Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
International developments in housing markets – lessons for Sweden E Philip Davis National Institute of Economic and Social Research Introduction • In this presentation we seek to give an overview of recent developments in housing markets for 12 OECD countries, via data and relevant research • We begin by noting key structural differences, before looking at developments in the crisis • We proceed to put these in a longer term context • And finally look at key implications of house prices for investment, consumption, public finance and financial stability/financial regulation Background – structural features • Housing markets cannot be treated as homogeneous • Population density is correlated with dwelling size and availability of land, although the latter is also affected by planning restrictions • Dwelling size and inhabitants per dwelling is indicators of living standards in terms of housing • Interest rate risk may affect both supply and demand for housing, and demand may also be affected by the prevalence of fixed rate loans Structure of housing markets Population Housing Dwelling size density (2005) density (2001) (2001) long real interest rate volatility(a) (persons per (per 1000 average m2 per sq km) inhabitants) capita 1980s 1990s 2000-2006 Australia 2.6 405 81.0 4.33 0.88 0.33 Canada 3.2 403 69.7 0.64 0.60 0.07 France 108.4 490 43.9 0.63 0.12 0.02 Germany 231.0 469 42.1 0.88 0.30 0.07 Italy 194.5 368(b) 35.0(b) 1.99 1.09 0.02 Netherlands 391.5 417 41.2 1.35 0.16 0.02 Spain 85.8 510 47.6 1.71 0.68 0.08 United Kingdom 246.3 431 36.4 1.08 0.55 0.09 United States 30.8 428 70.8 0.91 1.12 0.11 Floating rate debts as a proportion of disposable incomes 0.8 0.6 Germany 0.4 0.2 0 1 Italy Finland UK Sweden US 1.2 1.6 Spain Denmark 1.4 France 1 Neths 2 1.8 Ireland Personal sector borrowing cost vulnerability Recent house price developments • Boom-bust cycle in housing in a number of countries… • US housing credit linked to global crisis directly via falling CDO prices (note principal agent problem in US mortgage securitisation) • Since crisis, house price falls less marked than widely expected, recovery in some countries • Evidence of further financial distress with high level of arrears and repossessions in countries such as the US • Less so in those such as the UK as interest rates low and house price falls modest – and loans recourse based 20 01 -5 -10 -15 -20 Quarters 20 09 20 09 20 08 20 08 20 07 20 07 20 06 20 06 20 05 20 05 20 04 20 04 20 03 20 03 20 02 20 02 20 01 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Annual percent change Recent house price developments House prices since 2001 25 20 15 10 AUphi 5 CNphi FRphi 0 GEphi IRphi ITphi 20 01 Q 1 20 01 Q 3 20 02 Q 1 20 02 Q 3 20 03 Q 1 20 03 Q 3 20 04 Q 1 20 04 Q 3 20 05 Q 1 20 05 Q 3 20 06 Q 1 20 06 Q 3 20 07 Q 1 20 07 Q 3 20 08 Q 1 20 08 Q 3 20 09 Q 1 20 09 Q 3 20 10 Q 1 Annual percent change Recent house price developments House prices since 2001 30 25 20 15 JPphi 10 NLphi SDphi 5 SPphi UKphi USphi 0 -5 -10 -15 Quarters Latest “Economist” Data Country Year on year Country Year on year change change Australia 18.4 Japan -3.4 Canada 4.5 Netherlands 4.2 France 6.0 Sweden 8.9 Germany 4.8 Spain -4.0 Ireland -17.0 UK 3.0 Italy -2.8 US -4.9 (FHFA) 3.6 (CSNI) A longer term perspective • Boom in house prices following liberalisation in the 1980s, often leading to banking crises… • Long term rise in real