1. House Prices Bubbles and their Determinants in the Czech Republic and its Regions Luboš Komárek and Michal Hlaváček Czech National Bank Prague Based on CNB WP 12/2009 The views expressed in this presentation are not necessarily those of the Czech National Bank.

2. How we see our house….

3. ... as seen by those interested in buying it,...

4. ... as seen by your bank,...

5. ... as seen by an appraiser...

6. ... and how the tax office sees it

7. 7 O U T L I N E 1. Why to study house prices? 2. Factors influencing house prices 3. Sources of house price data in the Czech Republic 4. Empirical analysis 4.1 Simple indicators 4.2 Time series analysis (the CR and Prague) 4.3 Panel Analysis (by districts) 5. Conclusion

8. 8 1. Why study house prices? International comparision Until 2006- low price growth similar to GER or AT, 2007 renewed growth In 2008- growth of prices in the CR despite price drops in the USA, Ireland, UK, Spain, 2009 further price drops House prices of our neighbors/ trade partners/ similar countries

9. 9 Why to study house prices? (II) Role of house price bubbles and mortgage loans in recent financial crisis- Could this happen in the CR? Macroeconomic impacts of bursting of such bubbles are higher than for bubbles for other asset classes (e.g. stocks) because these effects: (i) last longer (4 Y compared 1.5 Y for stock market), (ii) present larger threat for the FS of giver country/region because house prices a) form the biggest part of HH wealth b) influence HH consumption via wealth effect b) function as collateral in balances of banking sector

10. 10 1. Why study house prices? Impact to the Czech Republic High growth of house prices in 2H2006-2008 Growth of household loans for house purchases Long horizon of those loans- increased probability of mis-pricing, change of conditions of HH, … House prices might influence PD and LGD Record housing construction Dynamics of loans to developers- again risk to banks Potential mutual relationship between housing prices and housing loans

11. 11 1. Why study house prices? Complications for the analysis Complications for house price analysis Standard problems: market heterogeneity (size, location, depreciation…), lower quality of data Transitive problems: converge character of the Czech Economy (catching-up effect), development of the mortgage market, increases im housing quality, distortion effects arising from rent deregulation

12. 12 2. Factors D etermining H ousing P rices Supply factors (conditional on profitability of construction industry; Supply inelastic in the short term): Saturation of housing needs and its dynamics (number of existing and newly finished apartments; (-) Cost factors (building plots prices; building construction costs); (+) Demand factors: Disposable income of households (wage); (+) Unemployment rate (-) Ratio of economic activity, number of vacancies (+) Demographic factors: Divorces (+), marriages (+), natural population growth and migration (+) Financial market development (+) Interest rate (-) Rents (+)

13. 13 3. Sources of Housing Price Data in the CR Two basic types of data: Transfer prices: CZSO- from 1998, but time lag Supply prices: CZSO, IRI, Dolanský (Realit), King Sturge Tax evasion vs. Unrealistic advertisements, Completeness, Averages vs. Selected prices vs. Hedonic indexes

14. 14 House Price variability and the variability of its possible determinants is often higher across regions than across time. 3. Sources of Housing Price Data in the CR

15. 15 4.1 Empirical analysis Simple indicators of house price sustainability: Rental Return Rental return is inverse value to price-to-rent ratio 2007/08- Due to increase of prices decrease of the rent returns …despite increase of yields by alternative assets and interest of house purchase loans 2009/10- situation better

16. 16 Decrease of ratio in 2003-2006- due to wage growth 2007/8- Price growth higher than growth of wages Regions with lower wages have lower price-to-income ratio Prague as the most risky region. 4.1 Empirical analysis Simple indicators of house price sustainability: Price-to-Income

17. 17 4. Empirical Analysis 4.2 Time series analysis: ov erall regression statistics for the CR and for Prague Period of: 1998 Q1 – 2009 Q2, 46 Q observations, differences, real variables

18. 18 4. Empirical Analysis 4.2 Time series analysis: ov erall regression statistics for the CR and for Prague Period of: 1998 Q1 – 2009 Q2, 46 Q observations, differences, real variables

19. 19 4. Empirical Analysis 4.3 Panel data analysis: compared to OLS on differences (whole CR)

20. 20 4. Empirical Analysis 4.3 Panel data analysis: o verall regression statistics for the CR and for Prague Panel regression across regions Apartment price overvaluation relative to apartment price (average residual for 1998-2008)

21. 21 5. Conclusion House Price determinants Demographic factors: confirmation of positive influence of net population growth and partly also migration and divorces. Supply Factors: mixed evidence- significant building plots prices. Demand Factors: significant influence of wage growth and rents, partly unemployment. Our estimate identified (in line with expectations) a bubble in house prices for 2002/03 and for 2007/08. However, in the second period the level of overvaluation much lower despite similar house price dynamics in both periods. Panel regression has shown that regions with higher prices are more likely to be over-valued. … with the exception of Prague..

22. Thank you for your attention! www.cnb.cz Luboš Komárek Czech National Bank lubos.komarek@cnb.cz Michal Hlaváček Czech National Bank michal.hlavacek@cnb.cz

23. 23 4. Empirical Analysis 4.3 Panel data analysis: Panel Unit Root Tests (Hadri Test) Period of: 1998-2008, 11 Y observations across 13 regions of the CR

24. Determining the equilibrium prices is tough task