February 2013

Are house prices driven by a housing shortage? Market Report Title: Are house prices driven by a housing shortage?, Market Report, February 2013

Published by: Boverket Author and contact person: Alexandra Leonhard, +46 (0)455-35 33 80 Co-Author: Peter Karpestam, Bengt Hansson Data gathering: Marie Rosberg Market Report February 2013 3

Introduction Figure 1. House price, 2011 Buying a house or a tenant-owned property is the biggest 4.0 investment most households make and in order to be able 3.5 to buy a place to live, almost all households require a loan. 3.0 The average debt ratio among households with mortgages 2.5 is more than twice their annual income before tax1. However, there is a great deal of variation, with young 2.0 households in mortgaged tenant-owned apartments in 1.5 Stockholm having an average mortgage equivalent to 1.0

4 times their annual income. As these loans are agreed 0.5 using the house and its market value as security, this intensifies the positive effects for households when house 0.0 Average purchase price, million SEK prices rise and the negative effects of price falls. Stockholm county Uppsala county Skåne county Halland county Västra Götaland county Västerbotten county Norrbotten county The return on residential property in Sweden between 1996 and 2011 was very good, which is primarily the Source: Statistics Sweden result of the increase in prices over this period2. House The figure shows the average price of a single-family house in prices move in cycles of anything between 2 and 22 years the counties with the highest and lowest prices. in length, but over longer periods they often fluctuate around a constant average3. So what is it then that makes The price increase in the various counties of Sweden is prices rise and fall in the short term? In this report, we primarily attributable to rising incomes, low interest rates answer this question by analysing price trends in all the and backward-looking expectations or speculation. In the Swedish counties. What proportion of the price increase counties with major cities, and neighbouring counties, an in the various counties of Sweden can be explained by increase in the population/dwelling ratio has had an what we call fundamental variables, such as higher impact on price trends. Many people tend to view a incomes, wealth, increased population/dwelling ratio housing shortage solely in terms of how many dwellings (number of people per dwelling) or low mortgage interest we have and how many people there are who want to live rates? Prices have increased 120 per cent since 1996 in in them. However, it is important to remember that real terms. However, there are large regional differences in increased incomes also lead to greater demand for houses. the rate of increase and in the price level. Figure 1 shows As we grow richer, we want to consume more houses, and the counties with the highest and lowest average purchase houses that are larger and more expensive. The current price in 2011. strong demand for houses and high prices are therefore primarily the result of us getting richer rather than as a consequence of overcrowding. If we look at the population/dwelling ratio, this has certainly increased somewhat in recent years, although it remains low from a historical perspective4. The most important explanation for the price increase, aside from incomes, is household expectations being backward-looking – in other words, prices are expected to continue to rise tomorrow because they rose today.

In the counties of Skåne and Stockholm, which have seen the largest price increase between 1996 and 2011, the 1 According to Sweden’s credit information agency, (UC) 2012. price of a single-family house has risen by 163 and 162 2 BKN [Sweden’s National Housing Credit Guarantee Board] (2012), “Choices per cent respectively in real terms (although the price on the Housing Market”, Market report, May 2012. The return on ownership consists of both the value of living in a property (implicit rent) and capital gains or losses. 3 Bracke, P. (2011), “How long Do Housing Cycles Last? A Duration Analysis for 4 See Boverket [Sweden’s National Board of Housing, Building and Planning] 19 OECD Countries”, IMF Working paper, No. 11/231. He shows that upturns (2012), Bostadsbrist ur ett marknadsperspektiv [Housing shortage from a market are often longer than downturns. perspective], No. 2012:18. 4 Market Report February 2013

level in Skåne is lower than in Stockholm). Prices have The user cost, which changes principally as a result of primarily been driven up by increases in income and mortgage interest rates falling, on average accounts for backward looking expectations, in other words both 12 per cent of the house price increases in the various fundamental and speculative forces have come into play counties. This means that falling interest rates (on the here. The population increase relative to housing whole) have led to higher house prices. construction accounts for only 21 and 12 per cent respectively of the price increase. The backward-looking expectations of households have a strong positive influence on house prices in all counties. Figure 2. Factors that have lead to house prices to Many households buy a house with the expectation that increase in Stockholm county the price will continue to rise. This could be considered to be speculation, particularly as households repay their mortgages only to a very small extent6. It can give rise to the feeling that repaying the mortgage is unnecessary when the value of the house quickly grows. Furthermore, Incom it is possible to take out larger loans or to borrow against Population/ dwelling ratio the property in order to buy a new kitchen or car when User cost the value of the house has increased. In this way, rising Backward-looking expectations house prices result in increased lending. Financial wealth How have house prices developed in relation to fundamental factors? A lot of research has been carried out on analysing what drives house prices. Residential properties are Source: Own calculations fundamentally just like any other good and the price is The figure shows the reasons for house price increases between 1996 dependent on supply and demand. and 2011 in Stockholm county. Other variables also play a part, but their impact on price trends is considerably less; see table 3. OECD has examined the supply and demand using the following fundamental factors: In Västra Götaland, the population/dwelling ratio is driving up prices to a lesser extent (5 per cent) than in • income Skåne and Stockholm. Here prices are instead influenced • borrowing costs more by increased income. In those counties where house • property taxes/charges prices have not risen so rapidly, the increase in income • expected inflation generally accounts for a greater proportion of the price • number of people needing a property increase than in the regions close to the major cities. • supply of residential property • construction costs If we exclude the counties with major cities, the link between the number of houses and the population has They found that Swedish house prices were 8 per cent either been more balanced or the population has fallen at above their fundamental value as early as 2005 and by a faster rate than the number of houses. In Dalarna, for 2006 the overvaluation had grown to 15 per cent7. example, the population has fallen by 4 per cent while the Between 2006 and 2011, real house prices rose by supply of housing has increased by more than 1 per cent. 15 per cent in Sweden and BKN estimated that prices In 13 of Sweden’s 21 counties, house price trends have were 20 per cent above their fundamental value in 20088. been dampened by a fall in the population/dwelling ratio5. 6 BKN (2012), “Choices on the Housing Market” and “Why repay your mortgage?”, Market reports, May and October respectively 2012. 7 Hüfner, F. and J. Lundsgaard (2007), “The Swedish Housing Market – Better 5 In Uppsala, Östergötland, Kronoberg, Jönköping, Kalmar, Gotland, Blekinge, Allocation Via Less Regulation”, Economics Department Working Paper, No. 558, Halland, Värmland, Dalarna, Västmanland, Gävleborg, Västernorrland, Jämtland, OECD. Västerbotten and Norrbotten counties, the population/dwelling ratio has fallen 8 BKN (2008), “Bostaden – en riskfylld tillgång” [Property – a risky asset], since 1996. Market report, December 2008. Market Report February 2013 5

