Why Do the Swiss Rent?

Abstract

At less than 34%, Switzerland has the lowest home ownership rate in Western Europe. This may seem odd given the economic strength of the country. We use household survey data for five Swiss cantons to explore some possible reasons for this. We estimate a tenure choice equation that allows us to analyze the impacts of a number of key variables on the ownership rate. We pay particular attention to the relative cost of owning and renting, which is a function of house prices, rents, and the user cost of owning. The latter is a function of income tax policy and expected house price inflation, among other things. We also measure mortgage underwriting criteria and consider rent control and other policies affecting rental housing. By simulating a number of hypothetical changes to taxation and other policies, underwriting criteria, and price levels, we assess the importance of these variables in explaining the ownership rate. We conclude that high house prices—relative to household incomes and wealth—and the tax on imputed rent are the most important causes of Switzerland’s low ownership rate.

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Notes

  1. 1.

    One could carry this argument further by pointing out that the scarcity of land means higher densities, and higher densities mean more multi-family housing. If multi-family housing can be supplied more efficiently as rental housing with single ownership of buildings or projects, then land scarcity causes lower ownership rates (Linneman 1985).

  2. 2.

    There are some exceptions to this. For example, a significant percentage of rental housing in Zurich is cooperative housing that receives a substantial subsidy in the form of below-market leasehold land rents.

  3. 3.

    A much larger percentage in Zurich benefits from the implied subsidy in the form of reduced land rents for cooperatives.

  4. 4.

    For an overview of taxation in Switzerland, see Bureau d’information fiscale (2006a).

  5. 5.

    More details about the wealth tax are available in Bureau d’information fiscale (2006b).

  6. 6.

    The ratio for single-family house prices may be more relevant to tenure choice than the condominium ratio, as most buyers prefer single-family houses. Of owning households in our sample, 74% occupy single-family houses.

  7. 7.

    Further details about the hedonic and other estimations not reported here are available from the first author.

  8. 8.

    Assuming no inflation in house prices, a 10-year holding period, a discount rate of 3%, and amortization of 1% of the value of the house each year, \(v^{ * }_{{UA}} = v_{{UA}} - 0.053\), where \(v_{UA} \) is the current unamortized LTV ratio.

  9. 9.

    For households that amortize only indirectly, \(v_{IA}^ * = v_{IA} + 0.053\), given the same assumptions as for \(v_{UA}^ * \) (see footnote 8). For households that amortize both directly and indirectly, the present value adjustment factor is multiplied by the proportion amortized indirectly.

  10. 10.

    We assume that households’ Troisième pilier contributions are independent of tenure choice and, therefore, that indirect amortization does not affect the user cost of ownership except with respect to mortgage interest payments.

  11. 11.

    The income constraint as defined here is a blend of the criteria of the two main mortgage lenders in Switzerland, Credit Suisse and UBS.

  12. 12.

    We initially also included the gender of the household head, but this was not statistically significant.

  13. 13.

    The Swiss user costs are similar in magnitude to those reported by Himmelberg et al. (2005) for U.S. cities in 2004.

  14. 14.

    We estimated a logit model to predict the probability of receiving a rental subsidy, and the likelihood of receiving rental subsidies is so low in the other cantons that the model predicts that none of the households in our sample in those cantons would receive such a subsidy.

  15. 15.

    The mean reduction for Basel is the weighted average deduction after applying the rules for Basel Landschaft (which allows a deduction) and Basel Stadt (which does not).

  16. 16.

    Following Haurin et al. (1997), Green and Vandell (1999), and others, we initially applied Heckman’s (1979) two-stage sample selection bias method to address the fact that we are using estimations based on owners to make predictions about renters. It was evident, however, that the inverse Mills ratio calculated from the first stage tenure choice equation was collinear with variables in the optimal house value, optimal rent, and loan-to-value ratio equations. As pointed out by a referee, the same variables that explain tenure choice are also likely relevant to these other factors, thus calling into question the appropriateness of the two-stage technique in these cases. Note that Haurin et al. (1997) concluded that there was no sample selection bias in their study. In any case, controlling for sample selection bias has only a trivial impact on the tenure choice estimates and simulation results.

  17. 17.