house prices (higher income, shortage of land) – implicit intergenerational transfers (Weale 2007) • Rise in debt-income ratios to households correlated with rise in house prices (house purchase but also equity extraction) • But credit should not drive house prices in liberalised financial system (conventional determinants are income, interest rates, supply conditions, demographics, see e.g. Muellbauer and Murphy 1997)) House price inflation since 1980 House price inflation 50 40 AUhpinfl 20 CNhpinfl FRhpinfl GEhpinfl IRhpinfl 10 IThpinfl -10 -20 Years 20 08 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 0 19 80 Annual percentage change 30 House price inflation since 1980 House price inflation 50 40 JPhpinfl 20 NLhpinfl SDhpinfl SPhpinfl UKhpinfl 10 UShpinfl -10 -20 Years 20 08 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 0 19 80 Annual percent change 30 Real house prices Real house prices (1980=100) 350 300 250 AUrph CNrph Index 200 FRrph GErph 150 IRrph ITrph 100 50 Years 20 08 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 19 80 0 Real house prices Real house prices (1980=100) 400 350 300 250 JPrph SDrph 200 SPrph UKrph 150 USrph 100 50 Years 20 08 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 0 19 80 Index NLrph Debt-income ratios Household debt/income ratios 250 200 AUdyr 150 Percent CNdyr FRdyr GEdyr IRdyr 100 ITdyr 50 Years 20 08 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 19 80 0 Debt-income ratios Household debt-income ratios 300 250 200 JPdyr SDdyr 150 SPdyr UKdyr USdyr 100 50 Years 20 08 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 0 19 80 Percent NLdyr Housing and investment • Housing investment typically a small proportion of the stock, given houses are long-lived assets • Overall housing investment has tended to decline as a proportion of GDP in a number of countries, even before 2008/9 when sharp falls especially Spain and Ireland • Key determinant Q ratio (house prices/housing investment deflator) (Jud and Winkler (2003), Berg and Berger (2005)) • Correlation of house price change to investment/GDP change in 2008/9 is 0.73 Housing investment/GDP Housing investment/GDP ratios 16 14 12 10 AUiy FRiy 8 GEiy IRiy 6 ITiy 4 2 Years 20 08 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 0 19 80 Percent CNiy Housing investment/GDP Housing investment/GDP ratios 12 10 8 JPiy SDiy 6 SPiy UKiy USiy 4 2 Years 20 08 20 06 20 04 20 02 20 00 19 98 19 96 19 94 19 92 19 90 19 88 19 86 19 84 19 82 0 19 80 Percent NLiy 1991-1995 1996-2000 2001-2006 US UK Spain Netherlands Germany France Canada Australia ave. annual percentage change Q ratios for housing in upturn 10 8 6 4 2 0 -2 -4 -6 House prices and consumption • Research on wealth effect shows strong link from house prices/housing wealth to consumption (e.g. Barrell and Davis (2007), Case et al (2005)), although effect on nonhomeowners should partly offset • Simple cross section regression shows house prices discriminated the falls in consumption between 2008/3 and 2009/4 better than equity prices, although RPDI and lagged debt/income also relevant • Collateral effect likely intensified by credit rationing, but banking crisis dummy not significant Change in consumption 2009/4 over 2008/3 • • • • • • • • • • • • • • • • • • • • • • • • • Dependent Variable: DC Method: Least Squares Date: 10/12/10 Time: 13:37 Sample: 1 12 Included observations: 11 Variable Coefficient Std. Error t-Statistic Prob. DPH DRPDI LDY DEQP 