Paloma Taltavull de La Paz,Universidad de Alicante
Federico de Pablo Martí, Universidad de Alcalá
Carlos Manuel Fernández-Otheo, Universidad Complutense
Julio Rodríguez, Universidad de Alcalá

 Introduction
 Description of the demand/supply drivers in housing market in Madrid
 Model
 Results
 Conclusions
2

 Between 1997 and 1999, housing prices in
Madrid falled in real terms without the existence of any economic crisis.
 At the same time than a strong rise in other
Spanish areas
3

EVOLUCIÓN DE LA CAPACIDAD DE COMPRA DE LOS SALARIOS EN MADRID
(En % de crecimiento anual)
40,00
35,00
30,00
25,00 inflación Madrid salarios REALES inflación en el precio de las viviendas. Madrid inflación en precio de las viviendas. España
20,00
15,00
10,00
5,00
0,00
9
199
0
199
1
199
2
199
3
199
4
199
5
199
6
199
7
199
8
199
9
200
0
200
1
200
2
200
3
200
4
200
5
200
6
-10,00
-15,00
Fte. INE y Ministerio de Vivienda
4

 With positive demand factors:
 Strong increase on GDP,
 the lowest interest rates in the Spanish history
 Enough flow of
mortgages

Affordability gains
 Strong growth on housing prices in other areas
 Reasons for the less dynamism in Madrid housing prices?
 Market factors?
 Public intervention?
5

180.000
160.000
140.000
120.000
CONCESIONES DE HIPOTECAS PARA FINCAS URBANAS. VIVIENDAS
(
En número de operaciones)
18,00
16,00
Madrid
TIPOS DE INTERÉS NOMINALES APLICADOS AL MERCADO HIPOTECARIO Y SU EVOLUCIÓN
(En % ) tipos de interés hipotecarios (eje izquierdo)
% anual de variación
100.000
14,00
80.000
12,00
60.000 10,00
40.000
8,00
6,00
20.000
-
19
62
19
64
19
66
19
68
19
70
19
72
19
74
19
76
4,00
Fte. INE.
19
80
19
82
19
84
19
86
1.
988
Fte. Banco de España 1.
990
1.
992
1.
994
1.
996
1.
998
2.
000
2.
002
2.
004
2.
006
2.
008
0,00
1 4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 4 3
19
87Q
19
87Q
19
88Q
19
89Q
19
90Q
19
90Q
19
91Q
19
92Q
19
93Q
19
93Q
19
94Q
19
95Q
19
96Q
19
96Q
19
97Q
19
98Q
19
99Q
19
99Q
20
00Q
20
01Q
20
02Q
20
02Q
20
03Q
20
04Q
20
05Q
20
05Q
20
06Q
20
07Q
2
10
0
-10
-20
-30
-40
50
40
30
20
6

100,00
90,00
80,00
INDICADORES DE ACCESIBILIDAD EN MADRID
(En % )
R.accesib 30 años.. 30%
R.accesib 20 años.. 30%
R.accesib 25 años.. 30%
R. Crédito/Valor (LVR).. 80%
R. Solvencia (IVR)..3-4
70,00
60,00
R. Crédito/valor .. 80%
50,00
40,00
30,00
20,00
R. Accesibilidad... 30%
10,00
Fte. INE, MFOM, BDE y Elaboración propia
R. Solvencia.... 3-4 o menos
0,00
1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
7

Capital of Spain
Mayor city: 6 millions P
17% of Spanish GDP
Main based on service activities and high quality jobs
Financial center
Decission center for business...
8

 Years later, we were ask to develop a research project to explain why Madrid housing prices rise more than in the rest of
Spain
 In only five years everything changed in Madrid housing market
 We are witness of what have happened during the period,
 from an static situation to a very dynamic process
9

Introduction – Methodology followed
 1st. Explore statistics trying to describe what has happened
 Different methodologies: Time series, Panel data,
GIS, combined.
 2nd. Inside a theoretical framework

Economic intuition to define the hipothesis
 3rd. Contrast the hipothesis
 4th. Need for spatial analysis
10