User cost Table 1: Real house price rise relative to fundamental The real mortgage interest rate which we use to factors between 1996 and 2011, per cent calculate the user cost of our houses is very important for County Price Price/ Price/ determining whether or not the housing market is increase income change in overvalued. The higher the real interest rate, the lower since growth* popula- the equilibrium price of residential property. There are 1996 tion/ various ways of calculating the real mortgage interest dwelling rate, but the most common is to deduct the expected ratio level of future inflation from the mortgage interest rate. Stockholm county 162 98 149 The five-year mortgage interest rate, after interest cost tax deduction, is currently just over 2 per cent. With Uppsala county 133 70 139 inflation rate expectations in line with the Riksbank’s Södermanland county 109 62 108 inflation target, this means that the current real Östergötland county 124 69 130 interest rate for mortgages is close to zero or only very slightly positive. The current low real interest rates Jönköping county 116 60 118 in many countries are the result of the financial crisis. Kronoberg county 98 47 106 The low real interest rate in Sweden is partly a result of Kalmar county 88 37 98 the very expansive monetary policy pursued by central banks around the world and partly also because global Gotland county 152 77 174 investors consider Sweden and Swedish securities to be Blekinge county 91 46 94 a safe haven. Skåne county 163 103 156 In view of the current low real interest rates, the Swedish Halland county 158 85 162 housing market is therefore not overvalued according Västra Götaland county 146 84 145 to the user cost model. Nevertheless, there are good Värmland county 85 46 90 arguments to suggest that today’s low real interest rates are temporary and a consequence of the economic Örebro county 90 47 90 crisis. From a longer historical perspective, the real Västmanland county 106 61 107 interest rate is around 2.5 per cent. A return to Dalarna county 83 40 93 “non-crisis interest rates” in the world would mean that interest rates on Swedish five-year mortgages would be Gävleborg county 83 41 85 between 5.5 and 6 per cent instead of the current rate Västernorrland county 60 23 63 of just over 3 per cent. According to the results of the Jämtland county 87 41 99 user cost model, current house prices, calculated using normal or long-term equilibrium interest rates, are just Västerbotten county 71 28 79 over 20 per cent too high. Norrbotten county 63 24 70

House prices in Sweden have more than doubled in real *) Income here means employment income per capita. Employment income is income before tax and includes unemployment, sickness and terms since 1996. Table 1 shows the price increase on parental benefit as well as pensions. It represents the situation onthe single-family houses in the various counties of Sweden. It labour market and is useful for the comparison between the counties. also illustrates how much the prices in the various House prices have been deflated using the CPIF. counties have risen relative to increases in income, Source: Statistics Sweden population and the number of residential properties. 6 Market Report February 2013

Prices rose the most in the counties of Stockholm, Skåne Figure 3. Property wealth, disposable income and and Halland. In the counties of Stockholm and Skåne, population/dwelling ratio they have risen twice as fast as income per capita. Incomes 3 000 3.0 in Stockholm were already higher than in the rest of Sweden in 1996, but the rate of increase up to 2011 has 2 500 2.5 matched the average rate for the country as a whole. In 2 000 2.0 Skåne, employment income per capita was generally equivalent to the average for Sweden and the rate of 1 500 1.5 increase has been slightly lower than average. In contrast, 1 000 1.0 the counties of Gotland and Uppsala have seen the most Index1970=100 rapid increase in incomes. This resulted in house prices 500 0.5 Persons per dwelling rising “only” 77 and 70 per cent faster than incomes respectively. 0 0.0 1971 1976 1981 1986 1991 1996 2001 2006 2011 Higher incomes mean greater demand for property, as the Property wealth Disposable income general purchasing power of households increases and Population/dwelling ratio (right axis) they choose to spend a greater proportion of their consumption on living, other things being equal. An Source: Macrobond, Statistics Sweden and own calculations increase in incomes is therefore expected to lead to rising Here we see that property wealth and disposable income run in parallel house prices. International literature usually assumes that until the year 2000, when property wealth began to increase much faster there is a 1:1 relationship between incomes and than income. At the same time, population/dwelling falls nationally. house prices9. This means that if incomes rise by 1 per cent, house prices will also rise by 1 per cent, assuming that the supply of housing remains constant. The figure shows that property wealth (which includes However, different studies have returned a wide variety of the value of single-family houses and tenant-owned results. The OECD and IMF have conducted extensive properties) has increased considerably more than incomes reviews of the literature, which have shown that income since the year 2000. Until the beginning of the 1990s, elasticity is often greater than 1 when estimated for an property wealth and incomes increased at the same rate. individual country, but is closer to 1 when estimated as an Following the financial crisis, property wealth increased average10. Elasticity also depends on the time period for more slowly than incomes, but this changed in the first which it is calculated. According to the Riksbank, Swedish decade of this century, when it increased more than households have increased their share of housing incomes. The most important reason for the growth in consumption relative to other consumption. This implies nominal wealth in the housing stock is rising house prices that price increases of houses have been higher than and inflation, with only 15 per cent of the increase income increases since the 1990s due to changed attributable to an increase in the number of properties. preferences. Figure 3 illustrates property wealth relative Despite this, it does not appear that the population/ to disposable income in nominal terms. We have also dwelling ratio increased during the period but in fact fell, added a line which shows that the population/dwelling although there are major variations in the country. ratio fell slightly up to the 1990s and then plateaued during the first decade of this century.

