Employment: documentation of statistics

Employment statistics are total statistics that cover the permanent population at the end of the year. Data on employed persons and workplaces are produced on employers of different sizes from all industries and sectors of the economy.

The statistical unit of the statistics is a person. The data from different registers are combined by means of a pseudo code formed from the personal identity code and business and establishment codes.

The population for the employment statistics is the permanently resident population in the country on the last day of the year.

The reference area of the employment statistics is the whole of Finland. The data can be compiled by all administrative and coordinate based area divisions, such as regions, wellbeing services counties, employment areas, municipalities, postal code areas, map grid squares or municipal sub-areas.

Annual data on the employment statistics are available on the web pages of the statistics starting from 1987. In addition, data are available for the population census years from 1950 onwards.

Data on occupation and socio-economic group are available for the years 1970, 1975, 1980, 1985, 1990, 1993, 1995, 2000 and annually starting from 2004. In addition, there is a 10 per cent sample of the 1950 population census, which contains data on occupations.

The measurement units of employment statistics are the number of persons and the number of workplaces.

The population of the employment statistics describes the situation on the last day of the year. The data on the population's activity and workplace are from the last week of the year. The statistics also contain accumulated data for the whole year (e.g. income data, months of employment and unemployment).

The compilation of statistics is guided by the Statistics Act. The Statistics Act contains provisions on collection of data, processing of data and the obligation to provide data. Besides the Statistics Act, the General Data Protection Regulation, the Data Protection Act and the Act on the Openness of Government Activities are applied to processing of data when producing statistics.

Statistics Finland compiles statistics in line with the EU’s regulations applicable to statistics, which steer the statistical agencies of all EU Member States.

Further information: Statistical legislation

Data from several different registers or data sets are used in the production of employment statistics. The most important of these are:

• Population Information System (Digital and Population Data Services Agency) 
• Incomes Register
• tax register
• the register of job seekers of the KEHA-center 
• different student registers 
• register of university personnel and local kind of activity units of The Ministry of Education and Culture 
• Conscripts Register of the General Staff of the Armed Forces and The Civil Service Register of the Centre for Economic Development, Transport and the Environment (ELY).
• the Finnish Centre for Pensions' register of YEL/MYEL insured persons
• Statistics Finland's Register of Enterprises and Establishments and the Register of Public Corporations.
• Statistics Finland’s Register of Completed Education and Degrees
• structure of earnings statistics 

In addition to registers, data is collected from multi-establishment enterprises:

• Inquiry on establishment structure and personnel

The key aspect of the system is that register identification systems are so good that combining different data is possible. Registers may contain overlapping information, partly also conflicting information. It is essential that registers complement each other and overlaps ensure that the system is not so vulnerable; if, for example, information on the employment relationship is not obtained from the employment pension system, information on a person's employment can be deduced through taxation data. Several data for the employment statistics can be obtained direct from some register without much change or editing. Such include the person's demographic data or income and wealth data. A number of data are also produced with the so-called register estimation method, where the value of each variable is defined for each person by utilising several register data simultaneously. An example of such a variable is the person's main type of activity. In its deduction, information is needed on the person's age, employment relationships, unemployment, studying, receiving pension, and so on. The deduction rules have been formed so that they produce data as close as possible to the data collected on the basis of questionnaires. The deduction rules were formed by utilising data from previous population censuses and register data from the same period. The deduction rules also include prioritisation of different data when the data are conflicting.

The register-based source data for the employment statistics are collected annually. As a result of the introduction of the Incomes Register, continuously updated data warehouses will be used. The inquiry on establishments of persons working in multi-establishment enterprises is carried out yearly.

Register-based data for the employment statistics are delivered to Statistics Finland in accordance with agreements made with data suppliers.

Inquiry on establishment structure and personnel is sent to multiple-establishment enterprises and corporations towards the end of the year. The inquiry covers annually approximately 5,000 enterprises or corporations. The inquiry is replied to using a web questionnaire. Finally, Statistics Finland's interviewers try to reach non-respondent enterprises and corporations.

