Transcript Diapositiva 1

The sources of house price change:
Identifying liquidity shocks to the
housing market
Michael White
Paloma Taltavull de La Paz
20th ERES Conference
Vienna, July, 2013
Agenda
• Introduction: Housing and the channels of
transmission
• Defining the channels
• Analysis and Model
• Data
• Results
• Conclusions
Introduction
• Liquidity increase was global since late 90’s
– Addressing towards growing economics
– Activities in strong expansion
• first industry goods –exports,
• second real estate –construction-housing
• Increasing activity through financial system and
capital markets
– Interbanking flows did increase
– Feeding economies through bank system: liquidity
acceleration
– Credit multiplier … finance accelerator
• Housing market role?
Introduction
• Analysis from fundamentals:
– General economic growth lead to
• D employment
• D immigration….. D housing demand
• D non residencial real estate.
– Whealth promotes ownership (social policy,
habits..)
– Credit needs … households and small enterprises
• Maximun level of credits?,
• no credit constrains?
Introduction
• Credit use ….. Macro economic effects
• credit channel..
• Credit multiplier …
• Promoting homeownership instead of rent
• Income and wealth effect
• Stronger housing markets ---- demand more
mortgages ---- more transaction --- stronger
HM
• Increasing prices?
Introduction
• Mid 2000’s ECB’s analysis dept on the fact that
most liquidity went into the housing market
(and real estate)
• Discover a strong channel between monetary
indicators and house prices
• Multiple ways through transmit monetary
impulses into house prices and reverse
• … House Price Channel
Aim of the paper
• Identify the channels for monetary policy to
affect housing prices
• An the role of housing supply elasticities
– 3 channels:
• Asset inflation channel
• Credit channel
• Transaction channel
• Find evidence in two countries: Spain and UK,
using a regional basis
Preview of results
Fundamentals
• Strong macroeconomics impacts from housing boom
– the house price bubble
– Construction cycle.
4 effects associated to the stress of housing market:
• (1) the aggregate effect on the output from the strong housing
construction process in some countries (supply side effect),
– Barker, 2004, Glaesser, Gyourko & Saiz, 2008, DiPasquale, 1999, Meen, 2002,
Saiz, 2008
• (2) the wealth effect…..increase of general consumption,
• (3) the increase on household leverage resulting from the ownership
entrance in the market,
• (4) the increase on systemic risk of the economies experiencing the
housing boom due to the rise in mortgage concessions
– (these three are effects from the demand side view).
– Case, Quigley and Shiller, 2001, 2005, 2011, Goodman, 2005, Muelbauer,
2008.. Among other
Fundamentals
• Mortgage credit allows ownership demand to become
effective … demand impulse
• It was thought that was exogenously determined
through the credit channel (main) and Asset inflation
channel
• (Mishkin (2007) and Muellbauer (2007))
• Its marginal effect on house price is captured by the interest rates
price elasticities.
• But there are also other channels influencing house
prices and liquidity simultaneously (endogeneity)
– Transaction Channel
Fundamentals
• Macroeconomic effect of mortgage generation is explained
through the credit channel theory (Mishkin, 1995)
• Two different transmission way + housing collateral effect
(Muelbauer, 2007)
(1) 𝑀 ↑⇒ 𝑏𝑎𝑛𝑘 𝑑𝑒𝑝𝑜𝑠𝑖𝑡𝑠 ↑⇒ 𝑏𝑎𝑛𝑘 𝑙𝑜𝑎𝑛𝑠 ↑⇒ 𝐼 ↑⇒ 𝑌 ↑
(2) 𝑀 ↑⟹ 𝑃𝑟 ↑⇒ 𝐴𝑆 𝑎𝑛𝑑 𝑀𝐴 ↓⇒ 𝑙𝑒𝑛𝑑𝑖𝑛𝑔 ↑⇒ 𝐼 ↑⇒ 𝑌 ↑, regarding P as equity prices
from the household perspective:
(3) 𝑀 ↑⇒ 𝑃𝑟𝑒 ↑⇒ 𝑓𝑖𝑛𝑎𝑛𝑐𝑖𝑎𝑙 𝑎𝑠𝑠𝑒𝑡𝑠 ↑⇒ 𝑙𝑖𝑘𝑒𝑙𝑖ℎ𝑜𝑜𝑑 𝑜𝑓 𝑓𝑖𝑛𝑎𝑙 𝑑𝑖𝑠𝑡𝑟𝑒𝑠𝑠 ↓⇒
𝑐𝑜𝑛𝑠 𝐷𝑢𝑟𝑎𝑏𝑙𝑒 𝑎𝑛𝑑 𝐻𝑜𝑢𝑠𝑖𝑛𝑔 ↑⇒ 𝑌 ↑
4 Δ𝑃ℎ ⟹ Δ𝑐𝑜𝑙𝑙𝑎𝑡𝑒𝑟𝑎𝑙 𝑣𝑎𝑙𝑢𝑒 ⟹ Δ𝐷𝑒𝑏𝑡 ⟹ Δ𝑙𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦 𝑜𝑓 ℎ𝑜𝑢𝑠𝑖𝑛𝑔 𝑤𝑒𝑎𝑙𝑡ℎ ⟹
Δ𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛
Fundamentals
• Recent analysis identify more preciselly the transmission channels
where house prices could play relevant role:
• Credit channel is the most analysed (Aron et al, 2010, Muelbauer,
2007, Otsuka, 2006, Mishkin, 2007, Lastrapes..)