0.092604 0.224692 0.005645 0.058024 2.796035 2.183794 -2.020971 -0.448169 0.0267 0.0653 0.0830 0.6676 0.258924 0.490681 -0.011408 -0.026005 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood 0.752215 0.646022 1.674003 19.61600 -18.78980 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Durbin-Watson stat -0.942513 2.813637 4.143600 4.288289 2.391862 Housing and fiscal position • NIER (2010) decomposed deterioration in fiscal position into cycle, policy changes, bank support and residual • Residual linked partly to revenue from financial sector but also housing market • Falling house prices affect tax revenues directly (via stamp duties and profits of construction/realtor sector) and indirectly (via consumption taxes – to the extent consumption fell more than in a normal cycle) House prices and deficits 6 House price growth 2009 4 2 Portugal Finland Germany Sweden 0 Italy Belgium -2 Canada Japan Netherlands Greece US -4 -6 France Spain -8 United Kingdom -10 -12 Ireland Denmark -14 -9 -8 -7 -6 -5 -4 -3 -2 Residual category of the deficit (% of GDP) -1 0 1 House prices and banking crises • Barrell, Davis, Karim and Liadze (2010) in JBF and subsequent work were first to find role for bank capital and liquidity in OECD crisis models • House price bubbles matter • Sustained deficits matter • Using logit model together with a banking sector sub-model of NiGEM global macro model enabled assessment of overall costs and benefits of regulation in the UK – optimal level of tightening (Barrell et al (2009) FSA OP) • Recent work looks at the split between on balance sheet and other revenues (OBS) • Level of OBS does not matter as it varies across countries a lot • Faster growth of OBS activity boosts crisis probabilities Calibrating macroprudential surveillance • In “Calibrating macroprudential surveillance” we put in all ‘normal’ variables including lagged house price rises and test down with 14 OECD countries, 12 crisis and data for 1980 to 1997 (vastly shorter sample than earlier work) • As in earlier work, found that “traditional” variables such as credit growth, output growth and M2/reserves less relevant to OECD – artefact of dominance of global samples by emerging markets • A researcher undertaking this work in the late 1990s could have picked the same equation Explaining OECD Financial Crises • We explain crisis probabilities (logit) in OECD 1980-1997 Pr obYit 1 F X it e 'Xit 1 e 'Xit Box 1: List of Variables (with variable key) Variables used in previous studies: Demirguc-Kunt and Detragiache (2005); Davis and Karim (2008). Variables introduced in JoBF. This paper 1. Real GDP Growth (%) (YG) 2. Real Interest Rate (%) (RIR) 3. Inflation (%) (INFL) 4. Fiscal Surplus/ GDP (%) (BB) 5. M2/ Foreign Exchange Reserves (%) (M2RES) 6. Real Domestic Credit Growth (%) (DCG) 7. Liquidity (%) (LIQ) 8. Leverage (%) (LEV) 9. Real Property Price Growth (%) (RHPG) 10 Current Balance as % GDP (CBR) Nested testing of the crisis model, 19801997 Step (1) -0.339 (1.7) (2) -0.339 (1.8) (3) -0.348 (1.9) (4) -0.347 (1.9) (5) -0.417 (2.9) (6) -0.345 (2.7) (7) -0.384 (3.2) NLIQ(-1) -0.106 (1.8) -0.106 (1.9) -0.108 (2.0) -0.113 (2.2) -0.126 (2.7) -0.104 (2.5) -0.105 (2.6) RHPG(-3) 0.091 (1.9) 0.091 (1.9) 0.089 (1.9) 0.095 (2.4) 0.09 (2.4) 0.086 (2.3) 0.081 (2.1) CBR(-2) -0.434 (2.3) -0.434 (2.3) -0.441 (2.4) -0.438 (2.4) -0.418 (2.3) -0.3 (1.9) -0.333 (2.2) DCG(-1) -0.101 (1.5) -0.101 (1.6) -0.1 (1.6) -0.1 (1.5) -0.108 (1.7) -0.053 (1.0) YG(-1)) 