Source data arriving to the employment statistics are checked technically. The frequencies of the data are compared with earlier years and if necessary, it is checked from the data supplier whether changes have taken place in the statistical topic, data content or classifications.

The main processes of the production of employment statistics are:

Main type of activity and period data, industry, sector

The data processing processes combine and complement the data and review and correct the data collected in the collections. These processes can be performed as source data are entered into the database. The process phases are checking and correcting of establishment codes, mechanical enterprise and entrepreneurial linking, manual enterprise linking, mechanical establishment linking, run of checking programs and manual correcting of data.

The main and secondary employment relationship for persons is selected possibly from several employment relationships and the person’s main type of activity is concluded (e.g. employed, unemployed, student, pensioner, etc.).

In addition, several further data are formed in the production of employment statistics (e.g. unemployment, job seeking, compulsory military and non-military service), which can be utilised in examinations of different reference periods.

Occupation

In the employment statistics, data on occupation are produced primarily for wage and salary earners and entrepreneurs aged 18 to 74 based on the person's main employment relationship during the last week of the year.

The occupational code is primarily formed for the person based on the occupational title, industry data, education and sector with an application. Some of the data on the occupations of wage and salary earners (employer organisations) are obtained as ready codes from the statistics on wages and salaries.

New occupational titles can be added to the application of the register of occupations as search words or synonyms for the search word. Rules can be added and updated for search words. The rules contain the establishment's or enterprise's industry data, sector data and enterprise's size data and the person's education and occupational status data (entrepreneur, wage and salary earner). In the dictionary of occupations of the occupation application, there are around 30,000 search words related to occupations and conditions related to them.

Entrepreneurs are also classified with the application of the register of occupations. Entrepreneurs' deduction rules are mainly based on industry and size of enterprise. Owners and managing directors of small enterprises employing under five persons are classified into occupations to which their work tasks relate, e.g. hairdresser, taxi driver, etc. In companies with 5 to 49 employees, managers are classified in categories 12, 13 or 14. For example, a managing director in a construction company with five or more but under 50 employees is classified in category 1323 Construction managers. In companies, with 50 or more employees, managing directors are classified in category 1120 Managing directors and chief executives.

In addition, so-called untitled data are formed for wage and salary earners without occupational groups, to whom occupations are also run with the application. In addition to the industry, education and sector, the deduction rules for untitled use age limit and pay limit conditions for some occupational codes.

Some, around six per cent, deduction of occupations must also be made manually and they mainly concern entrepreneurs, untitled and errors detected at the checking stage. In addition to background data revised at different stages of the process, data from previous years are also used here.

Because several occupational titles can be found for some persons from the sources, it is important to combine the occupation data with the main employment relationship during the last week of the year. Data on occupations and employment relationships are primarily taken from the same register but this cannot always be done. Then the person's occupation and main employment relationship with its industries selected in the employment statistics can describe a different employment relationship.

Socio-economic group

Data on socio-economic group are formed for the entire population, i.e. persons permanently resident in Finland on the last day of the statistical reference year.

Socio-economic groups are produced with the application. Data on socio-economic group are based on data on the person's age, main type of activity, occupation, status in occupations and industry. Starting from data concerning 2010, the Classification of Occupations 2010 is used as the basis for data on socio-economic groups. Persons have been classified according to their own activity, apart from persons aged 0 to 15 and the group ‘others outside the labour force’ (mainly home-makers), who have been assigned the same socio-economic group as the reference person in the household.

Administrative registers and other register-based data are mainly used as source data for the employment statistics. Thus, the quality of the statistics is directly dependent on the quality of the source data. Direct data collection takes place only in the definition of establishment data for those employed by multi-establishment enterprises.

