15533_om_not-searchable
/en/utdanning/statistikker/uh_statres/aar
15533_om
statistikk
2011-10-27T10:00:00.000Z
Education
en
false

Universities and colleges - StatRes (discontinued)2010

Content

About the statistics

Definitions

Name and topic

Name: Universities and colleges - StatRes (discontinued)
Topic: Education

Responsible division

Division for Education and Culture Statistics

Definitions of the main concepts and variables

Educational institution: University or university college.

Type of institution: Type of educational institution (universities, specialised colleges, state university colleges and other university colleges).

School ownership: Educational institutions are classified as state-owned, county-or municipally owned or privately owned. StatRes only covers universities and university colleges owned by the state.

Student statistics, study credits, publication points, application and admission figures and unit costs:

Registered students: Students registered at an educational institution.

Completed education: An education activity is recognised as completed when the student is awarded a diploma or certificate.

Completed credit points: After passing an examination in a given subject, the student is rewarded a certain amount of credit points. One year full-time study equals 60 credit points.

Educational level: The relevant educational levels of universities and university colleges are: First stage of tertiary education, undergraduate level; first stage of tertiary education, graduate level; and second stage of tertiary education, postgraduate level. The number of registered students may also contain pupils on levels below tertiary education (e.g. post-secondary non-tertiary education).

Education/study: One or more educational courses that are approximately equal with respect to academic content and level. The educational activities are classified in detail in the Norwegian Standard Classification of Education. When publishing official education statistics there is a need for a simplified standard grouping. In tables on through-put in tertiary education in StatRes one such grouping of tertiary qualifications is used.

Normal study duration: Completion of degrees according to normal study duration, is calculated based on the first semester the student was registered in the programme. Normal study duration requires a completion of 30 credit points (ECTS) on average per semester. Deferment of study is not included.

Publication points: Indicates the extent and quality of scientific publication. Publication points are produced by multiplying the number of author shares, weighted by the combination of publication form and quality (Source: the DBH).

Student places: The number of available student places for studies included in the national admission model (NOM). For open studies at the universities, the number of available student places is an approximate figure (Source: the Norwegian Universities and Colleges Admission Service (NUCAS - Samordna opptak)).

Primary applicants: A primary applicant is an applicant who has listed a particular education as his/her first priority on the application form (Source: the Norwegian Universities and Colleges Admission Service (NUCAS - Samordna opptak)).

Input statistics, account figures:

Operating expenditures: Includes compensation of employees, the use of goods and services, property expenditure, as well as transfers in the form of cash or payment in kind.

Compensation of employees: All the institutions’ outlays as employers, including national insurance contributions and pension premiums. Sick pay reimbursements from the National Insurance Scheme, parental reimbursements, labour market measure reimbursements and apprenticeship reimbursements are deducted from the compensation figures.

Use of goods and services: Goods and services used for the production of government goods and services, including repair and maintenance expense.

Property expenditure: Includes interest payments.

Gross acquisition of non-financial assets: Acquisition less disposals of non-financial assets (e.g. buildings, structures and land).

Depreciation: Distribution of the investment cost of assets over their economic life. This is applicable to operating equipment such as fixed assets as well as immaterial rights, while depreciation of assets with an unlimited economic life such as land does not take place. The annual depreciation is indicated as a cost in the accounts. In StatRes, depreciation is not included in the operating expenditure concept, but the figures are provided as additional information.

Opportunity cost (of capital): Corresponds to the potential income for the Government from alternative uses of their capital, i.e. the implicit cost for the Government caused by the tying up of this capital in the various assets of the universities. Opportunity cost is not included in the operating expenditure concept.

Revenue: Revenue includes transfers from the Ministry of Education and Research (KD) and other ministries, external financing from the Research Council of Norway (NFR), the EU and others, commission revenue, other revenue including sale of goods and services, and property revenue. The main part of the transfers to the institutions comes from KD, with the exception of the Norwegian Police University College where transfers come from the Ministry of Justice and the Police (JD).

Note that the figures for transfers in StatRes differ slightly from those in the institutions’ own accounts. This is because the institutions follow the accrual principle and distribute also the transfers related to investments in assets over their economic lifespan (see the discussion of depreciation above). In the accounts, this is done by subtracting the figure for gross acquisition of non-financial assets from the figures for transfers, and at the same time adding a figure for &“Postponed income related to investment (depreciation)´´ which balances the annual depreciations. In StatRes, however, the unadjusted transfer figures are used.

