Financial Stability 1/2004

2 Macroeconomic developments, households and enterprises

Rapportforside

2.1 Developments in the Norwegian economy
2.2 Households
2.3 Enterprises

Boxes:
- Fixed-interest mortgages
- What drives house prices?
- Predictions with two credit risk models

2.1 Developments in the Norwegian economy

Activity in the Norwegian economy is picking up. In Inflation Report 1/2004, it was projected that mainland GDP growth would be relatively high in 2004 and over the next two years compared with 2003 (see Table 2.1). The international recovery has also gained a firmer foothold.

Table 2.1

Norges Bank’s key rate has been reduced by 0.75 percentage point since Financial Stability 2/2003 and by a total of 5.25 percentage points since December 2002. The key rate is now 1.75%, which is historically low. The krone depreciated through 2003 and at the beginning of 2004, but has appreciated in recent months (see Chart 1.9). The underlying rise in prices in Norway is very low.

Private consumption expanded by a good 3.5% in both 2002 and 2003. The growth rate at the end of 2003 and the beginning of this year points to stronger growth in 2004. Low inflation and reduced interest expenses are expected to contribute to high growth in household real disposable income in the period ahead. This, combined with the prospect of some improvement in labour market conditions, has induced households to remain optimistic about the future (see Chart 2.1).

Chart 2.1

Gross capital formation for mainland Norway fell by 4.9% in 2003. However, the growth rate picked up and was positive at the end of last year. Service industries accounted for most of the increase, but housing and manufacturing investment also rose. According to Statistics Norway’s business tendency survey, Norwegian industrial leaders have become increasingly optimistic in their assessment of the short-term outlook (see Chart 2.2).

Chart 2.2

Petroleum investment exhibited brisk growth in 2003, primarily fuelled by investment in onshore installations. The average price of oil was USD 28.9 per barrel in 2003, which is the highest average annual price in 20 years. In April 2004, the average price was USD 33.4.

Since June 2003, the number of unemployed has gradually declined. In February 2004, seasonally adjusted LFS (Labour Force Survey) unemployment stood at 4.3%, compared with 4.6% on average in the second half of 2003. Unemployment is projected to edge down over the next few years.

Credit to mainland Norway as a percentage of GDP is at a historically high level (see Chart 2.3). Domestic credit to households is now increasing by around 11% at an annual rate (see Chart 3 in the Summary). The growth rate has ranged between 9% and 12% in the past four years. In February 2004, total credit to enterprises showed a year-on-year decline of 2.5%. The decline primarily reflects a fall in credit from foreign sources (see Chart 2.4).

Chart 2.3     Chart 2.4

There are a number of uncertainties associated with developments in the Norwegian economy in the period ahead. We have little experience of such substantial and rapid monetary policy easing as that seen over the past year and a half. A rising household debt burden means that private consumption will be more sensitive to interest rate changes. In addition, the interest rate level and the krone exchange rate influence enterprises’ competitiveness and earnings.

2.2 Households

Continued sharp growth in both debt and financial assets

The increase in household debt is largely matched by an increase in financial assets (see Table 2.2 and Chart 2.5). Household debt rose by NOK 110bn from the fourth quarter of 2002 to the fourth quarter of 2003, while gross financial assets increased by NOK 154bn.

Table 2.2     Chart 2.5

In order to analyse household transactions, we can disregard changes in insurance claims in group insurance schemes, which to a large extent consist of contributions by enterprises, and valuation changes as a result of changes in securities prices. Excluding such factors, household financial assets rose by NOK 80bn in 2003 (see Chart 2.6). Net investments in financial assets excluding group insurance claims have thus fallen to a negative NOK 30bn on an annual basis, from a negative NOK 5bn at the end of the 1990s. This implies that borrowing is now being channelled to consumption, investment in dwellings and other investments in fixed assets to a greater extent than to financial investments.

