Macroeconomics

1
Has There Been a British House Price Bubble?
Evidence from a regional panel
Thursday 3 November 2005
Anthony Murphy John Muellbauer Gavin Cameron
2
trends in real long-term interest rates

• World monetary policy has been extraordinarily
  relaxed since 2000, with interest rates falling
  to around 0 in Japan, 1 in the USA and 2 in
  Euroland.
• But short-term interest rates have now rising in
  the UK, USA, Australia and Canada, with the
  markets predicting further monetary tightening
  over the next two years.
• Meanwhile, in Japan and Europe, limited signs of
  economic recovery and some inflationary pressure
  have not yet led to any decisive moves in
  monetary policy.
• Real long-term interest rates remain low 10
  year US Treasury securities yield 4.57 in
  nominal terms, and 10 year indexed yields are 2.
• Possible explanations for continue low long-term
  rates global saving glut global investment
  shortfall excess liquidity heightened appetite
  for risk (qv. the Greenspan put).

3
Source Nickell (2005).
4
real house prices since 1970

• Source BIS Quarterly Review, March 2004.

5
a view from the top

• Thus, this vast increase in the market value of
  asset claims is in part the indirect result of
  investors accepting lower compensation for risk.
  Such an increase in market value is too often
  viewed by market participants as structural and
  permanent. To some extent, those higher values
  may be reflecting the increased flexibility and
  resilience of our economy. But what they perceive
  as newly abundant liquidity can readily
  disappear. Any onset of increased investor
  caution elevates risk premiums and, as a
  consequence, lowers asset values and promotes the
  liquidation of the debt that supported higher
  asset prices. This is the reason that history has
  not dealt kindly with the aftermath of protracted
  periods of low risk premiums, Alan Greenspan,
  August 2005.

6
bubbles in theory

• Many theoretical arguments have been advanced to
  justify rational bubbles in asset markets,
  although this is not the focus of our paper. For
  example
• The survival of noise traders in financial
  markets limits to arbitrage prevent rational
  traders from driving noise-traders out of the
  market (De Long, Shleifer, Summers, Waldmann,
  1990).
• Asset markets are micro-efficient but
  macro-inefficient (Samuelson, 1998).
• Global games dissatisfaction with common
  knowledge assumptions leads to games of
  incomplete information whose type space is
  determined by the players each observing a noisy
  signal of the underlying state. Differences
  between public and private information can drive
  selection between multiple equilibria (Morris and
  Shin, 2002).

7
features of good regional house price models

• Regional house price models useful to address
• The ripple effect from Greater London and the
  South East to the rest of Britain
• Housing affordability in different regions
• Policy issues relating to housing supply and
  migration.
• Meen and Andrews (1998) suggest these features
• Data-consistency, economic interpretation
• Spatial lags, errors, coefficient heterogeneity
• Plausible estimates of income and price
  elasticities
• Clear implications for housing market efficiency
• Explanation of the ripple effect and
  demographics.

8
preview of the model

• We estimate an annual econometric model of
  regional house prices for the 9 regions of Great
  Britain between 1972 and 2003. The model is a
  system of inverted demand equations with the
  predetermined housing stock as an explanatory
  variable along with regional income, real and
  nominal interest rates, demographics and other
  demand shifters.
• Our approach contrasts somewhat with two other
  recent approaches (structural time-series
  modelling, focussing on unit roots and
  cointegration and models of house price to
  rental ratios).
• Our model can be viewed as an equilibrium-correcti
  on model with positive effects from recent rises
  in house prices (the so-called bubble-builder
  effect) and negative effects from high levels of
  real house prices relative to their fundamentals
  (the so-called bubble-burster effect).

9
the Nickell version

• This discussion leads us to conclude that there
  has probably been a substantial rise in the
  equilibrium house price to earnings ratio since
  the mid-1990s. Of course, there is a good deal
  of uncertainty here, but it is clear that it may
  be legitimately argued that there has been no
  housing bubble whatever, speech to the B.A.
  September 2005.
• Equilibrium level of UK house prices has risen
  for four reasons
• Strong income growth (more two-earner households,
  more income inequality)
• Low elasticity of housing supply response
• Strong population growth and net household
  formation
• Low real interest rates and the disappearance of
  front-end loading.