Property revenue: Includes income from interest and share dividends.

Operating expenditure for research and development (R&;D): Includes compensation and other operating expenditures related to R&;D as calculated by NIFU. Capital costs are not included.

NIFU publishes data on an educational institution level every other year (uneven numbered years). Figures for even numbered years are based on the R&;D share of t-1 (except for 2004, which was based on shares from 2005). The first release of data (October) for an uneven numbered year will be based on the R&;D shares of t-2 since NIFU doesn’t complete figures until later on in the year. These figures are updated in a new publication with more accurate shares when data from NIFU are available.

The published R&;D figures in StatRes are, for some educational institutions, lower than the corresponding figures at NIFU. This is caused by two factors: Firstly, some units included in the figures from NIFU are deemed as not a part of the educational institution in a judicial sense, and thus are omitted. An example of this is units related to UNIFOB AS at the University of Bergen. As of 2009, Uni Research (formerly UNIFOB AS) changed sector in the R&;D-statistics, and is no longer part of the university and college sector.Secondly, as of 2007, NIFU splits health enterprises (including university hospitals) into a separate statistic. For comparison, certain units from UiO, UiT, UiB and NTNU, are therefore omitted also for 2005. It must be stressed that there is some uncertainty with regards to the comparability of the time series for educational institutions with associated university hospitals.

For all educational institutions there is some uncertainty attached to the figures for the years where NIFU doesn’t gather all data, and R&;D shares from year t-1 are used as a basis.

Operating expense for teaching: Total operating expense with R&;D expenses deducted. There are no authoritative data sources available when assessing the scope of operating expenses for teaching. Teaching expense is therefore, in lack of a better alternative, calculated as a residual. This may cause other expense, for instance expense to operate a museum, to be included. Statistics Norway will in the future be working on improving the methods for calculating these variables.

Input measured in contracted man-years adjusted for long term leaves:

Contracted man-years adjusted for long term leaves: is defined as the sum of the number of full-time jobs and part-time jobs converted to full-time equivalents, excluding man-years lost due to doctor-certified absence and parental leaveSee section 3.6 Estimation.

Teaching-, research- and dissemination-positions: The definition of &“Teaching-, research- and dissemination-positions´´ is identical to the definition used by the Norwegian Social Science Data Services (NSD) in their Database for Information on Research and Higher Education, but Statistics Norway and NSD count the man-years in different ways and use different data sources (see point 6.2 Coherence with other statistics).

The contracted man-years adjusted for long term leaves are distributed on groups of positions partly according to the Standard Classification of Occupations (STYRK98), and partly according to position-codes of the State's Central Register on Civil Servants (SST). The contracted man-years adjusted for long term leaves are distributed on two main groups of positions:

  • Teaching-, research-, and dissemination-positions.
  • Administrative- and support-positions.

Within the main group Teaching-, research-, and dissemination-positions, Statistics Norway has defined four subgroups of positions:

1) ´´Positions that require competence for an associate professorship´´

2) ´´Research positions´´

3) ´´Recruitment positions´´

4) ´´Teaching positions and others´´

Standard classifications

Educational institutions are classified as being tertiary by the Standard Industrial Classification.

Student statistics, study credits, publication points, application and admission figures and unit costs:

Educational activities: Educational activities are grouped by the Norwegian Standard Classification of Education, which was compiled in 1970 by Statistics Norway and revised in 1973, 1989 and 2000.

Input statistics, account figures:

Revenues and expenditures: The institutions’ accounts are processed for use in National Accounts, following international guidelines. Revenues and expenditures are classified into main groups according to whether the transactions are based on operations or investments. Expenses are also classified according to their main function. Classification of transactions by function is according to the United Nations' Classification of the Functions of Government (COFOG). All expenditures in Universities and colleges- StatRes are assigned to COFOG 0941, First stage of tertiary education. Data on operating expense for R&;D from NIFU is calculated according to the OECD Frascati manual. However, as described in section 4.1, Statistics Norway has made certain changes to the figures for some of the educational institutions.

Man-years statistics:

Groups of positions: The contracted man-years adjusted for long term leaves are distributed on groups of positions (see 4.1) partly according to the Standard Classification of Occupations (STYRK98), and partly according to position-codes of the State's Central Register on Civil Servants (SST).

Administrative information

Regional level

Educational institution

Frequency and timeliness

Annual

International reporting

Not relevant

Microdata

The microdata used in StatRes (student, accounts and man-year data) are stored in a standardised manner as recommended by the Norwegian Data Inspectorate.

