A room of one’s own or room enough for two? Access to housing and new household formation in Sweden, 1968–1992

Abstract

Familistic and individualistic theories both provide explanations for recent declines in family household formation. Securing access to housing plays a key role in new household formation for both these theories. Familistic theories hypothesize a positive relationship between access to housing and new family household formation. Individualistic theories hypothesize a positive relationship between access to housing and nonfamily household formation. Here I test these hypotheses in Sweden by modeling leaving home for family and nonfamily household formation using the Swedish Family Survey and supplemental housing data. I find significant support for the familistic notion that greater access to housing increases the likelihood of family household formation. I fail to find support for the individualistic theory.

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Notes

  1. 1.

    Simultaneous modeling of men and women with interactive dummy variables separating the sexes confirms the significance of differences between variable coefficients for variables of interest, although the results are not shown.

  2. 2.

    In models not shown here I also explore the possibility that relationships between access to housing and family household formation may be changing over time by interacting relationships with cohorts. Significant changes over time in the relationship might support the individualistic theory of a cultural change between cohorts. However, when measured, cohort effects tended to be insignificant, with the exception of a gradually diminishing effect of financial access to housing on the risk of leaving home single relative to remaining home for women (initially a strongly negative effect).

  3. 3.

    Results not shown here demonstrate that size and type of housing infrastructure may also be important. When modeled separately, the presence of small apartments and small apartment construction (as opposed to large apartments and detached dwellings) make leaving home to live alone slightly more likely. These small apartments are probably not of the quality deemed necessary to support family household formation, as indicated by more qualitative studies in Sweden (Pettersson, 1997).

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Acknowledgments

I received significant support for the research of this paper from Brown University. Professors Frances Goldscheider, John Modell, David Lindstrom, and Nicholas Townsend provided valuable commentary on and review of this paper. Professor Eva Bernhardt of Stockholm University and Lars-Erik Borgegård and Urban Fransson of Uppsala University also provided valuable review. Professor Rebecca Upton of DePauw University also provided significant review of this paper. All errors are my own.

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Correspondence to Nathanael T. Lauster.

Appendix A: Construction of housing measurements

Appendix A: Construction of housing measurements

Population data

Population data are obtained from Statistics Sweden (SCB) by age and sex for each län and year between 1968 and 1992. Län are defined here with respect to 21 distinct and contiguous units of territory, ranging in population (age 16+ only) from 40,841 to 1,359,298 during the time period studied. The average population (314,269) and function of län indicate a great deal of similarity between län and counties in the USA. As is common in Statistics Sweden definitions, Kristianstads and Malmöhus are combined to form Skåne län; Göteborgs och Bohus, Alvsborgs, and Skaraborgs are combined to form Västra Götalands län.

Housing infrastructure data

Housing infrastructure data are obtained from Statistics Sweden (SCB) for each län and year between 1968 and 1992. Län definitions are arranged similarly to those in the population data.

Price index data

Price index data are obtained from Statistics Sweden (SCB) for the nation for each year between 1968 and 1992.

Average rent data (price adjusted)

Average rent data for the nation are obtained from Statistics Sweden Yearbooks 1972–1994 for each year between 1970 and 1992. In order to provide comparability across years, I use two-bedroom apartment rents as an index to measure general rent changes for all apartments. Due to municipal dominance over the rental market, municipal rent-setting primarily according to perceived utility-cost, and lack of other data, I use national data only in analyses. In order to estimate rent data for the years 1968 and 1969, I extrapolate backward from the years 1970 through 1992, employing the “ipolate” command within Stata. All data are multiplied by a price index multiplier to obtain comparable values all in 1992 SEK (Swedish Kronor). The price index multiplier for each year is obtained by dividing the price index value of the given year into the price index value for 1992. In other options, I hold rent constant at 1970 levels, and employ the “impute” command in Stata. I also regress rents on price index for the years 1970 through 1992, with and without a constant. The values for price index in 1968 and 1969 are then entered into the regression equation to predict rent values for 1968 and 1969. Of the estimation techniques employed, extrapolation seems to provide the least variance from yearly trends, and the best likely estimate.

Average house sale price (price adjusted)

Average house sale price data are obtained from Statistics Sweden Yearbooks 1978–1994 for each län and year between 1976 and 1992. Län definitions are arranged without combining Kristianstads and Malmöhus, Göteborgs och Bohus, Alvsborgs and Skaraborgs, as in SCB definitions above. I have combined average sale prices based upon weights of the number of houses sold in each combined län to provide län units similar to those from SCB datasets. For instance, for Skåne län, the formula is the average sale price for Kristianstads, multiplied by the number of houses sold in Kristianstads plus the average sale price for Malmöhus, multiplied by the number of houses sold in Malmöhus, together divided by the total number of houses for Malmöhus and Kristianstad combined.

National data for average house sale price are also available for 1972 through 1992. I estimate national averages for 1968 through 1971 through extrapolation from years 1972 through 1992, employing the “ipolate” command in Stata. Then I predict län level house sale prices for 1968 through 1975 by using national average sale prices to predict län level values. I regress average sale price for län on average national sale price for each län separately for all years 1976–1992 without allowing a constant. The resultant coefficient provides a län-specific estimate of the relationship between län average price and national average price that is averaged across years. The values for national sale price for years 1968 through 1975 are then entered into the resulting regression equation to predict län sale prices separately for each län for these years. The relationship between average national price and average län price provides estimates for län prices based upon position in the urban system. However, for certain län, position in the urban system changes throughout the time period. This is particularly true for those län around the urban areas of Stockholm, Uppsala, Malmö, and Göteborg. For these län, including Stockholms, Uppsala, Södermanlands, Skåne, Hallands, and Västra Götalands, an additional interaction is added between year and national sale price, recognizing changing positions in the urban system, and changing trends with respect to the mean. R-squared measures for each län-specific model range are all above R 2 = 0.99, indicating that estimates for these years are likely very accurate. (Alternative means of estimating missing data include regression with constants, as above, extrapolation by year, and imputation. Of methods employed, the method described above provided results most consistent with later price trends in the evolving urban system of Sweden, though all results are highly correlated).

After estimating data for all missing years, all data are multiplied by a price index multiplier to obtain comparable values all in 1992 SEK (Swedish Kronor). The price index multiplier for each year is obtained by dividing the price index value of the given year into the price index value for 1992. Ultimately, estimated average house sale price values in 1992 SEK are obtained for all years 1968–1992 at the län level.

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Lauster, N.T. A room of one’s own or room enough for two? Access to housing and new household formation in Sweden, 1968–1992. Popul Res Policy Rev 25, 329–351 (2006). https://doi.org/10.1007/s11113-006-9000-y

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Keywords

  • Cohabitation
  • Family
  • Housing
  • Nest-leaving
  • Sweden