10
Source Nickell (2005).
11
Source Council of Mortgage Lenders (2005).
12
The ABC of house price determination

• An inverted demand equation suppose real house
  prices adjust to equate log demand with log of
  end of previous period supply, h(-1).
• Let log housing demand be given by h -?rp y
  z , rp log house price and y log real
  income and z other demand shifters. The own
  price elasticity of demand is -? and we assume
  the income elasticity is 1. Solving yields
• rp (y h(-1) z)/ ?.
• Note log (income per house) restriction.
• Consensus that ? is approx 2.
• z will include interest rates, demographics,
  expectations of rate of return or user cost, etc.

13
Modelling Regional House Prices

• We model real house prices in eight regions of
  Great Britain the North (NT), Yorkshire and
  Humberside (YH), East Midlands (EM), West
  Midlands (WM), Greater London (GL), the South
  (ST), the South West (SW), Wales (WW) and
  Scotland (SC).
• The choice of regions is determined by the need
  for consistent regional boundaries since the
  government switched from Standard Statistical
  Regions (SSRs) to Government Office Regions
  (GORs) in the mid 1990s.

14

• The regions experienced broadly comparable long
  run movements. Greater London is considerably
  more expensive than the other regions.

15

• The heterogeneity in house price inflation is
  more obvious.
• The leading role of Greater London house prices
  and the tendency of house prices in the North to
  lag further behind those in the West Midlands are
  clear.
• So called ripple effect.

16
Modelling

• We estimate a reasonably standard system of
  inverted housing demand equations.
• We use SUR to take account of contemporaneous
  spatial correlations.
• The equations are non-linear with many
  cross-equation restrictions, because of common
  parameters, and interaction terms.
• Some spatial coefficient heterogeneity is allowed
  for.
• We use annual data from 1972 to 2003.
• Details of the model used and the SUR parameter
  estimates are set out in the Appendices to paper.

17
Long Run Effects

• The long-run solution is for lrhpr, the real log
  level of house prices in region r.
• The key element in the long-run solution is the
  log of real personal disposable non-property
  income per house, the same as in Geoff Meens
  work.
• For region r, we call this lrynhsr defined as
• log(real non-property income) - log(housing
  stock)-1 - 0.7log(rate of owner-occupation)-1 in
  region r.
• The owner-occupation term implies a modest
  spill-over from non-owner occupied supply onto
  the owner-occupied housing market.

18

• lrynhsr is really a combination of three terms.
• The log per capita (or household) income and
  housing stock terms have equal but opposite
  signs.
• Population (or the number of households) is
  implicit in this formulation it just cancels
  out on both sides.
• All regions are influenced not just by the own
  region value of income per house lrynhsr but also
  by the GB value, lrynhsGB,with weights 0.3 and
  0.7 respectively
• The long-run effect of log real income per house
  on the log real house price is 2 in line with
  previous studies.
• The speed of adjustment is 0.25, meaning that
  about three quarters of the adjustment to an
  income shock is completed within four years.

19
Other Long Run Levels Effects

• Region specific intercepts and (small positive )
  time trends.
• The log price of house prices in London relative
  to GB (rlhpGL) which we allow to vary by region.
  This has a positive effect in the regions
  adjoining Greater London, capturing some of the
  role of London as the driver of UK house prices.
• An index of credit conditions (cci) which
  measures credit supply to UK households.
• The interaction of cci with both the log nominal
  mortgage rate (labmr) and the real mortgage rate
  (rabmr).
• The interest rate effect are consistent with
  findings for mortgage demand by
  Fernandez-Corugedo and Muellbauer (2005).

20
Other Long Run Levels Effects

• A reduction of rates from 5 to 4 has a stronger
  effect on house prices than a reduction from 10
  to 9.
• Nominal interest rate effects are also a little
  stronger in London and the South.
• We proxy downside risk using rrhnegr the average
  value over the previous 4 years of the negative
  return in the regions housing market. rrhnegr is
  significant which means that a history of
  negative returns depresses house prices for some
  time to come.
• Possessions not significant given rrhnegr.

