential processing errors might be the manual capturing of the data from questionnaires. Nevertheless, data-scanning is also a potential risk regarding the correct reproduction of handwriting; in fact, scanning tests in 2002 showed some problems in this regard. In the end, it was therefore decided to capture the data manually.

As to data delivery by electronic means, an Excel sheet with some incorporated validation checks was designed and put on the internet for download. The barriers were not very constraining, in order not to induce respondents to give faulty, but passing, answers. Anyway, data on almost any support was accepted, provided that it contained the relevant information in a clear way.

See also table in 6.3.2.

Item imputation rate

The table below shows the imputation rates of the variables in which imputation exists.

It is the first time that imputations have been carried out. For the variables not surveyed, most procedures are explained in chapter 6.3.2. Variable B43 results from the division of B42 by B32. The imputations concerning non-responses are mainly based on the principle of predominance; that means, it was observed which were the most prevalent response-categories in specific settings of variables (e.g. most frequent category of level of education in a specific cell combining NACE, professional position and kind of professional activity (“Swiss variables”)). The prevalent category was trans-ferred to the non-responses in the observed cell.

Overall imputation rate

Concerning the variable B42 (Gross earnings in the reference month), no modelling was used to correct for its deficiency (presented in chapters 6.3.2. and 6.3.4. Measurement and processing errors), as there are two contrary deficiency effects which we expect to level out.

Concerning correction for the smallest enterprise size class (1 or 2 employees – not sampled) no model was applied, because

• the information about size class smaller than 10 is optional
• it would be difficult to establish a reliable model
• until now, applying models for correction is not of common usage in SESS
• the effect of deficiency on earnings for the total of size classes and economic activities is es-timated to have only a small impact: in fact, applying an unofficial stopgap model showed an effect of around -0.5%

Concerning under-coverage of NACE Rev.2 division 94 (see chapter 6.3.1 Coverage errors) no modelling to correct for under-coverage was done.

Finally, due to the imputation of all missing items, no observations needed to be excluded from the datasets. Therefore, no correction of the original weights was necessary.

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The reference periods considered for the Swiss Earnings Structure Survey 2010 were:

• October 2010 for monthly earnings
• The whole year 2010 for irregular payments (B411)
• Yearly earnings (B41) were computed and relate to the year 2010.

The national results were published in two steps:

• November 2011: Private sector and part of the public sector (federal level)
• 5 November 2012: Whole economy, i.e., private sector and all public sectors (federal, cantonal and communal level).

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The harmonised Datasets EARNINGS_SES_A_A4 and EARNINGS_SES_B_A4 were delivered to Eurostat in time, i.e. in June 2012. There were no revisions of the delivered data.

The milestones for producing the Swiss Earnings Structure Survey 2010 were:

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The Swiss datasets EARNINGS_SES_A_A4 and EARNINGS_SES_B_A4 delivered to Eurostat are mainly in line with the relevant regulations.

Deviations were discussed in chapter 6.3 (Non-sampling errors).

The most important differences are the following ones:

• Absence of apprentices, trainees and home workers
• NACE Rev.2 of enterprise instead of local unit
• Annual Earnings (B41) is not the actual annual earnings, but the computed annual earning for a full year (consequently B31 is uniformly hardcoded 52.14).

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This is the first time that Switzerland delivers to Eurostat the harmonised Datasets EARN-INGS_SES_A_A4 and EARNINGS_SES_B_A4 – nothing can be said about comparability over time.

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The table below compares two alternative sources (Labour Force Survey and National Accounts) for annual earnings in Switzerland with the results of the Structure of Earning Survey (variable B41 – all amounts in Swiss francs).

Coherence is given between SES and LFS for the Total (Sections B-S of NACE Rev. 2), as well as for most of the sections. For the sections K, L, M, N and P important deviations exist. Further investigation is needed to explore the reasons of these divergences. Globally it can be said that it is not the main scope of LFS to measure earnings.

Concerning the National accounts, the annual amount for D11 in 2010 for the whole economy (including the first sector) was 272220 million Swiss francs. National Accounts do not break down this figure according to economic sections, and consequently it is not possible to limit it to NACE Rev. 2, B to S. National Accounts have no explicit adjustment for the non-observed economy, hence the latter is not included in National Accounts estimates of D11.

The corresponding number of employees was 4.159 million in Quarter4 of 2010.
If we calculate the weighted sum of B41 we get the amount of 264627 million Swiss francs for 3.582 million employees (sum of B52). This means that the employees not included in the Swiss SES (ap-prentices, trainees, home workers, employees in agriculture, employees of enterprises with staff smaller than 3) account for the difference between 272220 million (NA) and 264627 million (SES), which is CHF 7593 million for 577000 employees, resulting in yearly gross earnings of CHF 13159 per head. This seems low, but not impossible (many apprentices, trainees, part-timers).

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Results of the Swiss Earnings Structure Survey 2010 are published on the internet pages of the Swiss Statistical Federal Office.

So far, only data relating to the “Swiss variables” has been made available. These results are not directly comparable to those obtainable with the harmonised Datasets EARNINGS_SES_A_A4 and EARNINGS_SES_B_A4.