Background

Background and purpose

Universities and university colleges are a part of StatRes. The object of StatRes is to present statistics on central government input, to various central government activities, the results of this input in terms of activities and services, and the outcomes of the input. The purpose of such statistics is to give the general public and the authorities improved knowledge of state activities.

The StatRes project was started in 2005 and the first figures were published in October 2007. The development of StatRes takes place in cooperation with the Ministry of Government Administration and Reform, which also is financing parts of the project.

Users and applications

StatRes’ target group are users of statistics with some knowledge of and interest in central government activities who require on information on resource use, activities, services and outcomes of state activities. Such users could be the general public, the media, politicians, pupils and students. StatRes shall also provide the authorities with information which supplements other information used in the governance of central government activities.

Coherence with other statistics

Other figures for universities and university colleges are also published, or statistics where universities and university colleges are part of the population. In StatRes, the population is delimited by the central government (state-owned educational institutions). At the same time statistics and indicators are presented in an overall system with the objective of presenting statistics on central government input, to various central government activities, the results of this in put in terms of activities and services, and the outcomes of the input. This way of delimiting, linking, adaptating and presenting data and statistics distinguishes StatRes from other official statistics concerning central government and central government activity.

Student statistics:

Figures on tertiary education (irrespective of school ownership) are presented under Education statistics, universities and colleges. These statistics include students, degrees, credit point production and throughput of students.

Due to lack of information on funding of the different studies, some credit point figures are collected from the DBH (in Norwegian only). These figures are used in the unit costs. The DBH also publishes other figures concerning state-owned and private educational institutions funded by the Ministry of Education and Research. The universities and university colleges are the source of these figures, but as opposed to Statistic Norway’s figures, the DBH statistics are not individual-based.

Input statistics, account figures:

The statistics are based on the international standards for National Accounts: System of National Accounts (the UN a.o.) and European System of Accounts (the EU), plus the International Monetary Fund’s (IMF) A Manual on Government Finance Statistics. In certain cases the standards have however been disregarded in order to give a more accurate picture of the use of resources. No corresponding short-term statistics are disseminated, but the Central Government's revenues and expenditures are disseminated quarterly according to the Ministry of Finance's own table in the statistics Central Government fiscal account, revenue and expenditure. In principle the statistics are incorporated directly into the National Accounts, with certain exceptions as indicated above. Central government's revenues and expenditures can be found in various tables for the Central government in the institutional accounts of the National Accounts.

The figures for R&;D operating expenses are also published by NIFU. Previously only on an aggregated level with regards to colleges. As of 2009 NIFU publishes R&;D figures per College.

Input measured in contracted man-years:

Statistics Norway does not publish other particular statistics on employment in universities and colleges today, but the employees are included in Statistics Norway’s general register-based employment statistics where the employees and their contracted working hours are only counted in the enterprise where the employee performs her/his main position. StatRes also includes second jobs, in addition to 1) inclusion of employees more than 74 years old, 2) inclusion of employees on a short-term stay in Norway and 3) subtraction of doctor-certified absence and parental leave.

Until 2003, Statistics Norway published statistics on teachers in universities and colleges , based on information from the States Central Register,on Civil Servants. The teacher-statistics differs from StatRes-Universities and colleges in two respects. Firstly, the teacher-statistics included only teachers and administrative personnel that normally are teachers (headmasters, teaching inspectors and such). Accordingly, the teacher-statistics excluded administrative and support positions that are included in StatRes. All kinds of personnel are included in StatRes. Secondly, the teacher-statistics counted contracted man-years, whereas StatRes count contracted man-years adjusted for long term leaves (see section 3.6 Estimation).

The Norwegian Social Science Data Services (NSD) publishes statistics on personnel in universities and colleges in their Database for Information on Higher Education and Research DBH (in Norwegian only). DBH and StatRes are not comparable, for several reasons. Firstly, StatRes is based on information from several registers, whereas DBH is based on self-reported information from the enterprises to DBH. Secondly, StatRes counts contracted man-years adjusted for long term leaves (see section 3.6 Estimation), whereas DBH counts contracted man-years. Thirdly, DBH excludes all hourly paid personnel, whereas some of these are included in StatRes.

Legal authority

Statistics Act sections 2.2, 2.3 and 3.2.

EEA reference

Not relevant

Production

Population

The population includes all state-owned universities and university colleges except military colleges.