Chart 2.6

There is considerable uncertainty associated with calculations of households’ net investments in financial assets. They amounted to NOK 3bn in 2003 according to Norges Bank’s financial accounts, while according to the national accounts they were about NOK 31bn. The low figure in the financial accounts may indicate that disposable income has been lower or that consumption and/or households’ gross investments in fixed assets have been higher than assumed in the national accounts.2 The assessment of developments in household income and saving in recent years has been particularly difficult due to substantial fluctuations in share dividends as a result of the abolition of the tax on dividends followed by uncertainty concerning a reintroduction of dividend taxation. According to the national accounts, the household saving ratio rose from 4.2% in 2001 to 9.4% in 2002 before falling again to 7.5% in 2003. This must be viewed in connection with the increase in dividend payments to households, from NOK 13bn in 2001 to NOK 43bn and NOK 35bn in 2002 and 2003, respectively (preliminary figures). Total saving came to NOK 28bn, NOK 69bn and NOK 57bn in the three years, respectively.

House prices on the rise

Higher house prices are an important explanation for the sharp rise in household debt (see Chart 2.7).3 Mortgage loans account for more than 70% of household borrowing. The share of households that own their own dwelling is high in Norway compared with other countries. After falling slightly for the first half of 2003, house prices have risen at an annual rate of 10% in the last six months (see Chart 4 in the Summary). Since autumn 2003, the time it takes to sell a dwelling has also been reduced compared with the same period one year earlier. The driving forces for developments in house prices are discussed in a separate box on pages 22-23.

Chart 2.7

House prices are high in a historical context (see Chart 2.8). Deflated by the building cost index, house prices are 16% higher than in 1987. Deflated by the annual wage index, house prices are marginally lower than in 1987. However, viewed in relation to disposable income, which in addition to wages is influenced by employment and other income, house prices are still somewhat lower than in 1987.

Chart 2.8

Increase in housing loans noticeably higher than housing investment

Households can raise loans with collateral in dwellings that have increased in value. The loans may also be used for purposes other than house purchases and home improvements, such as consumption, repayment of debt, financial investments and other investments in fixed assets. When the net change in the stock of housing mortgages exceeds housing investment, mortgage equity withdrawal occurs. This has been widespread in, for example, the UK, the US, Australia, the Netherlands and Denmark. The increase in the value of dwellings, combined with low interest rates, has also resulted in mortgage equity withdrawal in Norway in recent years (see Chart 2.9). Mortgage equity withdrawal in Norway probably takes place largely in connection with house purchases and may therefore increase with the number of house sales. The housing loan survey conducted by Kredittilsynet (the Financial Supervisory Authority of Norway) shows a rising proportion of loans for refinancing and purposes other than house purchases, particularly in 2003 following the substantial decline in interest rates. A sample survey conducted by Kredittilsynet also indicates that growth in consumer loans from finance companies slowed in 2002 and 2003. The increase in the value of dwellings has contributed to better borrowing terms for refinancing home mortgages than for new consumer loans.

Chart 2.9

Rising debt burden, but falling interest burden

Households’ debt-servicing capacity depends on their income, the size of debt and the interest rate level. The household debt burden, i.e. loan debt in relation to disposable income, rose rapidly in 2003 and is beginning to approach the high levels recorded at the end of the 1980s (see Chart 2.10).

Chart 2.10

Only the liquid portion of disposable income can be used to service debt. The debt burden figures will be higher if the return on insurance claims, which are generally illiquid, is deducted from income. The return on insurance claims has fallen as a share of disposable income since the 1980s when interest rates were high. The difference between the debt burden and adjusted debt burden was therefore greatest in the 1980s.

The household interest burden, i.e. interest expenses after tax in relation to liquid disposable income plus interest expenses, has declined in spite of the high rate of debt accumulation (see Chart 2.11). The main reason is the substantial decline in interest rates. The interest rate burden was reduced by 2.5 percentage points from the fourth quarter of 2002 to the first quarter of 2004.