In Finland, the reliability of register-based data was studied even before the decision was made about the transition to a register-based population census system. In the 1980 and 1985 census data describing the population's economic activity and employment were still collected with questionnaires, but register-based data were also available at the same time. In the 1980 census a comparative survey was made for 20 municipalities and in the 1985 census for all municipalities. The survey compared register-based data on the population's main type of activity and status in occupation with data collected with questionnaires. The differences in data produced on the basis of registers and questionnaires were found to be so small that the decision to move to register-based statistics production could be made.

An extensive reliability study was conducted in 1990 in connection with the first entirely register-based population census. The register statistics were compared with the data provided by the sample-based questionnaire inquiry. The sample comprised around two per cent of buildings, dwellings and persons. The reliability study showed how large a share of the questionnaire data and register data differed from each other but not ultimately which data were correct. For example, a person with several jobs reported a different job as the main job in the questionnaire inquiry than the one inferred from the register. A working student was inevitably defined as employed based on register data even if he/she had not reported his/her job. Studies have shown that the difference between register-based and questionnaire-based data is not greater than the difference between two questionnaire-based data. Comparative studies have been published in Statistics Finland's series.

The use of the Labour Force Survey as comparison data has become the most important quality control method for the register-based employment statistics. The reliability studies of the 1995 and 2000 censuses were also based on the use of the Labour Force Survey as comparison data.

The use of the Labour Force Survey as comparison data works on two levels. On the one hand, the aim is to monitor the level of the results produced by these two methods and on the other hand, how well the methods produce data classified in the same manner at unit level. Unit-level comparisons are made by cross-tabulating register-based and interview-based data on main type of activity and industry from the same time for persons in the sample data of the Labour Force Survey. Comparisons have been made since 1987.

The deviations can often be explained by differences between the register system and the interview method, and it cannot always be unambiguously said which method produces the right result, that is, even the data obtained with the interviews are not necessarily absolutely correct. Often in reality the person or the interviewer has to make a decision based on conflicting information, while an unequivocal rule has been compiled in the register method. The advantage of the register method is then its logicality: the machine always makes the decision in the same way, but persons with the same information can end up with different results.

Quality management requires comprehensive guidance of activities. The European Statistics Code of Practice forms the basis for the common quality system of the European Statistical System.

The Code of Practice is based on 16 principles that concern statistical authorities' independence, accountability and the quality of the processes and data to be published.

The principles are in line with the Fundamental Principles of Official Statistics approved by the United Nations Statistics Commission and are supplementary to them. The quality criteria of Official Statistics of Finland are compatible with the European Statistics Code of Practice.

Further information: European Statistics Code of Practice | Statistics Finland and Recommendations of the Advisory Board of Official Statistics of Finland | Statistics Finland

The quality of the employment statistics is evaluated in several different stages of the statistical process. The published data are compared with previous years and other data sources, for example.

Revisions – i.e. improvements in the accuracy of statistical data already published – are a normal feature of statistical production and result in improved quality of statistics. The principle is that statistical data are based on the best available data and information concerning the statistical phenomenon. On the other hand, the revisions are communicated as transparently as possible in advance. Advance communication ensures that the users can prepare for the data revisions. 

The reason why data in statistical releases become revised is often caused by the data becoming supplemented. Then the new, revised statistical figure is based on a wider information basis and describes the phenomenon more accurately than before. 

Revisions of statistical data may also be caused by the calculation method used, such as annual benchmarking or updating of weight structures. Changes of base years and used classifications may also cause revisions to data. 

Main type of activity and status in occupation are completed approximately 12 months, workplace data 20 months and occupation and socio-economic group around 22 months after the reference period.

The data for the employment statistics are published as a rule on the days indicated in the release calendar. Possible delays have been caused by delayed source data, for example.

The changing regional classifications (such as changes in municipalities) affect the comparability of certain data (e.g. commuting between municipalities). The data of precise regional divisions (e.g. postal code areas) may contain errors due to the quality of the source data. Employment outside the borders of Finland may cause errors in the employment data of border municipalities.