• Collateral effect of housing wealth is the base of the lending channel
(Weber et al, 2011, Setzer et al, 2010)
• Global liquidity spillover exists to asset price inflation (Belke et al,
2008,
• And housing amplify its effects ( Greiber and Setzer, 2007)..
Housing price channel
• But depending on how housing supply reacts to the impulses…
supply elasticity
Fundamentals
• There are three channels (Greiber and Setzer,
2007)
– 1 Friedman – Money demand channel (classical)
– 2 Asset inflation channel
– 3 Credit channel
Fundamentals
1 Friedman – Money demand channel (classical)
– Wealth Effect
Δ𝑃ℎ ⟹ ΔHWealth ⟹ Δ portfolio composition ⟹ Δ𝑝𝑟𝑜𝑝𝑒𝑟𝑡𝑦 𝑑𝑒𝑚𝑎𝑛𝑑
– Substitution effect
⟹ Δ𝐶𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛
Δ𝑃ℎ ⟹ change in the attractiveness of different assets
⟹ Δ housing demand + money demand
⟹ Δ%𝑝𝑟𝑜𝑝𝑒𝑟𝑡𝑦 𝑖𝑛 𝑝𝑜𝑟𝑡𝑓𝑜𝑙𝑖𝑜
– Transaction effect
Δ𝑡𝑟𝑎𝑛𝑠𝑎𝑐𝑡ℎ ⟹ Δ Ph ∗ numbT ⟹ ΔM3 dem for payments
. . Higher in boom periods
⟹ 𝑛𝑒𝑒𝑑 𝑑𝑒𝑝𝑜𝑠𝑖𝑡𝑠 + 𝑙𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦 (𝑀3 + 𝑀1)
Fundamentals
2 Asset inflation channel
ΔM3 ⟹ ΔCPI or ΔAsset Price
⟹ 𝑤ℎ𝑒𝑛 𝑆𝑢𝑝𝑝𝑙𝑦 𝑒𝑙𝑎𝑠𝑡𝑖𝑐 𝑜𝑓 𝐶 𝑔𝑜𝑜𝑑𝑠 > 1 ⟹ ΔPcpi
→ 0 (goods competition)
⟹ 𝑤ℎ𝑒𝑛 𝑠𝑢𝑝𝑝𝑙𝑦 𝑒𝑙𝑎𝑠𝑡 𝑜𝑓 𝐴𝑠𝑠𝑒𝑡𝑠 < 1 ⟹ ΔP𝑎𝑠𝑠𝑒𝑡
𝑎𝑠 ℎ𝑜𝑢𝑠𝑖𝑛𝑔 𝑚𝑘𝑡 ℎ𝑎𝑠 𝑟𝑒𝑠𝑡𝑟𝑖𝑐𝑡𝑒𝑑 𝑠𝑢𝑝𝑝𝑙𝑦
→1
Then
ΔM3 ⟹ ΔCPI ∗ Esupply or ΔAsset Price ∗ Esupply =
inflation*Esupply or Ph*E supply⟹ ΔPh
Fundamentals
3 Credit or lending channel
higher collateral ……. improve lending conditions
Δ𝑃ℎ ⟹ Δ𝑐𝑜𝑙𝑙𝑎𝑡𝑒𝑟𝑎𝑙 𝑣𝑎𝑙𝑢𝑒 ⟹ Δlending conditions ⟹ Δ𝐷𝑒𝑏𝑡
⟹ Δ𝑙𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦 𝑜𝑓 ℎ𝑜𝑢𝑠𝑖𝑛𝑔 𝑤𝑒𝑎𝑙𝑡ℎ
– And, more credit increase liquidity
Δ𝑃ℎ ⟹ Δ𝑐𝑜𝑙𝑙𝑎𝑡𝑒𝑟𝑎𝑙 𝑣𝑎𝑙𝑢𝑒 ⟹ Δlending conditions ⟹ Δ𝑙𝑜𝑎𝑛𝑠
⟹ Δ𝑀3
• As causality is in two directions, the channel is identify as an
accelerator (Greiber and Setzer, 2007).