Chart 2.11

Debt burden in different groups of households

Developments in the interest burden of various groups of households have varied. It is particularly low- and middle-income households (deciles 1-6) that have seen an increase in their debt burden compared with the 1980s (see Chart 2.12). Households with higher income (deciles 7-9) have the highest debt burden. The debt burden in decile 10 was considerably higher than for other groups in the 1980s, but has since fallen markedly. One of the reasons is probably changes in the tax system at the end of the 1980s (reduction in tax deductibility of interest expenses, particularly for high-income groups) and in 1992.4

Chart 2.12

The debt burden rose in all income groups in 2002 (latest available data), with the exception of decile 10. High dividend payments contributed to higher income in 2002, particularly for households in the top income group, who own most shares. This pushed down the debt burden for decile 10 in 2002. From 2003, the debt burden has been projected using growth in the average debt burden based on macro figures (see Chart 2.10). Dividend payments were probably high again in 2003. This may contribute to slower growth in the debt burden in 2003 than in the projections, particularly for groups with the highest income.

The distribution of debt by age shows that it is in the higher age groups (over the age of 55) that the debt burden has increased since the period prior to the banking crisis. The debt burden is nevertheless still lower in these groups than in the other groups (see Chart 2.13). The rise in the debt burden in the age group 25-34 must be seen in connection with the start-up phase they are in and the sharp rise in house prices.

Chart 2.13

It may have become more common and accepted to leave mortgaged assets to the next generation. Increased debt in higher age groups may also be based on a desire to adapt current consumption to expectations concerning future income. The financial buffers, financial assets in relation to debt, also showed an increase at the end of the 1990s, particularly in the age group 55-66. The financial buffers dropped from 2001 to 2002 for all age groups.

Developments ahead

Growth in household debt has been high for a long period. The projections are based on the assumption of a gradual deceleration of household debt growth to the same level as growth in disposable income at end-2006. The assumptions underlying the baseline scenario in Inflation Report 1/2004 have otherwise been applied, including the assumption that unemployment edges down. In 2006, the household debt burden approaches the level prevailing at the end of the 1980s (during the banking crisis). Partly as a result of low interest rates, the household interest burden will remain fairly low in spite of high debt growth.

If household debt continues to expand at the current rate, the debt burden will increase rapidly and in the course of 2005 will exceed the level during the banking crisis (see Chart 2.10). The interest burden rises more than in the baseline scenario, but is relatively low due to low interest rates.

If the household interest burden were to reach the same level as at the end of the 1980s, interest rates would have to increase by 7 percentage points in relation to the baseline scenario at the end of 2005 (see Chart 2.11). This is 8 percentage points higher than today. As a simplification, it is assumed that other variables that influence the interest burden are the same as in the baseline scenario. In the calculations, household interest income rises, but inasmuch as household debt is greater than their interest-bearing assets, interest expenses rise at a faster pace.

All in all, the decline in interest rates has made it easier for households to service their debt. At the same time, growth in household debt remains strong and far higher than income growth. Household financial assets are also rising. However, debt and assets are unevenly distributed among households. Asset values often fall during downturns, while the value of debt remains the same. High and rising debt therefore makes households more vulnerable to economic disturbances such as higher interest rates, an increase in unemployment and a fall in house prices. However, flexible inflation targeting in monetary policy reduces the possibility that households are exposed to a dual shock in the form of higher unemployment and higher interest rates, as was the case at the beginning of the 1990s.


Box:

Fixed-interest mortgages

With fixed-interest loans, the borrowing rate is set for a specific period. In periods when interest rates are generally rising, fixed-interest loans may contribute to financial stability because servicing the loans does not (immediately) become more demanding. On the other hand, borrowers with fixed-interest loans will not benefit from a fall in interest rates.