    Generally, bootstrapping has a small impact on the standard errors, although the bootstrapped standard error for the gap variable is somewhat higher than the non-bootstrapped standard error (0.460 × 10−6 versus 0.289 × 10−6). The bootstrapped results are based on 100 random samples with replacement of the same size as the original sample (n = 3,588).

  18. 18.

    A similar approach is used to simulate impacts of hypothetical changes in tax and subsidy policies on home ownership in the U.S. in Bourassa and Yin (2006; 2008).

  19. 19.

    To bootstrap each simulated ownership rate we take 1,000 random samples with replacement of the same size as the original sample. The bootstrapped distribution is then centered on our simulated ownership rate and the estimated ownership rates corresponding to cumulative probabilities 0.025 and 0.975 are the lower and upper bounds, respectively, of the 95% confidence interval.

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Acknowledgments

The authors thank Peter Bolliger (Swiss Statistical Office) for providing the household survey data, Donato Scognamiglio and Philippe Sormani (CIFI) for calculating the hedonic estimates of house values, Séverine Cauchie and Céline Kuhn for collecting the tax and subsidy data, and Jörg Baumberger, Philippe Thalmann, and an anonymous referee for helpful comments.

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Correspondence to Steven C. Bourassa.

Appendix: Tenure Choice Tax Rates

Appendix: Tenure Choice Tax Rates

The tenure choice income tax rate measures the tax advantage (or disadvantage) of owning relative to renting and is an average rather than a marginal rate (Hendershott and Slemrod 1983). In the case of Switzerland, it is generally defined as:

$$\tau _Y = \frac{{T_{Y,RENT} - T_{Y,OWN} }}{{\hat H\left( {\left( {1 - v_{UA}^ * } \right)i_E + \left( {v_{UA}^ * + v_{IA}^ * } \right)i_F + \mu - \eta } \right)}}$$
(A1)

where T Y ,RENT is the federal and cantonal (including communal and church) income tax a household would pay if it rented; T Y ,OWN is the income tax it would pay if it owned a dwelling of value H; and the other terms are as defined previously. The denominator in Eq. (A1) is the change in taxable income when a household shifts from renting to owning.

The procedure for calculating the tenure choice tax rate is as follows. In the case of current owners, taxable income as a renter is calculated by adding the return to actual home equity, \(H\left( {1 - v_{UA} } \right)i_E \), to actual income. Here H is the value of each homeowner’s house and v UA is the homeowner’s current unamortized LTV ratio. Taxable income as an owner is then calculated for renters and recalculated for owners as taxable income as a renter less a predicted return to home equity, \({\ifmmode\expandafter\hat\else\expandafter\^\fi{H}{\left( {1 - \widehat{v}_{{UA}} } \right)}i_{E} }\), where \(\hat H\) is the household’s “optimal” house value and \(\hat v_{UA} \) is the predicted current LTV ratio. Then all of the applicable housing and other deductions are applied to income as a renter and as an owner before calculating the tax payments T Y ,RENT and T Y ,OWN , which are then inserted into Eq. (A1).

As noted above, the denominator in Eq. (A1) represents the change in taxable income if the household rented rather than owned. Additions to taxable income are the return to home equity, deductible mortgage interest payments, and maintenance and other deductible housing expenses. Imputed rent is a reduction from taxable income. For households in Vaud, where imputed rent is partially deductible, only the nondeductible portion of η affects cantonal tax liability. In the case of Geneva, expenses are not deductible at the cantonal level, so μ enters into Eq. (A1) only to the extent that it affects federal income tax liability. For households in Vaud and Basel Landschaft, where rent is at least partly deductible from income for cantonal income tax purposes, the difference in taxable income also takes into account the deductible portion of rent paid.

Similar considerations apply to the wealth tax rate:

$$\tau _W = \frac{{T_{W,RENT} - T_{W,OWN} }}{{\hat H\phi }}$$
(A2)

where T W ,RENT and T W , OWN are the wealth taxes the household would pay as a renter and as an owner, respectively. Here the denominator is the increase in the wealth tax base if the household rents rather than owns, which is due to the fact that housing wealth is undervalued for tax purposes.

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Bourassa, S.C., Hoesli, M. Why Do the Swiss Rent?. J Real Estate Finan Econ 40, 286–309 (2010). https://doi.org/10.1007/s11146-008-9140-4

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Keywords

  • Home ownership
  • House prices
  • Tax policy
  • Switzerland