National Bank of Poland - Narodowy Bank Polski ... Report has been prepared at the Economic...

National Bank of Poland

Economic Institute in collaboration with Regional Branches

Report on the Polish residential market in 2002-2009

Warszawa, May 2010

The Report has been prepared at the Economic Institute in collaboration with Regional

Branches for the purposes of NBP bodies and presents the opinions of the authors. The document should not be understood as an advisory material or a basis for investment decisions.

English version of the report is the shortened translation of the Polish original.

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Authors: Part I Augustyniak Hanna Economic Institute Łaszek Jacek Economic Institute Widłak Marta Economic Institute Part II Baldowska GraŜyna Regional Branch in Warszawa Barska Ewa Regional Branch in Bydgoszcz Białach Ewa Regional Branch in Lublin Borzym Henryk Regional Branch in Olsztyn Ceglacka Izabela Regional Branch in Zielona Góra Czapka Izabela Regional Branch in Katowice Czechowski Tomasz Regional Branch in Zielona Góra Czekała Magdalena Regional Branch in Wrocław Dmitrowicz Katarzyna Regional Branch in Szczecin Gałaszewska Krystyna Regional Branch in Gdańsk Jung Katarzyna Regional Branch in Wrocław Kiernicki Jarosław Regional Branch in Bydgoszcz KsiąŜczyk Jolanta Regional Branch in Łódź Leszczyński Robert Regional Branch in Białystok Leśniewicz Artur Regional Branch in Poznań Mach Barbara Regional Branch in Rzeszów Mach Łukasz Regional Branch in Opole Markowska Janina Regional Branch in Wrocław Messyasz-Handschke Arleta Regional Branch in Poznań Mikołajczyk Łukasz Regional Branch in Opole Misztalski Maciej Regional Branch in Wrocław Myszkowska Barbara Regional Branch in Warszawa Opioła Zbigniew Regional Branch in Katowice Orliński Sławomir Regional Branch in Kielce Osikowicz GraŜyna Regional Branch in Kraków Owczarek Ewa Regional Branch in Szczecin Perczak Jacek Regional Branch in Kielce Piwnicka Małgorzata Regional Branch in Poznań Soboń Janusz Regional Branch in Rzeszów Szmit Marian Regional Branch in Poznań Tomska-Iwanow Anna Regional Branch in Szczecin Tyszkiewicz Robert Regional Branch in Łódź ZadroŜna Iwona Regional Branch in Gdańsk

Approved by: Jakubik Jarosław Economic Institute Pawłowska Małgorzata Economic Institute

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Table of contents

Part I – Housing market in Poland......................................................................................... 3

Summary........................................................................................................................... 3

Introduction ...................................................................................................................... 6

Chapter 1. Proportions of the housing sector in Poland ................................................... 8

Chapter 2. Inflation in the housing market ..................................................................... 12

Chapter 3. Supply inflation............................................................................................. 17

Chapter 4. Other measures of inflation in the housing market ....................................... 19

Chapter 5. Tensions and adjustments in the housing market ......................................... 22

Chapter 6. Housing needs and availability ..................................................................... 26

Chapter 7. Demand, supply and market balance ............................................................ 33

Chapter 8. Regulations ................................................................................................... 42

Glossary of terms and acronyms .................................................................................... 44

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Part I – Housing market in Poland Summary

The Report presents the results of studies based on data collected by the National Bank of Poland and those provided by other entities. Their analysis leads to the following conclusions: • In the last twenty years the Polish housing sector has gone through three turning points,

two of which in the 1990s and one in the current decade. The first one was connected with the restructuring of the construction sector and the structure of investors; it ended up in the collapse of huge construction conglomerates. The second was associated with the change in the financing system; an abrupt withdrawal of the state from funding construction, amid a lack of a market system of crediting, led to a sudden breakdown in its level. The third transformation was connected with the privatisation of the municipal and, to a large extent, also cooperative housing stock. Even though the privatisation was conducted in an imperfect way, it laid the foundations for a market and the huge wealth transfer to households was a factor alleviating the effects of transformation. This process is being continued, though at a considerably smaller scale. In the second half of the present decade we can observe the continuation of the second turning point, i.e. a fast development of a market system of the sector’s financing, which is associated with a change in the consciousness both on the part of consumers and the banking sector. The availability of bank credit has become the main factor of housing demand growth, which contributed to meet the housing needs. On the other hand, the higher number of granted loans increased the role of this factor for the banking sector’s stability.

• Continuing transformation of the housing sector in Poland resulted in the appearance of cycles. The first cycle in the 1990s was to a large extent connected with the political transformation. The second cycle arose at the turn of the millennia and was already classically market-related. It resulted from a delayed demand response. We are currently dealing with a phase of the third cycle, which is a classical market cycle connected with the involvement of the banking sector. Analysis of these historical experiences and mechanisms observed at the Polish market suggest that cyclicality is rather unavoidable. The challenge, however, is to ensure that cycles do not turn into crises and stays relatively benign and unsynchronised with cycles in major markets. The prevention of such situation requires sectoral monitoring and appropriate counter-cyclical policies, such as counter-cyclical economic situation stabilisers – for example a valuation system that would restrict financing of housing with rapidly growing prices or systems of subsidising loans that would expire amid low levels of interest rate and high prices of housing. The currently applied instruments, including the “Rodzina na swoim” government subsidy programme, are procyclical and, on top of that, also prove financially ineffective. Another universal tool limiting the sector’s cyclicality can be a more active fiscal and pro-supply policy stimulating the competition among developer companies, making the supply more flexible and, consequently, curbing excessive price fluctuations and speculation.

• As the residential property sector is strongly affected by monetary policy, supervisory and fiscal policies, their coordination is necessary at crucial moments. The experience of international crises shows that this is difficult, among others, due to contradictory interests even within the public sphere. The Polish housing market avoided any greater problems thanks to the earlier breakdown in the US real estate market, which limited credit expansion and cooled down speculative expectations. By and large, it seems that in the medium term both the economic outlook for Poland and the perspectives of the sector’s

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development are relatively bright, which, however, does preclude the possibility that the problem of cycles and the threat of real estate crisis can come back in the longer term.

• The analysis of prices in the real estate markets in Poland demonstrates that at the current moment there is no universal method of constructing a price index. Therefore, it is necessary to monitor a bunch of indices. Such approach illustrates price tendencies from the perspective of economic policy and market entities sufficiently well for the assessment of the scale of the market’s risk. It also provides basis for the construction of a number of prudential measures to monitor sector threats. However, the risk connected with real estate valuation and, consequently, with the determination of the value of credit portfolio collateral proves to be significantly higher than commonly believed.

• The inclusion of housing prices in the inflation index would lead to significant fluctuations of this index. Additionally, the inclusion methods raise serious reservations, similarly as the validity of the whole idea. It is not clear who and by means of what instruments would control residential property prices, as the central bank’s toolkit does not seem sufficient for this purpose.

• Both theoretical and data-based analysis reveals that in the current conditions housing loans in Poland will be more available for the richer part of the society. On the other hand, the availability of loans for the wider public may be increased by a programme supporting the purchase of first flat, such as “Rodzina na swoim”. However, there arises the question of the first four deciles of households. Beyond any doubt, the problems of the first 20% of households should be met with the social housing stock. The function of the social housing stock should be performed by the still substantial municipal stock (which usually serves this function in developed economies). However, strong tenant protection safeguarded in the Polish law in combination with low rents means that this stock is used for social purposes to a limited extent. For this reason, it seems necessary to build strictly social stock for the least affluent as a supplement for the system of housing benefits. Alternatively, gminas (municipalities) could sign tenancy agreements with private individuals and rent such flats to them. The second necessary element of the housing programme is building flats of a modest standard for the remaining 20-30% of households seeking accommodation. In EU countries there are many examples of such construction, which is generally market-financed with state support and has flexible ownership forms (rental, joint or full ownership title). In Poland this need was to be addressed by Low-Cost Building Societies, but this programme has failed to play a significant social role while generating considerable costs for the central budget at the same time.

• The analysis of the structure of the Polish housing sector clearly shows that the market lacks private, fully commercial housing for rent. The share of this market is usually less than 10% of the urban stock and its primary function is not social assistance, but more a flexible housing market from the perspective of the labour market. In Poland the only barrier to the existence of this market is the overly restrictive law on tenant protection. It seems, however, that the increasing competition in the global economy and within the EU, which is based on the flows of the factors of production will be exerting growing pressure on this problem to be solved also in Poland.

• Overregulation of the question of tenant protection can be juxtaposed with no protection whatsoever of the person buying housing built by a developer, even though it involves risk. In this cycle Poland has been spared major problems connected with excessive risk incurred by developers, but the problem may return in the future.

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• Experience of the financial crisis has shown once again that there are no shortcuts as regards the risk in mortgage banking. The crisis has also shown the importance of the problem of liquidity in this market. In Poland, Recommendation S was introduced even before the crisis and Recommendation T – its elaboration and specification – in 2010. However, the effects of the undertaken activities solve the basic problems of the sector only to a certain extent. Therefore, it seems important to take further action for the diversification of the sources for funding bank lending.

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Introduction

The real estate sector is of considerable importance both as the employer and service provider and as the factor which destabilises the economy, especially the financial system as a result of the business cycles affecting this sector and recurring real estate crises. Of particular importance are residential real estates which usually account for the largest part of this sector, and additionally have a considerable social impact.

Business cycles affecting this market are the result of rapid changes in demand and rigid short-term supply combined with the lack of transparency of the market. As evidenced in the history of economy, including the most recent history, there are many risk factors which, when cumulated and occurring on a large scale, lead to domestic, regional or even global crises as well as smaller, local-scale problems. Both the market and the economic policy understood as fiscal, monetary and supervision policy may be responsible for such problems.

There are at least two reasons why analyses of the residential real estate sector are important for a central bank:

• Interest rates which are the basic tool of a central bank have a strong impact on the real estate prices which become an important factor influencing the economic situation in the real estate market and business cycles.

• The real estate sector is usually strongly related with the financial sector and excessively strong tensions in this sector may be a risk factor for the financial sector stability.

As regards the Polish housing real estate sector, its faster growth has been observed only since the second half of this decade. Nevertheless, this sector is marked by a whole range of disproportions and barriers likely to limit its growth, and, in the longer run, bring about problems. One of the most important issues is insufficient transparency of the market resulting from lack of information. This makes economic agents operating in this sector take wrong decisions.

The Report is aimed to provide the concerned economic entities, including real estate market participants, with, as complete, reliable and objective information as possible concerning the situation in the housing real estate market in Poland in the years 2002-2009.

The Report largely focuses on the most recent processes, i.e. those unwinding after 2005

and having a direct impact on the developments in 2010; yet, whenever it was possible and justified, the authors went back to the beginning of the decade (for example, data concerning the housing stock come from the 2002 National Housing Census, while more recent data are estimates only). As there are plans to prepare synthetic quarterly data, while discussing the current trends in the housing markets and their annual summaries, the presented Report is an “opening report” which justifies its partly historical character. The authors intend to present more detailed structural analyses in the subsequent issues of the annual report.