Historically, fixed-interest mortgages have not been common among Norwegian households. In 1994, fixed-interest mortgages accounted for 9% of the stock of loans to the household sector. A survey conducted by the Savings Banks’ Association in 2003 estimated that fixed-interest mortgages accounted for 20% of their stock of housing loans to households. The share is low compared with other countries (see Chart 1). In Norway, the trend over time is the opposite of what is observed in Sweden and Denmark where shares of fixed-interest mortgages have fallen, but from considerably higher levels.

Chart 1

The share of fixed-interest mortgages among new housing loans varies considerably from year to year (see Chart 2). The term of fixed-interest mortgages in Norway is often between 3 and 5 years.

Chart 2

A fixed-interest mortgage removes the uncertainty associated with interest expenses during the term of the loan and contributes to the predictability of the borrower’s expenses (“security motive”). Both the level of the fixed-interest rate and the fixed-interest rate relative to the floating interest rate may have a bearing on the choice of period for which the interest rate is fixed (“speculation motive”). Although long-term interest rates are historically low now, the difference between long-term interest rates and floating interest rates is considerable, so that these two factors have opposite effects.

The fairly limited number of fixed-interest mortgages in Norway may be due to a number of factors connected with both supply and demand:

  • Borrowers may want to have the option of changing their repayment plan and the period for which the interest rate is fixed. In Norway, it can be costly for borrowers to terminate a fixed-interest mortgage agreement. By comparison, the option of earlier loan repayment without a penalty charge is a standard term of fixed-interest mortgage agreements in the US and Denmark.1
  • Private home financing in Norway has traditionally been offered by banks and not mortgage companies. A larger presence of mortgage companies would probably result in a larger number of fixed-interest mortgages, because these companies obtain their funding in the bond market.
  • Fixed-interest mortgages increase banks’ interest rate risk if the banks have short-term financing. Small banks in particular may have lacked the expertise or financial resources to manage this interest rate risk.
1 Mercer Oliver Wyman (2003): “Study on the Financial Integration of European Mortgage Markets”, a study commissioned by The European Mortgage Federation, www.hypo.org and Frankel, Gyntelberg, Kjeldsen and Persson (2004): “The Danish Mortgage Market”, BIS Quarterly Review, March 2004.

Box:

What drives house prices?

House prices have a major impact on household gross debt and wealth. The debt is largely secured by mortgage. A decline in house prices may therefore increase banks’ loan losses. In this box, we will analyse developments in house prices using an empirical model.

House prices are determined by supply and demand. The supply is stable in the short term, however, since it takes time to build houses and since new construction each year is low compared to the housing stock. Therefore, prices for second-hand homes will fluctuate with demand in the short term.

The demand for owner-occupied dwellings depends primarily on housing costs, household income and household expectations concerning future income growth. Somewhat simplified, housing costs may be defined as interest costs minus the expected increase in the value of the dwelling.

Interest costs comprise interest expenses in connection with a mortgage as well as interest income that is relinquished when owning a dwelling. Higher interest rates increase housing costs and thus lower demand for dwellings. This puts downward pressure on house prices. Housing costs fall in pace with the expected rise in the value of the dwelling: if house price expectations edge up, it becomes relatively more favourable to purchase a dwelling now rather than later. The result is an increased demand for dwellings and higher prices today. Price expectations depend on observed developments in interest rates, income and house prices as well as household expectations of future interest rates and income growth in the Norwegian economy.

Developments in the labour market are important for households’ expectations concerning their own and others’ future income. Increased unemployment leads to expectations of lower wage growth and increased uncertainty concerning future income growth. Thus, demand for owner-occupied dwellings falls. Banks may also be more reticent about providing loans when unemployment rises.

The demand for dwellings also depends on population movement and demographic conditions such as cohabitation patterns, population size and the number of individuals in the start-up phase. Net migration to central areas has been positive in recent years. This has affected regional house prices in various ways but may also have changed average house prices for Norway as a whole.

