Sickness absence, Q2 2019

National, county, and municipality level.

The statistics are published quarterly and annually.

Reports to OECD each quarter, 

Not relevant

The statistics are intended to shed light on sickness absence trends in the aggregate and distributed by industry, sector, hours worked and various personal variables connected with those on sick leave. These are intended to form the basis for developing and evaluating measures aimed at sickness absence ('IA-agreement'). Publication began in 2001 and replaced the partially abridged statistics that had covered the central government and municipal sectors and parts of the private sector

Major users of the statistics are the authorities, employers' and employees' organisations, individual companies and researchers.

Aims that have governed the planning of the statistics are:

1. The possibility for employers and funds-appropriating authorities to make reliable estimates of expenses.

2. The possibility for employers' and employees' organisations to evaluate the efficiency of various measures implemented to reduce sickness absence.

3. The possibility of identifying risk groups in order to implement preventive measures.

4. The possibility of comparison over time as the basis for research in the area.

Admission to the figures before release date
As part of the collaborative effort on sickness absence with Statistics Norway (SSB) and The Norwegian Labour and Welfare Administration (NAV), NAV receives figures before release date on both self-certified and doctor certified sickness absence. SSB and NAV then releases the figures simultaneously.

Not relevant

Many different bodies produce or have produced sickness absence statistics that each covers various sectors of business and industry. The Confederation of Norwegian Business and Industry (NHO) compiled earlier sickness absence statistics covering blue-collar and white-collar workers in mining, manufacturing and general contracting activities. Now NHO has stopped their data collection and receives data from Statistics Norway in stead.

The Norwegian Association of Local and Regional Authorities (KS) compiles sickness absence statistics for permanent employees in nearly all municipalities and county authorities as well as for employees of companies that are associate members of KS. The Ministry of Labour and Government Administration compiles sickness absence statistics for all employees for whom the central government is the employer. A more detailed comparison of the various measurement figures for sickness absence has been made in the report from the Central Statistics on Sickness Absence pilot project. Other absence statistics are also available. For the retail and financial intermediation industries, the Federation of Norwegian Commercial and Service Enterprises and the Norwegian Financial Services Association (FNH) compile statistics respectively.

The Labour Force Survey, which Statistics Norway publishes quarterly, also contains some information about sickness absence. The target figure used in this survey is the number of employees who have been absent during the whole registration week in per cent of employees in total. The figure is given by gender and group of industry. This target-figure is less comparable with those in the other Norwegian statistics. The Central statistics of sickness absence for instance, include persons on partial sick leave and also cases of sickness absence shorter than one week. In addition these statistics also take into account both the working time and the duration of the sickness absence when the portion of sickness absence is calculated.

The Official Statistics and Statistics Norway Act § 10, cf. The employer's reporting of employment and income conditions Act, etc. (the a-opplysnings Act) § 3. 

The Official Statistics and Statistics Norway Act § 20 (compulsory fines)

Not relevant

The statistics does not include self-employed or conscripts. Further more it does not include absence related to a child's illness or family and maternity leave.

Doctor-certificated sickness absence
The population is all employees aged 16-69 residing in Norway and registered in the A Scheme (a-ordningen) Register classified as ordinary and maritime jobs during the reference week. The Reference week is the weeks each month containing the 16th. During a quarter there are Three Reference weeks, and the employment has to be active in at least one of these weeks to be counted.

Under the A Scheme Act, the reporting duty an employer occurs from 2015 for all his employees with payroll or expenditure allowance above 1000 Norwegian kroner per annum. Before 2015 the Employee register population was limited to employees having a job relation scheduled to more than four hours a week and lasting more than six days. Self-employed are not included in the statistics.

Self-certificated sickness absence
The population for the survey is all businesses operating in Norway with a few exceptions. Because of difficulties in obtaining reliable information about self-certificated sickness absence, the following businesses are kept outside the survey: private households with employed persons, extra territorial organizations, investment companies, extraction of crude petroleum and Natural gas, water transport and animal husbandry service activities (except veterinary activities).

