Migration for welfare (WELLMIG) Nurses within three regimes of immigration and integration into the Norwegian welfare state

The regimes of integration and housing

Symbol of the house with silver key on vintage wooden background

Sandlie has investigated the housing situation among nurses from Sweden, Poland, and the Philippines in Norway.

Importance of housing for integration

Housing is an important indicator for integration. Some structural features of the Norwegian housing market can be especially challenging for foreign workers. In Norway, often described as a nation of homeowners, owner-occupation is more or less the only tenure that can ensure households’ long-term stability on the housing market. The current rental sector is dominated by small-scale amateur proprietors, consisting of private individuals letting out a part of their own dwelling or an extra apartment they own.  The standard length of tenancy agreements is one to three years.

Although most Norwegian households become homeowners during their life course (about 80 percent), becoming a homeowner requires both equity and a regular income at a level that makes it possible to take out a bank loan. How immigrants solve such structural challenges in the housing market varies according to their individual circumstances. Their strategies differ according to the length of residence in Norway, family situation, assistance from employers, financial resources, and cultural and social resources.

Housing situation of migrant nurses in Norway

By applying administrative register data, we have investigated the housing situation among nurses from Sweden, Poland, and the Philippines. Not surprisingly, we found that renting is much more common among these nurses than among their Norwegian counterparts. The share of renters is higher among Polish nurses than among Swedish and Filipino nurses. This may be due to their length of stay in Norway.

On average, Swedish and Filipino nurses have stayed for a longer period in Norway than Polish nurses. In our sample, about 80 percent of the Swedish and Filipino nurses have lived 8 year or more in Norway, while the corresponding number among the Polish nurses are 59 percent.

Other factors affecting housing differences

Housing differences relate not only to the type of tenure (either renting or owning), but to other factors as well, including the type and the size of dwellings. Our data show that nurses from the Philippines live in smaller dwellings compared to nurses from Sweden and Poland. The Swedish nurses occupy the largest dwellings.

For example, 43 percent of Swedish nurses live in single-family houses, while the corresponding number among Polish and Filipino nurses are 34 and 30 percent, respectively. In contrast, 43 percent of Filipino nurses live in flats in apartment buildings. The share of Polish and Swedish nurses that live in this type of dwelling is 32 and 29 percent, respectively.

Overcrowding

To take our analysis a step further, we have mapped out the amount of overcrowding experienced by Polish, Filipino, and Swedish nurses in Norway. The Norwegian housing authority has a rather strict definition of overcrowding. Households are considered overcrowded if: (1) the number of rooms in a dwelling is less than the number of people living in the dwelling or if more than one person lives in one room, and (2) the number of square meters is below 25 sqm per person.

Overcrowding is most common among nurses from the Philippines. Every fifth Filipino nurse lives in overcrowded housing. Overcrowding is also more common among Polish nurses (13 percent) than among Swedish nurses (8 percent).

In conclusion

Housing data, while important, is not the only indicator of integration among the different groups of nurses in our study. However, these statistics indicate interesting correlations between immigrant workers facing different regimes of integration and their housing situation. To get a better understanding of the interrelationship between regimes of integration and housing, we need to examine the relationships at an individual level. The data presented here are aggregated averages.

By Hans Christian Sandlie

This post created by:

user
Nina Eriksen
Adviser