21
Some Short Run Effects

• Short run effects include house price and income
  dynamics as well as changes in nominal interest
  rates, the housing stock, population structure
  inter alia.
• There is persistence in house price inflation.
  The estimated coefficient on the previous years
  house price growth rate is about 0.45.
• We allow the relative weight attached to house
  price inflation in the own region (?lrhpr,-1), in
  contiguous regions (?clrhpr,-1) and in Greater
  London (?lrhpGL,-1) to vary by region.
• Generally speaking, regions closer to London have
  the largest weights on London house price growth,
  reflecting the ripple effect emanating from
  London.

22

• Income dynamics are important.
• Outside London and the South East, the estimated
  coefficient on current rate of growth of national
  disposable non-property income (?lrpdin) is about
  0.66.
• In London and the South East the estimated income
  growth coefficients are higher.
• As expected, the effect decline over time as
  credit conditions (proxied by cci) have improved.
• The previous years income growth rate
  (?lrpdin-1) has an estimated coefficient of about
  0.56.
• Region specific income growth rates have little
  explanatory power.
• Surprising? Common trends. Regional A/Cs income
  data very poor.

23

• The question of stock and flow equilibrium
  effects on house price determination is
  important.
• The stock equilibrium effect enters through the
  log income per house variables, lrynhsr and
  lrynhsGB, discussed above.
• A flow equilibrium can be examined through the
  effects of housing stock changes and population
  changes.
• The idea is that short term increases in the
  housing stock relative to population lead to
  short-term local excess supply, with downward
  pressure on local prices.
• We measure this effect by including
  ?log(wpopr/hsr,-1) in each regions equation.
• We find a significant effect, suggesting that a 1
  percent rise in working age population relative
  to the housing stock has a short run effect of
  the order of 1.5 to 2 percent on the regions
  house price index.

24

• Stock market or financial wealth effects? We
  failed to find a positive levels effects unlike
  earlier national studies.
• Reason? Probably because no regional wealth data.
• The rate of growth of the FTSE index in real
  terms (?lrftse) has significant positive effects,
  especially in Greater London and the South.
• Also looked at a simple measure of downside risk
  for the stock market. ?lrftseneg, which equals
  ?lrftse if this is negative and zero otherwise,
  is important in Greater London and the South
  only.
• The two stock market effects together suggest
  that, for example, a 20 stock market downturn
  has a much smaller (absolute) effect on house
  price inflation in Great London and the South
  than a 20 upturn.

25

• We investigated whether the growth in the
  regional population proportion in the main ages
  for first time buyers (20 to 39) had any effect.
  The estimated effect of this ?pp2039 variable is
  statistically significant and positive.
• We include dummy variables for 1988, 1989 and
  2001.
• In 1988 it became clear that domestic rates would
  be abolished in England and Wales and replaced by
  the Poll Tax. It also marked the March
  announcement that from August 1st, tax relief for
  mortgage interest would be restricted to one per
  property.
• The 2001 dummy reflects 9/11 and stock market
  turmoil effects, likely to have been more severe
  in London

26
Checks on Model Adequacy

• Overall the model fits well, although there is
  some evidence of mild autocorrelation in a couple
  of equations.
• The stability of the model was checked by
  estimating it on different sub-samples.
• In particular, there is no evidence that we over
  fitted the recent house price boom.
• The specification was checked against quarterly
  house prices equations for the UK and the North
  and South of Britain and consistent results were
  obtained.

27
Some Caveats

• We checked for income distribution effects, since
  space is a luxury good, and property tax effects
  (domestic rates, council tax) since variations in
  tax rates over time and over regions should have
  effects on prices.
• Income distribution changes are trend like and so
  are hard to detect.
• Despite pain-staking work constructing regional
  tax data back to 1975, the estimated tax effects
  were insignificant. The use of 1988 and 1989
  dummies probably picks up much of the effects of
  the tax switches of the time.
• Further work on the issue desirable, although
  handling expectations of tax changes will always
  be difficult.
• It seems likely that property taxes linked more
  closely to house prices could have damped the
  market and had some long run effects.

28
Caveats (Contd)

• No frenzy effects of the kind used by Hendry
  (1984) and Muellbauer and Murphy (1997) in the
  model.
• No income expectation terms, though expectations
  effects are likely to be reflected in the
  interest rate and income dynamics which are in
  the model.

