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Asymmetries in the interaction between housing prices and housing credit in Estonia

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Juan-Carlos Cuestas, Merike Kukk.
19th June 2017

Published in: Economy & Finance
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Asymmetries in the interaction between housing prices and housing credit in Estonia

  1. 1. Motivation Literature Data Results Final comments Asymmetries in the interaction between housing prices and housing credit in Estonia Juan-Carlos Cuestas Merike Kukk 19th June 2017 Cuestas & Kukk Housing prices and housing credit 1 / 20
  2. 2. Motivation Literature Data Results Final comments Table of contents 1 Motivation Theoretical background 2 Literature Research question 3 Data 4 Results 5 Final comments Cuestas & Kukk Housing prices and housing credit 2 / 20
  3. 3. Motivation Literature Data Results Final comments Theoretical background Motivation Figure: The dynamics of real house prices Cuestas & Kukk Housing prices and housing credit 3 / 20
  4. 4. Motivation Literature Data Results Final comments Theoretical background Motivation Figure: Estonia: Household sector’s debt-to-disposable income ratio (%) Cuestas & Kukk Housing prices and housing credit 4 / 20
  5. 5. Motivation Literature Data Results Final comments Theoretical background Motivation The big question we try to answer is: What is the interrelation between housing prices and domestic credit in Estonia? Estonia is an interesting case study: one of the countries with the highest growth and drop in housing prices, real terms, during 2000-2015, one of the countries with the highest growth in debt-to-disposable income ratio, and one of the countries with the highest degree of banking sector concentration in Europe. Cuestas & Kukk Housing prices and housing credit 5 / 20
  6. 6. Motivation Literature Data Results Final comments Theoretical background Theoretical background House prices → credit: The higher the prices, the larger amounts are needed to purchase real estate Housing wealth effect → borrow to smooth consumption (Carroll et al., 2011) Collateral effect → housing equity withdrawal (Muellbauer, 2010) Asset allocation choice: Residential investment → higher demand for real estate (Piazzesi and Schneider, 2016). Credit supply channel: Via the balance sheet of banks (Chen 2001) Cuestas & Kukk Housing prices and housing credit 6 / 20
  7. 7. Motivation Literature Data Results Final comments Theoretical background Theoretical background Credit → House prices: Increase in the availability of credit increases demand for housing if households have constraints in borrowing (Muellbauer et al., 2015) Increase in credit supply → lower interest rate → higher expected returns on property and an increase in the demand of housing (Goodhart & Hofmann, 2008) ⇒ the effect on house prices depends on the elasticity of housing supply Cuestas & Kukk Housing prices and housing credit 7 / 20
  8. 8. Motivation Literature Data Results Final comments Research question Brief literature review Papers on house prices ⇔ credit Most papers on one country: Finland (Oikarinen, 2009), Ireland (Fitspatrick & McQuinn, 2007), Spain (Martinez-Carrascal, 2010, and Cuestas, 2017), Greece (Brissimis & Vlassopoulos, 2009), Norway (Anundsen & Jansen, 2013), Sweden (Turk 2015), Hong Kong (Gerlach & Peng, 2005), China (Liang & Cao, 2007). Long time series (20-30 years) → VECM framework In all studies the sample period is until the recession, the only study covering more recent period is Turk (2015) on Sweden. Although there is mixed evidence, still more evidence for housing prices → credit growth than for credit growth → housing prices Cuestas & Kukk Housing prices and housing credit 8 / 20
  9. 9. Motivation Literature Data Results Final comments Research question Research question Literature focuses mainly on developed countries (particularly OECD countries) → What is the empirical evidence for countries with high debt accumulation? What is the relationship between house prices and new loans for Estonia? Are there other factors/fundamentals which may have fueled housing prices? Are there any asymmetries in the effect from new loans to house prices? Cuestas & Kukk Housing prices and housing credit 9 / 20
  10. 10. Motivation Literature Data Results Final comments Data Variables: Log of real house price index deflated by the HICP. Log of new housing loans in real terms, deflated by the HICP (Fitspatrick & McQuinn, 2007). Log of labour income deflated by HICP (Gimeno & Martinez-Carrascal, 2010). The main alternative is GDP as a proxy for economic activity (Hofmann, 2004, Liang & Ciao, 2007, Gerlach & Peng, 2005, Oikarinen, 2009, Brissimis & Vlassopoulos, 2009). We have also tested with disposable income and average wage. Cuestas & Kukk Housing prices and housing credit 10 / 20
  11. 11. Motivation Literature Data Results Final comments Data Nominal interest rate for housing loans divided by 100 (Gimeno & Martinez-Carrascal, 2010). Real interest rate has also been tested. Log of completed new dwellings (Gerlach & Peng, 2005, Fitspatrick & McQuinn, 2007). An alternative variable is stock of dwellings (Anundsen & Jansen, 2013, Turk, 2015) Consumer confidence indicator to capture expectations (Anundsen & Jansen, 2013) Cuestas & Kukk Housing prices and housing credit 11 / 20
  12. 12. Motivation Literature Data Results Final comments Empirical analysis Data: 2000/Q1-2015/Q4. Some variables have been seasonally adjusted using the X13 procedure. Method: (Structural) Bayesian VAR, we have also tested VECM and VAR. Cholesky, ordering as follows: labour income, confidence, new dwellings, house prices, new loans, interest rates. (This has been borrowed from the literature, Hofmann, 2004, and Goodhart and Hofmann, 2008) Cuestas & Kukk Housing prices and housing credit 12 / 20
  13. 13. Motivation Literature Data Results Final comments Figure: Estonia: The dynamics of new loans and house prices (in real terms) Cuestas & Kukk Housing prices and housing credit 13 / 20
  14. 14. Motivation Literature Data Results Final comments Cuestas & Kukk Housing prices and housing credit 14 / 20
  15. 15. Motivation Literature Data Results Final comments Cuestas & Kukk Housing prices and housing credit 15 / 20
  16. 16. Motivation Literature Data Results Final comments 1 Splitting the sample in 2008 and testing the relationships before and after the crisis gives unreliable results due to the the small number of observations and the corresponding reduction in degrees of freedom. 2 We propose to split the credit TURNOVER variable in two: increases and decreases of turnover as follows (Goodhart & Hofmann, 2008, Shin et al, 2014, Schorderet, 2001) turnover+ t = T j=1 max(∆turnovert, 0) turnover− t = T j=1 min(∆turnovert, 0) Cuestas & Kukk Housing prices and housing credit 16 / 20
  17. 17. Motivation Literature Data Results Final comments Cuestas & Kukk Housing prices and housing credit 17 / 20
  18. 18. Motivation Literature Data Results Final comments Conclusions In Estonia, house prices had a positive impact on housing credit in 2000-2015, and viceversa. The effect from housing credit to housing prices is found to be stronger for the period of declining turnover of housing credit. The reaction of credit turnover to shocks to house prices seems to be stronger in periods of increasing turnover. House prices and housing credit are also affected by real labour income and confidence. Cuestas & Kukk Housing prices and housing credit 18 / 20
  19. 19. Motivation Literature Data Results Final comments Conclusions In line with the results obtained in the papers analysing fiscal and monetary policy shocks on GDP during expansions and recessions. Message: during good times increase the credit buffers so they can be released during bad periods. (Similar pattern in Lithuania. However, it is difficult to detect asymmetries.) (In Latvia, an increase in the loan stock related to the increase in house prices...) Cuestas & Kukk Housing prices and housing credit 19 / 20
  20. 20. Motivation Literature Data Results Final comments Thank you! Cuestas & Kukk Housing prices and housing credit 20 / 20

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