Data sources and sampling

Student statistics:  

Pursuant to the Statistical Act, Statistics Norway collects student data from Database for Statistics on Higher Education (DBH) and the administrative systems of the various tertiary institutions.

Information on Norwegian students abroad is provided by The State Education Loan Fund.

Surveys are not employed to collect education statistics. All data is obtained from university and college databases

Information on completed doctoral degrees is collected from NIFU.

Credit points:

Since there is no information in type of funding in education statistics in Statistics Norway, credit point figures used in unit costs and other productivity indicators are collected from the Database on Information on Research and Higher Education (DBH).

Publication points:

Figures are collected from the Database on Information on Research and Higher Education (DBH).

Application and entry figures:

Figures are collected from the Norwegian Universities and Colleges Admission Service (NUCAS - Samordna opptak).

Input statistics, account figures:

For all universities and university colleges except for the Norwegian Police University College, accounts data are collected from the Database for Information on Research and Higher Education (DBH) which is a database for information about Norwegian universities and university colleges. The system is operated by the Norwegian Social Science Data Services (NSD) sponsored by the Ministry of Education and Research (KD).The universities and university colleges submit their accounts in Excel or PDF format to this database, which is publicly available through the home page of NSD (in Norwegian only). For the Norwegian Police University College the source of data is the figures reported by the Norwegian Government Agency for Financial Management (SSØ) for the Central Government Budgetary Accounts (Report to Stortinget, no. 3).

Figures for operating expenditures for research and development (R&;D) are received from NIFU (see 4.1).

Figures for operating expenditures for teaching are total operating expense with R&;D expenses deducted.

Input measured in contracted man-years:

Register-based employment statistics in Statistics Norway are based on individual register data from various registers. Information related to employees and agreed working hours per week is mainly collected from the Nav State Register of Employers and Employees, the End of the Year Certificate Register, the Tax Register (the Directorate of Taxes), and payroll registers. The Central Coordinating Register for Legal Entities in Brønnøysund and Statistics Norway’s Central Register of Establishments and Enterprises provide data on industries and sectors for enterprises and underlying establishments. NAV’s register of participants in labour market initiatives, recipients of parental benefits and doctor-certified absence are also included. The employment statistics is therefore based on a number of different sources. Statistics Norway has developed a system for common utilization of these sources.

Collection of data, editing and estimations

Student statistics:

Pursuant to the Statistics Act, Statistics Norway collects student data from the administrative systems of the various tertiary institutions.

Credit points containing information about financing, and publication points:

Manual registration of data collected from the DBH.

Application and entry figures:

Manual registration of data from Norwegian Universities and Colleges Admission Service (NUCAS - Samordna opptak).

Input statistics, account figures:

Accounts are downloaded from the DBH (see 3.2). Figures for operating expenditure for R&;D are received on a data file from NIFU.

Input measured in contracted man-years:

Extracts from several registers (see 3.2).

Definition and classification of the population for each year are controlled against the Central Register of Establishments and Enterprises (BoF), in practice identical with the Brønnøysund Register of Business Enterprises.

Student statistics:

Control and revision are carried out on all data received from educational institutions. This includes the deletion of duplicate records, controlling for correct and valid values for each variable and checking for missing information. Several variables are re-coded to comply with control programs run by Statistics Norway. In addition personal ID numbers are checked against Statistics Norway's population database.

Input statistics, account figures:

Processing and coding of the accounts is mainly done automatically by programs. The coding of the individual accounts is controlled by checking the totals for revenues and expenditures as well as other figures against the unprocessed accounts from the DBH. The coded figures for operating expenditures for R&;D are checked against the received data file from NIFU. Figures are also compared to the figures in previous years. Operating expenditures on R&;D is checked against figures from NIFU, and are also compared to figures of previous years. There are also automatic controls of data.