29

• Figure 3 shows the estimated long-run effect of
  the credit conditions index (cci), real and
  nominal mortgage rates interacted with cci and
  inflation volatility. Relative to the 1970s, the
  estimated effects of cci, in terms of its direct,
  positive effect on real house prices, is roughly
  canceled out by the effect of the rise in real
  interest rates.

30

• Figure 4 shows the effects of downside risk,
  clearly a lagged endogenous variable, measured as
  if it were a long run effect.
• It suggests that the depth of the early 1990s
  housing market recession had much to do with the
  negative rates of return (and probably the
  associated payment difficulties and possessions
  problems faced by homeowners).
• This was so especially in Greater London, where
  the effect only began to lift after 1995.

31

• Figure 5 shows the effect of changes in the
  proportion of the working age population aged
  20-39, an approximate I(1) varable.
• It plays a considerable role in explaining the
  out-performance of Greater London house prices in
  the late 1990s and early 2000s.
• It also helps explain why house prices were
  apparently slow to respond to the interest rate
  rises of 1988-90 - the changing age structure was
  still supporting the market as well the weak
  market conditions between 1992 and 1997.

32

• Figure 6 suggests that, before 1997 or so, the
  rate of house building broadly matched rises in
  real incomes and working age populations (and
  implicitly household formation).
• Since then, the latter have greatly outpaced the
  rate of house building, especially in Greater
  London. In Greater London, this was the result
  both of higher per capita income growth and of
  population growth, driven by net foreign
  immigration.
• The composite effect explains most of the rise in
  real house prices since around 1997, thus
  confirming the relevance of the Barker Inquiry on
  Housing Supply (Barker, 2004).
• .

33

• Figure 7a shows one version of an error
  correction term including income per house,
  Greater London catch up, credit, interest rate
  and inflation volatility effects.
• The change in age structure and the rate of
  change in population per house, two near I(1)
  variables in our data, are excluded from this
  figure.
• Figure 7a suggests that, given interest rates,
  incomes, population and housing stock, Greater
  London was only moderately overvalued in 2003,
  while the West Midlands and the North were
  substantially undervalued

34
Base scenario

• Forecast period 2004 to 2010
• Growth rate of real non property income-
• 0.021 0.015 0.015 0.020 0.023 0.025 0.025
• Inflation rate-
• 0.013 0.021 0.027 0.028 0.026 0.024 0.022
• Mortgage interest rate-
• 0.050 0.055 0.055 0.055 0.050 0.050 0.050
• Growth rate of real FTSE index-
• 0.09 0.08 0.07 0.05 0.05 0.05 0.05
• CCI constant.

35
Base scenario contd

• Regional population projections from Govt
  Actuaries Dept.
• Shows decline in growth of working age population
  over next 7 years.
• Further decline of proportions aged 20-39, with
  largest decline around 2006, then tailing off a
  little.
• Rate of growth of regional housing stocks
  average of last 7 years.
• Relative per capita regional earnings, tax
  factors, and employment rates unchanged.
• Growth of owner-occupation average of previous
  7 years.

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Results

• No house price bubble if this is plausible
  scenario.
• Increase rate of growth of housing stock by 50
  house price growth only marginally lower, though
  level effect accumulates.
• What could go wrong? Economy turning sour.

37
Scenario B

• Growth rate of real non property income-
• 0.021 0.012 0.005 0.005 0.010 0.015 0.020
• Inflation rate-
• 0.013 0.025 0.03 0.028 0.028 0.026 0.024
• Mortgage interest rate-
• 0.050 0.055 0.065 0.060 0.055 0.055 0.050
• Growth rate of real FTSE index-
• 0.09 0.08 0.00 0.00 0.05 0.05 0.05 0.05

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Conclusions

• UK base scenario suggests there has been no
  bubble.
• If REITS and SIPPS valuation effects are
  significant, could be upturn.
• If economy turns sour and no REITS, SIPPS
  valuation effects, could see moderate nominal
  falls in 2006-7, esp. in London and South.
• System response is important for answering
  question if consumption, income, exchange rate
  feedbacks are large, could be self-reinforcing,
  but temporary, downturn.
• Exposure to debt, high house prices in
  Anglo-Saxon economies is high, so global interest
  rate environment will remain kind.