The compilation of employment statistics was started in 1987. The population and definitions of the employment statistics have remained more or less the same since 1987. The classifications used in the statistics have changed over the years. For example, the Standard Industrial Classification has changed in 1993, 2001 and 2007 and the Classification of Occupations in 1995 and 2010. The changes in the classifications have an effect on the comparability of earlier years, because it is not possible to build complete conversion keys between all classifications. The classifications used in the statistics and the keys between the classifications are available on Statistics Finland's website.

Changes in legislation also affect the comparability of statistics. The so-called short-term employment act entered into force at the beginning of 1998, when short employment relationships were also covered by the pension insurance. This increased the number of employed persons somewhat. From 2005 to 2016, persons aged 18 to 67 were covered by employment pension insurance. Before 2005, persons were covered by employment pension insurance from the age of 14. This is visible in the employment statistics from 2005 onwards as a fall in employment by young people and a rise in the number of students.

In connection with the pension reform of 2017, the minimum age limit for employment pension insurance was lowered to 17 years.

The minimum age limit for entrepreneurial pension insurance remained at 18 years. The change in 2017 has not been taken into account in the deduction of employed persons in the employment statistics, but the age limit for employed persons is still 18 years.

Since the beginning of 2009, grant recipients have been insured under statutory employment pension security in accordance with the Farmers’ Pension Act (MYEL), which means that they are classified as entrepreneurs.

Starting from the 2010 statistics, the definition of entrepreneurs takes into account not only entrepreneurial income but also the so-called entrepreneurial pay included in earned income in personal taxation (pay of self-employed persons insured under the YEL/MYEL insurance), which an entrepreneur can receive, for example, as a partner in an open partnership, as a liable partner in a limited partnership and as a shareholder in a leading position in a limited company. If a person acts both as an entrepreneur and an employee during the last week of the year, he/she is defined as an entrepreneur if his/her combined entrepreneurial income and pay are higher than other earned income, and vice versa. Taking entrepreneurial pay into account in defining entrepreneurs increased the number of entrepreneurs by around 3,300 in the 2010 statistics.

In 2010 to 2011, the number of entrepreneurs rose by 9,600 in the whole country. The rise was affected by the widening of the definition of an entrepreneur in the Self-employed Persons’ and Farmers' Pensions Act from the beginning of 2011. An entrepreneur is a person working in a limited company or in another community in a leading position who alone owns more than 30 per cent of the shares in the enterprise or who alone holds more than 30 per cent of the votes produced by the shares or who has equivalent control in another community. Previously the limit was 50 per cent.

The duration of military service and non-military service was shortened by 15 days from 1 February 2013 (acts amending the Conscription Act and the Non-Military Service Act). As a result of the legislative amendment, a majority of conscripts leave the service before Christmas and are thus no longer in military or non-military service during the reference period of employment statistics (last week of the year). As a result of the amendment, the number of conscripts decreased in 2012 to 2013 by nearly 9,400.

The number of persons on unemployment pension has fallen strongly since the end of the 2000s. Unemployment pensions have not been granted since 2011.

Starting from the 2013 statistics, statistics on those employed in industry 97000 Activities of households as employers of domestic personnel were compiled more extensively than before. In the statistical reference year 2013, industry 97000 grew by nearly 7,600 employed persons. If the persons were employed in the previous year, the most common earlier industry was unknown.

Starting from the 2015 statistics, data on the agricultural industry have become revised. Changes between the statistical reference years 2014 to 2015 are visible on the more detailed classification levels of industry 01 (Crop and animal production, hunting and related service activities) as moves to categories describing the agricultural line of production more closely.

In 2017, regular interviews of unemployed job seekers were started with which the job seeker register could be updated. The fall in the number of unemployed between 2016 and 2017 may be partly affected by the updates made to the job seeker register based on the interviews. There are no exact data on the effect of interviews on the number of unemployed persons, but the Ministry of Economic Affairs and Employment has estimated that the effect could be 20,000 to 30,000 persons (Ministry of Economic Affairs and Employment analyses 83/2017).

The concepts of earned income and entrepreneurial income used in the deduction of wage and salary earners were widened in 2014.

