Selected Issues

Abstract

Selected Issues

Are House Prices Overvalued in Norway?—A Cross-Country Analysis 1

House prices in Norway have increased substantially over the past two decades, including by comparison to other countries. Given the importance of the housing market to both financial and macroeconomic stability, it is essential for policymakers to monitor the extent to which house prices deviate from economic fundamentals. This paper examines various factors driving the uptrend in house prices, with a particular focus on institutional and structural factors. The extent of a possible valuation gap is gauged empirically in the context of a cross-country panel analysis of long-run fundamental determinants of house prices using data from 20 OECD countries.

A. Introduction

1. House prices in Norway have risen strongly over the past two decades. (Figure 1). Norway has seen a long housing boom since the mid-1990s apart from a brief and mild downturn during the global financial crisis, with house price inflation exceeding income growth by a wide margin. While real house prices have also been up strongly during the same period in the majority of advanced economies, Norway experienced one of the highest increase in the OECD. Real house prices have more than tripled since 1995 and more than doubled since 2000, with average annual nominal house price growth of 9.3 percent during 2000–07 and 5.1 percent since 2008. Following a short pause in 2013, house price inflation reaccelerated in recent years and reached double digits in the second half of 2016, particularly in the Oslo area (21.7 percent y/y in 2016 Q4).

Figure 1.
Figure 1.

The Housing Boom

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

2. House prices-to-income ratios are high by international standards. (Figure 1). With house prices rising ahead of income, the average cost of a home relative to the median household income nationwide has almost doubled since the mid-1990s, rising much faster than OECD average. In absolute terms, the house price-to-income (PTI) ratio is also high relative to a range of countries. In Oslo, the ratio has soared to nearly twice the national average and is among top in major cities worldwide. Household debt as a share of disposable income has also increased along with house prices from around 145 percent of disposable income in 2002 to 227 percent as of end-2016, higher than in most comparator countries.

uA01fig01

Price-to-income Ratio

(1980Q1=100)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: OECD and Fund staff calculations.

3. For policymakers, it is important to monitor the extent to which house prices deviate from economic fundamentals. If house prices significantly exceed fundamentals, this raises the risk of a house price correction, which could significantly reduce household consumption through wealth effects (Mian et al., 2013). Even though bank losses related to residential mortgages may not increase much,2 both financial and macroeconomic stability could be undermined if lower consumption impairs business activity, which would negatively impact output and pushes up unemployment and bank losses associated with enterprise loans. While it is difficult to detect housing `bubbles’ in real time, it is helpful to gauge the degree of overvaluation or undervaluation in the housing market by comparing actual price levels to those that would be justified by demand, supply, institutional factors.

4. The paper is organized as follows. Section B discusses the driving forces behind the uptrend in house prices, including demand, supply, and institutional factors. Section C presents the cross-country analysis of long-run equilibrium house prices using data from 20 OECD countries. Section D concludes with policy implications.

B. Factors Driving the Uptrend in House Prices

Demand Factors

5. Robust income growth, low unemployment, and rapid accumulation of household financial net wealth, have contributed to strong demand for housing. Real personal disposable income (RPDI) grew by 5.5 percent per year on average over the past two decades—the highest in the sample―and high oil prices helped keep unemployment down. Even following the GFC and the oil price slump in 2014, annual RPDI growth averaged 4.2 percent and unemployment remained relatively low in Norway. The favorable economic and labor market trends, combined with the solid financial position of households, increased housing demand pressure.

uA01fig02

Earnings Growth and Unemployment Rate

(Percent and percent of labor force)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: Haver Analytics.
uA01fig03

House Prices and Net Financial Wealth of Households

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: OECD and Fund Staff Calculations.