Due to the local character of housing markets, the analysis focuses on sixteen voivodeship markets, including, in particular, the markets of Poland’s six largest cities (Warszawa, Kraków, Wrocław, Łódź, Poznań and Gdańsk together with Gdynia).

The Report consists of two parts. The first part presents certain processes common for the real estate market in Poland. The second and more analytical one contains attachments providing detailed data on the sixteen markets in capital cities of voivodeships.

The Report was based on the data derived from various sources. The main source of information about housing prices and structure were data taken from the Real Estate Market

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Database (BaRN) created by the NBP. The BaRN database was established thanks to voluntary provision of data by real estate agents and developers with considerable involvement of Regional Branches of the NBP. The analysis and studies also made use of databases prepared and kept by PONT Info Nieruchomości containing data on asking price of housing, being part of the Polish Bank Association’s SARFIN database containing data on housing market financing and AMRON database containing data on housing appraisal and transaction prices of housing financed with housing loans, as well as collective credit data of BIK. The available statistical data of Central Statistical Office (GUS) and numerous analyses and sector data kept by specialised companies1 were used in the structural analysis. The authors also relied upon the results of the annual household surveys conducted in six cities by the NBP from the point of view of households’ plans, preferences and expectations connected with this market.

Although many sources of information were used, missing data or insufficient quality of data were a significant barrier. In such situations, the authors relied upon estimates verified on the basis of experts and specialists’ opinions. While drawing up the Report the authors adopted the assumption that even estimates, verified in several sources, provide better information than general opinions.

The Report focuses mainly on general trends and conclusions resulting from analyses, while detailed statistical information is presented in figures and tables.

The layout of the Report, especially its division into chapters and subchapters was dictated by the aim of the Report, namely the analysis of the housing market from the central bank’s perspective, as goods prices and inflation are of particular importance from the monetary policy perspectives, similarly to the channels through which the housing sector affects the economy.

1 This concerns in particular Sekocenbud surveys concerning the structure and construction costs, surveys conducted by the REAS concerning the real estate development market, by PABB concerning the construction sector and many other entities and associations operating in the same market. The most important ones include the Polish Bank Association (ZBP), PSBD, SPPB and many others.

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Chapter 1. Proportions of the housing sector in Poland

In all developed countries the real estate sector, in particular the residential real estate sector, is of considerable social and economic importance.2 This is reflected in the sector’s main indicators presenting it against the background of micro (entities and markets), mezzo (business areas, regions) and macroeconomic values (the economy and its basic aggregates). The largely domestic character of the housing sector causes differences in the basic indicators across countries. This is true also for the housing sector in Poland. The share of investment outlays for residential construction (multi-family housing and single-family housing in urban and rural areas; cf. Figure 1) was in the past decade rather volatile and ranged from 1.4 to 2.4% of GDP. The main driving force behind this volatility was a cyclical character of the largest housing markets that resulted from the general economic conditions. Decline in expenditure in the years 2000-2004 was a consequence of the first business cycle and bad economic situation in these markets. Growth recorded in these markets since 2006 was a delayed response to the credit boom and entry into another business cycle.3 The described aggregate is the sum total of two components whose shares are close to 50% in material terms: the more stable one, i.e. the outlays on single-family housing that is generally owner-built and the more volatile one that, in most cases, means multi-family housing construction by developers. The former is primarily observed in rural areas and in small and medium-sized towns and is mainly sensitive to prices of construction materials, while the latter can be mostly seen in larger cities and is affected by a number of different factors described further in the Report. The discussed indicator, apart from measurement of the outlays aimed to meet the housing needs, shows the scale of the sector’s impact on GDP through the investment channel. It is rather insignificant in Poland as even business cycles in which the declines in construction output in cities will reach as much as 50% will result in GDP adjustment of around 1%, additionally spread over 2 or 3 years period. For the same reason, fluctuations in the housing demand are not devastating for the construction sector, which has the possibility to cushion them through considerably higher, if less profitable, orders from the general construction sector. Another problem caused by a low share of housing investment in Poland, especially as compared with highly developed countries during the housing market boom in the 1950–70s, is the low level of residential construction and a slow progress in the housing situation of the society.

Housing units are capital-absorbing and inter-generational goods, and their stock is accumulated over several dozens of years. As a result, the value of residential fixed assets calculated in market prices usually exceeds the GDP level. In the analysed period, Poland saw a considerable rise in this value. This increase concerned mainly the largest cities which in the second half of the decade saw a credit boom and growth in housing prices (cf. Figures 2-4). As a result, the structure of the housing stock (cf. Figure 5), which is dominated by the countryside and smaller towns, differs considerably from its value structure. At present, the value of the housing stock estimated in market prices exceeds the GDP level two times, and its absolute value in current prices has doubled over the decade. This means that household savings accumulated in housing stock exceed almost two times their annual income, and increase in consumption expenditure over the decade driven by the wealth effect was considerable.4

2 Łaszek J. (2003), Sektor nieruchomości mieszkaniowych w Polsce. Stan i perspektywy rozwoju, SGH, Warszawa. 3 Łaszek J. (2003), ibid. 4 Georgieva M., Fano D., Marzorati L., Sbano T. (2008) Wealth Effect in the New Europe Countries, PGAM Economic Research.

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Another important phenomenon which marked the past decade was a fast growth of the real estate financing sector which was reflected in the growth of housing loans (cf. Figure 6). As a result, their balance reached at the end of 2009 the level exceeding 20% of banking assets and 16% of GDP. This share in the developed European countries and in the USA is at least twice as high, but their financial system was shaped several dozen years ago. As shown by international experience, too rapid development of the financial system usually brings about serious economic problems.5 The consequence of the rising housing debt is the increase of the share of this debt in relation to the market value of the housing stock. This relation continues at a low level which, in theory, allows for the financing with mortgage loans not only of the housing sector but also of other economic activity, in particular, small enterprises. Yet, a more thorough use of this possibility would require enhancing the role of mortgage security.

It is beyond any doubt that despite the current turmoil in the financial markets, the share of housing loans in the assets of the banking sector will continue to grow, and the housing sector will become an important factor affecting the financial sector’s stability, which is reflected in the considerable share of housing debt in banks’ own capital.

Although housing loans have become in Poland in the past decade a popular and relatively common instrument giving the households, especially the younger ones, access to their own housing, yet, the level of economic growth in Poland and the ensuing income level cause that credit is, and will continue to be in the years to come, available at the level likely to solve housing problems mainly of households whose income exceeds the average level.

The results of GUS surveys concerning budgets of households repaying mortgage loans show that they are twice as high as the budgets of households without mortgage loans. Households with lower income will continue to have recourse to family financial support, additional income from work abroad or government subsidy programmes.6

The share of loan repayment in household budgets has reached over the past few years the level of 16-18% of income and shows a slightly upward trend (cf. Figure 7). This interdependence concerns both the largest cities as well as other provincial capitals, while households’ disposable income in the largest cities is considerably higher.

Higher loans result from considerably more expensive housing. While analysing the information from the household surveys concerning expenditure on housing loan (cf. Figures 8 and 9) it should be remembered that these values come from surveys representing the households’ structure all over Poland, and not the structure of households with mortgage loans. As a result, these data may be supposed to fail to provide a full picture of the phenomena connected with the credit boom observed in the past few years. The data on housing loans derived from the household surveys compiled with the SARFIN data7 make us suppose that the actual expenditures of households who took out loans in the years 2006-2008 should be higher than shown by the budget survey findings. On the other hand, like each

5 European Central Bank (2003), Structural Factors in the European Union Housing Markets. 6 Mortgage loan growth is supported, for example, by the “Rodzina na swoim” [Family’s Own Place] government programme, which operates on the basis of a law laying down the rules for subsidising the interest charged on loans granted for the purchase of housing, construction and purchase of a single-family home or making a building contribution to a housing cooperative (Act of 8 September 2006 on the financial support for families in acquiring own housing (Journal of Laws No. 183, Item 1354) amended with the Act of 15 June 2007 (Journal of Laws No. 136, Item 955) and the Act of 21 November 2008 (Journal of Laws No. 223, Item 1465). The preferential loans are granted by institutions thus authorised by law which sign an appropriate agreement with BGK. The “Rodzina na swoim” programme did not attract much interest of borrowers initially. This was partly due to the criteria that the borrower had to meet and the lack of awareness of bank customers that they could benefit from the programme. It was only in 2008, following a change in the conditions for granting the preferential loans, that this situation improved. 7 See Glossary of terms and acronyms.

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indicator based on the general trend, the average of expenditures calculated in the sample fails to take account of their actual diversity, which has taken place in the past few years as implied by empirical observations.

The other group of housing expenditures are broadly understood costs of housing maintenance. This aggregate includes both heating and electricity expenses, as well as costs connected with housing stock management, waste disposal and current repairs and maintenance. This aggregate is internally diversified due to technical reasons and housing stock factors. Similarly to loan servicing costs also households’ housing maintenance expenditures were diversified in the two discussed groups of cities (Figures 9 and 10).

Undisputedly higher expenditures in larger cities corresponded with slightly lower share in budgets which was the result of higher income of inhabitants of the largest cities. Yet, generally speaking despite their increase in absolute values, these expenditures in both of the discussed groups showed a downward trend as regards expenditure share in the budgets which was the result of a higher rise in income and reached in the past few years the level of 17-20%, i.e. very close to the level of expenditure connected with housing loan servicing.

To sum up, it may be concluded that housing expenses of households that purchased their own flats were slightly below 40% of all households’ expenditures in the years 2005-2007, with approximately half of these expenses spent on debt servicing and half on housing maintenance.

Over the past twenty years, Poland has seen a radical change in the perception and financing of housing. There has been a shift from the economy in which housing was strictly rationed, and total expenses connected with housing did not exceed 10% of household budgets (and were considerably lower in many cases), to the reality where the method of meeting housing needs may be freely chosen and the housing expenses account for a considerable share of the household budget.

However, changes in the financing of home purchases in Poland have given rise to quite new problems. Almost 40% share of housing expenses in the average household budget, especially budget of young households, means a high risk of problems in the case of job loss or work incapacity. Assuming the situation which is typical of young couples, where both persons are professionally active, job loss by one of them increases housing expenses to the level of 70-80%, which is bound to cause problems connected with loan repayment. Therefore, it seems necessary to follow the example of other countries and supplement the traditional family support system existing in Poland with an insurance system established with the participation of the government and partly subsidised by it.

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Figure 1. Investment outlays on construction in Poland in % of GDP

1%

3%

5%

7%

9%

11%

13%

2000 2001 2002 2003 2004 2005 2006 2007 2008

construction and assembly output

housing construction output

Figure 2. Housing wealth in Poland in % of GDP

0%

50%

100%

150%

200%

250%

2002 2003 2004 2005 2006 2007 2008

6 cities10 citiesrest of Poland

Source: own analysis based on GUS, NBP.