9 See, for example, P. Englund (2011), “Swedish house prices in an international perspective”, in The Riksbank’s inquiry into the risks in the Swedish housing market. 10 Girouard, N., M. Kennedy,P. Van den Nord and C. André (2006) “Recent House Price Developments: The role of Fundamentals” OECD Working Paper, No. 475. Iossifov, P, M. Čihak and A. Shanhgavi (2008) “Interest Rate Elasticity of Residential Housing Prices”, IMF Working Paper, No. 08/247. Market Report February 2013 7

Population has increased the most in Stockholm Table 2: Real price rise for tenant-owned apartments (20 per cent), in spite of which prices have risen relative to fundamental factors between 2000 and 2011, 119 per cent faster. In all counties, prices have increased per cent roughly twice as fast as the population. In some counties, County Price price/ price/ the population has fallen while prices have risen. Table 1 increase income change in shows that prices have risen more compared to the since growth* popula- population/dwelling ratio than to themselves during the 2000 tion/ time period. dwelling ratio Generally speaking, prices have risen considerably faster Stockholm county 99 71 93 than the supply of houses. This may seem slightly Uppsala county 172 125 178 surprising, given that construction firms should want to Södermanland county 392 317 387 build more when house prices rise. However, the housing Östergötland county 412 335 414 stock is slow moving and prices may rise in the short term as a result of construction simply not keeping pace. As Jönköping county 366 289 369 Boverket’s study on housing shortages states, there was a Kronoberg county 358 287 362 large supply of residential properties following the crisis Kalmar county 391 304 404 of the 1990s, which may explain why there was little Gotland county 268 195 294 construction during the late 1990s. The county of Skåne Blekinge county 304 245 307 saw the fastest price rises relative to the supply of property, which increased by 9.3 per cent during the Skåne county 291 234 280 period. An increase in supply of 9.3 per cent is Halland county 402 302 405 considerably higher than the average for the country of Västra Götaland county 283 221 280 4.4 per cent. The greatest increase in the number of Värmland county 434 362 442 residential properties (of around 15 per cent) was in Örebro county 239 192 236 Uppsala, in spite of which prices increased at about twice this rate. There are also counties where the supply of Västmanland county 316 258 312 housing has fallen. In the county of Jämtland, the number Dalarna county 367 295 377 of residential properties has fallen by 0.4 per cent, but the Gävleborg county 298 241 297 population has fallen quicker. Therefore has the Västernorrland county 212 167 208 population/dwelling ration decreased from 1.97 person per dwelling to 1.87, which is the lowest figure in the Jämtland county 304 240 314 country. This means that prices have increased twice as Västerbotten county 274 213 283 much as persons per dwelling. Norrbotten county 232 177 241

*) Income refers to employment income per capita. Prices have been deflated The prices of tenant-owned apartments have risen more using CPIF. than the prices of single-family houses over the last 11 years. Table 2 illustrates the price trend for tenant- Source: Statistics Sweden owned properties relative to fundamentals. Unfortunately, there are no statistics available on tenant-owned property Despite the fact that the period is four years shorter, the prices at county level before the year 2000. prices of tenant-owned properties have increased considerably more than prices for single-family houses in all counties except Stockholm. In Stockholm, tenant- owned property prices doubled during the first decade of this century, which on average means a real increase in value of over SEK 1 million per tenant-owned property. 8 Market Report February 2013

Figure 4. Price on a tenant-owned apartment, 2011 more in the future. And lenders’ security for the loan increases as house prices rise, which reduces the lenders’ 2.5 risk.

2 A study which examines what drives house prices in 17 developed countries shows that fundamental factors have 11 1.5 a more long-term effect on house prices . If you want to know what drives house prices in the short term, however, 1 it is more relevant to examine the state of the mortgage market. The Swedish mortgage market was most similar 0.5 to those of Ireland, the United Kingdom, Australia and Norway when the study was carried out. Characteristic of

Average purchase price, million SEK 0 these are still the following:

Stockholm county Uppsala county Gotland county Västra Götaland county Halland county Skåne county • Variable interest rates. Dalarna county Västernorrland county • Ability to withdraw equity from the property. • Loan-to-value ratios of 80-90% of the market value. Source: Statistics Sweden • The current market value is used to determine the The figure shows the average price of a tenant-owned apartment in the counties with the highest and lowest prices. value of the property at the mortgage approval stage12. In Sweden, real prices for single-family houses have risen by an average of SEK 480,000. Like house prices, the The study shows that house prices in Ireland, the United prices of tenant-owned properties have increased Kingdom, Australia, Norway and Sweden are influenced considerably more than the increases in income, to a great extent by access to household credit, the ability population and property. In Jämtland the number of to borrow a lot in relation to the purchase price and low properties has fallen by 17, the population has fallen by variable interest rates. Their results show that if the real 3,267, and incomes have risen by almost 16 per cent in three-month interest rate falls by 1 percentage point, real real terms since the year 2000. In spite of this, prices have house prices rise by 2.6 per cent over a five-year period. risen by 300 per cent, which means that on average the This is a stronger response than in those countries with a price of a tenant-owned apartment has risen from more conservative mortgage market (such as Germany, SEK 130,000 to SEK 500,000 in real terms in 11 years. In Italy and France). They also show that mortgage trends in view of the fact that the prices of both houses and tenant- Ireland, the United Kingdom, Australia, Norway and owned apartments have increased considerably more than Sweden are highly correlated with house price trends, can be explained by the fundamental factors (particularly which means that the value of the house affects the with regard to tenant-owned apartments), there is reason household’s ability to take out even larger loans. This can to believe that prices are being driven by something other also result in behaviour such as increasing borrowing than these variables. against the house in order to buy a new kitchen, renovate the bathroom or buy a new car13. This grew more The mortgage market and house prices common even in Sweden during the first decade of this century. The demand for residential property is affected by the various factors discussed above, but is also dependent on 11 Tsatsaronis, K. and H. Zhu (2004), “What drives housing price dynamics: how expensive it is to borrow money, how easy it is to cross-country evidence”, BIS Quarterly Review, March 2004. They find that GDP- borrow and the house price expectations. In a world with growth can be used to measure where a country is in the business cycle, as well as good economic growth, low inflation and policy rates, it is the size of incomes and unemployment. 12 In Sweden, the market value (usually the purchase price, as this is an easy to get too optimistic and to underestimate the price indication of the market value) is used to determine the value of the property risk. When house prices rise, concerns about large amounts when the bank or building society is deciding whether to approve a mortgage. In Germany, for example, they do not use the market value to determine the of borrowing to buy a house are lessened. Mortgage value of a property at the mortgage approval stage, but instead use a long-term customers are not troubled with thoughts on how to sustainable value calculated according to special guidelines. repay as they assume that the property will be worth 13 We reported on the occurrence of this behaviour on the Swedish mortgage market in our market report of October 2012, op. cit. Market Report February 2013 9

Regulatory changes on the mortgage market in Denmark Quick rises in asset prices and price bubbles are not at the end of 2003 fundamentally changed the operation necessarily the result of access to credit, but access to of the mortgage market. This also led to their mortgage credit increases leverage15. market resembling those described above. The Danish Nationalbank reports that interest-only mortgages with In the USA, it was found that those regions with variable interest rates quickly became popular14. The aggressive sub-prime lending also were those with the proportion of mortgages with variable interest rates strongest price increases16. When the crisis hit, prices fell doubled in 7 years and in 2010 represented 43 per cent of more strongly in these areas than in the rest of the the Danish mortgage market. Their analysis shows that country. In this way, aggressive lending increases house more than half of the real price increase between 1999 price fluctuations and prices rise and fall more strongly and 2007 was the result of the introduction of interest- than they would have done if lending were not so high. only mortgages combined with the fact that many people We also demonstrated this in the Market report of May opted for loans with variable interest rates. Denmark 201217. We showed how much greater risk homeowners traditionally had a mortgage market that required bear if they have a mortgaged property. The more repayments as well as interest rates which were fixed for indebted, the greater the possibility of seeing positive or long periods. Since, under normal circumstances, the yield negative returns, depending on the way the market curve turns slightly upwards, a variable interest rate is moves. often lower than an interest rate that is fixed for a longer period, as this is subject to forecast inflation and risk Figure 5, shows the real house price trend in countries premium. The variable interest rate which Danish lenders with a mortgage market similar to the Swedish one. In were able to offer was therefore lower than the traditional three of the countries prices have fallen sharply and here fixed interest rate and many households therefore you talk about house prices having burst. Since 2007, replaced their fixed-rate loans with variable-rate ones. however, prices have plateaued in Sweden, which could perhaps be the beginning of a return to a more sustainable Figure 5. Real house price development 1970-2012 long-term price level. What is problematic, however, is 160 that the mortgage loan stock has continued to increase.

140 House prices in Sweden have risen by more than 120 120 per cent over the last 16 years (in real terms). At the 100 NO same time, the size of household mortgage loan stock has 80 SE increased by over 260 per cent (in real terms). Figure 6 DK 60 UK shows the annual change in mortgage loan stock and IE house prices, with the data series displaying a very similar Index2005 = 100 40 trend even if the mortgages grow faster than house prices 20 during the 2000s. The large increase in mortgage loan 0 stock in 1986 is most likely the result of the financial deregulation which applied from this year onwards. 1971 1976 1981 1986 1991 1996 2001 2006 2011

Source: Macrobond, OECD

15 Fisher, I. (1933), “The debt-deflation theory of great depressions”, Econometrica, Vol. 1, No. 4. 16 Pavlov, A. and S Wachter (2009), “Subprime Lending and House Price Volatility”, University of Pennsylvania Institute for Law and Economic Research Paper, No. 08-33. 14 Danmarks Nationalbank (2011), Monetary Review 1st Quarter 2011, Part 2. 17 BKN (2012), “Choices on the Housing Market”, Market report, May 2012. 10 Market Report February 2013

Figure 6. Annual change in house prices and the equity required for a mortgage to be approved. mortgages, real terms 25 Figure 8. Mortgage interest rate and house 20 price index, current prices 15 18 180 10 16 160 5 14 140 0 12 120 per cent -5 10 100 -10 8 80