6. Population trends reinforced the high demand for owner-occupied housing. Population growth averaged about 0.6 percent from 1995–2005, and increased to about 1.1 percent on average for the past decade—higher than most advanced economies―due to a steady inflow of immigrants. Despite the recent decline due to the economic downturn, annual immigration and net migration remained at around 1.3 and 0.5 percent of total population, respectively. Meanwhile, urbanization— with an average annual rate of 1.4 percent over 2010–15―is exerting additional pressure on demand for housing in the main urban areas.

uA01fig04

Population and Immigration

(Million persons and percent)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: Haver Analytics and IMF staff calculations.
uA01fig05

Urbanization

(Percent)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Source; CIA World Fact Book,

7. Housing demand has also been fueled by declining interest rates. Mortgage rates have gone down substantially since 2000 and stayed low in recent years, with real mortgage rates falling close to zero by end-2015. In addition, housing investment returns have held up as long term bond yields declined along with the slide of policy rates, which stimulated purchases for investment purposes by the wealthier.

uA01fig06

Interest Rates

(Percent)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: Statistics Norway, Norges Bank, and Fund staff calculations.
uA01fig07

Investment Returns: Housing vs. Long-term Bonds

(Percent)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: Statistics Norway, Haver Analytics, and Fund staff calculations.

Supply Factors

8. Housing supply plays an important role in house price dynamics in Norway as it has not kept up with demand. Residential investment has risen in response to higher prices, but housing starts remained below estimated household formation until recently. This results in a continued increase in the ratio of population aged 20 and over to the stock of dwellings over the past decade, contributing to prices rising faster than incomes.

uA01fig08

Housing Supply and Demand Indicators

(Thousands)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Source: Norges Bark.
uA01fig09

Housing Supply Relative to Demographic Needs

(Index)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: OECDr Statistics Norway, and Fund staff calculations

9. The slow supply response to rising demand can amplify price increases. The supply of housing has been falling behind the growing number of households due to both natural (i.e. topographical) and man-made constraints (e.g. local regulations on land use and minimum unit size, including zoning codes and building permits). According to an OECD estimate, Norway has a relatively low price responsiveness of housing supply, with the long-run price elasticity of new housing supply estimated at about 0.5 compared to the OECD average of 0.7. Subject to a given increase in demand, markets with inelastic supply cannot build new dwellings quickly enough to meet the higher demand, resulting in a larger price increase relative to markets with more elastic supply (Anundsen et al., 2016).

uA01fig10

Supply Responsiveness

(Long run price elasticity of new housing supply)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Source: OECD.

Institutional or Structural Factors

10. Generous tax incentives for home ownership and mortgage financing have substantially reduced the user cost of housing, contributing to high and rising house prices. Housing investment receives favorable tax treatment relative to other investment (IMF, 2013).3 Compared with other assets, owner-occupied housing enjoys a large discount in tax base calculation for wealth taxation (25 percent of market value for primary dwellings and 90 percent for secondary dwellings).4 In addition, interest on mortgages is fully tax deductible, which effectively reduces the debt service costs, thereby incentivizing households to borrow more and purchase more expensive houses. As a result, Norway is among OECD countries with one of the lowest recurrent tax revenue from immovable properties and one of the highest degrees of tax relief on debt financing of housing purchases. The favorable tax treatment on housing investment may crowd out capital from more productive use than housing, resulting in efficiency losses and housing demand distortions by reducing the user cost of housing and encouraging excessive leverage (OECD, 2009; Geng et al., 2016).5 Other things equal, housing demand in markets with more favorable tax treatment on housing would be higher for a given level of income or lending rate, pushing up house prices relative to markets with lower tax preferences, which could lead to more pronounced housing boom-bust cycles. In addition, tax relief such as mortgage interest deductibility also tends to be regressive as it is a deduction against earned income instead of a credit, and therefore matters more when income and/or interest rates are higher.

uA01fig11

Property Tax Revenue

(Percent of GDP; 2015 or latest available)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: OECD and Fund staff calculations.Note: Revenue from “recurrent taxes on immovable property.” 2014 data for *.
uA01fig12

Tax Relief for Housing Finance

(Index; increasing in degree of tax relief)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Source: OECD.Note: This indicator takes into account if interest payments on mortgage debt are deductible from taxable income and if there are any limits on the allowed period of deduction or the deductible amount, and if tax credits for loans are available.