In 2019, the Incomes Register was introduced as a new source data in employment statistics. The Incomes Register replaced several employment data previously used in the statistics. From 2023, pension information will also come from the Incomes Register.

In 2019, the data of persons in the 9th and 10th grades were compiled from the Koski data repository for the first time. Due to the way the data was stored, the data was partially incomplete. As a result, about 400-800 16-year-olds are classified in the group of the other inactive population instead of students.

The used definitions now correspond with the corresponding income concepts of the total statistics on income distribution.

Before 1987, data by municipality describing the economic activity of the population were produced in questionnaire-based population censuses (from 1950, 1960, 1970, 1975, 1980 and 1985). Differences between register-based and questionnaire-based data have proven to be so small that comparability over time can be regarded as relatively good for other classification changes than those mentioned above.

Data on the population's economic activity are also obtained from Statistics Finland's Labour Force Survey, which is a monthly sample survey. Due to the collection method and the deduction of the employed, the data differ somewhat from those of the employment statistics. For example, the number of employed persons is some percentages higher in the Labour Force Survey.

Statistics concerning occupations are, in addition to the employment statistics, published at Statistics Finland also in structure of earnings statistics and in the Labour Force Survey. The occupational data of the structure of earnings statistics and the employment statistics are quite similar because the statistics use the same main data sources. The data of the structure of earnings statistics does not, however, contain self-employed persons, and enterprises whose main industry is agriculture, forestry or fishing. The occupational data of the employment statistics and the Labour Force Survey derive from different sources and concern different time periods - the Labour Force Survey is compiled monthly while the reference period of the employment statistics is the last week of the year. The concepts used by the statistics also differ slightly from one another. For example, in the employment statistics only self-employed persons whose enterprise size according to the Business Register is at least five staff-years are classified as managers, otherwise the occupations of self-employed persons are defined based on the main industry of the enterprise.

KEHA-center publishes statistics on the number of unemployed job seekers. The data of the KEHA-center's job seeker register describe the number of unemployed job seekers on the last weekday of the month. The employment statistics' data on unemployment are based on the data of the KEHA-center's job seeker register. Thus, the employment statistics and the KEHA-center's figures on unemployment are relatively close to each other.

The population, concepts, definitions, classifications, reference periods and methods of other labour market statistics differ from the employment statistics.

Statistics Finland publishes new statistical data at 8 am on weekdays in its web service. The release times of statistics are given in advance in the release calendar available in the web service. The data become public after they have been updated in the web service.

Further information: Publication principles for statistics at Statistics Finland

Future publications of the employment statistics

The data are released to all users at the same time. Statistical data may be processed at Statistics Finland and information on them may be given before release only by persons involved in the production of the statistics concerned or who need the data of the statistics concerned in their own work before the data are published.

Further information: Publication principles for statistics

Unless otherwise specifically stated in connection with the product, data or service concerned, Statistics Finland is the producer and copyright owner of the data. The terms of use for statistical data.

The employment statistics are produced yearly. Main type of activity and status in occupation are completed approximately 12 months, workplace data 20 months and occupation and socio-economic group 22 months after the reference period.

The release is published annually on the home page of the statistics.

The database tables of the statistics can be found in the StatFin database.  

The data protection of data collected for statistical purposes is guaranteed. The compilation of statistics is guided by the Statistics Act. Alongside the Statistics Act, the EU’s General Data Protection Regulation and the Finnish Data Protection Act are applied to the processing of personal data. Provisions on the confidentiality of data collected for statistical purposes are laid down in the Act on the Openness of Government Activities.

The data are processed only by persons who need the data in their work. The use of data is restricted by usage rights. All persons employed by Statistics Finland have signed a pledge of secrecy, where they have obliged to keep secret the data prescribed as confidential by virtue of the Statistics Act or the Act on the Openness of Government Activities.

Further information: Data protection | Statistics Finland (stat.fi)

The data of the statistics are not released in identifiable form outside Statistics Finland. The use of the data for scientific research and statistical surveys is possible only on the basis of a separate decision on user licence and in unidentifiable form. Further information about user licences.