Doctor-certified sickness absence

The Sick Leave Register is the main source of information for doctor-certified sickness absence. The Norwegian Labour and Welfare Administration (NAV) is responsible for the register.

The Sick Leave Register is based on the local NAV offices registrations of medical certificates ("Sykemeldingsattest IA") as part of its sickness benefits routine. These registrations covers all doctor-certified absences due to a person's own illness. The Sick Leaves are linked to employees by the national identity number.

As from January 2015 the Employee register was replaced by a new register on monthly reporting of employee and payroll information (a-melding) to NAV, Tax Administration and Statistics Norway. Jobs classified as ordinary and maritime in the A Scheme register corresponds to the population of employees in the earlier Employee register. Still, the earlier Employee register was supposed to contain all job relation scheduled to more than four hours a week and lasting more than six days. Under the A Scheme Act the reporting duty for an employer occurs for all his employees with payroll or expenditure allowance above 1000 Norwegian kroner per annum. Due to this new and more strict reporting duty, the A Scheme register have a wider scope than the earlier Employee register, and this has produced a minor level shift from the 1st quarter of 2015.

Self-certified sickness absence

The statistics on self-certified sickness absence are based on data reported by a sample of establishments. A random sample of nearly 10 000 establishments is drawn from The Central Register of Establishments and Enterprises (CRE). The establishments are stratified by industry, size and county of work. All the establishments in the population with at least 5 employees are divided into 4 groups depending on the number of employees. The establishments are stratified on most Divisions (2-digit groups) in the Standard Industrial Classification (SIC2007). This ensures a representative sample in 44 groups of industry, sizes of establishment and counties. All establishments in the same strata have the same probability to be drawn. The probability to be drawn increases by size. None of the small establishments (four or less employees) are drawn, while all big establishments (more than about 150 employees) are included. This ensures that the survey covers about 35 per cent of all employees while only 5 per cent of all establishments are surveyed. While the biggest establishments are always surveyed, most others participate for four years at a time. Therefore, we replace almost a quarter of the sample each year. The drawing of the sample is coordinated with several other surveys in Statistics Norway in order to disperse the burden placed on smaller and medium sized establishments.

The questionnaires are sent out the last week of each quarter to the enterprises having establishment(s) in the sample. The personnel office of the enterprise fills in the questionnaire or forwards it to the personnel office of their establishment. The deadline for delivery is about four weeks after receiving the questionnaire. An establishment may contact the Division for Data collection at Statistics Norway if it is impossible to separate the sickness absence figures for the chosen establishment. In this case the enterprise may give figures for the enterprise as a whole.

Doctor-certified sickness absence
The Norwegian Labour and Welfare Administration performs a number of controls and corrections on the doctor's certificates especially related to overlapping/inconsistencies in the dates.

Employees from the A Scheme Register
There are a number of controls in the reporting system. In addition, Statistics Norway makes a number of checks and reworking to arrive at the active employments.

For employments with position proportion over 1.2, the position proportion is set to 1.2. The total postion proportion for a person is not allowed to exceed 1.6. For persons where this is the case, some of the employments are removed, because we do not believe them all to be active in the reference week.

Until 2014, there was a limit regarding how many employments one person could have.

Self-certified sickness absence
Absolute checks: verification controls in the last stage of the optical data registration to reveal obvious errors from the optical reading, misunderstandings or inaccuracy in the reporting. An example would be wrong totals compared to the partial figures.

Evaluation checks: these checks aim to reveal errors due to extreme values reported or due to incorrect number of employees reported. For this purpose a check variable is being used, sickness absence cases per 100 employees. Large establishments that report extreme values on this variable will be more closely examined. Data from whole enterprises will also be adjusted in proportion to the portion of employees the sampled establishments represent in the enterprise as a whole. Before the final estimation, we also check that the net samples in each industry and size strata are large enough. If the net samples are too small for some strata, they will be added to the "neighbouring" strata in the same industry.

