Inhalt
Seite 1
Tend German households to be net-savers?Seite 2
Return on average households’ asset holdingsSeite 3
Be concerned about the formation of bubbles? Auf einer Seite lesenReturn on average households’ asset holdings
Since this data is only available for 2010, in the following we assume that households do not rebalance their portfolio and keep portfolio shares of different assets at the 2010 level.4 Figure 2 presents the composition of average wealth of German households in income quartiles. Figure 3 shows the relative amount of each asset class to the total wealth.5
Figure 9 shows the monthly amount of borrowing by German households in aggregate. In total, Germans borrow about 70 billion Euro per month. Most of this comes in the form of overdrafts on checking accounts. Mortgages comprise about 15 billion Euro and consumption loans about five billion Euro per month.
Figure 10 shows the interest rates that households have to pay on each class of liabilities. As it is seen in the figure, interest rates on almost all types of debt instruments have declined during the last few years, although for some debt categories this decline has been surprisingly small. The pass through from policy rates to retail rates is asymmetric. All interest rates rise sharply in response to contractionary monetary policy (prior to the financial crisis), but only decline slowly or not at all in the recent low interest rate environment. Among the different debt categories, mortgage rates are more sensitive, whereas consumer loans and credit card debt show only very sluggish downward adjustment.9
To calculate the interest payments, we assume a maturity of twelve months for consumption loans and one month for credit card debt. For mortgages, to be conservative, we only consider the interest payments from the time of issuance until the end of the period under study, i.e. December 2014. Finally, we sum up the interest payments of the issued loans during 2010-2014, and compare it with the total interest payments of exactly the same borrowing but under the assumption that the interest rates were equal to those of 2003-2007. The difference between these two is 19 billion Euro. This is the benefit from total borrowings of German households during the recent low-interest environment in comparison to the years prior to the crisis. The bulk of this benefit comes from mortgage borrowings, due to the longer maturity of mortgage loans and sharper decline in mortgage rates after 2009.10
Aggregate effects
As a final step, we calculate the overall effects on households in Euro terms by income quartile. We obtained the average household size in Germany of 2.04 individuals in 2010 from the HFCS. For simplicity, we assume that it has been constant at 2 individuals per household during the last decade. That implies that there are about 40 million households in Germany, hence in each income quartile there are ten million households. Homeownership varies across the income distribution. Homeownership rate is 20% for low income households, 39% (49%) for the second (third) quartile and 70% for high income households. Using this information and multiplying the total benefits (relative to 2003-2007) from assets (see Table 1) that we calculated in previous sections for each income group, we find a total benefit of 9.4 billion Euro for low income households (households in the first income quartile), 36 (69.5) billion Euro for the second (third) income quartile and a total benefit of 230 billion Euro for high income households. In total, German households are better off due to higher returns on their savings in the low policy rate environment relative to 2003-2007 by 345 billion Euro (see Table 2).
In total, German households are better off due to higher returns on their savings in the low policy rate environment relative to 2003-2007 by 345 billion Euro.
Figure 2: Households’ asset holding in absolute terms
for households in each income quantile – Sources: Eurosystem’s HFCS; own calculations and illustration
Figure 3: Households’ portfolio weights
for households in each income quantile – Sources: Eurosystem’s HFCS; own calculations and illustration
This is what we use as the households’ portfolio weights. The figures confirm common wisdom about the portfolios of German households: The largest share is real estate, followed by deposits and life insurance. Equity investment and bonds are below 2% of portfolios even for households in the top income quartile. Nevertheless, the share of equity and bonds are increasing across the income distribution while the share of deposits is decreasing. In the following, we take these portfolio weights as given and calculate the annual return for each income quartile in each quarter.6 We compare the current low policy rate period (mid-2010 to mid-2015) to the pre-crisis period (2003-2007), in which policy rates were at “normal” levels (around 2%-4%).
We do not observe the actual returns on the respective portfolios of households. Instead, we use average values and make some simplifying assumptions. For example, we bundle pension-plans, life insurance together with deposits and assume that the households earn the deposit rate on three portfolio components. This is due to the difficulty in finding reliable return data on pension and insurance schemes.7 The data on average yearly deposit rates with a monthly frequency come from the Bundesbank. We also assume that the average German household invests in the DAX portfolio if she reports any equity holdings. Therefore, we consider the yearly return of DAX as equity returns. Moreover, we assume the investors buy only long-term German government bonds, therefore they earn yields on long-term German bonds for which we collect the data from St. Louis Federal Reserve Economic Database. Finally, we collect house price index from the Bank for International Settlements’ Property Price Index.