0.277 (1.5) 0.277 (1.5) 0.274 (1.4) 0.279 (1.5) 0.29 (1.5) RIR(-1) -0.054 (0.3) -0.055 (0.6) -0.055 (0.6) -0.06 (0.7) BB(-1) 0.022 (0.2) 0.02 (0.2) 0.023 (0.2) -1.51E-05 (0.2) -1.52E-05 (0.2) LEV(-1) M2RES(-1) INFL(-1) -0.0012 (0.1) Model character • Up to four lags tried in house prices, credit growth, current account and GDP growth – Cyclical variables drop out – Lending growth drops out • Lending quality matters with house price growth and current balances as indicators Estimated Equation Dep=0 Dep=1 Total 143 3 146 55 9 64 Total 198 12 210 Correct 143 9 152 % Correct 72 75 72 % Incorrect 28 25 28 P(Dep=1)< 0.057 P(Dep=1)> 0.057 9 out of 12 crises called Almost half of false calls precede crises Using the model in macroprudential surveillance setting • Forecasts over 1998-2008, using actual for RHS (bold exceeds sample mean) BG CN DK FN FR GE IT JP NL NW SD SP UK US 1998 0.005 0.032 0.015 0.004 0.025 0.026 0.001 0.071 0.020 0.011 0.019 0.005 0.049 0.025 1999 0.004 0.054 0.041 0.006 0.018 0.027 0.002 0.025 0.018 0.006 0.016 0.006 0.060 0.032 2000 0.003 0.056 0.060 0.011 0.012 0.029 0.002 0.009 0.050 0.039 0.034 0.010 0.088 0.044 2001 0.004 0.033 0.046 0.007 0.014 0.045 0.009 0.010 0.049 0.016 0.048 0.028 0.173 0.074 2002 0.009 0.018 0.048 0.000 0.040 0.058 0.017 0.007 0.157 0.001 0.039 0.043 0.203 0.081 2003 0.005 0.022 0.029 0.000 0.028 0.031 0.020 0.007 0.141 0.001 0.058 0.044 0.201 0.067 2004 0.007 0.026 0.043 0.000 0.032 0.016 0.026 0.003 0.079 0.006 0.017 0.047 0.115 0.103 2005 0.014 0.037 0.030 0.004 0.053 0.020 0.039 0.002 0.028 0.003 0.006 0.096 0.207 0.064 2006 0.025 0.030 0.042 0.002 0.100 0.007 0.034 0.001 0.017 0.002 0.009 0.266 0.282 0.075 2007 0.048 0.036 0.030 0.007 0.193 0.007 0.054 0.001 0.019 0.001 0.011 0.516 0.277 0.097 2008 0.070 0.042 0.113 0.008 0.218 0.007 0.019 0.002 0.007 0.001 0.008 0.580 0.254 0.125 Using the model in macroprudential policy setting • We can invert the probability model to calculate the additional levels of liquidity and leverage required for the probability of a crisis to be 0.01 in each country and year – Re-estimate each year from 1997, predict one year – Raise capital and liquidity to get probability 0.01 • Capital and liquidity form the defences, while house prices and current balances are the problems we need to provision against, not cycles or credit. • Separate result shows credit does not Granger cause OECD house prices either (except Belgium, Canada and Finland) Country and aggregate targets • Country max reduces probability to 0.01 in worst year • The average of these could be used as a criterion • Major cross country differences in warranted tightening Column Top Panel Belgium Canada Denmark Finland France Germany Italy Japan Neths Norway Sweden Spain UK US Mean (International Benchmark) SD 1 2 Additions to country specific levels of liquidity and leverage to reduce all prob. to 0.01 or below* lev+nliq lev alone 2.11 2.56 3.31 4.15 3.35 4.15 0.00 0.00 5.08 6.25 3.12 3.79 1.74 2.14 3.96 5.19 4.72 5.80 2.34 2.87 2.38 2.90 9.32 11.48 6.08 7.63 4.35 5.34 3.70 2.24 4.59 2.77 3 4 Under or overshoot (column 1 3.7) lev and nliq -1.59 -0.39 -0.35 -3.70 1.38 -0.58 -1.96 0.26 1.02 -1.36 -1.32 5.62 2.38 0.65 (column 2 4.59) lev -2.03 -0.44 -0.44 -4.59 1.66 -0.80 -2.45 0.60 1.21 -1.72 -1.69 6.89 3.04 0.75 Countercyclical provisioning • Has to be calibrated on house prices and current account and not credit or output gap – example of 5% higher house price growth France 