Figure 6.13 illustrates a small deviation between C2 and C3, which means that only a small amount of household´s debt stems from foreign sources.
There has been a significant increase in credit growth and house prices over the last years. This coincides with Case and Shiller’s criterion “Limited understanding of risk attached to the investment”, as households have a higher willingness to incur risks by issuing more loans. Rising debt and house prices can mutually influence each other (ECB, 2003). The interaction between house price- and credit growth has several underlying explanations; firstly, households aiming to buy a house have to borrow more to finance the housing procurement if house prices increase.
Subsequently, when a household seek to issue loans, the banks are mainly focusing on two factors:
household income and the collateral value of the particular property. The collateral values increase when house prices rise, and households may therefore be able to issue higher mortgage loans. In addition to these two channels, higher house prices will reduce the risk of mortgages the banks already have exposed, and it may encourage banks to faster expansion in terms of new mortgages.
When lending increase, it results in households being able to bid a higher price of housing (Anundsen and Jansen, 2013).
Figure 6.14: Development in total credit growth and house prices in Norway 1985-2015 (1985=100)
By comparing figures for house price- and credit growth for Norway from 1985 and onwards, it is evident that these series follow a similar trend. However, as illustrated in figure 6.14, the variables have surpassed each other several times throughout the period. Credit growth has been higher than growth in house prices since 2008, despite the years 2012 and 2013. This indicates that households are borrowing more than what house prices have grown, which means that the ability to invest in housing is higher. This further result in increased housing demand.
Conclusively, we can argue that the high growth in house prices can be supported by a high credit growth.
Debt ratio in percent of disposable income
The debt/disposable income ratio represents the debt in percent of disposable income.
Figure 6.15: Development in debt/disposable income ratio in Norway 1996-2015
Figure 6.15 illustrates that developments in the debt/disposable income ratio have increased since 1996. However, the ratio has been on a relatively stable level since 2007. As the figure illustrates, households have twice as high debt as disposable income. The sustained rise in the debt/disposable income ratio reflects the fact that house prices are raising. In addition, the growth in the debt ratio is affected by a high growth in the GDP, a low unemployment, growth in disposable income, lower
lending rates, positive future expectations among households and higher house prices. According to Statistics Norway (2016), households debt growth has remained unchanged so far this year, and the growth has been relatively stable the last year and a half. Nevertheless, the debt still has a higher growth rate than income, which means that the debt load is still growing. The Ministry of Finance (2013) argues that a high debt ratio in percent of disposable income leads to an unbalanced economy and increased risk of debt- and housing bubbles.
6.3.2 Number of unsold homes
Another factor we find important regarding the housing market development is the number of unsold homes. A reduction of unsold homes might be an explanatory factor of increased house prices, as it probably is signs of continuous rise in house prices, because the housing demand is higher. Conversely, an increase in the number of unsold homes will push the prices down. In both cases there will be an unbalanced market that drives prices in opposite directions.
Figure 6.16: Unsold homes in Norway 2011-2016
Real Estate Norway reports statistics of the number of unsold homes. We only have access to numbers from 2011 to 2016, and as the figure illustrates it has overall been relatively stable.
According to Dagbladet (2008), there were a number of 20 503 unsold homes in 2008. This
indicates a high market demand if we compare it with today’s level of 11 789 unsold homes. Hence, many houses are purchased as soon as they are put up for sale.
6.3.3 Financing
House procurements are mainly financed by loans. Naturally, the bank’s lending policy highly influence household’s mortgage financing. The Financial Supervisory Authority is setting a capital requirement, and in 2011, they introduced a capital requirement of 15 %. This was an increase from the previous requirement of 10 %. It would be rationale to assume that this increase would entail lower demand for mortgage loans, as borrowers are restricted to issue limited loans relative to the previous requirement of 10 %. However, as discussed in 6.2.1, the debt level has continuously increased.
Despite the capital requirement of 15 %, it is still possible to issue start-up loans through the Norwegian State Housing Bank (NSHB). A start-up loan is an opportunity to enter the house market for households that are not able to fulfil the capital requirement. The department director in NSHB, Are Sauren, stated that they saw a definite increase in the number of people seeking start-up loans after 2011. According to the discussion in section 6.1, an increase in debt will lead to higher risk, and this especially applies to households issuing start-up loans as their equity. As stated in the report
“Strategy for the housing market” (2015), the Financial Supervisory Authority has implemented additional regulations in order to prevent an even higher debt level:
• 1 out of 10 loans that can be issued without 15 % equity
• Minimum requirement of 2.5 % installment payments on mortgage loans with less than 30 % equity
7 EMPIRICAL ANALYSES
This chapter will further seek to answer the problem statement of the thesis, by providing an empirical analysis of both the Norwegian housing market today and the Danish housing market prior to the financial crisis. Two different house price models will be introduced and applied as tools to identify if the markets can (could) be characterized with bubble tendencies. The respective models are the Hodrick-Prescott filter and Price-to-Rent. As mentioned in section 1.3, Denmark will not be included in the P/R analysis due to limited data access and rental market regulations. As these models examine the housing market based on different underlying factors, we believe that they are contributing to a solid picture of the conditions in the housing markets.