 Agreement about the fundamental reasons to explain housing prices last decade
 Meen, 2001, Andrew and Meen, 2003, Case and Shiller,
2003, Case, Quigley and Shiller, 2005,
 In dense cities... Gibb,and O’Sullivan, 2002, Wheaton,
1998..
 If income and financial growth process do not create restrictions
 Demografics? .... Where?
 Spatial effects
11

Description of driver: total population
12

Description of driver: population mobility
(number of arrivals and departures)
ALTAS Y BAJAS RESIDENCIALES DESDE Y HACIA MADRID
(En número de individuos/mes)
45000
40000
35000
30000
25000
20000
15000
ALTAS
BAJAS
10000
5000
0
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
13

Description of driver: population mobility
(Spanish and foreigners –all arrivals)
ALTAS RESIDENCIALES EN MADRID
(En número de individuos/mes)
30000
ESPAÑOLES
EXTRANJEROS
25000
20000
15000
10000
5000
Fte. EVR, microdatos1988-
2006
0
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
14

Description of driver: population mobility
(Spanish and foreigners –all departures)
BAJAS DESDE MADRID A OTRAS LOCALIZACIONES
(En número de personas) 25000 españoles
Extranjeros
20000 Fte. INE. EVR microdatos
15000
10000
5000
0
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
15

 These behaviour show a double shock in basic demand of houses
 From foreigners
 From increase on internal mobility
 Located from 2001
 Increasing the size of the housing market
 Along the territory?
16

Description of drivers: Spatial demographic movements
17

Description of drivers: Spatial demographic movements
18

Description of drivers: Spatial demographic movements
19

Description of drivers: Spatial demographic movements
20

Description of drivers: Spatial demographic movements
21

Description of drivers: Spatial demographic movements
22

Description of drivers: Spatial demographic movements
23

Description of drivers: Spatial demographic movements
24

Description of drivers: Spatial demographic movements
25

Description of drivers: Spatial demographic movements
26

Description of drivers: Impact on prices?
27

Description of drivers: migration and prices
28

Description of drivers: Supply reactions
60000
50000
HOUSEBUILDING CYCLE IN MADRID
(num starts a year)
Source: Housing Ministery
PROTEGIDAS iniciadas iniciadas libres
40000
30000
20000
10000
0
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
29

Description of drivers: Supply reactions.. Enough??
VIVIENDAS A CONSTRUIR EN MADRID RELATIVAS AL TOTAL NACIONAL
En %
40,0
35,0
30,0
25,0
20,0
15,0
Madrid/España
10,0
5,0
Fte. Ministerio de Fomento
0,0
1990
Ene
1991
Ene
1992
Ene
1993
Ene
1994
Ene
1995
Ene
1996
Ene
1997
Ene
1998
Ene
1999
Ene
2000
Ene
2001
Ene
2002
Ene
2003
Ene
2004
Ene
2005
Ene
2006
Ene
2007
Ene
30

Description of drivers: Supply reactions
Spatial segmentation
31

Description of drivers: Supply reactions
Spatial segmentation
32


Qv d t

Qv o t
=
= f
[
A
(pop, y,f) t
,
B
(Pv t
, ti t
, tr t
, cu t
)] g
[Pv t
, Cm t
, ti t
, Otros t
]

Pv t
=
G
[ k
(pop, y,f, h t
) t
, m
( ti t
, tr t
, cu t
)]
Where:

Qv d t is housing demand,
 pop is population,
 y , income
 f mortgages funds

Pv t
, housing prices
 ti t
, interest rate
(1)
(2)
(3 )
 tr t
, transactions
 cu t housing use cost

Qv o t
Housing supply

Cm t
, construction costs

Otros t other components, like land, developers market size, market power, administrative restrictions, housing policy, regional differences
33

(See Andrew and Meen, 2003, DiPascuale and
Wheaton, 1996 and many others references)

Ph d *
(w) t t
=
– a
6 a
1
+ a
(uc) t
2
+ a
(pop) t
6
(ff) t
+ a
+e t
3
(ry) t
– a
4
(h) t
+ a
5