Input measured in contracted man-years:

The three most central registers concerning production of the statistics follow this procedure for control and revision: The Norwegian Labour and Welfare Administration conducts an annual control of the NAV State Register of Employers and Employees. Statistics Norway controls that enterprises with more than one establishment have separate numbers for each, and that the employees are registered with the correct establishment. Statistics Norway also controls the NAV State Register of Employers and Employees by comparing it with the End of the Year Certificate Register etc. Some kinds of errors are also corrected directly in the basic data for the employment statistics. Further, the contracted man-years adjusted for long-term leaves are checked against the wage costs mentioned above, in addition to the basic data for the wage statistics from payroll registers

Input measured in contracted man-years:

 

The three most central registers concerning production of the statistics follow this procedure for control and revision: The Norwegian Labour and Welfare Administration conducts an annual control of the NAV State Register of Employers and Employees. Statistics Norway controls that enterprises with more than one establishment have separate numbers for each, and that the employees are registered with the correct establishment. Statistics Norway also controls the NAV State Register of Employers and Employees by comparing it with the End of the Year Certificate Register etc. Some kinds of errors are also corrected directly in the basic data for the employment statistics. Further, the contracted man-years adjusted for long-term leaves are checked against the wage costs mentioned above, in addition to the basic data for the wage statistics from payroll registers. In connection with StatRes &– Universities and university colleges &– Statistics Norway conducts an annual control of the population of enterprises, and the grouping of the contracted man-years adjusted for long term leaves in groups of positions.

Student statistics:

No estimation is required as the statistics are based on a full count of students, graduates and completed credit points.

Unit costs:

Operating expenditures for R&;D and for education respectively (and contracted man-years adjusted for long term leaves) are measured in relation to 60 credit point units (one year full-time tertiary study equals to 60 credit points), and in relation to publication points. Because the educational institutions offers with different expenditures, an indicator where the 60 credit point units are adjusted in lines with the rates used in the funding system of universities and university colleges, has been made.

Input statistics, account figures:

Some of the accountindicators in StatRes cannot be directly retrieved from the accounts of the universities and colleges submitted to DBH, but are calculated on the basis of the figures in the accounts. Certain adaptations are also made to the figures for R&;D operating expenditure from NIFU. See section 4.1 for details on the indicators.

Input measured in contracted man-years:

Contracted man-years adjusted for long term leaves, is estimated by Statistics Norway as the number of full-time jobs and part-time jobs calculated as full-time equivalents adjusted for doctor-certified sickness absence and parental leave. Man-years are estimated as a percentage of ordinary full-time jobs (37.5 hours per week). The estimation of man-years is based on the contracted working hours at a reference week (the third week of November in the statistics year) which is considered to be representative for the whole year. The register information on contracted man-years adjusted for long term leaves will not be identical to the actual number of man-years worked, since the statistics does not capture overtime work, self-reported sickness absence, vacations, and other deviations from contracted man-years, except for parental leave and doctor-certified absence. For employees with more than one central government working relation in the reference week, contracted man-years adjusted for long-term leaves are estimated for each working relation and linked to each of the state enterprises where the persons are employed

The grouping of the contracted man-years adjusted for long term leaves in groups of positions is estimated by Statistics Norway on the bases of the position-/occupation-codes that occur in the population. For definitions of the groups of positions, see section 4.1.

Confidentiality

The figures are published per educational institution as long as this does not conflict with the Statistics Act or the data quality. To prevent identification of individuals within the statistics the statistics are not published if fewer than three units are the basis for the result.

Comparability over time and space

Some of the figures which form the basis for the figures in StatRes (student and account figures) have a long time series, and are comparable with figures going back several years. In StatRes, however, figures are included back to 2004.

The man-year figures involve the enterprises’ own employees. It may vary whether the enterprises choose to purchases their services, or to produce by their own employees, i.e. purchase of supporting services such as cleaning, kindergarten and canteen. The accounting figures show both wage costs related to own employees and purchases of goods and services.

Input statistics, account figures:

There may be changes in the classification of revenues and expenditures in the accounts of the institutions over time. One important example is the choice between classifying purchases of equipment as operating expenditure or investment. The introduction of the accruals principle has in some cases led to some smaller purchases of equipment which were formerly classified as operating expenditure, now being classified as investments and indicated in the balance sheet. Such changes may make the figures for consecutive years less comparable. There may also be partly different practices among institutions within a given year, especially if they have to a different extent completed the work of implementing the accrual principle.

The figures for R&;D-expenditures from NIFU may be less comparable over time following changes in e.g. methods and populations (see also sections 4.1 and 5.1 above).

Accuracy and reliability

Sources of error and uncertainty

Student statistics:

It is difficult to estimate the extent to which errors occur in student registers. A person may be incorrectly registered as a student, particularly at institutions that use a different enumeration date than Statistics Norway (1 October). Over-estimation of student numbers is common at Norway's universities as the registration occurs upon payment of the registration fee, not enrolment in subjects. Students may also remain in the registration system after they have completed their studies. Furthermore, the students may provide inaccurate information or personnel responsible for the registers may make errors during data input or use variables incorrectly.