Figure 4 presents the average yearly return on deposits, bonds, equities and real estate separately. Average yearly deposit rate has been about 2% since 1996 until 2008 where it starts to gradually decline to just above zero in 2015. Yields on long-term bonds decline from 8% in 1990 to about 4% prior to the financial crisis and to just above zero in 2015. Equity returns are more volatile with two sharp declines for the dot.com bubble burst of 2001-02 and the financial crisis of 2008-09 and a strong increase recently. Finally, the non-commercial real estate market did not show any particular trend until 2009. Since then, real estate prices have appreciated strongly in Germany. Even at this level of analysis, it is clear that the question to which extent the average German household “suffered” or “benefited” in the low policy rate environment depends on her portfolio. While households that invested only in deposits may indeed have suffered, a low policy rate environment benefits those that hold a more diversified portfolio that includes real estate and equity.
Combining the return data with the household portfolio share data, we obtain a stylized portfolio return for German households. We calculate these portfolio returns across the income distribution for homeowners as well as renters and in nominal and in real terms (adjusted for ex post inflation). The results are presented at Figures 5-8.
Figure 5: Return on households’ portfolio
for households in each income quantile – Source: Own calculations and illustration
Figure 6: Return on renters’ portfolio
for households in each income quantile – Source: Own calculations and illustration
Figure 7: Inflation-adjusted return on households’ portfolio
for households in each income quantile – Source: Own calculations and illustration
Figure 8: Inflation-adjusted return on renters’ portfolio
for households in each income quantile – Source: Own calculations and illustration
For households with an average portfolio composition performance during 2010 to 2015, when monetary policy rates declined rapidly to zero, was significantly better than in the years 2003 to 2007, when monetary policy rates were at "normal" levels of 2%-4%. The improvement is very substantial at around 10% over the five-year period and benefits both low and high income households (see Table 1).
Table 1: Return on portfolios
Source: Own calculations
In real terms, the low policy rate environment was even more beneficial to essentially all households. The only exception being renters, i.e. households without real estate, who earned lower returns of about 1%-2% over five years.
We can translate these differences in returns into Euro amounts. For households with some real estate, the gains are quite substantial and vary from 5,000 Euro for low income households to more than 30,000 Euro for high income households. For renters, there are small losses that vary from 340 Euro to 1,400 Euro across the income distribution.
Interest cost on average households’ liabilities
The net savings position of a household not only depends on her assets, but also on her liabilities. It is obvious that in a low interest environment, those that borrow money may benefit. However, as we will see, this benefit is surprisingly small due to the incomplete pass through of policy rates to retail interest rates.
Unlike for household assets, where we can simply use the asset composition of households, for liabilities we need to distinguish between loans taken out before the low policy rate environment and new loans. The interest saving effect arises only for new loans. While this distinction makes little difference for short term loans like overdrafts or consumer loans, it is important for mortgages. At the same time, mortgages are the single largest liability of households. Since we do not have access to representative data on the distribution of new loans taken out across the income distribution, we instead use aggregate monthly issuance of mortgages, consumer loans and overdrafts for all households complemented by the respective interest rates. Both data were obtained from the Bundesbank.8
Using total monthly issuance of different types of debts to all households in Germany and the corresponding interest rates, we can calculate the total interest payments of households during 2010-2014. Next we can compare this with a hypothetical case where the same amounts are assumed to be borrowed during 2003-2007. The difference between these two gives us the benefits accrued to households due to lower interest rates.
Figure 10: Cost of borrowing
nominal cost of borrowing – Sources: Bundesbank’s Time Series Database; own calculations and illustration
High income home owners benefit disproportionally, renters lose.
This total benefit hides some important distributional effects. High income home owners benefit disproportionally, renters lose. 67% of the total gains accrue to high income homeowners. At the same time, the Euro amounts of the losses to renters are small and vary from less than 100 Euro for low income households to just above 1,300 Euro for high income households for a five-year period, i.e. less than 20 (260) Euro per year for low (high) income households.
Given data limitations, we are unable to allocate the total savings from reduced interest rates on new household debt that we calculated in the previous section (19 billion Euro) across the income distribution. However, given that these interest savings largely arise from new mortgage debt, we would conjecture that these benefits also disproportionally accrue to high income households, who are more likely to be homeowners.
Nevertheless, taking the higher returns and the lower borrowing cost together, the low policy rate environment resulted in a benefit to German households of 364 billion Euro during 2010 to 2015.