Doctor-certified absence
Persons with a so-called active self-certificate are included in the statistics as ordinary doctor-certified sickness absence.

Measures of sickness absence
The sickness absence rate is sickness absence man-days in per cent of contractual man-days. The proportion of employees with sickness absence at a given date is also calculated. See under 'Definitions' for more information regarding these measures. 

Self-certified absence
Sheltered workshops and establishments in the following industries are not a part of the sample: Animal husbandry service activities (except veterinary activities), extraction of crude petroleum and natural gas, water transport, private households with employed persons and extra territorial organizations. In the estimation, employees from these groups are represented by employees from other industries.

Estimation at national level
A model-based ratio estimator is used to inflate sample data of self-certified sickness absence to population level. The ratio model corresponds to a linear regression model without a constant term and with the disturbance term that are proportional with the number of male (female) employees. Auxiliary variables about total number of male (female) employees in each establishment in the population are used. The figures are taken from the A Scheme Register. The dependent variable is the number of self-certified sickness absence man-days for male (female). A weighted least square method is used to fit the regression models. The population totals for each group are predicted by using the groups model estimates and the population sums of the number of employees in each group.

Because the smallest establishments are not sampled, a "Cut-off"-estimator is being used for these strata. This means that the number of male (female) employees in the population of the smallest strata is being multiplied by the ratios for the second smallest strata. This method is being done separately for each industry strata. This method assumes that the ratios in the strata with the smallest establishments are similar to the corresponding ratios in the strata with the second smallest establishments. If the ratios are very different we introduce a bias.

Estimation at county level and institutional sector level
Self-certified sickness absence by county of work and institutional sector is estimated with a different method than the national level estimates, because the sample is not stratified on these variables. For the figures by county and sector, we use model based ratio estimators for different groups.

The estimations of sickness absence by county are done separately for two industry groups, sex and the 19 counties of work. One industry group consists of agriculture, forestry and fishing, and industrial activities; the other group is service activities.

In the estimation of figures by institutional sector, each of the tree sectors 1) central government, 2) counties and municipalities, and 3) private sector and government enterprises are estimated separately for male and for female for groups of industry. Depending on what the sample sizes allow, different groups of industry are used for each of the tree sectors.

The different model-based ratio estimators can add up to figures of totals that are a little different from the official national totals from the design-based ratio estimator. Due to that, we use the county and sector divided figures to make percentage distributions, which the official national totals are broken down with, so that the totals also are right.

Seasonally adjusted data are calculated by using the X-13ARIMA-SEATS software. The adjustment is done indirectly. We separately seasonally adjust the numerator and denominator for gender divided sickness absence rates certified by doctor and for self-certified sickness absence rates by gender. We let the
X-13ARIMA-SEATS automatically decide on which seasonal adjustment decomposition, forecast model, seasonal filter and trend filter that gives best results for each time series. These optimal choices are locked between yearly reviews of the method. Regression models in X-13ARIMA-SEATS pre-adjust the series, where we specify variables for influenza irregularities (numerators only), the number of working days in the quarter. All these pre-adjustment variables are deseasonalized.

Sickness absence man-days (both self- certified and certified by a doctor) are pre-adjusted for the number of working days in the quarter, the proportion of lost doctor-certified man-days with influenza diagnosis by gender and a level shift 1^st quarter 2015 because of the transition from the Aa-register to the a-scheme register. A level shift is also specified for sickness absence man-days certified by a doctor from third quarter 2004 (doctor certification reform). Also, an additive outlier third quarter 2009 is specified for self-certified sickness absence man-days for men (beginning of the swine influenza).

Contractual man-days are pre-adjusted for the number of working days in the quarter and break variables related to transition to the A-Scheme register (both level shift and seasonal outlier in 1^st quarter).