We have estimated a model for house prices as a whole (see below). The model contains effects of the housing stock, the unemployment rate, banks’ lending rates after tax, total wage income in the economy and an indicator of household expectations concerning their own financial situation and the Norwegian economy. We find no evidence that population movement or demographic conditions have a strong direct impact on house prices as a whole. However, demographic changes will affect prices indirectly by affecting overall wage income in the economy. The model is estimated on quarterly data from 1990 to the first quarter of 2004. It provides a good explanation of price developments (see Chart 1).

Chart 1

The model implies that house prices will rise by ½% in the first year and by 1¾% in the long term if wage income increases permanently by 1% and the other explanatory factors are unchanged. However, a rise in house prices will result in increased new construction and housing stock over time. House prices will fall by 1¾% in the long term if the housing stock, as measured in the national accounts, increases by 1%. In the period 1999-2003, the housing stock and wage income increased on average by 2% and 5% per year. If the housing stock and wage income grow at the pace prevailing for the last five years, house prices will increase by about 5% per year for a given interest rate and unemployment rate.

According to the model, house prices will fall by 2¼% in the first quarter and by 3¼% in the long term if banks’ lending rates increase by 1 percentage point and the other explanatory factors are unchanged. The interest rate is measured at the end of each quarter. The strong short-term effect may therefore reflect the reaction of demand to changes in market rates before lending rates are changed. We do not find any significant effects of market rates other than those that are captured by lending rates.

The analysis indicates that house prices will fall by 10½% over time if the unemployment rate increases from 4% to 5%. The adjustment is relatively sluggish: even though increased unemployment is quickly reflected in household expectations concerning the Norwegian economy, it takes longer for households to adjust their expectations concerning their own financial situation.

Interest rates and unemployment have a major impact on household expectations. Expectations may also shift as a result of a change in political conditions, new forecasts for the Norwegian economy and negative shocks such as war, terrorism and a fall in stock markets. The model captures such effects by including an indicator of household expectations concerning their own financial situation and the Norwegian economy. The indicator is calculated by correcting TNS Gallup’s consumer confidence indicator for effects of the interest rate and unemployment. Therefore, it measures a shift in expectations that is due to factors other than changes in the interest rate and unemployment.

Chart 2 decomposes the rise in house prices in line with the estimated model. The calculations show that new construction pushed down four-quarter growth by 3-4 percentage points in the period from 2001 to the first quarter of 2004. Growth in wage income pushed up the rise in house prices by 9-10 percentage points in the first two years of the period. In 2003 and the first quarter of 2004, the rise in house prices was curbed by lower income growth, increased unemployment and a negative shock in household expectations concerning the Norwegian economy in the first half of 2003 (see Chart 2.1 on page 16). The interest rate reductions since December 2002 have pushed up the rise in house prices by reducing interest expenses, boosting optimism and generating expectations of higher house prices.

Chart 2

The model discussed above is defined as follows:

Δhousepricet = 0,12 Δincomet - 3,16 Δ(INTEREST·(1-τ))t - 1,47 Δ(INTEREST·(1-τ))t-1 + 0,04 EXPECt
  (1,94) (7,04) (3,27) (3,09)
 - 0,12 [housepricet-1 + 4,47 (INTEREST·(1-τ))t-1 + 0,45 unemploymentt - 1,66 (income - housingstock)t-1]
 (5,69) (2,54) (3,48) (8,63)