Figure 3. Housing wealth in Poland (in PLN billion)

0

500

1 000

1 500

2 000

2 500

3 000

2002 2003 2004 2005 2006 2007 2008

in 6 citiesin 10 citiesrest of Poland

Figure 4. Housing stock in Poland (in million square metres)

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2002 2003 2004 2005 2006 2007 2008

6 cities10 citiesrest of Poland


Figure 5. Structure of housing stock in Poland according to ownership

0%

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6 cities 10 cities Poland's cities andtown

Municipalities Cooperatives Private Enterprises TBS Other

Figure 6. Relations of housing loans in Poland

0%

5%

10%

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20%

25%

2002 2003 2004 2005 2006 2007 2008 2009

0%

50%

100%

150%

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250%

300%to bank assetsto GDPto housing wealthto banks' own capitals (RSH)


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Figure 7. Repayment of housing loans vs. disposable income

0%

5%

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15%

20%

2005 2006 2007 20087 cities Cities 200+

Figure 8. Disposable income of households repaying housing loans

0

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2 000

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7 000

2005 2006 2007 2008

PLN

7 cities Cities 200+

Source: own analysis based on GUS.

Figure 9. Housing maintenance spending vs. disposable income

15%

17%

18%

20%

21%

2005 2006 2007 20087 cities Cities 200+

Figure 10. Household spending on housing maintenance

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2005 2006 2007 2008

PLN

7 cities Cities 200+


Chapter 2. Inflation in the housing market

2.1 Prices

The second half of the current decade brought a sharp increase in the prices of housing in Poland. This phenomenon was primarily observed in Poland’s largest cities and its direct cause was the combination of the credit boom, which resulted from the surplus liquidity of international financial markets, and demographic factors. Increased demand, amid short-term rigidity of supply of housing, triggered speculation and expectations for further price growth, which in the seven largest city markets lasted till 2007 Q3. Price tendencies in the markets of other provincial capitals were similar and secondary to the largest city markets, though with considerably lower price levels (cf. Figures 11-18). The price tendencies at the beginning of the decade are assessed based on the PONT database of asking prices. The NBP’s own studies, carried out since mid-2006, and the constructed BaRN database of asking and transaction prices extended the scope of analysis. Among others, data collected in the BaRN database reveal that asking prices seem to be a good indicator of real price tendencies (even though differences can be observed between the levels of asking and transaction prices, both

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series display the same trend (cf. Figures 43 and 44)). Though the primary market is commonly believed to have been a price-rising factor, this varied across markets and periods (cf. Figures 45 and 46).

In the analysed period (form the end of 2002 till the end of 2009), the highest year-on-year growth rates of average asking prices were recorded in 2007 Q1 and Q2, i.e. 87% in the primary markets of ten cities8 and 67% in the group of the seven largest cities, and in the secondary markets the values of 70% and 92%, respectively. Transaction prices, available since mid-2006, display a similar trend as asking prices, though the differences in the level between these two groups of prices also result in different values of price dynamics indices (cf. Figures 11-18). Owing to the heterogeneity of housing and the difficulty in the selection of samples that would be representative for the market in all quarters, the popular housing inflation measure based on average price dynamics is biased due to differences in the quality of examined goods.9 For this reason, in the present Report we also make use of two indices that, at least to some extent, are quality-adjusted. These indices, i.e. the hedonic index and the weighted average index10, illustrate the course of transaction price growth in the secondary markets of the largest cities. The hedonic index for the seven largest cities showed an increase in housing transaction prices by 61% y/y in 2008 Q3, and by 46% in the group of the remaining ten provincial capitals. Analogically, simple average price dynamics amounted to 52% and 60%, respectively. As can be seen, these are significant differences and suggest that the adjustment for quality seems to be an important factor in choosing the appropriate housing price dynamics index (cf. Figures 19 and 20).

The comparison of the level of average price and average price adjusted for quality differences (cf. Figures 21 and 22) indicate that in the period of sharp price growth the contribution of factors connected with the changes in the quality of analysed housing was less significant than in the period of their relative stabilisation and decline.

Housing price levels and their dynamics highly varied across particular city markets. The factors responsible for this differentiation are discussed further in the Report. Figures 23 – 28 show quarter-on-quarter transaction price change for the secondary markets of the main cities. This price dynamics is illustrated with quality-adjusted housing price indices (the hedonic index and the weighted average index).

8 See Glossary of terms and acronyms. 9 For a more detailed account, see Łaszek, J. and Widłak, M. (2008) “Badanie cen na rynku mieszkań prywatnych zamieszkałych przez właciciela z perspektywy banku centralnego”, Bank i Kredyt No 8, pp. 12-41, Warszawa and Tomczyk, E. and Widłak, M. (2010) “Konstrukcja i własności hedonicznego indeksu cen mieszkań dla Warszawy”, Bank i Kredyt No 41, pp. 99-128, Warszawa. 10 Ibid. and Glossary of terms and acronyms.

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Figure 11. Average asking price of housing – primary market

0

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Q4

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PLN

/ s

q. m

10 cities - BaRN 7 cities - BaRN

10 cities - PONT 7 cities - PONT

Figure 12. Average transaction price of housing – primary market

0

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8000

2006

Q3

2006

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2007

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2007

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PLN

/ sq

. m


Source: NBP, PONT Info. Source: NBP.

Figure 13. Dynamics (y/y) of average asking price of housing – primary market

80

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2003

Q4

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Figure 14. Dynamics (y/y) of average transaction price of housing – primary market

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Figure 15. Average asking price of housing – secondary market

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Figure 16. Average transaction price of housing – secondary market

0

2 000

4 000

6 000

8 000

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

/ s

q. m



15

Figure 17. Dynamics (y/y) of average asking price of housing – secondary market

80

100

120

140

160

180

200

20

03 Q

4

20

04 Q

2

20

04 Q

4

20

05 Q

2

20

05 Q

4

20

06 Q

2

20

06 Q

4

20

07 Q

2

20

07 Q

4

20

08 Q

2

20

08 Q

4

20

09 Q

2

20

09 Q

4

10 cities - BaRN 7 cities - BaRN10 cities - PONT 7 cities - PONT

Figure 18. Dynamics (y/y) of average transaction price of housing – secondary market

80

100

120

140

160

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4



Figure 19. Dynamics (y/y) of average transaction price of housing – 7 cities, secondary market

80

100

120

140

160

180

200

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

2010

Q1

average hedonic index

Figure 20. Dynamics (y/y) of average transaction price of housing – 10 cities, secondary market

80

100

120

140

160

180

200

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

2010

Q1

average hedonic index

Source: NBP.

Figure 21. Average price vs. price adjusted with hedonic index – secondary market

2 000

4 000

6 000

8 000

10 000

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

2010

Q1

PLN

/ sq

. m

Kraków Wrocław Warszawa

Kraków hed. Warszawa hed. Wrocław hed.

Figure 22. Average price vs. price adjusted with hedonic index – secondary market

0

2 000

4 000

6 000

8 000

200

7 Q

1

200

7 Q

2

200

7 Q

3

200

7 Q

4

200

8 Q

1

200

8 Q

2

200

8 Q

3

200

8 Q

4

200

9 Q

1

200

9 Q

2

200

9 Q

3

200

9 Q

4

201

0 Q

1

PLN

/ sq

. m

Łódź Gdańsk Poznań

Łódź hed. Poznań hed. Gdańsk hed.

Source: NBP.

16

Figure 23. Dynamics (q/q) of average transaction price of housing – Warszawa, secondary market

70

80

90

100

110

120

130

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

weighted average index hedinic index

Figure 24. Dynamics (q/q) of average transaction price of housing – Kraków, secondary market

70

80

90

100

110

120

130

20

06

Q4

20

07

Q1

20

07

Q2

20

07

Q3

20

07

Q4

20

08

Q1

20

08

Q2

20

08

Q3

20

08

Q4

20

09

Q1

20

09

Q2

20

09

Q3

20

09

Q4

weighted average index hedonic index

Source: own calculations based on BaRN and AMRON.

Figure 25. Dynamics (q/q) of average transaction price of housing – Wrocław, secondary market

70

80

90

100

110

120

130

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4


Figure 26. Dynamics (q/q) of average transaction price of housing – Trójmiasto (Gdańsk, Gdynia, Sopot), secondary market

70

80

90

100

110

120

13020

06 Q

4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4



Figure 27. Dynamics (q/q) of average transaction price of housing – Poznań, secondary market

70

80

90

100

110

120

130

140

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4


Figure 28. Dynamics (q/q) of average transaction price of housing – Łódź, secondary market

70

80

90

100

110

120

130

140

150

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4



17

2.2 Rents

High price inflation in the housing market had a limited impact on the level of rent in 2006-2009, as in the period of boom and speculation in the market of owner-occupied flats the demand for rented housing decreases. However, it has to be borne in mind that the market of rented housing in Poland, for regulatory reasons, is significantly less liquid and transparent then the owner-occupied one. This influences the quality of data and, to some extent, explains strong fluctuations of rent prices observed in the six analysed markets (i.e. the largest and most active housing markets in Poland – cf. Figure 29).

Figure 29. Rent, average of asking and transaction prices

15,0

20,0

25,0

30,0

35,0

40,0

45,0

50,0

55,0

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

/ s

quar

e m

etre

Warszawa Kraków Gdańsk Wrocław Poznań Łódź

Source: own estimates, GUS.

Chapter 3. Supply inflation

Rapid growth of housing prices and, consequently, increased construction demand resulted in a marked rise of the costs of construction and assembly production. Additionally, the beginning of the second half of the decade two phenomena coincidence and accumulated: the sector’s employee outflow to European labour markets and the accelerated implementation of general construction objectives. This was connected with Poland’s accession to the EU.

In the 1990s a negative demand shock occured11, which brought about a strong negative reaction on the supply side, causing both an employment reduction in the residential construction sector and a partial liquidation of fixed assets. This shock also affected residential construction and its effects in the form of low developer profits in residential construction were still visible in 2004. In this situation, output growth was only possible with a rising level of costs (cf. Figure 30), especially amid extremely high profitability of development projects, which construction companies were eager to participate in. However, the increased cost of construction and assembly production and other costs, including that of land, were significantly slower from price growth. In consequence, till 2007 the share of developer profits in the price of housing (cf. Figure 31) reached unprecedented record scale,

11 Łaszek J. (2003), ibid.

18

(such a scale was never before observed in Poland). This high double-digit profit share in combination, with the advance financing provided by clients, i.e. a zero cost of capital for the developer, resulted in an extremely high profitability of development projects, which created a strong stimulus for the inflow of both domestic and foreign capital into the sector. In 2008, a deteriorated economic climate and a shrinking size of construction also led to a decrease in production costs. Thanks to that factor, despite shrinking prices of housing, the high profitability of development projects could be preserved (cf. Figures 32-37). In turn, the competition for clients intensified, though it only slightly translated into any significant decline in prices and profits.