Inaccuracies in graduation statistics may occur when students are defined as meeting the requirements for completing a degree. The reporting of combined bachelor degrees is a problem at several institutions because these degrees do not have a set curriculum and are only registered as complete when a diploma is issued. In many cases, this occurs some time after the students actually completed their degree, for example in the following study year as defined by Statistics Norway (1 Oct.-30 Sept.).

There are inconsistent practices by the institutions with regard to registration of credit points. It appears that for certain courses, some institutions do not register completed credit points at the end of each year, but at the end of the final year. This means that students are registered with zero credit points for the first two or three years and 180 or 240 credit points in their final year.

Incorrect registration of student data and delayed registration of graduates result in lower throughput figures.

Input statistics, account figures:

The institutions may classify revenues and expenditures wrongly in their accounts, transactions may be omitted and/or be registered wrongly and registered transactions may be invalid or fictitious. However, the prevalence of such errors is probably rather low due to strict demands concerning accounting, including independent external revision.

Figures for depreciation and imputed interest with regards to opportunity costs are based on the balance sheets of the educational institutions. In 2007, figures for theses variables were not available for most educational institutions. As of 2009, all educational institutions are reporting these figures. However, there is reason to believe that the values are too low, as many assets have been reported without any valuation. This is especially the case for the University of Oslo, where such calculations are only performed for property under the Observatory Fund and the Tøyen Fund, but not for the remaining assets/property held by the University of Oslo.

Statistics Norway may also make errors in processing and in the classification of revenues and expenditures according to type and function; however, the figures are checked against the accounts of the institutions.

This statistic utilises and connects data from two different sources; DHB and NIFU. In general, combining data from different sources may cause consistency issues, as units and variables may be defined in different ways. Statistics Norway’s data is based on judicial entities, while NIFU STEPs data also includes entities linked with the respective educational institutions but not necessarily a part of the judicial entity (se section 4.1). Operating expense for R&;D is calculated according to standards set forward in the Frascati manual, which may lead to a different treatment of purchases of durable supplies/equipment when compared with National Accounts standards.

In consideration of this, Statistics Norway has made certain adjustments to the data from NIFU, as described in section 4.1, before these data are matched with data from DBH. In spite of these adjustments, there may still be problems with regards to consistency between the different sources for the statistic.

Input measured in contracted man-years:

See section 5.4 Other sources of error.

The update of the definitions and grouping of the StatRes population is maintained by performing situational extractions from the Central Register of Establishments and Enterprises (BoF) in week 17 in the year after the statistic year. This extraction includes the units with organizational attachment for firms and enterprises in the central government, in addition to synopsis of changes, i.e. new enterprises, deleted enterprises, adjusted attachments etc. during the previous calendar year. There might be an incomplete overview of organisational changes, or time lags according to this, in the data sources.

Input measured in contracted man-years:
The data quality concerning minor and sporadic employment will be poorer than for employees registered in the NAV State Register of Employers and Employees. For persons who are identified as employees on the basis of the End of the Year Certificate Register, the employment is not dated precisely.This is the case for 3.8 percent of the contracted man-years adjusted for long term leaves in the StatRes-population in 2009.Some of these can however be dated based on information from other registers. For the remaining undated contracted man-years adjusted for long term leaves, information about salary-size is used as a criteria for defining whether the person is employed or not. Accordingly, there is some uncertainty about whether the persons included from the End of the Year Certificate Register, actually were working in the enterprise at the time (the third week in November).

There are also some missing-values on position/occupation. Contracted man-years adjusted for long term leaves that are included from the End of the Year Certificate Register, does not have information about position/occupation, but for some of these such information can be found in the State’s central Register on Civil Servants (SST). In addition there are also some missing-values on position/occupation in the Register of Employees. In the StatRes-population in 2009 3,5 percent of the contracted man-years adjusted for long term leaves have missing values on position/occupation. In 2008 this percentage is 4,6, in 2007 6,4, in 2006 5.9, in 2005 6.5 and in 2004 8.2 percent. This is a source of error when the contracted man-years adjusted for long term leaves are to be distributed on groups of positions. Enterprises where the share of missing-values exeeds 10 percent of the contracted man-years adjusted for long term leaves, are therefore excluded from publishing on these StatRes indicators, due to poor data quality. 1 entreprise is excluded for this reason in 2008, 6 enterprises in 2007, 5 in 2006 and 2005, and 16 enterprises in 2004.