Estimation period: 1990 Q2 – 2004 Q1. R2 = 0,88. Absolute t-values are shown in parentheses under the estimates.Δ is a difference operator:ΔXt = (Xt - Xt-1).
The variables are defined as (small letters indicate that variables are measured on a logarithmic scale):

houseprice = Price index for resale homes. Source: NEF, EFF, finn.no, ECON and Norges Bank
INTEREST = Banks’ average lending rate. Source: Norges Bank
τ = Tax deduction for interest on debt (0.28 since 1992)
EXPEC = (E–F) + 100·(E–F)3
E = Indicator of household expectations concerning their own financial situation and the Norwegian economy. Measured as a rate. Total over two quarters. Source: TNS Gallup
F = Value of E which can be explained by the interest rate, unemployment and seasonal variation. Calculated from an estimated model for TNS Gallup’s consumer confidence indicator
unemployment = Unemployment rate. Source: The Directorate of Labour
income = Total wage income in the economy. Depends on the wage level and employment. Source: Statistics Norway
housingstock = Housing stock at constant prices. Source: Statistics Norway

The expression in square brackets measures the deviation between the house price in the last quarter and an estimated long-term relationship between house prices, the interest rate, the unemployment rate, wage income and the housing stock. The model also contains a constant and effects of seasonal variation. The values of INTEREST and income for 2004 Q1 are based on projections from Inflation Report 1/2004. The variable EXPEC is equal to zero in the period for which consumer confidence data from TNS Gallup is unavailable..


2.3 Enterprises

Improved profitability

Listed companies’ annual accounts for 2003 indicate an improvement in corporate profitability compared with 2002, but there are considerable differences across industries. A rise in turnover, increased efficiency and lower interest expenses have contributed to improving profitability. The depreciation of the krone through 2003 also made a positive contribution to many enterprises.

According to preliminary national accounts figures, enterprises’ gross interest expenses fell more than 11% from 2002 to 2003, while net interest expenses declined by over 7%. This is in fairly close accord with the percentage decline in interest expenses for large listed companies. If all interest-bearing debt in enterprises had been based on a floating krone interest rate, gross interest expenses should have fallen by more than 30%. There may be several reasons, in addition to fixed-interest loan agreements, why interest expenses have not fallen to this extent. One explanation is that a substantial portion of large enterprises’ debt is in foreign currency, from countries where interest rates have fallen less than in Norway. The use of interest rate derivatives, which makes it possible to exchange a floating interest rate for a fixed interest rate on debt, may also have played a role. The return on equity before tax was 7.8% for the average enterprise in 2002. Judging by the balance sheet at the end of 2002, a reduction in net interest expenses of 7% will in isolation have boosted the return on equity by about half a percentage point in 2003.

Record-high dividends

Allocations to dividends as a percentage of equity and dividends came to more than 7% in the 2002 accounting year. The proposed introduction of dividend taxation makes it likely that dividend allocations will again be high in the 2003 accounting year. An estimated increase in dividends from listed companies to private investors of about 60% from 2002 to 2003 has been reported. As a result of improved profitability, enterprises can pay large dividends without eroding their financial strength. Record payments for the 2002 accounting year only resulted in a small decline in the overall equity ratio from 2001 to 2002.

Lower debt and interest burden

The fall in interest rates in 2003 contributed to a lower interest and debt burden that year, even though debt in nominal terms was approximately unchanged (see Chart 2.14). Given developments in the Norwegian economy corresponding to the baseline scenario in Inflation Report 1/2004, the debt and interest burden will fall markedly this year.5

Chart 2.14

Fewer bankruptcies

The number of reported bankruptcies rose by 17% from 2002 to 2003. However, the number of bankruptcies (seasonally adjusted) has fallen since peaking in the second quarter of 2003 (see Chart 2.15). CreditInform reports that the number of bankruptcies has continued to fall in the first four months of 2004. Measured by turnover and employment in bankrupt entities, the bankruptcy peak was passed in the second half of 2002. The total sales of the bankrupt entities fell by a little more than 1% from 2002 to 2003.

Chart 2.15

Of the major industries, it was only in the property management sector that the turnover of bankrupt enterprises showed an increase from 2002 to 2003 (see Chart 2.16). The turnover of unincorporated firms that went bankrupt more than quadrupled from 2002 to 2003, but still only accounted for 4% of the total sales of all bankrupt entities.

