9 March, 2013

Index of human development for Swedens’s municipalities

The Reform Institute of Stockholm has developed an index that starts with the UN index for human development (HDI – Human Development Indicator). Sweden though, keeps a wider range of statistics, so the number of indicative factors for such an index can be broadened. The Reform Institute has weighed eighteen factors together to compare outcomes in five main categories: Schools, Jobs, Health, Income, and ‘Hopelessness and exclusion’. The variables considered are described in more detail here (in Swedish).

The Reform Institute has calculated the ranking of all of Sweden’s municipalities, identified for each of the five main categories that you can review here. The underlying data values used for the ranking are charted here.


A new index measuring human development in Sweden’s municipalities

A common element between municipalities in Sweden, and in other countries, is the historic difference between so-called ‘Wealthy’ municipalities and those seen as ‘Poor’. This phenomenon is found throughout Sweden, and many countries elsewhere, and is perhaps as well-known as it is expected. But, there are differences that should be considered unacceptably large for seemingly similar municipalities (both socioeconomically and in population terms). The index that the Reform Institute has created starts from the UN index for human development (HDI – Human Development Indicator). With the wider range of statistics available in Sweden, we could broaden the number of factors considered. With 18 weighted factors we can compare various outcomes for five main categories: Schools, Jobs, Health, Income, and ‘Hopelessness and exclusion’.

The list of 18 misery variables including facts related the statistics is shown here. These public statistics were collected for every municipality. From these we could rank municipalities in relation to each other within each variable column, where the best values are ranked high (1) and the worst ranked low (290). The average placement for each municipality in all 18 variables provides an average ranking, where the highest score is ranked 290 (and worst) and the lowest score is ranked 1 (as the best).

We can always discuss which variables should be included in such an index. Crime, perhaps, should have been included. But statistics of this kind on the local level are highly uncertain and sometimes contradictory. Research on personal security, for example, provides entirely different findings than the number of reported crimes.




The 18 variables considered are described below.


1. Total number of non-pass students, proportion in one or more subjects in 9th grade (finishing elementary school). Adjusted for socioeconomic background (using SALSA values) Obtained from the Skolverket (the Swedish National Agency for Education) in 2011.

2. Drop-outs from upper secondary school. The share of students who do not complete the three-year upper secondary education degree within 4 years, as measured by the Skolverket in 2011.

3. University transition within 3 years. The share of upper secondary school graduates that have entered a university degree programme within three years. Skolverket 2010/2011.


4. Youth unemployment. The proportion of youth from 18 to 24 years within the register-based labour force in the period. As recorded by Arbetsförmedlingen Feb. 2012 (The Swedish Public Employment Agency) 6. The Arbetsförmedlingen has modified somewhat their method of calculating the register based labour force e after this study was completed.

5. General unemployment. The proportion of those in the register-based labour force in the period. As recorded by Arbetsförmedlingen (Feb. 2012) for each municipality.

6. Unemployment among foreign born. The proportion of foreign born within the register-based labour force in the period, as recorded by Arbetsförmedlingen (April 2012).

7. Long-term unemployment. Both unemployed and those participating in any program for the unemployed who have not held formal employment in 6 months or more as a proportion of the population between 20 and 64 years in the period. Arbetsförmedlingen (April 2012).


8. Long term sick disabled – proportion. The total number of ongoing sickness cases where the period of sickness disability is 90 days or longer per 100 sickness insured individuals for the period in every municipality. Försäkringskassan as per 31 Dec. 2011 (Swedish Social Insurance Agency)

9. Disability retirement. The proportion of the population who received either sickness or activity compensation in the period. Försäkringskassan (April 2012).

10. Average life expectancy. Remaining life expectancy for those born in the period. SCB (2007 – 2011)



11. Income. Salary for each employed, which equals the total salary for the entire municipality divided by gainfully employed who are 16 years or older in the period (2012). The total salary includes everyone who receives statements of income from Skatteverket (Swedish Tax Agency), including youth summer jobs workers.

12. Orders to Pay (Collection by public Enforcement Agency). The total number of applications for orders to pay in the period (2011) in relation to population (excluding legal entities). Kronofogdemyndigheten (the Swedish Enforcement Agency). This measure involves the average number of orders to pay per resident.

13. Aid dependent individuals. Total social aid recipients between 20 and 64 years in relation to the population within the same ages in the period. Socialstyrelsen (Swedish National Board of Health and Welfare) and SCB (Statistics Sweden). Average over 5 years (2008 – 2011).

Hopelessness and Exclusion

14. Vulnerability Index. Ranking for dependency on a single large employer, weighted with the ranking for outgoing commuters. From the study of the Confederation of Swedish Enterprise/Tillväxtverket (Swedish Agency for Economic and Regional Growth) ranking ‘Vulnerable Municipalities’, table 3, column 2 (2011).

15. Depopulation. Increase or decrease in population in per cent between 2002 and 2011. SCB.

16. Housing pricing trends over 10 years. Price fluctuations for home purchases by per cent for the 10 year period SCB.

17. Youth exclusion. Share of youth 20 to 25 years neither in employment or studying, 2010. SCB.

18. Adult exclusion. Share of population 20 to 64 years neither in employment or studying, 2010. SCB.