11. The underdeveloped rental market put further pressure on the owner-occupied housing market. The rental market in Norway is small, with private and public rental combined accounting for about 23 percent of the total dwelling stock, compared to an average of 38 percent for the Nordic neighbors (IMF, 2015). In addition, protection for tenants in Norway is among the lowest in OECD countries. These factors led to people entering the owner-occupied housing market and taking mortgages at a relatively younger age.

uA01fig13

Tenant-landlord Regulations in the Private Rental Market 1/

(Index, increasing in protection for tenants)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Source: OECD.1/ The indicator measures the extent of tenant-landlord regulation within a tenancy. It includes the ease of evicting a tenant, degree of tenure security, and deposit requirements. See Johansson (2011) for details.

C. A Cross-Country Housing Valuation Model

12. To gauge the extent of a possible housing valuation gap, the long-run relationship between real house prices and their potential determinants discussed above is estimated in a cross-country panel model. Following the literature, the observed real house prices, Pit, are modeled in the form of an inverted demand function of the long-run equilibrium real house prices, Pit*, which are determined by the housing stock, demand shifters, and time-invariant unobserved housing market characteristics:

Pit=Pit*+ϵit=β1Realpercapitadisposableincome(RPDI)it+β2Realmortgagerate(RMORR)it+β3RealHouseholdNetFinancialWealth(RHNFW)it+β4Housingstock/populationaged20andoverit+β5Taxreliefi*RPDIit+β6Taxreliefi*RMORRit+αi+ϵit

Where i denotes country and t year. Besides the commonly used demand shifters, i.e., real disposable income, real mortgage rates, population and its composition, the model also includes household real financial net wealth as an explanatory variable to capture the wealth effects. In addition, the differential impact of tax relief on housing financing cost on house prices are captured by two interaction terms of the tax relief index from the OECD with income and mortgage rate in the augmented model presented in column (3). All variables are in log terms except for mortgage rates and the tax relief index. Country fixed effects are used in the panel estimation to control for direct influences of housing market characteristics or policies that cannot be identified separately—such as cultural attitudes toward housing and the size and efficiency of the rental market. In addition, robust standard errors are clustered at the country level. The estimation sample covers 20 advanced countries in the OECD over the period of 1990Q1–2016Q4.6

13. Estimation results confirm that these factors play important roles in shaping long-run house price developments. (Table 1). The explanatory variables all have the expected sign and are statistically significant. On the demand side, higher incomes, lower lending rates, or more household net financial wealth have a positive impact on house prices. Tax relief on housing also contributes to spurring housing demand and driving up house prices. For example, a one percent increase in real per capita disposable income will raise the long-run equilibrium house price by about 1.4– 2.0 percent, with a greater impact in countries having more generous tax relief. In other words, a positive income shock in Norway translates into an increase in house prices that is around 25 percent larger than in a OECD country with median level of tax relief. On the supply side, a reduction in housing stock relative to the population aged 20 and over is associated with higher prices. In total, the model explains about 86 percent of the cross-country and overtime variation in house prices.

Table 1.

A Cross-Country Panel Model: Long-Run Determinants of Real House Prices

article image
Note: Dependent variables are the logarithm of real house prices. Significance at 1, 5, and 10 percent levels indicated by ***, **, and *, respectively. Robust standard errors clustered at the country level.

14. Estimation results suggest that current house prices in Norway are moderately overvalued. The model is used to gauge the extent of a possible housing valuation gap. The advantage of our housing valuation model over standard metrics such as the PTI ratio is that it considers a comprehensive list of determinants of long-run equilibrium prices—instead of only one ‘fundamental’ variable, e.g., income—in assessing the degree of over- or undervaluation. Based on the model estimates in column (3), the degree of price deviation from long-run values implied by fundamentals is measured by:

ϵit=PitPit*

Based on the metric, the average house prices in Norway in 2016 Q4 are found to be about 16 percent above the estimated equilibrium value as implied by fundamentals. This is comparable to—albeit still slightly below―the estimated deviation during the 2007 peak, and is among the highest in the 20 OECD countries covered in the analysis (also see Annex I).