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Spain UK US Regulatory adjustment Actual RHPG (-3) Regulatory adjus tment Actual RHPG (-3) Regulatory adjustment Actual RHPG (-3) Regulatory adjustment Ac tual RHPG (-3) 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.7 2.2 3.7 4.0 -3.2 1.3 0.8 1.7 7.5 6.2 6.1 7.2 10.0 13.4 13.6 0.0 0.0 0.0 0.0 0.3 0.4 0.5 2.1 4.6 6.8 7.3 -0.1 -1.7 0.0 3.8 5.3 4.7 6.1 12.5 14.1 13.4 10.2 0.6 1.0 1.9 3.5 3.8 3.8 2.5 3.9 4.8 4.7 4.4 -2.5 0.2 6.2 8.9 9.5 13.7 6.1 14.3 13.9 10.1 3.0 0.0 0.0 0.4 1.5 1.7 1.2 2.2 1.1 1.5 2.1 2.7 0.8 1.5 1.8 4.2 3.1 4.0 5.4 4.9 4.3 6.7 8.4 Decomposing changes in crisis probabilities France 2004 2005 2006 2007 2008 Sum of changes Contribution to change in probability Probability NLIQ LEV RHPG CBR DOFFTOON 0.006 0.046 0.131 0.106 0.895 na na 0.007 0.011 0.016 -0.000 0.034 na 0.005 0.030 -0.008 0.013 0.040 na 0.004 0.023 0.024 0.001 0.051 na 0.006 0.006 0.027 0.001 0.039 na 0.036 0.044 -0.126 0.775 0.729 Spain 2004 2005 2006 2007 2008 Sum of changes Adj for Change in Interaction probability na 0.017 0.030 -0.043 -0.000 0.004 na 0.040 0.085 -0.025 0.789 0.889 Contribution to change in probability Probability NLIQ LEV RHPG CBR DOFFTOON 0.035 0.067 0.173 0.398 0.479 na na 0.022 0.031 0.065 -0.021 0.097 na -0.012 0.040 0.044 0.016 0.089 na 0.026 0.017 -0.013 -0.063 -0.033 na 0.004 0.055 0.120 0.098 0.277 na -0.009 -0.007 0.045 0.050 0.079 Adj for Change in Interaction probability na -0.001 0.030 0.037 -0.001 0.064 na 0.032 0.106 0.225 0.081 0.444 Decomposing changes in crisis probabilities UK 2004 2005 2006 2007 2008 Sum of changes Contribution to change in probability Probability NLIQ LEV RHPG CBR DOFFTOON 0.116 0.241 0.442 0.292 0.253 na na 0.002 0.009 -0.002 0.010 0.020 na 0.010 0.057 0.024 0.026 0.118 na 0.099 -0.008 -0.066 -0.119 -0.094 na -0.007 0.031 0.026 0.036 0.087 na 0.035 0.127 -0.135 -0.007 0.020 US 2004 2005 2006 2007 2008 Sum of changes Adj for Change in Interaction probability na 0.015 0.016 -0.003 -0.015 0.013 na 0.125 0.201 -0.151 -0.038 0.137 Contribution to change in probability Probability NLIQ LEV RHPG CBR DOFFTOON 0.074 0.045 0.043 0.064 0.087 na na -0.017 0.002 0.002 0.004 -0.008 na -0.015 -0.000 -0.008 0.004 -0.019 na -0.002 -0.002 0.011 0.010 0.017 na 0.004 0.006 0.008 0.002 0.019 na 0.003 -0.009 0.010 0.004 0.008 Adj for Change in Interaction probability na 0.001 -0.001 0.002 0.002 0.004 na -0.029 -0.002 0.021 0.023 0.013 Conclusion • Caution needed in directly comparing housing markets due to structural differences • Housing finance clearly at core of recent financial crisis – US housing loans packaged into CDOs and recent defaults following price falls • Falls in house prices can be related inter alia to changes in consumption, housing investment and fiscal deficits since the crisis • And clear relation of lagged house price increases to OECD banking crises – relevant to ongoing bank regulation reform also • Key lesson for Sweden is to avoid boom-bust cycle in housing, given macroeconomic volatility and systemic financial risk it generates – and long term intergenerational implications • Control could be via appropriate monetary and macroprudential policies (including control of LTVs) – possibly also planning regulations • If using securitisation ensure system is transparent and incentive compatible • Ensure banks have sufficient capital as well as countercyclical reserves based on trends in house prices (not credit per se)