However, data on age, sex, occupation, socio-economic group and education may be released for the above-mentioned purposes with identification data as well.

Data to be protected

Tabulated data refer to statistics where unit-level data have been aggregated and arranged in table format. In the information service of the statistics the statistical unit can be a person, family, household, dwelling, household-dwelling unit or building. In addition to these data, data on enterprises or establishments can be published.

According to the use target, tabulated data can be either 

• A frequency table where the cell values are the numbers of statistical units belonging to the cell (e.g. employed persons), where the cell values are sums, averages or 
• other corresponding key figures of some variable to be tabulated (e.g. income data), or a combination of the above where both cell frequencies and magnitude data are visible.

Tabulated data are subject to a data protection risk whenever there is a risk of disclosure for some statistical unit in the table.

When determining the risk, the following are taken into consideration: sensitive variables or special groups in the table (foreigners, high income groups), number of variables and classification categories, cell and category frequencies (threshold value rule), and the size and location accuracy of the statistical area.

Particular attention is paid to sensitive data defined in the Personal Data Act concerning a person's

• race or ethnic group,
• social, political or religious affiliation or trade union membership, criminal act, punishment or other criminal sanction,
• state of health, illness or handicap of a person or the treatment or other comparable measures directed at the person;
• sexual preferences or sex life; or
• social welfare needs or the benefits received, support or other social welfare assistance received by the person and other sensitive data; such as
• cause of death, language, nationality, origin or country of birth, income, liabilities and assets as well as main type of activity, occupational status, rare occupation or other variable describing socio-economic group.

When the table has three or more variables and at least one variable is sensitive or the area level is smaller than that of a region (e.g. municipality or sub-region), the disclosure risk is probable and more attention is paid to protection.

The principle is that data relating only to the workplace or municipality of residence (e.g. employed persons by industry or commuting data by municipality) need not be protected due to data protection risks. Protection is also not made when mere numerical data are released, and nothing special is revealed, for example, about individual persons.

More attention is paid to data protection whenever more data on the statistical unit can be revealed through the table (e.g. the above-listed sensitive data, income, etc.) or when the regional data are a more detailed regional division than a region, which enables the possibility of indirect identification.

If a disclosure risk exists, the data in the table must be sufficiently protected. The cell-specific threshold value 3 is used in the statistics of the unit when defining the disclosure risk. The dominance rule is not used in the statistics. Protection methods Suppression or changing the structure of the classification/table is almost always used as the protection method for tables:

• Suppression pays attention to primary suppression of cells with a risk of disclosure and secondary suppression. Secondary suppression ensures that the values of primarily suppressed cells cannot be calculated by means of table row or column totals. Secondary suppression can be done so that in addition to the smallest cell frequency, the second smallest cell frequency is also suppressed (protection based on SAS code) or so that the number of cells to be suppressed is minimised (Tau-Argus). The cell value is replaced in suppression with the symbol “..”.
• When needed, suppression can also be made specifically for each row. This means that if only a small number of statistical units belong to a row total of the table (fewer than the used threshold value 3), the row in question is suppressed in its entirety. The values of the row cells are replaced in suppression with the symbol “..”.
• If the table has many sensitive cells or the cells to be protected are centred in only a few categories, the protection can also be made by changing the structure of the table. The structure of the table can be changed, for example, by reducing the number of variables or by changing the classifications of variables. The smaller area the statistics concern, the lower the number of table variables must be. Cross-tabulation of several variables must also be avoided in small area statistics.
• By changing the classification, the cells with a risk of disclosure are removed from the table by combining the categories contained in them to other categories in the table or by forming a new category (e.g. others). Changing the classification usually means that the whole classification becomes less detailed.

The disclosure risk of units included in table data is always assessed when planning tables and before publishing data. The aim is to carry out SDC measures so that the disclosure risk is small but without unnecessarily losing information from the data as a result of protection.