15. The implied valuations from this exercise should be interpreted with caution. The results can only be indicative of potential valuation gap in the sense that the estimated equilibrium price levels are subject to uncertainties. For example, developments in the housing market are complicated by purchases for investment purposes by high-income households—as rental returns exceed long-term bond yields. Meanwhile, while low interest rates have driven up equilibrium house prices which mitigates overvaluation concerns, they do not rule out that demand is excessive, nor that it could fall sharply as interest rates normalize. This could complicate the housing valuation analysis and potentially bias up the estimates of long-run equilibrium prices.

uA01fig14

Norway: Housing Market Valuation

(Index; percent)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: CBS, Haver, OECD, and IMF staff estimates.
uA01fig15

Housing Valuation Gap

(Percent, as of 2016Q4 or latest available)

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Sources: CBS, Haver, OECD, and Fund staff estimates.

D. Conclusion and Policy Implications

16. High and overvalued house prices are a source of vulnerability in Norway, in view of the importance of the housing market to both financial and macroeconomic stability. A large correction of house prices, driven by slower real income growth, a reverse in sentiment, or interest rate hikes could weaken household balance sheets and depress private demand, and in turn adversely affect corporate and bank earnings. The authorities have been vigilant about the risks and have implemented a list of measures to strengthen the resilience of banks and households, including additional bank capital buffer requirements in line with Basel III/CRD IV, higher risk weights on residential mortgages using IRB models, tighter mortgage regulations, and the introduction of the debt-to-income limit of five times the borrower’s gross annual income to complement the loan-to-value (LTV) limits and affordability tests. Nevertheless, further targeted macroprudential measures should be considered to help contain systemic risks if vulnerabilities in the housing sector intensify, including: tighter LTV limits, a reduction in banks’ scope for deviating from mortgage regulations, and/or higher mortgage risk weights.

17. In the longer term, the macro-financial resilience of the economy to housing market shocks should be enhanced through tax reform and structural measures. A stable housing market (without pronounced boom-bust cycles) would contribute to smoother economic development. While macroprudential measures play an important role in containing the buildup of financial imbalances, a holistic approach is needed to fundamentally address the issue: (i) reducing the generous tax preferences for housing investment would help prevent demand distortions and excessive leverage, thereby dampening housing cycles; (ii) while the recent streamlining of building codes―which shortened the time needed to obtain a building permit and finish construction—is welcome, relaxing land-use and remaining constraints on new property construction, including at the municipal level, should facilitate a more efficient use of land and a flexible adjustment of housing supply, which will mitigate house price growth; and (iii) a more developed rental market would help relieve demand pressures—especially in view of the recent large influx of asylum seekers―as well as support labor mobility across regions as the economy goes through structural change.

References

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Annex I. Actual and Estimated Long-run Equilibrium

uA01fig16

House Prices in Selected OECD Countries

Citation: IMF Staff Country Reports 2017, 181; 10.5089/9781484306659.002.A001

Note: Red lines represent estimated long-run equilibrium prices, while blue lines refer to actual house prices.
1

Prepared by Nan Geng.

2

The direct effect on default rates would likely be limited given that: (i) households have sound repayment buffers in view of their high and strengthened financial asset holdings and the social safety net; and (ii) the full recourse nature of mortgages has typically meant that households prioritize mortgage payments over other payments.

3

Like in many other countries, the imputed rent from home ownership is tax exempt in Norway. Also there is no capital gains tax if a house has been owned for more than one year and the owner has used it as their own home for at least 12 out of the past 24 months.

4

The valuation discount in tax base calculation of second homes for wealth taxation purpose has recently been reduced from 30 to 10 percent stepwise.

5

Capozza et al. (1996) and Harris (2010) showed that tax-favoring of housing tends to encourage excessive leverage and be capitalized into house prices, without necessarily expanding housing opportunities for households.

6

The 20 countries included in the sample are Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Ireland, Israel, Italy, Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, United Kingdom, and United States.

Norway: Selected Issues
Author: International Monetary Fund. European Dept.