Identifying the role of different components of population dynamic

Pop =
D p + IR + OI
34

Model: empirical exercise (ECM model)
 D ln(P
Ht
)
= L
0
+ l
3
[
X lnFF
1
] + L t-1
+ l
4
1
+ d
+ d
4
1
D lnP
D lnFF
H,t-i t-i
+ d
+
5 d
2
[ ln(P
Ht-1
) + l
1 lnInf t-1
D lnRY
D lnInf t-i
+ l
+ d t-i
6 lnRY t-1
5
+ lnri d
D lnri
3 t-i t-1
+ l
2
+ l
6 ln
D
POB t-1+ ln
D
H t-1
] +
D ln
+ d
7
D
POB t-i
D ln
D
H t-i
+
+ m t
 P
Ht
 RY t
Housing prices in the moment t

POB t

FF t real income
Existing population in the Madrid region.
Mortgage finance flows

Inf t
 ri t
Madrid inflation rate
Real interest rate.
 H t
 [
X
1
 L
0,
Housing stock.
] matrix of exogenous variables
L
1,

T time l i, d i parameters to be estimated
Identifying the impact of different demographics component:
DPop is population in differences
EVRAL is household arrivals with house
EVRALEXT those coming from foreign countries
DEVR is arrivals in differences
35

 HOUSING DEMAND MODELS FOR MADRID MARKET
 Variable dependiente
 LRPRV(-1) 1
D(LRPRV) D(LRPRV) D(LRPRV) D(LRPRV)
 Mod 1 Mod. 2

Long term relationship 1988-2007
 l t
 l t
1
Mod.3
1 l t
Mod. 4 l
1 t
 LRY(-1)
 t-stud
 LDPOB(-1)
 t-stud
 LEVRAL(-1)
-0,75
[-2,64182]
-0,13
[-2,33740]
-1,53
[-6,63478]
0,31
-1,99
[-4,27342]
1,22
[1,72930]
 t-stud

LEVRALEXT(-1)
 t-stud
 LDEVR(-1)
 t-stud
 LFF(-1)
 t-stud
 LINF(-1)
 t-stud
 LRI(-1)
-0,36
[-4,58717]
[3,20846]
[4,81938]
-0,19
[-2,67231]
0,24
[-3,86900]
0,42
[5,25553]
0,56
[3,47261]
-0,22
[-4,95648]
-0,11
[-3,01786]
0,02
[0,14267]
-0,55
[3,66203]
-0,06 0,18 0,63 0,049
 t-stud

LDH(-1)
 t-stud
 C

[-1,54677]
0,42
[7,10577]
[4,76728]
0,04
[0,72742]
[6,39406]
-0,64
[-4,63171]
[0,56357]
0,37
[4,21846]
-9,76
[-3,39184]
 Convergence coefficient

-0,23
 t-stud [-6,16575]
-0,11
[-3,22361]
-0,05
[-3,68685]
-0,085
[-6,00824]
0,44
36

Model 1 model 2 model 3 model 4
Adj,Rsquare d
Sumsq, S,E,eq FLoglikel resids uation statistic ihood
0,62 0,01 0,02 4,51 224,2
0,35 0,04 0,02 5,9 174,24
0,38 0,04 0,02 6,54 175,9
0,62 0,01 0,02 6,46 153,03
37

RELACIÓN DE LARGO PLAZO ENTRE LOS FACTORES DETERMINANTES DE LA DEMANDA
0,30
Relación de largo plazo
0,20
Efecto de corrección de las variables de corto plazo
0,10
0,00
1 4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1 4 3 2 1
19
87Q
19
87Q
19
88Q
19
89Q
19
90Q
19
90Q
19
91Q
19
92Q
19
93Q
19
93Q
19
94Q
19
95Q
19
96Q
19
96Q
19
97Q
19
98Q
19
99Q
19
99Q
20
00Q
20
01Q
20
02Q
20
02Q
20
03Q
20
04Q
20
05Q
20
05Q
20
06Q
20
07Q
20
08Q
20
08Q
4
-0,10
-0,20
-0,30
-0,40
38

Model: fundamental effects in all Spain
EFECTO DE LOS FACTORES FUNDAMENTALES EXPLICATIVOS DE LA VARIACIÓN DE LOS
PRECIOS RESIDENCIALES EN ESPAÑA. 1988-2007
0,5
0,1
0
-0,1
-0,2
-0,3
-0,4
-0,5
0,4
0,3
0,2
Serie2
39