-15 per cent 6 60

-20 4 40 Index2005=100

1972 1977 1982 1987 1992 1997 2002 2007 2012 2 20 House prices Mortgages 0 0

Source: Statistics Sweden, Macrobond 1981 1986 1991 1996 2001 2006 2011 5 year 3month House price index (right axis) We can also compare how mortgages have increased in relation to property wealth since the 1970s. Figure 7 Source: Macrobond shows current prices and property wealth, which is The figure shows the 3-month and 5-year mortgage interest rates defined as the number of houses multiplied by their expressed as an annual average from the major building societies and market value. Over time, the loan-to-value ratio becomes banks. Interest rates have fallen, making it cheaper to borrow money, increasingly higher, as mortgages rise more than the while at the same time, house prices have risen. housing stock. The interest rate is of major importance in terms of Figure 7. Development of property wealth and lending. Sweden appears to be no exception. While the mortgages, current prices interest rate has been falling, the mortgage loan stock has grown. 8 000 7 000 Increasing house prices are self-perpetuating 6 000 If individuals and households make the decision to buy a 5 000 house based on the expectation that prices will continue 4 000 to rise, price increases become self-perpetuating. A 3 000 distinction is often made in economic literature between

Index1970=100 2 000 rational and adaptive expectations. A household with 1 000 rational expectations bases its forecasts for the future on 18 0 all the information available to it at the time . Individuals with back-ward looking expectations, or adaptive 1971 1976 1981 1986 1991 1996 2001 2006 2011 expectations, on the other hand, develop their forecast for Property wealth Mortgages the future only by observing the trend to date. Expectations based on past performance can lead to bubbles. House Source: Statistics Sweden, Macrobond and own calculations price bubbles grow and thrive when property buyers buy In the diagram, we can see that the aggregate loan-to-value ratio is increasing. Mortgages are increasing considerably faster than wealth in residential property that is already overvalued because the housing stock.

Since the 1980s, mortgage interest rates have experienced a downward trend. At the same time, the banks have 18 Fama was one of the first to define efficient markets. An efficient market where everyone acts rationally is defined as a market “in which prices always become more generous with their lending and in terms of fully reflect available information”. Fama, E. (1970), “Efficient Capital Markets: A Review of Theory and Empirical Work”, Journal of Finance, vol. 25 pp. 383-417. Market Report February 2013 11

they expect prices to continue to rise in the future19. We Which variables can explain regional house can refer to this as speculation. Speculation does not price trends? necessarily take the form seen in the USA or in Spain In order to determine which variables explain the trend in during the early years of this century, when households real house prices in the various counties of Sweden since bought two residential properties – one to live in and one 1996, we are using a dynamic panel regression model (see as an investment. The increased use of phrases such as appendix). Using this model, we calculate the relationship property development and “property ladder” reflects between the trend in real house prices and the trend in people’s attitude towards the housing market. They the following factors: expect that prices will continue to rise and that they will be able to make money by investing in property. If they • Real employment income per capita. invest using borrowed funds, which they never actually • Number of inhabitants and age structure. intend to repay but instead expect that prices will rise, • Supply of dwellings. thus reducing the loan relative to the value of the • User cost (mortgage interest rate, interest cost property, this results in an unhealthy housing market. deduction, effective property tax, operating and maintenance costs, risk premium and inflation Whether or not people with back-ward looking expectations24). expectations are rational is debatable. Since house prices • Real financial wealth per capita25. run in long cycles it may be, as Englund says, rational to • House prices lagged 1 year (here expressed as a self- expect that a price rise will be followed by further price perpetuating effect, which takes into account the fact rises, since this is the easiest and best information the that households have backward-looking agent has20. From a historical perspective, house prices expectations). have normally risen or fallen over long periods21. A study of the trend over the last 16 years is sufficient to support In addition to the above variables, we control for the this statement. On the other hand, 16 years is not a effect of the mortgage ceiling introduced during autumn particularly long period of time and one could believe 2011, as well as for the abolition of the property tax and that those active on the market behave irrationally after the introduction of the property duty in 2008, and also all. Chow (1989) demonstrated that econometric models the property tax reduction from 1.5 to 1 per cent in 2001. for the stock market work better if one assumes that those active in the market have back-ward looking The results are shown in table 3. It illustrates how much expectations22. A new study which analyses the housing real house prices rose by between 1996 and 2011 in market in the USA also shows that models with per cent, as well as what proportion of the price increase completely rational households find it difficult to explain can be explained by the different variables. In Stockholm the perpetually recurring fluctuations on the housing county, for example, real house prices rose by market23. If, on the other hand, some households have 162 per cent between 1996 and 2011. The increase in back-ward looking expectations and base their decisions incomes over the same period can account for 46 per cent on the most recent house price trend, this provides a of the price increase, while the increase in the population/ better explanation for price fluctuations. We have dwelling ratio had less of an impact on the price therefore chosen to include yesterday’s prices as an (21 per cent). When assessing the effect of the explanatory variable in the model below. population/dwelling ratio on the price trend, we must also take into account the age structure and examine how many people are over the age of 19 and can therefore be 19 Himmelberg, C., C. Mayer and T. Sinai (2005), “Assessing High House Prices: Bubbles, Fundamentals, and Misperceptions”, Federal Reserve Bank of New York expected to require their own place to live. Staff Reports, No. 218. 20 Englund op. cit. We can also see similar results in the county of Skåne. 21 See for example BKN’s Market report “Housing choices” of May 2012 or P. Bracke, op. cit. 22 Chow, G.C. (1989), “Rational versus adaptive expectations in present value 24 See BKN (2008), “Bostaden – en riskfylld tillgång”, [Property – a risky asset], models”, The Review of Economics and Statistics, Vol. 71, No.3. Market report, December 2008, for further details. This shows that the interest 23 Gelain, P., K.J. Lansing and C. Mendicino (2012), “House Prices, Credit rate is the variable which has the greatest influence on the user cost. Growth, and Excess Volatility: Implications for Monetary and Macroprudential 25 Since financial wealth statistics are unavailable at county level, these have Policy”, Federal Reserve Bank of San Francisco Working Paper, No. 2012-11. been estimated; see appendix for description. 12 Market Report February 2013

