Statistical database
The 3 steps are Choose table, Choose variable and Show result. You are currently at Choose variable

Employment, unemploymend and overqualification by background and sex 2008-2017

Choose variables

Percentege/ confidence intervall
Now you have come to the page, Choose variable. This page give you the oportunity to select which variables and values you want to display in your result of the table. A variable is a property of a statistical unit. The page is divided into several boxes, one for each variable, where you can select values by click to highlight one or more values. It always starts with the statistics variable which is the main value counted in the table.

Selected 1 of total 10


Selected 0 of total 3


Selected 0 of total 2


Selected 0 of total 3


Selected 0 of total 2

Number of selected data cells are:
(maximum number allowed is 100,000)

Presentation on screen is limited to 10,000 rows and 100 columns

Number of selected cells exceeds the maximum allowed 100,000
The results are based on information from the labour force survey



Persons are classified as working if they worked one hour or more in the reference week or were absent from the work they usually carry out.


Unemployment is the ratio of the unemployed to all persons in the labour force. The Labour force is considered to consist of employed and unemployed persons. Unemployment. Persons are classified as unemployed who have no employment and satisfy one of the following criteria:1. Have been seeking work for the previous four weeks and are ready to start working within two weeks from when the survey is conducted. 2. Have found a job which will begin within three months but could start working within two weeks. 3. Await being called to work and are able to start working within two weeks. 4. Have given up seeking work but wish to work and could start working within two weeks.


Over-qualification is defined here in the same way that OECD defines it: 'Overqualification is the share of highly educated people employed in low- ormedium-skilled jobs. The over-qualification rate is calculated as the share of highly educated people employed in low- or medium-skilled jobs among all employees. The classification of low and medium-skilled jobs is taken from the International Standard Classification of Occupations (ISCO) drawn up by the International Labour Organization (ILO, It classifies jobs into three main skill levels: highly skilled – senior managers, professionals, technicians and associate professionals (ISCO 1-3); low-skilled – elementary occupations (ISCO 9); and medium-skilled, all other (ISCO 4-8)“.



Immigrant is defined as an individual that is born abroad and has parents that both are born abroad and have a foreign background. That means that both grandparents are born abroad.


Local is used for everyone that cannot be defined as an immigrant. Local can be seen as a broad category that includes many sub-categories. For example a person can be seen as local if they have no foreign background, if they are born abroad but have an Icelandic background, individuals that are born in Iceland and have one parent that is an immigrant, an individual that is born abroad and has Icelandic grandparents, and an individual that has immigrant parents but is born in Iceland.


confidence interval, ±

The results come from the labor force survey that is based on a sample of the population and therefore there is some uncertainty surrounding the results. To estimate this uncertainty confidence intervals are calculated. The confidence interval estimates how exactly the sample value represents the true value of the population. The calculations of confidence interval are based on the standard error of the estimate. The confidence interval reaches above and below the percentage point, and is added and deducted from the percentage point. If an estimate is 10%, and the confidence interval is ±1,2, then the lower confidence interval is 8,8 and the upper confidence interval is 11,2. A difference between two estimates can be said to be statistically significant if the confidence interval of the estimates do not overlap. 95% confidence intervals are calculated by multiplying the standard error with 1,96. That confidence interval will contain the mean with 95% certainty. If a series of random samples of the same size are taken from the same population, then 95% of the confidence intervals would contain the population mean. The precision requirements for this publication are that an estimate does not have a larger standard error than 5%.