 Long term components explain the price evolution,
 in the general model (all population)
 Negative impact of income, finance, changes on population and interest rates (increase on prices, reduces the demand)
 Short run impacts of income (2 lags) and changes on population, finance and interest rates (3 lags)
 Positive impact on prices from inflation and available stock
 Short run effects for stock (4 lags) and inflation (3 lags)
 Strong dynamic relationships
40

 Migration models:
 Higher sensibility to changes on income
 Migration is positive correlated with changes on prices: arrivals stress the prices (both cases, total and foreign)
 Total inmigration is positivelly correlated with interest rates but not with existing stock, so, household movements could stress construction outside Madrid
 Foreign inmigration is positive correlated with finance and interest rates, and negativelly with housing availability.
 These could suggest that their arrival depends of income but also of the existent stock available, purchase capacity and the availability to have finance.
 From 2000, banks in Spain start to give mortgages masivelly to inmigrans with permanent job....
41

 Migration models (cont):
 Positive correlation among stock and prices in presence of foreign movers suggest that there is a lack on supply for this demand
 Negative correlation in the case of all movers
(most are previous residents, spanish and foreigners) suggest that they could decide move to other market in the case of good condicions.
 This also suggest that higher prices or other factors expulse this demand to other housing markets.
42


Goodman, 2005, Meen, 2003, Malpezzi y Maclenan, 2000 y Glaeser y Gyourko, 2005
 Q t s = f(P
H,t
, C t
,H t-1
, G t k , p
H
) =

=e a
1 P
H,t a2
Cm t a3
Cs t a4 i t a5 p t a
6 H t-1 a6
[ h k
G t k ] a7 p
H e a8 e t

Where:

- P
H,t

- Cm t

- Cs t

.- i t housing prices materials costs cost of salaries interest rates

- p t cpi

- H t-1 existing stock

-
 p h
H e k
 - e t

G t k regional caracteristics matrix inflation expectations in housing random component a
1..8
estimated parameters
43


Ln (Viv in,t
) = a
1 a
4 ln Cs t
+ a
5
+ a
2 ln i t ln P
H,t
+ a
6
+ a ln p t
3 ln Cm t
+ a
8 h k
+
G t k
+ n t
 Looking for the supply elasticity a
2

Method: 2 stages regression 2SLS

1988-2007
44

EVOLUCIÓN DE LA ELASTICIDAD PRECIO DE LA OFERTA DE VIVIENDAS NUEVAS EN MADRID
2,00
1,00
0,80
0,60
0,40
1,80
1,60
1,40
1,20
Elasticidad precio de la oferta nueva
Largo plazo corto plazo
0,20
0,00
1988Q1
2007Q3
1989Q1
2007Q3
1990Q1
2007Q3
1991Q1
2007Q3
1992Q1
2007Q3
1993Q1
2007Q3
1994Q1
2007Q3
1995Q1
2007Q3
1995Q1
2007Q3
1998Q1
2007Q3
1999Q1
2007Q3
2000Q1
2007Q3
2001Q1
2007Q3
2003Q1
2007Q3
45

Model: Supply Elasticity and model
ELASTICIDAD Y SIGNIFICATIVIDAD DE LA OFERTA DE VIVIENDAS NUEVAS EN MADRID
0,70
0,60
0,50
0,40
0,30
0,20
0,10
0,00
0,00 0,20 0,40
1988Q1 2007Q3
1989Q1 2007Q3
1991Q1 2007Q3
1990Q1 2007Q3
1992Q1 2007Q3
1993Q1 2007Q3
1994Q1 2007Q3
Serie1
2001Q1 2007Q3
1999Q1 2007Q3
1998Q1 2007Q3
2000Q1 2007Q3
2003Q1 2007Q3
1995Q1 2007Q3
0,60 0,80 1,00 1,20
Elasticidad precio de la oferta
1,40 1,60 1,80 2,00
46

 High supply elasticity which suggest rapid reactions of the developers when prices rise
 Low capacity of explanation, which suggest that the share of the market performing as a market is small
 Also suggest that there are other variables affecting the new supply decissions process,
 The existence of supply restrictions in Madrid markets
 Lack on supply... Expulse demand
 And increase prices in a market segment
47

48