Figure 30. Cost of building one square metre of an average flat (object 1121)12 according to Sekocenbud

1500

1700

1900

2100

2300

2500

2700

2900

2004

Q2

2004

Q4

2005

Q2

2005

Q4

2006

Q2

2006

Q4

2007

Q2

2007

Q4

2008

Q2

2008

Q4

2009

Q2

2009

Q4

PLN

/ sq

uare

met

re

Warszawa Kraków GdańskWrocław Poznań Łódź

Figure 31. Changes in share of developer profit in market price of one square metre

0%

10%

20%

30%

40%

50%

60%

70%

2004

Q4

2005

Q4

2006

Q4

2007

Q4

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4


Source: own estimates based on Sekocenbud, NBP.

Figure 32. Warszawa – price structure (PLN/square metre)

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

2004

Q4

2005

Q4

2006

Q4

2007

Q4

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

land design materialsmachinery labour int.costscontr.profit gen.costs devel.profits

Figure 33. Kraków – price structure (PLN/square metre)

0100020003000400050006000700080009000

2004Q

4

2005

Q4

2006Q

4

2007

Q4

2008Q

2

2008

Q3

2008Q

4

2009

Q1

2009Q

2

2009

Q3

2009Q

4



12 See Glossary of terms and acronyms.

19

Figure 34. Poznań – price structure (PLN/square metre)

0

1000

2000

3000

4000

5000

6000

7000

8000

2004

Q4

2005

Q4

2006

Q4

2007

Q4

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4


Figure 35. Gdańsk – price structure (PLN/square metre)

01000

200030004000

500060007000

80009000

2004Q4

2005Q4

2006Q4

2007Q4

2008Q

2

2008Q

3

2008Q4

2009Q1

2009

Q2

2009Q3

2009Q

4



Figure 36. Wrocław – price structure (PLN/square metre)

0

1000

2000

3000

4000

5000

6000

2004Q4

2005Q4

2006Q4

2007Q4

2008Q

2

2008Q

3

2008Q4

2009Q1

2009Q2

2009Q3

2009Q

4


Figure 37. Łódź – price structure (PLN/square metre)

0

1000

2000

3000

4000

5000

6000

2004Q

4

2005

Q4

2006

Q4

2007

Q4

2008Q

2

2008Q

3

2008Q

4

2009Q

1

2009Q

2

2009

Q3

2009

Q4



Chapter 4. Other measures of inflation in the housing market

Experiences of many countries indicate that a developed market-driven real estate sector should be subject to constant monitoring on the part of the public authorities responsible for economic policy (including monetary policy). The reason for this is both cyclicality and the cycles' tendency to turn into real estate crises.

As the most frequent reason for cycles is an excessive demand growth (usually credit demand) and speculation, the best way to measure threats is to monitor real estate prices, including the prices of housing. The second reason why these prices should be analysed is the social nature of a housing unit as consumption good, necessary for normal functioning of households. It should be borne in mind, however, that even though the monitoring of housing prices and, in particular, of their growth, is the base for market risk assessment, the risk-factors analysis is much more complex. The nature of housing as a consumer good also implies that the analysis of the consequences of price growth from the perspective of

20

household budgets is not easy. The problem lies not only in the heterogeneity of housing and local character of markets (resulting in significant local price variations), but is also due to the specificity of housing as a good.

Housing is a long-lived good which is usually bought on credit and, additionally, is usually treated as an investment, with the secondary market being the dominant factor in its purchasing and selling. Moreover, in housing markets, which are usually highly regulated, there are various ways of satisfying the need for housing ranging from rent, through various mixed forms, up to full ownership. This means that the measurement of the cost of housing should be based on a basket of these forms. However, the main question is how to measure the cost of consumption of owner-occupied flats, which usually dominates the market, and then the change of that cost. This measurement, though, is not about maintenance costs but capital costs.

Global consequences of turmoil in real estate markets bring back the ideas of including housing prices, together with the cost of acquiring owner-occupied housing, in the price index of consumer goods and services, the CPI (HICP for EU countries). Previous experiences in this field did not yield any definitive solutions. Apart from the described methodological problems there also arise further ones such as the shape of the monetary policy of the central bank, typically having too few instruments to stabilise the price of housing. In addition, there appears a conflict of purposes due to the infrequent synchronisation of the real estate with the overall business cycle.

In order to outline the problem, the Report offers an approximate estimate of the impact of housing prices on the overall inflation rate made with three methods that are most commonly used in similar studies in the world, i.e. the Discounted Rent Approach, the Net Acquisition Cost and the Payment Approach.13 The information on rent and purchasing prices obtained in NBP survey were adopted as the basis for calculations.

The most consistent approach is the measurement of alternative costs as well as actual costs and capital gains and treating them as the cost of an owner-occupied flat. This method, called the User Cost Approach, sums up the interest costs of a loan, the alternative costs of own contribution, tax charges and adjusts them for capital gains. The main problem of this approach, apart from the difficulties with determining proxies for certain variables, is the fact that what is calculated here is the efficiency of the capital investment in a flat, rather than the costs of consumption. For these reasons, the index constructed on the basis of this method has not been calculated in the present study. Such costs are measured by the credit cost of housing or, in simplification, by interest costs. This method, called the Payment Approach, does not include capital gains, i.e. clearly an investment and non-consumption element. Its application is presented in Figure 38.

The problem of eliminating the investment factor from the measurement of housing price dynamics can be solved in two ways. The first way is measuring the growth of the market prices of new housing excluding land prices (cf. Figure 39). Focusing exclusively on new housing is meant to solve the second problem – the lack of consistency with consumer price indices, measuring the prices of newly manufactured goods. These two solutions are rather illusory. From the practical perspective, we can have two extreme situations here: either the housing market operates poorly and the prices of land do not discount the prices of housing, or it performs well and the increase in housing value is discounted in the land price. As a consequence, we obtain a growth rate close to that of housing prices with land or the price index of construction and assembly production. These numbers, depending on the character of the market, may occur to be two different indicators. Thus the nature of the market determines the performance of the index. The second, equally important problem is that such a measure

13 For more details, see Łaszek, J. and Widłak, M. (2008), ibid.

21

does not reflect anything in principle, as a flat is inextricably linked to the land – there is no possibility of constructing it without incurring the costs of acquisition or long-term lease of land. Likewise, the study of the prices of new housing, which annually meet only a small part of the needs, is very debatable.

Another method of eliminating the investment factor is to calculate the housing price index based on discounted rents (cf. Figure 40), i.e. the pure price of housing services. This method, however, which is theoretically the best, has two drawbacks that render it unreliable. Firstly, the rent market is usually regulated and is not a good representative of the ownership market. The second drawback is much more serious, in periods of strong tensions, and it is precisely what we aim to measure, both markets may behave differently.

The aggregate measure of the housing price dynamics in the six largest markets (cf. Figures 41-42) indicates that the Polish market of land for construction operates with a clear lag and, consequently, the growth rate of housing prices without the value of the land is close to the growth rate including the land. As regards the Discounted Rent Approach there arise problems with the shift in time, well-known from other markets. In turn, larger differences appear while measuring the price of ownership by means of interest charged on the loan. This is the result of changes in structure of foreign currency loans into zloty-denominated ones and the lack of accounting for the exchange rate risk in the credit cost of housing.

Based on the comparison of the results obtained with the use of the three different methods the following conclusions can be formulated. The costs of acquiring housing in the Discounted Rent Approach, the Net Acquisition Approach, i.e. without the value of the land, or the Payment Approach, if housing prices were included to the CPI, would considerably increase its volatility. This would mean considerable problems both with fiscal policy, since the CPI is the index for a number of economic aggregates, and monetary policy.

Figure 38. Change (y/y) of ownership costs and interest charged on loans

0

50

100

150

200

250

300

350

400

2003 2004 2005 2006 2007 2008 2009

Kraków Gdańsk WrocławPoznań Warszawa Łódź

Figure 39. Housing price growth according to Net Acquisition Approach (without land) (y/y)

60

80

100

120

140

160

180

2006 Q4 2007 Q4 2008 Q4 2009 Q4


Source: own analysis based on GUS, PONT Info, NBP. Source: own analysis based on Sekocenbud, NBP.

22

Figure 40. Housing price growth according to Discounted Rent Approach (y/y)

80.0

100.0

120.0

140.0

160.0

180.0

200.0

2007

Q4

2008

Q4

2009

Q4


Figure 41. CPI vs. different housing price indices in 6 cities

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

2006 Q4 2007 Q4 2008 Q4 2009 Q4

price growth according to disconted rentscost of housing ownershiphousing price growth according to net acqusition cost (without land)CPI XII/XII


Figure 42. CPI vs. CPI with different housing price indices in 6 cities

80.0

90.0

100.0

110.0

120.0

2006 Q4 2007 Q4 2008 Q4 2009 Q4

CPI with price growth according to disconted rentsCPI with cost of housing ownershipCPI with housing price growth according to net acqusition cost (without land)CPI XII/XII

Source: own analysis based on GUS, NBP, Sekocenbud, PONT Info.

Chapter 5. Tensions and adjustments in the housing market

5.1 Main tension indicators

Strong tensions arising in the housing markets between supply and demand resulted in changes of difference between transaction and asking prices (cf. Figures 43 and 44). In the primary market of the largest cities in the period of price increase these differences decreased when buyers competed for housing and then rose again when the surplus of supply was exercising downward pressure on prices. In other provincial capitals this tendency was rather less visible, due to a larger variety of market conditions and smaller liquidity of the primary market. In the secondary market, where sellers and buyers acted under less time pressure, the level of those differences was similar, though significantly higher for the largest cities. Higher asking prices were accompanied by a higher propensity to negotiate.

23

The comparison of prices for secondary and primary markets within two groups of cities does not lead to clear conclusions (cf. Figures 45 and 46). However, the price level in the primary market was generally higher than in the secondary market. The phenomenon was usually explained by the higher quality of newly built housing units, despite the fact that they are sold without fixtures and fittings and so included an additional element of risk and implied additional costs.

In general, the discussed relationships developed in very individual way in particular local markets.

Figure 43. Asking vs. transaction price – primary market

0

2 000

4 000

6 000

8 000

10 000

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

/ sq

. m

10 cities - asking price 7 cities - asking price10 cities - transaction price 7 cities - transaction price

Figure 44. Asking vs. transaction price – secondary market

0

2 000

4 000

6 000

8 000

10 000

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

/ s

q. m

10 cities - asking price 7 cities - asking price10 cities - transaction price 7 cities - transaction price

Source: NBP.

Figure 45. Primary vs. secondary markets– askingpprices

0

2 000

4 000

6 000

8 000

10 000

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

/ s

q. m

10 miast r. pierw. 7 miast r. pierw.10 miast r. wt. 7 miast r. wt.

Figure 46. Primary vs. secondary markets– transaction prices

0

2 000

4 000

6 000

8 000

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

/ s

q. m

10 miast r. pierw. 7 miast r. pierw.10 miast r. wt. 7 miast r. wt.