Table 3, Contribution of different variables to the increase in house prices between 1996 and 2011

County House In- Popula- User Finan- 2 011 Got- Jämt- Skåne Self- Un- price come tion/de- cost cial effect land land effect perpu- explained increase effect welling wealth effect effect tating since ratio effect 1996 and ( %) demo- graphy Stockholm 162 0.46 0.21 0.10 0.03 -0.016 0.30 -0.08 Uppsala 138 0.57 -0.02 0.10 0.03 -0.017 0.31 0.02 Södermanland 109 0,55 0.05 0,12 0.04 -0.021 0.32 -0.05 Östergötland 124 0.54 -0.06 0.11 0.04 -0.019 0.30 0.09 Jönköping 116 0.61 0.00 0.11 0.04 -0.019 0.30 -0.02 Kronoberg 98 0.66 -0.12 0.12 0,04 -0.021 0.29 0.04 Kalmar 88 0,75 -0.19 0.12 0,04 -0.022 0,29 0.00 Gotland 152 0,58 -0.15 0,09 0.03 -0,015 0.13 0,31 0.02 Blekinge 91 0,65 -0.04 0,13 0.04 -0.023 0,30 -0.05 Skåne 163 0.42 0.12 0.09 0.03 -0.016 -0.03 0.33 0,04 Halland 158 0.56 0.02 0.09 0.03 -0.015 0.30 0.01 Västra Götaland 146 0.52 0.05 0.10 0.03 -0.017 0.30 0.02 Värmland 85 0.59 -0.09 0,13 0.04 -0.025 0.32 0.02 Örebro 90 0.61 0.04 0.13 0.04 -0.023 0.31 -0.11 Västmanland 106 0.53 0.01 0.12 0.04 -0.021 0.32 0.00 Dalarna 83 0.68 -0.19 0.13 0.05 -0.024 0.28 0.08 Gävleborg 83 0.66 -0.07 0.13 0.05 -0.025 0.31 -0.05 Västernorrland 60 0.81 -0.09 0.16 0.06 -0.030 0.33 -0.24 Jämtland 87 0.67 -0.22 0.12 0.04 -0.023 0.15 0.31 -0.05 Västerbotten 71 0.79 -0.17 0.14 0.05 -0.026 0.32 -0.11 Norrbotten 63 0.82 -0.22 0.16 0.06 -0.029 0.27 -0.06

For further details about the model, see the appendix. Please note that the figures in the columns add up to one, which means that they represent the proportion of the price increase accounted for by the various factors. To determine the exact proportion of the price increase accounted for by the different variables in the various counties as a percentage, the figures must be multiplied by the price increase. For example, to find out what proportion of the price increase in Gotland is the specific Gotland effect, the calculation is as follows: 152*0.13≈20, i.e. the Gotland effect represents 20 percentage points of the 152 per cent price increase in Gotland. The analysis below refers the shares expressed in per cent in order to be able to compare the counties with each other.

Source: Own calculations Market Report February 2013 13

As expected, the increase in incomes accounts for a large effect”, which measures effects which may arise from proportion of the price increase in all counties. The households buying property in Gotland which they do weakest effect, however, is to be found in the counties of not use as their permanent residence. The estimates show Stockholm and Skåne. Here, rising incomes have had a that this effect is statistically significant and positive, positive impact on prices and have helped to increase which means that 13 per cent of the house price rise in prices by 46 and 42 per cent respectively of the total price Gotland can be attributed to households registered increase during the period. Compared with the other elsewhere buying property in Gotland. counties, the increase in incomes accounts for a smaller proportion of the price increase in Skåne and Stockholm. There has been a similar significant phenomenon in the Incomes were of the greatest significance in counties counties of Jämtland and Skåne. In Jämtland, this may be which did not have such strong house price increases and because households buy property in Åre and other ski which are located in Norrland. resorts, and also because of its proximity to Norway. This increases demand and drives up house prices by Overall we find that incomes have a positive effect on 15 per cent of the total rise in house prices in Jämtland. house prices across the country. The coefficient for the The county of Jämtland has experienced the strongest income variable is estimated at 1.48, which means that increase in prices among the counties of Norrland. the elasticity is greater than 1 and that if incomes increase by 1 per cent, prices will increase by 1.48 per cent (see It could be assumed that there would be a similar effect in table 5 in the appendix). This supports the assertion and Skåne. During the first decade of this century, many Danes calculations of the IMF, the OECD and the Riksbank that chose to move to Skåne, as the new bridge made increased incomes have had an impact on house prices of commuting to Copenhagen easier and the level of house more than 1:1 in Sweden in recent years26. prices were lower in Malmö than in Copenhagen. However, as we demonstrated above, Danish house prices The increasing population/dwelling ratio and changed age have fallen by 28 per cent since 2007, reaching 2003 structure can account for 21 per cent of the price increase levels. Skåne has been affected by this crash and during in Stockholm and 12 per cent in Skåne. These calculations 2011, house prices fell in 76 per cent of Skåne’s have been made at county level and it is likely that there municipalities, which compares with 49 per cent of the will be a wide variation within the counties. The effect of municipalities in the rest of the country. population/dwelling ratio on house prices is probably the strongest in the municipalities with major cities and Figure 9. "Denmark effect" weaker in the outlying municipalities. In most counties, 15 the demographic variable has a negative impact on the house price trend. And in some counties, e.g. Jönköping, it has no effect on house prices. 10

The user cost, where short-term 3-month mortgage 5 interest rate tend to dominate, has had a positive effect on house prices in all counties. In the user cost, we have 0 taken into account the conversion of the property tax into

a duty and the fact that mortgaged households are able to percentage points make a deduction for their interest costs. In Västernorrland -5 and Norrbotten, where house prices have risen the least, the falling user cost has had the greatest impact on house -10 2001 2003 2005 2007 2009 2011 prices. In the counties with major cities and their neighbouring counties, as well as in Gotland, the user cost Source: Own calculations has had the least impact on house prices. In Gotland, it The figure shows that house prices in Skåne were positively affected by has long been popular to buy a house that can be used as the proximity to Denmark up to mid-2007. After 2007, this effect lessened a holiday home. We have therefore added a “Gotland and it is now negative.