Aim of this paper
• Approach the credit channel theory with some empirical
evidence, testing:
– Asset inflation channel
– Subject to supply responses
• Test the causal-channel relationship
Ph t  [M 3t , inft , Ε sup, controls]  t
r
• With elasticities being calculated as:
E sup t  [ Pht , rirt , Rt ]  t
• Apply to two countries and their regions (R):
– Spain and UK
Data
• National and regional data, quarterly
• Pool with regions and time series (1995-2011)
• Secundary sources: official databases
data
Variables
Definition
Source
Period
lRPH
Real House prices (logs)
LMIG
Migration. Net increase on population
(logs)
Ministry of Fomento-Spain 1995q1-2011q2 (1989q1 for
Spain)
HBOS
1983q1-2011q1
INE. Sp
1988q1-2010q4
Government Statistics - UK 1983q1-1009q2
LRINC
Income (logs)
RIR
Real mortgage interest rate
INF
Inflation
LRMORTG
Flow of real mortgage credits to finance INE. Spain
housing purchases (logs)
Council of Mortgage
Lenders - UK
Liquidity in the economy-M3 (logs)
Bank of Spain
LM3
INE. Sp
Regional Statistics - UK
Bank of Spain
Bank of England
INE. Spain
Government Statistics - UK
Bank of England
1990Q1-2011Q1
1990q4-2009q4
1990q1-2011q1
1983q1-2011q1
1992q1-2011q1
1983q1-2011q1
1990Q1-2011Q1
1983q1-2011q1
1990q1-2011q1
1983q1-2010q4
Regional data
Definition in the pool
Countries
UK
United Kingdom
Sp
Spain
UK Regions included
ea
East Anglia
em
East Midlands
gl
Greater London
ni
Northern Ireland
no
North
nw
North West
sc
Scotland
se
South East
sw
South West
wa
Wales
wm
West Midlands
yh
Yorkshire & Humberside
Spanish regions included
AND
Andalucía
ARA
Aragón
AST
Asturias
BAL
Balearic Islands
CAN
Canary Islands
CANTA
Cantabria
CAT
Cataluña
CLE
Castilla León
CMA
Castilla La Mancha
CVA
Valencia Community
EXT
Extremadura
GAL
Galicia
MAD
Madrid
MUR
Murcia
NAV
Navarra
PVA
Basque Country
RIO
La Rioja
data
UK prices
Liquidity
Empirical evidence
• Asset inflation channel
Ph t  [M 3t , inft , Ε sup, controls]  t
r
– Panel techniques
• 2 separate pools (UK and Spain)
• Pooled least square
– UK: 1996-2011, 12 regions, 660 obs
– Spain: 1995-2011, 17 regions, 969 obs.
• With elasticities ‘bi’ being estimated as:
• D
Hsit  a  b1iPhit  b2rirt  giRit  t
Empirical evidence
• Elasticities. The supply model:
Hsit  a  b1iPhit  b2rirt  giRit  t
• For Spain and UK
• Let the elasticities to vary among regions, so,
estimating b1i
• Test for breaking points.. Chow test show 2008
(UK) and 2007 (spain) as structural changes with
permanent effects
• Logs, regional (fixed) effects
Empirical evidence
Elasticityp-value
Elasticity
p-value
AN--LRHPAN
1,62 ***
_EA--LRPH_EA
0,33 **
AR--LRHPAR
1,43 ***
_EM--LRPH_EM
0,55 **
AS--LRHPAS
1,44 ***
_GL--LRPH_GL
0,06
BA--LRHPBA
0,92 ***
_NI--LRPH_NI
0,05
CA--LRHPCA
1,80 ***
_NO--LRPH_NO
0,38 ***
CANT--LRHPCANT 1,46 ***
_NW--LRPH_NW
0,48 ***
CLM--LRHPCLM
2,70 ***
_SC--LRPH_SC
1,01 ***
CLE--LRHPCLE
1,52 ***
_SE--LRPH_SE
0,09
CAT--LRHPCAT
0,73
_SW--LRPH_SW
0,29
CV--LRHPCV
1,13 ***
_WA--LRPH_WA -0,05
EX--LRHPEX
2,01 ***
_WM--LRPH_WM 0,23
GA--LRHPGA
1,82 ***
_YH--LRPH_YH
0,50 ***
MA--LRHPMA
1,13 **
MU--LRHPMU
0,81 **
NA--LRHPNA
1,22
PV--LRHPPV
-0,06
RI--LRHPRI
1,21
CYM--LRHPCYM
3,17
DlPrit = a + b1lM3 t-1 + b2inf t + b3 e_supi t+ t
Empirical evidence. Asset i. channel
DlPrit = a + b1lM3 t-1 + b2inf t + b3 e_supi+ control+ t
Where
• lPr is a matrix with logs of house prices by i regions
• LM3 is m3 monetary aggregate: total liquidity
• inf is inglation rate by country,
• e_sup is the elasticity of suppy by region i, constant for
all period
• The subscript ‘i’ refers each region (UK and Spain) and
• m is the stochastic disturbance term
• Control by fundamentals
Discussion
• Money supply inflation results:
– M3 significant in Spain and inflation in UK but not
in Spain (consistent in all estimated models)
• The channel captures direct relationship between
liquidity and house prices
– Regional elasticities are significant in most regions
but not in others
• Significant in less expensive and less volatile regions
other than East of England
• Significant in most Spanish regions
Discussion
• Money supply inflation results:
– M3 results
• 1% increase in M3 (-1) causes 9,2% reduction on the
rate of increase of house prices in Uk and 5,8% in Spain
• The impacts on prices from M3 changes comes through
regions captured by the significance of supply
elasticities and regional characteristics (fixed effects)
All comments are welcome