Source: NBP.

24

5.2 Other market tension indicators

To reach equilibrium in the housing market usually takes years. This is particularly true about the supply-side adjustments, because housing prices are generally flexible in relation to demand growth.14 The accumulation of tension, however, can lead to very sharp price drops, as exemplified by numerous real estate crises in the world, including the latest ones. Since housing markets usually have a local nature, the simplest measure of tensions is the indicator that compares the market prices of average housing (P) in the historical perspective with the average household income (I) in a given market – the P/I ratio.

The credit boom in the largest domestic markets triggered a sharp increase in the P/I ratio and a deviation from long-term averages, in the case of Warszawa estimated at about 5, and for other cities – between 4 and 5.15 The decline in housing prices that had originated back in 2008 resulted in a significant downward correction of the index, but there are grounds to believe that the balance has not yet been achieved (cf. Figure 47).

Other commonly used indicators of this type include the comparison of the cost of housing rental (computed in different ways by analysts) with the cost of loan interest and the comparison of market prices of housing with the discounted rent costs (using long-term interest rates). Interest costs higher than the rent show that the consumer is not guided by comparing the prices of housing services, but hope that the value of the flat will increase. When rents discounted with long-term interest display a lower value than the market price this means that the consumer expects a speculative price increase which finds no support in fundamentals. Unfortunately, both these indicators, and especially the second one, have failed in Poland (cf. Figures 48-51), which is due to the weakness of the capital market and the rent market and the fact the consumers ignored the exchange rate risk and obtained financing from loans denominated in Swiss francs, which undervalued the cost of ownership. Despite this it is clear that during the boom rents did not follow the prices of housing, reflecting the speculative nature of price developments in the analysed period.

Since the nineteenth century, the main threat to stable development of the housing market have been frequent demand shocks, which result in strong price movements and then delayed in time and usually inadequate supply adjustments. Currently, they are usually associated with the financial system and its product innovations that increase demand at the expense of risk. In the first decade of this century, the housing market in Poland has experienced many such shocks, starting form inflation shocks and shocks of regulatory changes (VAT, the system of subsidies), to product innovations associated with extending the maturity of loans and denominated products. Illustration of changes in just the interest costs from the market dominant loan for the average flat in the given housing market in relation to the average household budget at the moment of concluding the loan contract (cf. Figure 52) clearly indicates that these fluctuations themselves may be a factor generating cycles and problems in this market. In this context, the unstabilised rent market in Poland (cf. Figure 53) presents itself as a stabilised one.

14 Łaszek, J. Augustyniak, H. and Widłak, M. (2009) “Euro a ryzyko bąbli na rynku nieruchomoœci mieszkaniowych” [The euro and the risk of bubbles in the housing market], Materiały i Studia (NBP Working Papers) No. 238, Warszawa. 15 Łaszek, J., Augustyniak, H. and Widłak, M. (2009), “Cycles in the residential real estate market in Poland and the risk of real estate crisis” paper prepared for ENHR Conference – Changing housing markets: integration and segmentation, Prague, 28th June 2009 and NBP, Inflation Report, June 2008, pp. 39-42.

25

Figure 47. Price of housing vs. disposable income (P/I ratio)

2

3

4

5

6

7

8

9

10

2002

2003

2004

2005

2006

2007

2008

2009

year

s

Warszawa Kraków Gdansk

Wrocław Poznań Łódź


Figure 48. Price vs. rent (with PLN loan)

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4


Figure 49. Price vs. rent (with CHF loan)

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4



Figure 50. Actual vs. expected price (10-year T-bonds)

3000

4000

5000

6000

7000

8000

9000

10000

11000

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

/ s

quar

e m

etre

Kraków actual price Kraków expected priceWarszawa actual price Warszawa expected pricePoznań actual price Poznań expected price

Figure 51. Actual vs. expected price (10-year T-bonds)

3000

4000

5000

6000

7000

8000

9000

10000

11000

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

/ s

quar

e m

etre

Łódź actual price Łódź expected priceGdańsk actual price Gdańsk expected priceWrocław actual price Wrocław expected price


26

Figure 52. Cost of housing ownership vs. income

5%

10%

15%

20%

25%

30%

35%

40%

2002 2003 2004 2005 2006 2007 2008 2009

Sha

re o

f ave

rage

inco

me

Gdansk Kraków ŁódźPoznań Warszawa Wrocław

Figure 53. Cost of housing rental vs. income

30%

35%

40%

45%

50%

55%

60%

65%

2006 2007 2008 2009

Sha

re o

f ave

rage

inco

me

Gdansk Kraków ŁódźPoznań Warszawa Wrocław


Chapter 6. Housing needs and availability

6.1 Financial availability of housing

The main factor triggering the fundamental demand in Poland (its underlying factors being developmental backwardness and demographic factors) was growing availability of loans to households. This growing loan availability was driven by falling inflation, decline in interest rates (cf. Figures 55 and 56), growth in household disposable income and new financial solutions reducing the costs of housing funding. Correlation between growing loan availability to urban households calculated on the basis of a representative sample and increases in loan balances (cf. Figure 54) shows that the decline in lending observed in 2008 was not the result of a change in fundamental factors but internal problems of the financial sector.

Growing housing loan availability, including a shift to cheaper Swiss franc denominated loans, combined with liquidity surplus in the global markets fuelled credit boom and, in consequence, rapid increase in housing prices (amidst small housing supply). As a result of falling costs of financing (decreasing interest rates) in the first part of the business cycle mortgage housing availability was rising despite growing prices of housing. In the subsequent period, the main factor driving demand and further price growth was consumers’ belief in further growth of housing prices. Already the occurrence of a considerable surplus of newly built homes coupled with a more restrictive lending policy pursued by the Polish banks (connected with the financial crisis affecting the US market), made the credit boom run out of steam.

The analysis of housing loan availability shows a considerable difference between the availability of loans in PLN and availability of CHF denominated loans (cf. Figures 60-63) caused by interest rate decline and failure to account for the foreign exchange risk in the availability indicator (availability indicator for each period is calculated on the basis of current exchange rate). In reality, while taking a decision to take out a foreign currency loan, a household should additionally take into account the foreign exchange risk factor, which causes sometimes a dramatic change in the amount of the granted loan when translated into the Polish zloty. Its consequences include higher capital repayment costs and possibly, the

27

need to provide the bank with additional collateral, if the debt increases excessively in relation to the value of the real estate and such a clause was contained in the loan contract. Figures 55 and 56 show current interest rate fluctuations and changes in bank commission charged on loans in PLN and foreign currency loans. Figure 58 shows this impact for particular generations of loans granted in the analysed period, on the example on a loan in the original value of two hundred thousand PLN denominated and serviced in CHF. It may be concluded that the impact of the foreign exchange risk, albeit significant, was not so dramatic for household budgets. It should be noted that the financial crisis affected highly developed countries; as a result, their central banks reduced interest rates and capital outflow from emerging markets was moderate. For the long term liabilities such as mortgage loans it is almost impossible to predict the foreign exchange risk which, moreover, often goes hand in hand with the interest rate risk. Therefore, foreign currency denominated loans that in some circumstances may generate foreign exchange gains should be taken out only by those households that can afford to cover the ensuing costs, if any; government subsidy programmes should ensure better availability of housing to poorer households.

Figure 54. Global credit availability

0

100

200

300

400

500

1997

Q1

1998

Q1

1999

Q1

2000

Q1

2001

Q1

2002

Q1

2003

Q1

2004

Q1

2005

Q1

2006

Q1

2007

Q1

2008

Q1

2009

Q1

PLN

bill

ion

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

PLN

bill

ion

global credit availability housing loan balance (quarter change)

Figure 55. Interest rates of housing loans in PLN

0%1%2%3%4%5%6%7%8%9%

10%20

04Q

4

2005

Q2

2005

Q3

2005

Q4

2006

Q2

2006

Q3

2006

Q4

2007

Q2

2007

Q3

2007

Q4

2008

Q2

2008

Q3

2008

Q4

2009

Q2

2009

Q3

2009

Q4

gap between housing loan interest and deposit rateprofit margin on housing loan=PLN interst rate-WIBOR3M3M WIBORdeposit ratehousing loan interest rate

Source: GUS, NBP.

Figure 56. Interest rates of housing loans denominated in CHF

0%1%

2%3%

4%5%6%

7%8%

9%10%

2004

Q4

2005

Q2

2005

Q3

2005

Q4

2006

Q2

2006

Q3

2006

Q4

2007

Q2

2007

Q3

2007

Q4

2008

Q2

2008

Q3

2008

Q4

2009

Q2

2009

Q3

2009

Q4

CHF loan rateprofit margin on CHF housing loans=CHF-3M LIBOREUR loan rateprofit margin on EUR housing loans=EUR -3M EURIBOR

Figure 57. Foreign exchange rate and interest rate fluctuations in the case of CHF denominated loans

2.0

2.1

2.2

2.3

2.4

2.5

2.6

2.7

2.8

2.9

3.0

3.1

3.2

2006

Q1

2006

Q2

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

4%

4%

5%

5%

6%

6%

7%

7%

PLN / CHF rate (LSH)

interest rate (RSH)

Source: GUS, NBP.

28

Figure 58. Repayment of different generations of loans denominated in CHF

1 000

1 100

1 200

1 300

1 400

1 500

1 600

1 700

1 800

2006

Q1

2006

Q2

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

inst

alm

ent a

nd in

tere

st p

aym

ent c

onv.

to P

LN

loan incurred in 2006 r.




Figure 59. Housing availability

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

2004

Q1

2004

Q3

2005

Q1

2005

Q3

2006Q

1

2006

Q3

2007

Q1

2007

Q3

2008Q

1

2008

Q3

2009

Q1

2009

Q3

squa

re m

etre

/ av

erag

e w

age

Warszawa Kraków Gdańsk

Wrocław Poznań Łódź Source: NBP. Source: GUS, NBP, PONT Info.

Figure 60. Availability of loans in PLN

70

90

110

130

150

170

190

2004 Q

1

2004Q

3

2005 Q

1

2005Q3

2006Q1

2006Q3

2007Q

1

2007Q3

2008Q1

2008Q3

2009Q1

2009Q3

PLN

ths

/ ave

rage

wag

e


Łódź Poznań Wrocław

Figure 61. Availability of loans in CHF

70

90

110

130

150

170

190

2004

Q1

2004

Q3

2005 Q

1

2005Q

3

2006Q

1

2006

Q3

2007Q

1

2007Q

3

2008Q

1

2008

Q3

2009Q

1

2009Q

3

PLN

ths

/ ave

rage

wag

e



Source: GUS, NBP, PONT Info.