26 Englund (2011), Girouard et. al. (2006) and Iossifov et. al. (2008) op. cit. 14 Market Report February 2013

The trend for the “Denmark effect” on Skåne is illustrated The self-perpetuating effect has a further positive effect above. Until 2007, it contributed to rising house prices in on house prices, as it enables households to borrow even Skåne by more than 13 percentage points. However, once larger amounts. If the market value is high, the loan is house prices began to fall in Denmark, this effect began to large. If the market value of the property then rises, the decline and in 2011, the accumulated effect was minus household is often able to increase its loan-to-value ratio 5 percentage points. There are indications that house in order to buy a new kitchen or car. The introduction of prices are about to plateau in Denmark, which supports the “ROT” refurbishment deduction has probably the hypothesis that the Denmark effect is played out, at encouraged people to renovate and take out further loans least for now. Figure 9 shows the trend for the whole of on their property. In October, we showed that older Skåne county and it is likely that the effect was greater in people are taking out large loans and the statistics of the municipalities closest to the Öresund Bridge and Sweden’s credit information agency (UC) also indicate Helsingborg. that the debt ratio is increasing among older people. The reason for this is subject to speculation, but one possible In order to control for the effect of the mortgage ceiling, reason is that parents are helping their children to buy a which was introduced in autumn 2010, we include a house by increasing borrowing against their own house. dummy variable for 2011. The 2011 effect is negative, In this manner, the loan-to-value ratio rises in the albeit weak, and covers everything that happened in 2011 economy and the leverage increases. that is not already covered by the other variables. We must therefore exercise caution before attributing the whole of Unfortunately, statistics on the prices of tenant-owned this effect to the mortgage ceiling. In the county of properties are only available from 2000, and the model Stockholm, for example, we estimate that the 2011 effect does not produce statistically significant results. We had a negative impact on the real house price trend of nevertheless assume, supported by table 2 and efforts to 1.6 per cent of the total rise in house prices. estimate using the model, that the self-perpetuating effect is even greater and has more of an impact on tenant- Like the Riksbank27, we find that the increase in financial owned property price trends than on house prices. wealth has had a small but significant effect on house prices. It explains 3 to 6 per cent of the increase in prices across the counties. As previously mentioned, we have been obliged to approximate the financial wealth, since wealth statistics are not available at county level.

The self-perpetuating effect accounts for a large proportion of the price increase in all counties. It also supports the idea that Swedish households have backward-looking and that price increases lead to future price increases. As we stated in the introduction, the self- perpetuating effect can also involve an element of speculation. Swedes only repay their mortgages to a very slight extent, around 1.2-1.3 per cent of the mortgage loan stock per annum which indicates an expectation that the price of the property will either increase or remain the same, resulting in the feeling that repaying the mortgage is unnecessary.

27 C.A. Claussen, M. Jonsson and B. Lagerwall (2011), “A macroeconomic analysis of house prices in Sweden”, The Riksbank’s inquiry into the risks in the Swedish housing market. Market Report February 2013 15

Conclusions Overall, the fundamental factors account for approximately 2/3 of the increase in house prices over the Increased incomes are the primary reason why house last 15 years. The remaining 1/3 can be attributed to the prices have increased since 1996. Increased incomes lead self-perpetuating effect, which represents the actors’ to an increased willingness to consume larger and better backward-looking expectations and the way the mortgage residential properties and create a housing shortage if market operates in Sweden. It could be said that the everything else remains constant. Combined with a rising Swedish house price trend results in increased debt ratios, population/dwelling ratio, this causes an even greater as larger loans are permitted as the market value of demand for residential property, however, the population/ residential properties increases. In countries where dwelling ratio is only rising in the counties with major lenders do not use the current market value of the cities. In the other counties, the correlation between the property as a measure of the size of the security for the population and the supply of houses appears to be in mortgage and which are more restrictive with regard to balance or even negative. In 13 counties, house prices the withdrawal of equity, house prices and the debt ratio have been negatively affected by decreasing population/ have not risen as rapidly as in Sweden. There are therefore dwelling ratio. factors on the Swedish mortgage market that cause debts to rise and support further price increases on the housing In these counties, increases in income are an important market. reason for the price rises. In Norrbotten and Västernorrland, more than 80 per cent of the price increase is accounted If property prices were to fall, there is the risk that the for by increased incomes. In the counties of Skåne and price fall will be greater as a result of the backward- Stockholm, the contribution of increased incomes to looking expectations which also prevail when prices are rising house prices was less than 50 per cent. We therefore falling. This means that if prices fall today, they are come to the conclusion that housing shortages in terms of expected to fall again tomorrow. House buyers therefore increasing incomes and population/dwelling ratio can want to pay as little as possible because they believe the account for more than half of the total increase in house risk of losing money to be great, while at the same time prices between 1996 and 2011. the banks’ securities reduce in value. In other words, lending is strangled. We are able to determine that Falling user cost, a result of decreasing mortgage interest backward-looking expectations and a high level of rates, has had a positive effect on house price trends in all borrowing have strong pro-cyclical effects on the housing counties, with the effect being roughly the same. Increased market. financial wealth also has a positive effect on prices, but this effect is small. As a result of insufficient observations of tenant-owned apartment prices, we have been unable to perform the same econometric calculations as for single-family house prices. Nevertheless, we are able to confirm that the prices of tenant-owned properties have increased considerably more than single-family houses over the last 11 years and the fundamental variables in table 2 are unable to account for or keep pace with the tenant-owned apartment price trend. 16 Market Report February 2013