Access to Swiss results based on the harmonised variables within the framework of Commission Regulation (EC) No 1738/2005 is currently given only on internet pages of Eurostat.

http://www.bfs.admin.ch/bfs/portal/en/index.html

Main access to the Swiss Federal Statistical Office

http://www.bfs.admin.ch/bfs/portal/fr/index/news/publikationen.html?publicationID=4938

Print publication (only in French and German – available for free download):
The Swiss Earnings Structure Survey 2010 – commented results. Neuchâtel, 2012.

http://www.bfs.admin.ch/bfs/portal/en/index/themen/03/04/blank/key/einleitung.html

Wages and income from employment - indicators

http://www.bfs.admin.ch/bfs/portal/en/index/themen/03/04/blank/data/00.html

Wages and income from employment – detailed data (tables)

http://www.bfs.admin.ch/bfs/portal/en/index/themen/03/04/blank/key/lohnstruktur/salarium.html

Salary calculator (“Salarium”): An interactive application based on a model allowing the calculation of the gross monthly earning and its dispersion (interquartile range) for an individual profile

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http://www.bfs.admin.ch/bfs/portal/en/index/dienstleistungen/informationszentrum/europa_daten_support.html

Accessing European Data

No systematic feedback of their results is given to the reporting units – this is only available upon request.

Explanations concerning the scope, the legal aspects, the processing and the methodology of the Swiss Earnings Structure Survey are accessible on the internet pages of the Swiss Federal Statistical Office.

Users are provided information about links to the data through press-releases, newsletters, print publications, letters, e-mails, by phone and through personal contacts.

Metadata is implicitly contained in the tables, where definitions and codes are explained. Until recently, the questionnaire with its annex explanations of the Swiss Earnings Structure Survey 2010 was on the internet, but with the 2012 revision of the survey, only the new questionnaire is made available in order to avoid confusion. All important nomenclatures are accessible on
http://www.bfs.admin.ch/bfs/portal/en/index/infothek/nomenklaturen.html

Some additional key publications are listed below:

Surveys, Sources - Swiss Earnings Structure Survey
Fact file (available in German, French and Italian).

http://www.bfs.admin.ch/bfs/portal/de/index/infothek/erhebungen__quellen/blank/blank/sle/01.html

Surveys, Sources - Swiss Earnings Structure Survey
Legal basis / Data protection (available in German, French and Italian).
http://www.bfs.admin.ch/bfs/portal/de/index/infothek/erhebungen__quellen/blank/blank/sle/04.html

Methodological aspects, comprehensible to the general public, of the 2010 survey are summed up on pp. 19-21 of the latest print publication (only in French and German – available for free download): The Swiss Earnings Structure Survey 2010 – commented results, Neuchâtel, 2012.
http://www.bfs.admin.ch/bfs/portal/de/index/infothek/publ.html?publicationID=4937

Several methodological reports, addressed to the scientific reader, have been published in the past and are available for free download on the internet:

Andrade, Beatriz; Graf, Monique / BFS : Enquête sur la structure des salaires 2006 - Aspects métho-dologiques du modèle des salaires «Salarium». Neuchâtel, 14.7.2008

This methodological report concerning the salary calculator is available only in French

http://www.bfs.admin.ch/bfs/portal/de/index/themen/03/22/publ.html?publicationID=3277

Graf, Monique ; Ferrez, Jacques / BFS: Enquête suisse sur la structure des salaires - Programmes R pour l'intervalle de confiance de la médiane. Rapport de méthodes. Neuchâtel, 2007

This methodological report concerning the calculation of the confidence interval based on the median is available only in French

http://www.bfs.admin.ch/bfs/portal/de/index/themen/03/22/publ.html?publicationID=2719

Graf, Monique / BFS: Swiss Earnings Structure Survey 2002-2004 - Compositional data in a stratified two-stage sample: Analysis and precision assessment of wage components. Methodology Report. Neuchâtel, 10.6.2006

http://www.bfs.admin.ch/bfs/portal/de/index/themen/03/22/publ.html?publicationID=2233

Graf, Monique ; Matei, Alina / BFS: Enquête suisse sur la structure des salaires 2002 – La précision du salaire brut médian. Rapport de méthodes. Neuchâtel, 2005

This methodological report concerning the calculation of the confidence interval based on the median is available only in French

http://www.bfs.admin.ch/bfs/portal/de/index/themen/03/22/publ.html?publicationID=1862

Graf, Monique / BFS : Enquête suisse sur la structure des salaires 2002 - Plan d'échantillonnage et extrapolation pour le secteur privé. Neuchâtel, 2004

This methodological report concerning sampling and extrapolation is available only in French

http://www.bfs.admin.ch/bfs/portal/de/index/infothek/publ.html?publicationID=1354

Graf, Monique / BFS : Enquête suisse sur la structure des salaires 2000 - Plan d'échantillonnage, pondération et méthode d'estimation pour le secteur privé. Neuchâtel, 2002

This methodological report concerning sampling and extrapolation is available only in French

http://www.bfs.admin.ch/bfs/portal/de/index/infothek/publ.html?publicationID=1642

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