Figure 62. Mortgage housing availability (loans in PLN)

30

50

70

90

110

130

150

170

2004

Q1

2004

Q3

2005

Q1

2005

Q3

2006

Q1

2006

Q3

2007

Q1

2007

Q3

2008

Q1

2008

Q3

2009

Q1

2009

Q3

squa

re m

etre

s o

f hou

sing

bo

ugt w

ith P

LN

loan


Figure 63. Mortgage housing availability (loans in CHF)

30

50

70

90

110

130

150

170

2004

Q1

2004

Q320

05 Q

1200

5Q320

06Q1

2006Q3

2007Q

120

07Q3

2008Q

1200

8Q320

09Q1

2009Q3

squa

re m

etre

s of

hou

sing

bou

gt w

ith C

HF

lo

an


Source: GUS, NBP, PONT Info.

29

6.2 Housing needs

Housing situation in Poland, although considerably different from the level noted in the so-called old European countries16 does not vary greatly from the level of Poland's delay in other areas of the economy. Improvement in the housing situation is a long-term process and any attempts to speed it up, as evidenced by numerous examples of countries where the overall economic growth has shown a considerable acceleration, generally result in problems affecting this market. The level of the most synthetic measure of the housing situation, namely the number of housing units per 1000 inhabitants, has slightly improved over the past decade, especially in Poland’s six major cities. Fast growth of this indicator for Poland taken as a whole, recorded in the years 2002-2003, resulted from a change in the method of housing qualification criteria during the national census (broad definition of housing including “second homes”) rather than from the actual improvement. At present, the average saturation indicator in Poland’s six largest cities is getting closer to the level recorded in EU-15. Yet, it should be noted that housing units in Poland are of considerably smaller area and lower standard and that the housing situation varies greatly between regions (cf. Figures 64-73). Local diversity in Poland’s housing situation is due to historical reasons. In general, in rural areas and smaller town where the share of single-family houses is higher, the indicators of housing area per person are higher too. Large flats are characteristic for old cities which did not suffer war destructions; yet, they are densely occupied and the indicators do not look good there (cf. Figures 66-68 and Figures 72 and 73).

Poland’s economic delay results in smaller than in developed countries quantity of housing stock and causes another socially distressing phenomenon – lack of housing and households’ shared occupancy of housing. This problem looks different in various local markets as it results from both housing structure and household structure. Thus, in markets dominated by large old flats there may be favourable population density indicators (i.e. the number of square metres per person) and unfavourable indicators of independent occupancy (number of households per 100 housing units, percentage of households enjoying single occupancy); other markets can witness a totally different situation or accumulation of problems. This problem in statistical terms, and partly in real terms, has intensified as a result of demographic changes leading to an increase in the number of households and a decline in household size. As a result, despite unquestionable improvement in housing conditions in Poland over the last decade, this indicator has generally worsened. In this situation, one positive phenomenon is the structure of housing stock in Poland, with a dominant share of small flats which several dozen years ago led to the opposite problems than those experienced nowadays (large families in small flats). Yet, in general, demographic developments (marriages, net migration, birth rate) just like demand on the local markets are far more likely to change than the housing stock; therefore, problems of this kind are unavoidable. The best solution is then to make the housing stock more flexible by reducing real estate transaction costs and increasing the housing stock for rent. In the discussed period, Poland noted a considerable progress as far as the first issue is concerned; the second problem still remains unsolved.

16 Chiquier L. (2006), Poland Housing Finance Policy Note, World Bank.

30

Figure 64. Housing stock per 1000 inhabitants

250

270

290

310

330

350

370

390

410

430

450

2002 2003 2004 2005 2006 2007 2008

dwel

lings

/100

0 in

habi

tant

s

6 cities10 citiesPolandcountryside

Figure 65. Housing stock per 1000 inhabitants in 6 cities

340

360

380

400

420

440

460

480

2002 2003 2004 2005 2006 2007 2008

dwel

lings

/100

0 in

habi

tant

s

Warszawa Kraków GdańskPoznań Wrocław Łódź

Source: GUS.

Figure 66. Average housing usable area in housing stock

55.0

60.0

65.0

70.0

75.0

80.0

85.0

90.0

2002 2003 2004 2005 2006 2007 2008

squa

re m

etre

/ dw

ellin

g 6 cities10 citiesPolandcountryside

Figure 67. Average housing usable area in housing stock in 6 cities

50.0

52.0

54.0

56.0

58.0

60.0

62.0

64.0

66.0

2002 2003 2004 2005 2006 2007 2008

squa

re m

etre

/ dw

ellin

g


Source: GUS.

Figure 68. Average housing usable area in housing stock per person

20.0

21.0

22.0

23.0

24.0

25.0

26.0

2002 2003 2004 2005 2006 2007 2008

squa

re m

etre

/ pe

rson


Figure 69. Average housing usable area in housing stock per person in 6 cities

19.0

20.0

21.0

22.0

23.0

24.0

25.0

26.0

27.0

2002 2003 2004 2005 2006 2007 2008

squa

re m

etre

/ pe

rson


Source: GUS.

31

Figure 70. Number of households per 100 housing units in housing stock in 2002

100

110

120

130

140

150

160

6 cities 10 cities Poland countryside

Figure 71. Number of households per 100 housing units in housing stock in 2002 in 6 cities

102

104

106

108

110

112

114

Warszawa Łódź Kraków Poznań Gdańsk Wrocław

Source: GUS.

Figure 72. Number of persons per 100 rooms in housing stock in 2002

80

82

84

86

88

90

92

94

96


Figure 73. Number of persons per 100 rooms in housing stock in 2002 in 6 cities

72

74

76

78

80

82

84

86

88

90

92

Wrocław Warszawa Łódź Poznań Gdańsk Kraków

Source: GUS.

Figure 74. Housing constructed

0

20 000

40 000

60 000

80 000

100 000

120 000

140 000

160 000

180 000

2002 2003 2004 2005 2006 2007 2008 2009

dwel

lings

countrysiderest of Poland10 cities6 cities

Figure 75. Housing constructed in 6 cities

0

5 000

10 000

15 000

20 000

25 000

30 000

35 000

40 000

45 000

50 000

2002 2003 2004 2005 2006 2007 2008 2009

dwel

lings


Source: GUS. The past decade has seen considerable fluctuations in the size of residential construction

which started in 2002 from the level below 90 thousand housing units annually to reach in 2008 the level of almost 170 thousand housing units. Changes in the level of residential construction brought about by business cycles are characteristic for this market and Poland’s experience in this respect is not unique. The whole analysed period saw persisting or growing importance of housing markets in Poland’s six major cities, including Warszawa. Regular growth was also noted in the size of owner-built construction in rural areas and in smaller

32

towns (cf. Figures 74 and 75). The end of expansionary lending in 2008 resulted in a decline in demand for housing and a surplus of expensive, unsold flats in majority of markets in larger cities. As a result of persistently high housing prices and high profitability of real estate development, decreases in the number of newly constructed housing units are smaller than it could have been expected (cf. Figures 30-37). As there is still room for price drops, especially given falling construction costs, competition may be expected to decline in the longer run and differentiate housing prices to a larger extent.

6.3 Housing availability as the objective of housing policy

The objective of housing policy in the market economy is usually defined as measures aimed to enable households to choose the form of meeting their housing needs tailored to their individual preferences and income17. This policy usually assumes there should be a certain minimum standard affordable for each household, and its implementation tools include various forms of subsidies and regulations. The addressed problem concerns usually young, newly formed households and those households that change their place of residence. The main problem faced by housing policy in Poland has always been its declarative character, combined with solutions implemented accidentally and partially. The rapid development of bank financing in the past few years has solved the problem of the wealthiest households only. Figure 76 presents aggregated curves of average housing availability in Poland's seven major cities. These curves are combination of credit and housing availability. They show, for a particular interest rate, banks’ prudential indictors and the average housing size (60 square metres) and at a given price per square metre, the percentage of households able to purchase housing secured with a mortgage loan considering. In 2009 approximately 32% of households in need of housing could afford to purchase it on market conditions (point A). As prices in 2009 were at least by 10-15% overstated, and interest rates also deviated from the natural interest rate on mortgage loans, it may be assumed that the long-term equilibrium should be at point B which would concern approximately 40% of households. Actually, some of those households should be given loan guarantees as banks are most eager to extend loans to households earning income which is at least one and a half times above average. Interest subsidies and guarantees would make it possible to achieve the condition where half of households would be able to satisfy their housing needs by purchasing owner-occupied housing (point C). In order to meet housing needs of approximately 70% of the population (point D) it would be necessary to significantly reduce housing costs and standard, reduce its size (50-60% of the average set at 60 square metres). The remaining part of the population is prospective tenants of social housing and cheap rental housing subsidised with allowances.

The discussed example shows that the Polish market suffers a shortage of credit guarantee programmes and programmes supporting the construction of housing for rent and owner-occupied housing financed from the capital market or subsidised by the government. This situation is primarily the result of the lack of a more complex housing policy.

17 Merrill S. R., Lawrence R., Lea M. J., Diamond D. B., Sickles-Grabowska M. (1998), Public Sector Housing Finance Policy Strategies for Poland, Urban Institute.

33

Figure 76. Estimate of the maximum housing price affordable to a household in 7 cities in 2009 depending on the amount of interest rate on mortgage loan

0

2000

4000

6000

8000

10000

12000

14000

2% 13% 23% 34% 44% 55% 65% 76%percentage of households

max

imum

pric

e of

an

aver

age

hous

ing

unit

4%

5%

6%

7%

8%

9%

10%

AB C

D

Source: NBP analysis based on GUS.

Chapter 7. Demand, supply and market balance

7.1 Demand and supply for space, fundamental factors

The housing boom in the largest Polish cities in 2006-2008 had its base in the fundamental factors, therefore, despite the undoubted speculative bubble, the process of adjustment did not lead to crisis phenomena. Of fundamental importance here was the rising number of households driven by demographic processes, a good indicator of which was the increase in the number of young married couples and an increase in income resulting form economic growth acceleration (cf. Figures 77-80). Migrations from smaller towns and villages, which recorded positive population growth, although statistically elusive, as often taking place outside the administrative borders of the largest cities, could also be emphasised in this context (cf. Figures 81-86).

34

Figure 77. Average wages in enterprise sector

2 200

2 400

2 600

2 800

3 000

3 200

3 400

3 600

3 800

2005 2006 2007 2008 2009

PLN

/ m

onth

6 cities

10 cities

Poland

Figure 78. Average wages in enterprise sector in 6 cities

2 000

2 500

3 000

3 500

4 000

4 500

2005 2006 2007 2008 2009

PLN

/ m

onth

Warszawa Gdańsk Kraków

Wrocław Poznań Łódź Source: GUS.

Figure 79. Marriages per 1000 inhabitants

4,0

4,5

5,0

5,5

6,0

6,5

7,0

2002 2003 2004 2005 2006 2007 2008


Figure 80. Marriages per 1000 inhabitants in 6 cities

4.0

4.5

5.0

5.5

6.0

6.5

7.0

2002 2003 2004 2005 2006 2007 2008



Figure 81. Net migration per 1000 inhabitants

-10.0

-9.0

-8.0

-7.0

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2002

2003

2004

2005

2006

2007

2008

6 cities

10 cities

Poland

countryside

Figure 82. Net migration per 1000 inhabitants in 6 cities

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

2002

2003

2004

2005

2006

2007

2008



35

Figure 83. Population growth per 1000 inhabitants

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2002 2003 2004 2005 2006 2007 2008

6 cities

10 cities

Poland

countryside

Figure 84. Population growth per 1000 population in 6 cities

-7.0

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2002

2003

2004

2005

2006

2007

2008



Source: GUS.