Appendix Table 4: Description of variables and their abbreviations in the above equation In order to determine what drives regional house prices and what proportion of the price increases can be HP Real house prices. attributed to different variables, we have used a dynamic it panel regression model. We use this to model the annual INKit Real employment income per capita. change in real house prices for each individual county as a Employment income primarily compri- function of the annual changes in incomes, household ses salaries, as well as unemployment size, the size of the adult population, financial wealth, benefit, sickness benefit, parental pay and pensions. user cost and the change in real house prices in the UC User cost, lagged by one period, calcula- previous year. The statistics come from Statistics Sweden it-1 and include annual data for all the counties of Sweden ted accordingly: 3-month mortgage rate after tax – efficient property tax/duty + 4 – between 1993 and 2011. The equation used is as follows: expected inflation from Prospera.

BOTÄT The number of people per dwellin, lag- + it it 1 it 2 it-1 3 it 4 it ged by one year, as the supply of housing 5 it 6 7 ∆HP =β *∆INK +β *∆UC +β *∆BOTÄT +β *∆POP20 is reported at the end of the year and 8 9 in order to avoid problems of reverse β *∆NF +β *SKÅNEPOST2000+β *SKÅNEPOST2007+ 11 it-1 it causality. β *JÄMTLANDPOST2000+β *GOTLAND+β10*ÅR2011+ POP20 The size of the population over 19 years. Theβ *∆HP model+ εis dynamic, as it includes a lag for the it NF Real financial wealth per capita. Since dependent variable as an explanatory variable. In order to it calculate the parameter estimate, we have used the wealth statistics at county level are 28 unavailable, this has been approximated Andersson-Hsiao method . There are several methods to on the basis of Sweden’s total financial choose from for dynamic panel data estimations, but wealth, where we have assumed that many of them are best suited to microeconomic panels, each county’s share of the total financial where the number of individuals included is significantly wealth for any given year is the same as greater than the number of time periods. In our case, the each county’s share of the country’s total number of individuals (21 counties) almost the same as employment income for that year. the number of time periods (19 years). A simulation study SKÅNE- Dummy variable for Skåne 2001-2011. which compared various methods found that the POST2000 Andersson-Hsiao method provides the least erroneous SKÅNE- Dummy variable for Skåne 2008-2011. parameter estimates when the number of individuals is POST2007 29 similar to the number of counties (=20) . We therefore JÄMTLAND- Dummy variable for Jämtland county chose the Andersson-Hsiao method. POST2000 2008-2011. GOTLAND Dummy variable for the year 2011. ÅR2011 Dummy variable for Gotland.

HPit-1 House prices the previous year.

28 Andersson T.W. and C. Hsiao (1981) “Estimation of Dynamic Models with Error Components”, Journal of the American Statistical Association, Vol. 76, No. 375, page 598-608. 29 Judson, R.A. and A.L. Owen (1999) “Estimating Dynamic Panel Data Mo- dels: A practical guide for macroeconomists”, Economic Letters, Vol. 65, No.1. Market Report February 2013 17

The real prices have been deflated using the CPIF and The parameters have been estimated using GLS, which logarithms have been calculated for all variables other corrects for autocorrelation and heteroscedasticity. Where than dummy variables. i represents the county and t the there is spatial autocorrelation, we rectify this, at least year. ∆ represents the difference. If i=Stockholm and partially, by including the following variables in the t=2005, ∆HPit then represents the change in the regression: time dummy for 2011, user cost and logarithm house prices in the county of Stockholm population (the population in the county rises or falls between 2004 and 2005. it is the difference between the partly as a result of migration). The method has been used actual house price change and the house price change to estimate without constant or fixed effects for each estimated by the model, i.e.ε the proportion of the house county, as these theoretically disappear when variables are price change each year which the model is unable to transformed to level form for the first difference. However, explain. we have included fixed effects for Skåne, Gotland and Jämtland, as we found this to be justifiable, taking into

1 11 account their particular characteristics. A Jarque-Bera test cannot rule out the normal distribution of the residuals β – β are the parameters to be estimated. These show and the t statistics and the estimated P values are can the relationship between the real house prices and the therefore be applied. variables included in the model. Since logarithms have been calculated for all variables, other than the dummy 1 variables, the parameters can be roughly interpreted as elasticities. For example, if β = 0.5, this should be interpreted as meaning that a 1 per cent increase in incomes results in a change in real house prices of 0,5Table per 5: cent Regression during the results same year.from the estimates of the equation Variable Standard t-stat P-value ( 1 11) deviation β – β ∆INKit 1.48 0.07 20.07 0.00

∆UCit-1 -0.10 0.00 -27.42 0.00

∆BOTÄTit 2.95 0.09 34.48 0.00

∆POP20it 0.38 0.06 6.43 0.00

∆NFit 0.05 0.01 7.64 0.00 SKÅNE- 0.012 0.01 2.46 0.01 POST2000 SKÅNE- -0.043 0.01 -4.60 0.00 POST2007 JÄMTLAND- 0.01 0.00 10.22 0.00 POST2000 GOTLAND 0.0098 0.00 13.61 0.00 ÅR2011 -0.02 0.00 -8.92 0.00

∆HPit-1 0.31 0.02 13.77 0.00 Weighted 0.974 and adjusted R2 Unweighted 0.55 R2 No. of obser- 399 vations

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