The focus of the dissemination of sickness absence statistics is on the seasonal and influenza adjusted sickness absence. In addition to being seasonally and influenza adjusted, this is also adjusted for the break in the time series due to the A-Scheme register from 2015. Statistics Norway believes that these figures give the best picture of the underlying development in sickness absence from quarter to quarter. For those who want numbers that are only seasonally adjusted, these are also published in StatBank.

For more detailed information about the seasonal adjustment of this statistics, please see  About seasonal adjustments.

Not relevant

In the autumn of 2001 the authorities and the organisations of employers and employees signed an agreement aiming at reducing the level of sickness absence. One of the means was to offer the employees an expanded period of self-certified sickness absence beyond three days combined with dialogues with the employer. This effort might turn some of the sickness absence from the doctor- to the self - certified kind. Due to this - the survey has to capture a greater part of the sickness absence than earlier, and our questionnaire for the 4th quarter of 2001 was changed accordingly. This change implies more questionnaire-based reporting from the establishments at the expense of register data based on the doctors' reports.

The effect of the A Scheme Register on the sickness absence rate

Introduction of the A Scheme register to replace the Register of Employees and Employers (Aa-register), from the 1st quarter of 2015, gives somewhat changing figures for the number of employees. This is due to a somewhat broader coverage of the group, and a better quality. The transition to the new data has had a small, but still observable effect on the sickness absence rate at the aggregate level. The effect of the transition to the new data is small also when it comes to self-certified and doctor-certified sickness absence separately. But since the self-certificated absence is lower than the doctor-certificated, this small effect provides a greater impact on the numbers of alteration for self-certified absence than for doctor-certified absence, and for the total absence.

Only the seasonal and influenza adjusted sickness absence rates are also adjusted for the break in the time series due to the A-Scheme register from 2015.

We haven’t calculated the size of possible breaks related to the a-scheme for other variables or groups, but the size may vary between groups. Of importance may be the fact that the A Scheme register captures more of the small job relations, than the Aa-register did.

Also, direct reporting of position proportion is now being used, while Aa-register only gave information about contractual working hours, and one assumed that 37.5 hours per week equaled a full position. This may also have affected the figures, especially for industries with a high degree of shift and rotation.   

New industry classification

A new industry classification (SIC2007) was introduced from the publication of the first quarter of 2009. Compared with earlier published figures classified by the previous industry standard (SIC2002) there will be a break in the time series.

It is not a one to one link between all the detailed codes of SIC2002 and SIC2007. However, 1 ^st quarter 2009 all active establishments in the Central Register of Establishments and Enterprises are coded both after SIC2002 and SIC2007. This information is utilized to construct conversion matrixes. These conversion matrixes are used to calculate aggregated SIC2007 divided historical figures from aggregated SIC2002 divided figures.

For the variable doctor-certified sickness absence man-days and for (non-holiday corrected) contractual man-days the conversion calculations are made separately for males and females for the most detailed industry code as possible. For the conversion of all the above variables the conversion percentage distributions are calculated from (non-holiday corrected) contractual man-days 1st quarter 2009.

Self-certified sickness absence man-days figures are converted from SIC2002 to SIC2007 within the industry stratums used in the sampling and estimation before and after the change. This is done separately for males and females based on conversion percentage distributions made from the variable contractual man-days 1 ^st quarter 2009. Gender and SIC2007 divided figures are converted quarterly for the period 2000 – 2007 under the assumption that the different detailed conversion percentage distributions are constant and equal to the once in 1 ^st quarter 2009.

The methods for converting sickness absence rates with non-holiday corrected denominator are closely related to the methods we used from Q4 2014 on sickness absence rates with holiday-corrected denominator. However, now we wanted to make the method a bit simpler, more robust, transparent, and consistent between numerator and denominator, for the best possible result for industry-divided sickness absence rates. Previously, the absolute figures were more in focus when we decided upon method of conversion.