Chart 2.16

It is not only business start-ups that declare bankruptcy. An analysis of the age of enterprises that have gone bankrupt since 1992 shows that the proportion of older enterprises has increased in recent years (see Chart 2.17).6 After having fallen for several years, the proportion of bankrupt enterprises with a life of less than 4 years rose in 2003.

Chart 2.17

The average age of bankrupt enterprises declined up to 1998, but has since risen (see Chart 2.18). The industry with the most bankruptcies is wholesale and retail trade, and the average age of bankrupt enterprises in this industry is virtually identical to the average for all industries. The average age of bankrupt enterprises in manufacturing is higher than for most other industries. Bankrupt enterprises in property management are also characterised by a high average age. However, the average age has fallen somewhat in recent years. The hotel and restaurant sector is one of the industries with the lowest average age for bankrupt enterprises.

Chart 2.18

Default probabilities decline

According to Moody’s credit risk model KMV, the probability of large Norwegian unlisted enterprises defaulting on their debt obligations declined through 2003.7 The decline has continued in 2004 (see Chart 2.19). Default probabilities for the most exposed enterprises (90 percentile) have, however, fallen less than for other enterprises. This indicates that the risk of losses on loans to this type of enterprise is still relatively high.

Chart 2.19

The default probability for the median enterprise in most industries has fallen over the past year (see Chart 2.20). In the shipbuilding industry, the default probability has declined by more than 4 percentage points since the end of 2002. There has also been a decline for service industries. Profitability problems in the fish farming industry have resulted in high default probabilities in this industry.

Chart 2.20

Since the end of 2002, the default probability for the median enterprise has fallen markedly in the Nordic countries (see Chart 2.21). With the exception of Sweden, default probabilities are close to the trough level for the last five-year period.

Chart 2.21

The main reason for the fall in default probabilities in Moody’s KMV model is the rise in equity prices, which has increased the value of enterprises’ assets. Reduced volatility in equity markets has until recently also contributed to the decline in default probabilities.

Risk associated with property companies

Property companies have higher debt financing than other enterprises. The property industry is also the largest recipient of bank loans. The sharp fall in interest rates since December 2002 has contributed to reducing the interest burden and thereby strengthened the debt-servicing capacity of property companies. Even enterprises with a large share of fixed-interest loans have now begun to benefit from the decline in interest rates.

Statistics Norway has constructed a price index for office and commercial properties in Norway. The price index is updated every six months and the first data were published this spring. Between end-2002 and end-2003, prices for office and commercial properties rose by 8% (see Chart 2.22). The index is nevertheless 4% lower than at the peak in the first half of 2001. Property companies are a diverse group that consists of enterprises influenced by developments in various markets. The situation is still weakest in the market for rental of office premises. Figures from OPAK show that both rental prices for office premises and the value of office buildings have continued to fall (see Chart 2.22). However, there are wide variations in developments in value, depending on the quality of leaseholders and length of leases. The decline in rental prices and the value of office premises in 2003 is confirmed by figures from Investment Property Databank. There is a marked difference in developments for different types of commercial property. For example, the value of shop premises increased in 2003.

Chart 2.22

According to Eiendomsspar’s annual survey for the Oslo area, the rise in vacant office space is showing signs of slowing (see Chart 2.23). In contrast to 2002, rented space (in square metres) rose in 2003. Figures from Statistics Norway show that office and commercial building starts increased by 6% from 2002 to 2003, after having fallen by 30% from 2000 to 2002. This fall contributed to a decline of 18% in completed office and commercial buildings from 2002 to 2003. Eiendomsspar’s survey shows that a sharp reduction in completed premises is expected in 2004 compared with recent years. This reduction, along with a brighter outlook for service industries, which heavily influence demand for office premises, may contribute to improving market balance in the years ahead.