Figure 85. Population growth and net migration per 1000 inhabitants

-10.0

-9.0

-8.0

-7.0

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2002 2003 2004 2005 2006 2007 2008 2009

6 cities

10 cities

Poland

countryside

Figure 86. Population growth and net migration per 1000 inhabitants in 6 cities

-10.0

-8.0

-6.0

-4.0

-2.0

0.0

2.0

4.0

6.0

2002 2003 2004 2005 2006 2007 2008 2009

Warszawa Gdańsk PoznańWrocław Kraków Łódź

Source: GUS.

Figure 87. Completed housing units per 1000 marriages in Poland

300

500

700

900

1100

1300

1500

2005 2006 2007 2008


Figure 88. Completed housing units per 1000 marriages in 6 cities

200

400

600

800

1000

1200

1400

1600

1800

2000

2200

2005 2006 2007 2008

Warszawa Gdańsk Poznań

Wrocław Kraków Łódź Source: GUS.

36

Figure 89. Outlook for housing construction in Poland

0

50 000

100 000

150 000

200 000

250 000

2005 2006 2007 2008 2009 2005 2006 2007 2008 2009

Building permits issued Dwellings under construction

dwel

lings

6 cities 10 cities Poland

Figure 90. Outlook for housing construction in 6 cities

0

10 000

20 000

30 000

40 000

50 000

60 000

70 000

2005 2006 2007 2008 2009 2005 2006 2007 2008 2009


dwel

lings

Warszawa Kraków WrocławGdańsk Poznań Łódź

Source: GUS.

Figure 91. Outlook for residential construction per 1000 inhabitants in Poland

0

2

4

6

8

10

12

14

2005 2006 2007 2008 2009 2005 2006 2007 2008 2009


dwel

lings

/ 1

000

inha

bita

nts

6 cities 10 cities Poland

Figure 92. Outlook for residential construction per 1000 inhabitants in 6 cities

0

2

4

6

8

10

12

14

16

18

20

2005 2006 2007 2008 2009 2005 2006 2007 2008 2009


dwel

lings

/ 1

000

inha

bita

nts

Warszawa Kraków GdańskŁódź Poznań Wrocław

Source: GUS.

Significant surplus of unsold housing units in the largest city markets, which resulted from the boom of 2006–2007, is responsible for reducing the size of the construction sector in 2009–2010 on the part of developers, which is reflected in leading indicators, i.e. the number of newly commenced housing units and issued building permits for housing construction (cf. Figures 90-92). Taking into account the considerable "hoarding" of building permits over the past few years, the second indicator is particularly significant. This trend is evident in all markets, especially while analysed in relative terms per 1000 inhabitants (cf. Figures 87 and 88).

7.2 Loans

Demand for housing was most strongly determined by loans (especially those denominated in Swiss francs), which was supported by Poland’s banking system model based on universal banks belonging to large international capital groups. This enabled the transfer of funds from international markets by-passing more conservative regulations applying to mortgage banks. In the decade under review, the level of loan indebtedness of households increased from a value insignificant for the sector and the economy to such that it became a key demand factor in the largest Polish residential markets. This fact is not fully illustrated (cf. Figures 97 and 98) because the loan portfolios are aggregated only in the administrative

37

areas of cities and, consequently, the aggregate of Poland includes a significant volume of loans granted in the neighbouring local areas.

Heavy bank lending, bringing about housing market inflation, caused, in second half of the decade, increasing liquidity problems of banks, which consequently began to gradually increase their interest rates, despite the fact that the margin in relation to WIBOR was generally stable. The financial crisis and its consequences led to a sharp change in the domestic banks’ perception of exchange rate risk and credit-related risk connected with housing loans (cf. Figures 99 and 100). Similar phenomena also occurred in other countries. Even though central banks cut the interest rates, the risk premiums were rising. At the same time, the increasing costs of refinancing from ever more expensive deposits in the domestic market led to a drop in the profitability of housing loans, as WIBOR ceased to reflect the real costs of money, which were growing (cf. Figure 54). As a result, lending decelerated, and then started to fall (cf. Figures 93-96). The access to foreign funds was also sharply reduced, which was a consequence of declining confidence in international capital markets. The domestic credit supply was also significantly affected by the condition of the parent banks, which in the face of capital losses and declining solvency ratios reduced lending in their subsidiaries.

Figure 93. Housing loan balance in Poland (according to NBP)

0

50

100

150

200

250

2002

Q4

2003

Q1

2003

Q2

2003

Q3

2003

Q4

2004

Q1

2004

Q2

2004

Q3

2004

Q4

2005

Q1

2005

Q2

2005

Q3

2005

Q4

2006

Q1

2006

Q2

2006

Q3

2006

Q4

2007

Q1

2007

Q2

2007

Q3

2007

Q4

2008

Q1

2008

Q2

2008

Q3

2008

Q4

2009

Q1

2009

Q2

2009

Q3

2009

Q4

PLN

billi

on

Foreign currency

PLN

Figure 94. Annual changes in housing loan balance in Poland (according to NBP)

0

10

20

30

40

50

60

70

80

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

PLN

bill

ion

nominal

exchange rate adjusted

Source: NBP.

Figure 95. Banking sector in Poland (balance)

-50 000

0

50 000

100 000

150 000

200 000

250 000

300 000

350 000

400 000

450 000

1996

Q4

1997

Q4

1998

Q4

1999

Q4

2000

Q4

2001

Q4

2002

Q4

2003

Q4

2004

Q4

2005

Q4

2006

Q4

2007

Q4

2008

Q4

2009

Q4

PLN

mill

ion

LiquidityDepositsCreditsHousing Loan

Figure 96. Housing credit in Poland (growth structure)

90%

91%

56%

20% 27

%

74%

19% 36

%

62% 74

%

10%

9%

44%

107%

80% 73

%

26%

81% 64

%

38%

91%

26%

9%-7%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

PLN Foreign currency

Source: NBP.

38

Figure 97. Value of new housing loans in Poland (according to BIK)

0

10

20

30

40

50

60

2004 2005 2006 2007 2008 2009

PLN

bill

ion

rest of Poland10 cities6 cities

Figure 98. Value structure of new housing loans in 16 Polish cities (according to BIK)

0%

20%

40%

60%

80%

100%

2004 2005 2006 2007 2008 2009

Warszawa Kraków Wrocław PoznańGdańsk Łódź Szczecin LublinBydgoszcz Katowice Olsztyn BiałystokZielona Góra Rzeszów Kielce Opole

Source: BIK, NBP.

Figure 99. Housing credit in PLN (credit risk assessment by banks)

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

2003

Q4

2004

Q2

2004

Q4

2005

Q2

2005

Q4

2006

Q2

2006

Q4

2007

Q2

2007

Q4

2008

Q2

2008

Q4

2009

Q2

2009

Q4

PLN minus 5year bond rate

PLN minus 10year bond rate

Figure 100. Housing credit in CHF (exchange rate risk assessment by banks)

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

2003

Q4

2004

Q2

2004

Q4

2005

Q2

2005

Q4

2006

Q2

2006

Q4

2007

Q2

2007

Q4

2008

Q2

2008

Q4

2009

Q2

2009

Q4

CHF minus 3M LIBOR minus 5year credit risk

CHF minus 3M LIBOR minus 10year credit risk

Source: NBP.

7.3 Markets

In the largest housing markets, strong tensions can be observed between supply and demand, yet their scale is varied. This is due to the credit boom (which caused excessive growth in housing prices), reduced availability of housing loans (as a consequence of the financial crisis and internal problems of the banking sector) and a significant increase in housing supply (due to high prices). These problems additionally coincide with the weakening of economic development resulting in a decline in income growth, concerns about employment and, consequently, the overall decrease in optimism and consumer spending as well as halting the migration to the largest cities. It should also be borne in mind that the record-high purchases of housing at the end of the decade were, to some extent, made ahead of actual needs and currently result in a weakened demand. The demand curve in the largest residential markets of Poland (cf. Figures 101-112), estimated on the basis of the curve of housing availability to households from different cities, shows how many average-sized flats can be bought on credit by households in a given city at a given level of income, interest rates and at given lending conditions. Assuming that the population of households aspiring to their own housing does not differ from the average structure of all households’ representation, the

39

central part of this curve can serve as an approximation of demand. Equilibrium prices were obtained from quarterly NBP surveys in these markets, and the housing supply situation—from the survey performed by REAS Company. The shape of the supply curve was estimated based on the distribution of asking prices of housing.

The situation that has emerged in the largest housing markets after the credit boom is rather typical. Housing prices, which were flexible while the demand was growing, stiffened and diversified at its decline. In consequence, the short-term supply curve is not a straight line perpendicular to the X axis, only has become close to a parabolic shape. The result is a significant surplus of unsold housing units, which at current prices, income and interest rates can be estimated, depending on the market, at 1.5 to 2 years in the absence of new output. Thus, it is not possible to achieve a quick equilibrium through price adjustments at particular markets, as this would lead to sharp downward corrections of housing prices. Such variant does not seem probable either, as the Polish market is dominated by large and well-capitalised companies, which in case of problems can obtain financing from construction companies and material suppliers, and primarily by collecting advance payments from their customers. Nor is it possible to sell off housing units put up for sale, since it would require a high lending disbursed by means of cheap loans. It can be assumed that in the longer-term, the supply pressures and increasing competition between new investment projects will lead to price reductions and a gradual restoration of the market balance. The rebuilding lending of banks should have similar effect. As it seems rather impossible, however, that the credit availability should return to its level in the previous period, the market will be enforcing corrections in housing prices.

Additionally, the situation in the housing market in the largest cities is illustrated with the figures below, which compare the curves of demand and supply. Since the equilibrium prices in 2009 were not market-clearing prices, and due to location constraints the sale is often close to a monopoly that differentiates prices, it is important to consider the question whether the households intending to buy a flat could purchase it at the current price if they were convinced they should do it. In other words, the question is: if banks did not apply credit limitations, and developers managed to generate a buying fever similar to that in previous years, would the housing units currently on the market be sold within one year. Comparing the availability of housing to its supply (cf. Figures 107-112), the situation is the worst in Kraków, Wrocław and especially in Poznań, where the supply curves run for the most part above the demand curve, while it is quite good in the Trójmiasto (Gdańsk, Gdynia, Sopot) and Warszawa markets. This means that in the case a new boom arises in the housing market and consumers no longer behave rationally, the Warszawa and Trójmiasto market would be most probably able to absorb housing units offered for sale.

