Low Homeownership in Germany - A Quantitative Exploration

Abstract

The homeownership rate in Germany is one of the lowest among advanced economies. To better understand this fact, we analyze the role of three specific policies which discourage homeownership in Germany: an extensive social housing sector with broad eligibility criteria, high transfer taxes when buying real estate, and no tax deductions for mortgage interest payments by owner-occupiers. We build a lifecycle model with uninsurable income risk and endogenous homeownership in order to quantify the policy effects on homeownership and welfare. We find that all three policies have sizable effects on the homeownership rate. At the same time, household welfare would be reduced by moving to a policy regime with low transfer taxes and mortgage interest tax deductions, but it would improve in the absence of social housing, in particular when coupled with housing subsidies for low-income households.

Differences in Euro-Area Household Finances and their Relevance for Monetary-Policy Transmission

“…Kindermann and Kohls (2016) analyze the extent to which differences in rental-market efficiency in the euro area can explain differences in home ownership where higher homeownership rates imply lower wealth inequality. Kaas et al (2017) argue that lower transaction costs for housing in the U.S. compared with Germany are an important factor for explaining the higher homeownership rates in the U.S. Our structural approach is similar to these papers but we focus on the question of what the observed differences in household finances imply for the transmission of price changes to consumption. In our calibration of the model we find, as Kindermann and Kohls (2016) and Kaas et al (2017), that differences in transaction costs and rental efficiency are important to match the differences in home ownership across the four analyzed euro-area countries.…”

“…Kaas et al (2017) argue that lower transaction costs for housing in the U.S. compared with Germany are an important factor for explaining the higher homeownership rates in the U.S. Our structural approach is similar to these papers but we focus on the question of what the observed differences in household finances imply for the transmission of price changes to consumption. In our calibration of the model we find, as Kindermann and Kohls (2016) and Kaas et al (2017), that differences in transaction costs and rental efficiency are important to match the differences in home ownership across the four analyzed euro-area countries. In line with Pham-Dao (2016), we account for differences in the design of social security across euro-area countries in the calibration.…”

“…Pension savings that are contained in household-specific accounts are reported in the HFCS and thus part of the targeted net worth that we match in the model calibration.4 We convert the cross-sectional age profiles into life-cycle income profiles, accounting for cohort effects that result from average annual income growth of 1%.5 Kaas et al (2017) emphasize the importance of transaction taxes to explain the lower home ownership rate in Germany compared to the U.S Kindermann and Kohls (2016). find quantitatively sizable differences in the euro area for rental market efficiency.…”

Private rental housing market underdevelopment: life cycle model simulations for Poland

“…In this section I propose a theoretical framework that incorporates many factors described in the previous section. In particular, it is a life cycle model with housing, uncertain lifespan and idiosyncratic productivity, which is similar to the framework by Chen (2010), Cho and Francis (2011), Kaas et al (2017) or Rubaszek (2012). In the model economy households derive utility from consumption of non-housing goods and housing services, as well as from leaving bequests.…”

“…To simulate the above-described shift in the rental market structure I calibrate a quantitative general equilibrium life cycle model to the Polish data. The model is rich enough to incorporate a number of rental market features, which were considered to be important in the previous studies: fiscal incentives to own (Cho & Francis, 2011;Gervais, 2002;Kaas, Kocharkov, Preugschat, & Siassi, 2017), maintenance costs dependent on the tenure status (Yao & Zhang, 2005), transaction costs of selling and buying houses (Yang, 2009), the quality of rental services (Kiyotaki, Michaelides, & Nikolov, 2011), credit constraints (Chambers et al, 2009;Iacoviello & Pavan, 2013) or mortgage rate spread (Bajari, Chan, Krueger, & Miller, 2013). In this sense, the value added of this study to the literature is that it applies a life cycle model to explain the structure of the rental housing market in a country from the Central and Eastern European region.…”