Housing Affordability, Housing Tenure Status and Household Density: Are Housing Characteristics Associated with Union Dissolution?


Housing is an important dimension of social inequality between couples, but it has been largely ignored in prior research on union dissolution. Extending the literature that controlled for the stabilizing effect of homeownership, we investigate whether housing, measured as household density, housing tenure and housing affordability, is related to the risk of union dissolution. Based on data from the German Family Panel (pairfam), we analyze 3441 coresidential partnerships. We run discrete-time event-history models to assess the risk of separation within a time frame of 7 years. Housing affordability is found to be negatively related to the risk of union dissolution among couples, as those couples with a high residual income (i.e., household income after deducting housing costs) were less likely to separate than those with a lower residual income. By contrast, household density is found to be unrelated to separation. In line with previous research, our findings indicate that homeowners had more stable relationships than tenants. The analysis shows that this was the case regardless of whether the home was jointly owned or was owned by one partner only.

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Fig. 1

Source: Pairfam waves 1–7. Authors’ own calculation. Multiply imputed data. Control variables: duration of coresidential union, duration squared, age of female partner, partnership status, region, number of children in the household, housing tenure. Average marginal effects and significance levels are presented in Table 6 in “Appendix”

Fig. 2

Source: pairfam Waves 1–7. Authors’ own calculation. Multiply imputed data. Control variables: duration of coresidential union, duration squared, age of female partner, partnership status, region, number of children in the household, housing tenure, household density. Average marginal effects and significance levels are presented in Table 6 in “Appendix”


  1. 1.

    As the number of multiple cohabitations of the same main respondent was small, we refrained from running multilevel analyses.

  2. 2.

    Moreover, we excluded those couples who reported a cohabitation break because if the partners did not share a dwelling, their housing conditions were less relevant for their partnership development.

  3. 3.

    We calculated an alternative measure of the person–room ratio in which we counted all household members as one person (instead of 0.5 of a person for each child under age 12). The use of this measure led to substantially the same results in our regression analyses (not shown here).

  4. 4.

    When we checked how high-density living was distributed among higher- and lower-income households, we found that high density was more common in households with below median income (9.2%) and less common in households with median income or higher (2.8%).

  5. 5.

    This correlation coefficient is calculated based on the complete case sample of our analyses.

  6. 6.

    When running regression models with other socioeconomic variables, such as partners’ education and labor force status, the effects of residual income turned insignificant; but the added variables themselves did not show strong and significant effects. We interpret this result as an overspecification of the model. Given our focus on housing characteristics, and in order to keep the models parsimonious, we decided to exclude the employment and education characteristics of the two partners from the models.

  7. 7.

    Changing the reference category, the difference between male and female homeowners was also insignificant (results not shown).

  8. 8.

    In order to determine whether the effect of housing affordability might differ according to housing tenure status, we performed an additional analysis. However, we found no indication of an interaction of housing costs and housing tenure on the risk of separation (see Fig. 3 in “Appendix”).

  9. 9.

    In the baseline model (not shown here) with only the two relationship duration variables and density, we did find a significantly increased dissolution risk among couples who were living in a low-density household (i.e., a household in which the average number of persons per rooms was smaller than one) compared to couples in dwellings with a medium level of density (reference category). However, this effect turned insignificant after including the other control variables.

  10. 10.

    Controlling for age and education homogamy did not change our results substantially.


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We thank Lisa Schmid, Philipp Lersch, Nicole Hiekel and the PartnerLife team members for their valuable comments on an earlier version of this paper. This paper uses data from the German Family Panel pairfam, coordinated by Josef Brüderl, Sonja Drobnič, Karsten Hank, Bernhard Nauck, Franz Neyer und Sabine Walper. Pairfam is funded as a long-term project by the German Research Foundation (DFG).


The research for this paper is part of the project “Partner relationships, residential relocations and housing in the life course” (PartnerLife). Principal investigators are Clara H. Mulder (University of Groningen), Michael Wagner (University of Cologne) and Hill Kulu (University of Liverpool). PartnerLife is supported by a grant from the Netherlands Organisation for Scientific Research (NWO, Grant No. 464-13-148), the Deutsche Forschungsgemeinschaft (DFG, Grant No. WA1502/6-1) and the Economic and Social Research Council (ESRC, Grant No. ES/L01663X/1) in the Open Research Area Plus scheme.

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See Tables 4, 5, 6 and Fig. 3.

Table 4 Discrete-time event-history models of union dissolution (average marginal effects). Complete cases.
Table 5 Discrete-time event-history models of union dissolution (odds ratios).
Table 6 Interaction effects (models 6, 7 and 11). Discrete-time event-history models of union dissolution (average marginal effects).
Fig. 3

Source: pairfam Waves 1–7. Authors’ own calculation. Multiply imputed data. Control variables: duration of coresidential union, duration squared, age of female partner, partnership status, region, number of children in the household, household density. Average marginal effects and significance levels are presented in Table 6 in “Appendix”

Interaction effect (Model 11). Average marginal effects of housing tenure on union dissolution for different levels of housing affordability (residual income after housing costs are deducted). Reference category: joint homeowners (dashed line).

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Krapf, S., Wagner, M. Housing Affordability, Housing Tenure Status and Household Density: Are Housing Characteristics Associated with Union Dissolution?. Eur J Population (2020) doi:10.1007/s10680-019-09549-6

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  • Housing cost
  • Household crowding
  • Homeownership
  • Separation
  • Socioeconomic
  • Situation