Chart 2.23

Owing to property companies’ substantial debt combined with a continued fall in rental prices for office premises, parts of this industry are financially vulnerable. However, low interest rates, higher growth in the economy and a reduction in probable new construction over the next few years help to make the situation somewhat brighter for property companies.

Developments ahead

The fall in interest rates since December 2002 has substantially reduced the interest burden of the enterprise sector. As a result, many enterprises can service their debt even with low operating margins. Enterprises’ underlying earnings have improved. Higher growth in the Norwegian economy may contribute to further earnings growth. Although financial vulnerability varies across industries, we assess risk as moderate and somewhat lower overall than six months ago.


Box:

Predictions with two credit risk models

Norges Bank uses two different models to analyse financial exposure in the enterprise sector. Norges Bank’s SEBRA model1 predicts bankruptcy probabilities based on annual accounts figures for all Norwegian limited companies. The disadvantage of the SEBRA model is that new information comes in only once a year and that there is a time lag of nine months between the closing of the annual accounts and the availability of the accounts in the database. For example, the SEBRA model as at June 2004 is based on annual accounts from 2002. The model that Norges Bank uses from Moody’s KMV predicts default probabilities for non-listed enterprises based primarily on market information. The model is based on some key variables from the annual accounts that are combined with developments and the volatility of equity prices for listed companies in the same industry and country as the enterprise in question. The KMV database in question is limited to large unlisted companies with annual turnover exceeding NOK 70m.

We have compared the SEBRA model with the KMV model, looking at the predictions after the accounting years 1998 - 2001 and bankruptcies in the three following years.2 For example, the bankruptcies in the period 1999 – 2001 are used to evaluate the quality of the predictions after the accounting year 1998. For each of the accounting years, both the SEBRA and the KMV models include somewhat more than 3000 non-financial enterprises, excluding enterprises in the oil and gas industry. Of the enterprises represented in both databases in the accounting year 1998, 100 went bankrupt in the period 1999 - 2003, 33 of them in the period 1999 - 2001.

The SEBRA model predicts the probability of bankruptcy, whereas the KMV model predicts the probability of default on debt. An enterprise that defaults on its debt will not necessarily go bankrupt. Therefore, the default probability for an enterprise will never be lower than the bankruptcy probability. In practice, the default probability from the KMV model is considerably higher than the bankruptcy probability from the SEBRA model. There is reason to assume, however, that the ranking of enterprises, based on the bankruptcy and default probabilities (risk exposure), respectively, is approximately the same.

Chart 1 shows that the SEBRA and KMV models are approximately equal in their ability to pick bankrupt enterprises and are considerably better than a random selection. For example, with a random selection, one would expect to find 20% of the bankrupt enterprises among the first 20% of enterprises selected. Close to 55% of the enterprises that went bankrupt in the period 1999 - 2001 were among the 20% of the enterprises that the SEBRA model predicted to have the highest risk exposure as at September 1999, while the comparable figure for the KMV model was more than 45%.

Chart 1

The KMV model has the advantage over the SEBRA model that it is based on current market data. To evaluate the significance of the market data, we have compared the KMV model’s March predictions (15 months after the close of the accounting year) with the September predictions (9 months after the close of the accounting year). These two predictions are based on the same accounting data, but the March predictions use more recent market data. On the whole, the March predictions appear to be somewhat more accurate than the September predictions, indicating that current market information improves predictions.

A comparison of the SEBRA and KMV models shows that both models are effective in selecting bankruptcy candidates among large unlisted Norwegian limited companies. The SEBRA model’s use of a larger number of accounting variables compensates for the KMV model’s advantage of using updated market information. However, use of more recent market information improves the KMV model’s prediction capabilities. A further development of the SEBRA model may therefore be to include some market indicators.



Norges Bank, Bankplassen 2, PB 1179 Sentrum, 0107 Oslo, tlf (+47) 22 31 60 00
Last updated 10.06.2005