40

Figure 101. Primary housing market in Warszawa in 2009

0

3 000

6 000

9 000

12 000

15 000

18 000

21 000

24 000

0 5 000 10 000 15 000 20 000No of housing units

hous

ing

pric

e (P

LN /

sq. m

)

demand short-term supply

Figure 102. Primary housing market in Kraków in 2009

0

5 000

10 000

15 000

20 000

25 000

0 2 000 4 000 6 000 8 000

No of housing units

hous

ing

pric

e (P

LN /

sq. m

)


Source: NBP.

Figure 103. Primary housing market in Wrocław in 2009

0

5 000

10 000

15 000

20 000

25 000

30 000

0 1 000 2 000 3 000 4 000 5 000

No of housing units

hous

ing

pric

e (P

LN /

sq. m

)


Figure 104. Primary housing market in Trójmiasto (Gdańsk, Gdynia, Sopot) in 2009

0

5 000

10 000

15 000

20 000

25 000

30 000

0 1 000 2 000 3 000 4 000 5 000

No of housing units

hou

sing

pric

e (P

LN /

sq. m

)


Source: NBP.

Figure 105. Primary housing market in Poznań in 2009

0

2 000

4 000

6 000

8 000

10 000

12 000

14 000

16 000

18 000

0 500 1000 1500 2000 2500 3000 3500

No of housing units

hou

sing

pric

e (P

LN /

sq. m

)


Figure 106. Primary housing market in Łódź in 2009

0

2 000

4 000

6 000

8 000

10 000

12 000

14 000

0 500 1000 1500

No of housing units

hous

ing

pric

e (P

LN /

sq. m

)


Source: NBP.

41

Figure 107. Primary housing market in Warszawa in 2009

0

5 000

10 000

15 000

20 000

25 000

0 20 40 60 80 100 120

percentiles

hous

ing

pric

e (P

LN /

sq. m

)

demand short-term supply transactions

Figure 108. Primary housing market in Kraków in 2009

0

5 000

10 000

15 000

20 000

25 000

0 20 40 60 80 100 120

percentiles

hous

ing

pric

e (P

LN /

sq. m

)


Source: NBP, PONT Info.

Figure 109. Primary housing market in Wrocław in 2009

0

5 000

10 000

15 000

20 000

25 000

0 20 40 60 80 100 120

percentiles

hous

ing

pric

e (P

LN /

sq. m

)


Figure 110. Primary housing market in Trójmiasto (Gdańsk, Gdynia, Sopot) in 2009

0

5 000

10 000

15 000

20 000

25 000

0 20 40 60 80 100 120

percentiles

hous

ing

pric

e (P

LN /

sq. m

)



Figure 111. Primary housing market in Poznań in 2009

0

5 000

10 000

15 000

20 000

25 000

0 20 40 60 80 100 120

percentiles

hous

ing

pric

e (P

LN /

sq. m

)


Figure 112. Primary housing market in Łódź in 2009

0

5 000

10 000

15 000

20 000

25 000

0 20 40 60 80 100 120

percentiles

hous

ing

pric

e (P

LN /

sq. m

)



42

Chapter 8. Regulations

During the past decade the housing market has undergone thorough transformation connected with the catching-up process in home financing. It was affected by the second business cycle, this time very classical one. Those changes led to the implementation of supplementary banking regulations (inter alia, implementation of Recommendation S, and in 2010 of Recommendation T)18, as well as the set-up of temporary government programmes aimed to limit the consequences of business cycles. The effects of undertaken measures, that addressed the basic problems of the housing sector, seem to be insufficient.. The measures conditioning sector sustainable and more stable development include:

• Better management of credit risk and banks’ liquidity. The recent experience has clearly shown that departure from classical rules of mortgage banking brings about serious problems. Those problems have been addressed both in Recommendation S and in Recommendation T implemented in 2010. Yet, there is persistent shortage of measures aimed to ensure further diversification of sources of bank financing, including capital market financing.

• Amendments to the Act on tenant protection19 making it less restrictive together with the provision of a wider range of housing allowances and establishment of conditions necessary for the development of commercial housing for rent.20 The situation may change thanks to amendments in the Act on the protection of tenants' rights, on housing stock of the municipality and on changes in the Civil Code (came into force at the end of January 2010) which introduced the so-called occasional tenancy contract. The amendment is aimed to stimulate the housing rental market by providing a definition of occasional tenancy and excluded it from the regime of the majority of provisions contained in the Act on tenant protection and to eliminate the “grey market” of housing rental. Since January 2010 private owners may conclude occasional occupancy contract for a definite period of time not exceeding ten years which gives them the possibility to evict tenants being in arrears with rental payments without the need to obtain a court judgment. Upon concluding such a contract owners will pay a low (8.5%) tax on income provided they notify the fiscal office about concluding such a contract. Occasional tenancy contracts may be concluded only by a private home owner being a natural person who does not pursue any business activity in the field of housing rental. Housing rental under an occasional tenancy contract provides a better protection of the landlord’s interests than before; as a result, the number of rented housing is likely to increase. As the Act applies to private home owners (natural persons) only, the new regulations do not provide a stimulus for real estate developers to engage in housing rental business.

• Introduction of the law protecting real estate developers’ clients and allowing bank control of real estate investments conducted by developers as well as setting-up of an insurance system of these investments.

• The reform of the Low-Cost Building Society (TBS) System aimed to transform it into two programmes addressed at two different social groups, i.e. social programme based on

18 See Glossary of terms and acronyms. 19 The Act of 21 June 2005 on the protection of tenants' rights, on housing stock of the municipality and on changes in the Civil Code (Journal of Laws of 2005 No. 31, Item 266, as amended). 20 Dubel H. J., Brzeski W. J., Hamilton E. (2006), Rental Choice and Housing Policy Realignment in Transition – the Housing Post-Privatisation Challenges in the Europe and Central Asia Region, World Bank.

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public sector subsidies and programme of leased housing with moderate rental payments.21 The second one should be addressed to wider social groups and offer a modest, albeit acceptable standard. They should also be financed on a commercial basis with government subsidies including the possibility of its privatisation.

• Improvement of the local housing policy.

21 Chiquier L. (2006), ibid.

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Glossary of terms and acronyms

AMRON – System for Analysis and Monitoring of Real Estate Market Transactions.

BaRN – Real Estate Market Database. Database recording the asking and transaction prices of housing in 16 largest provincial (voivodeship) capitals in Poland. It also holds data on market rents. Data come from real estate agents, developers who volunteered for the survey and partially also from the Registers of Prices and Values of Real Estates maintained at Polish administrative units (counties). Data are gathered and verified by the Regional Branches of the NBP.

BIK – Credit Information Bureau.

Cities 200+ – stands for all cities in Poland with a population of at least 200 thousand.

Credit availability – a measure of potential credit available at a specific interest rate, amortisation, credit requirements (social minimum), average monthly wages in the enterprise sector; it expresses the amount of credit that the borrower is able to obtain for average monthly wages in the enterprise sector in a given market (GUS) in view of the credit requirements of the bank and the parameters of the loan (interest rate charged, amortisation period, social minimum understood as the minimum income left after the payment of loan instalments); what is informative is the change rate and regional differentiation rather than the actual level of the indicator.

Credit availability of housing – a measure specifying how many square metres of housing of an average asking price in a given market (PONT Info) may be purchased with the use of a housing loan obtained based on average monthly wages in the enterprise sector in the given market (GUS), in view of the credit requirements of the bank and loan parameters (interest rate charged, amortisation period, social minimum understood as the minimum income left after the payment of loan instalments); what is informative is the change rate of the index and spreads between particular markets.

Financial market overliquidity – the surplus of financial capital unallocated by financial institutions.

Global credit availability – a measure specifying the sum of mortgage loans available for all the city households in Poland; it is calculated based on individual disposable income of households (household budgets according to GUS) as well as credit requirements of the bank and loan parameters.

GUS – Central Statistical Office.

Hedonic housing price index – a measure reflecting the “pure” price change, i.e. a change resulting from other factors than changes in quality (structure) of analysed housing units. The quality-adjusted hedonic housing price index holds the mix of housing characteristics constant in analysed periods. This is the main advantage of the hedonic index in comparison to the simple average or median dynamics measures.

Housing availability – a measure of the potential ability to purchase housing area at the asking price for average monthly wages in the enterprise sector; it expresses the number of square metres of housing at an average asking price in a given market (PONT Info) that can be purchased for average wages in the enterprise sector in a given city (GUS).

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Object 1121 – a residential multi-family five-storey building, which since 2004 has served as a basis for monitor the average price of constructing one square metre of living space (cf. bulletins of building prices published by Sekocenbud).

PABB – Polish Construction Research & Forecasting.

PONT Info Nieruchomości (PONT) – database holding data on asking prices of real property. Asking price data are gathered by PONT Info company.

Product innovations – modern banking products; a number of instruments, including brokerage services, selling products of other establishments (mutual funds, insurance companies) and, last but not least, issuing services (issue of securities, servicing and underwriting of the issuance of shares), managing clients’ investment portfolios and deposit certificates (debt securities issued by banks with a guaranteed purchase time and price).

PSBD – Polish Association of Home Builders.

Recommendation S – a collection of good practices for mortgage secured credit exposures; introduced in 2006 by the Commission for Banking Supervision, issued pursuant to Art. 137 Point 5 of the Banking Law Act (Journal of Laws No. 72/2002, Item 665, as amended).

Recommendation T – a collection of good practices for managing the rise of retail credit exposures; introduced in 2010 by the Commission for Banking Supervision, issued pursuant to Art. 137 Point 5 of the Banking Law Act (Journal of Laws No. 72/2002, Item 665, as amended).

SARFIN – Analytical System for the Real Estate Financing Market.

Sekocenbud – a publication gathering data about costs in the construction sector; the Authors of the Report make use of the quarterly bulletins that contains information on building prices.

Six cities – Warszawa, Kraków, Wrocław, Poznań, Gdańsk, Łódź; (whenever seven cities are mentioned, Gdynia is included in the group).

TBS – Low-Cost Building Society is a company operating on the basis of the Act of 26 October 1995 on certain forms of supporting housing construction (consolidated text – Journal of Laws No. 98/2000, Item 1070, as amended) active in the area of the construction of residential houses and their maintenance on a rental basis, management and administration services and performs activities connected with residential construction and accompanying infrastructure. The offer of Low-Cost Building Societies is addressed to families of modest means, which may obtain from the National Housing Fund (KFM) a loan subsidised from the central budget. The tenants pay the rent, which is generally higher than that in municipal housing stock (as it is partially used to pay off the loan) but lower than the market rent.

Ten cities – Szczecin, Katowice, Bydgoszcz, Opole, Olsztyn, Rzeszów, Kielce, Zielona Góra, Białystok, Lublin.

Weighted average index – a measure reflecting housing price dynamics adjusted for location differences, (location is proved to be the most important price-influencing characteristic of a dwelling). Housing price dynamics is calculated independently for selected locations (districts) within each city, and then aggregated in the weighted average formula.

ZBP – Polish Bank Association.

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