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Housing market reactions in presence of retirees migration

Paloma Taltavull, University of Alicante, SpainKaren Gibler, Georgia State University, US

Presented at European Real Estate Society Meeting. Stockholm, June 24-27, 2009

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Introduction• Economic changes from 1990s have

produced at least three phenomena simultaneously stressing housing demand– Increased employment and wages for Spanish

households– Increased worker immigration as the economy

enlarged– Increased non-working migrants flows for leisure

or residential purposes only

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RESIDEDNTIAL VARIATIONS IN SPAIN

0

20000

40000

60000

80000

100000

120000

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

changes on residence from foreigncountries

number of people

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Introduction• Large inflow of retiree migrants to Alicante

– From 1998 onwards• Impact housing market

– In some small and medium cities.. Mediterranean coast and islands

• Stable arrival of >55 years old Britons, Germans and other Europeans citizens+/-3000 per month, +2000 Britons)

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IntroductionRESIDENTIAL VARIATIONS IN ALICANTE. BRITONS AND GERMANS ARRIVALS TOTAL AND UP

FROM 55 YEARS OLD

0

500

1000

1500

2000

2500

3000

3500

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Britons up to 55

total Britons

Germans up to 55

Total Germans

(persons by month)

Source: INE, EVR

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Introduction RESIDENTIAL CHANGES BY NATIONALITY

0

50

100

150

200

250

300

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Swedish

to Alicante and older than55

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Introduction• Impacting especially in some specific

housing markets• Distinct effect depending on which

population group creates the increased demand

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Introduction: Previous study of the retiree migrants

• From REVIcVAL (Taltavull et al, 2008, Gibler et al, 2009) we know:– Economic features are important:

• Good house price (perceived in terms of their income)• Low cost of maintenance and taxes• Premium in relative cost of living• Strong purchase capacity of their income• Pay cash

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Research questionsDo these retirees:• affect housing prices…..as in the U.S.? • increase housing construction.... (Hanushek y Quigley, 1979, Coulson, 1999

Eaton & Eckstein, 1997; Meen & Andrew, 1998.)

Hypothesis:• 1st…Increase in demand … affect housing prices• 2nd… affect construction of ‘specific’ houses

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Housing market mechanismHousing prices

Houses

SupplyDemand

Time

P0

P2

P1

H0 H1

1 2 3 4 5 6

7 8 9 10 1112

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Housing market mechanism• So retiree immigration expected to create

unexpected increase in demand• Reactions…

– 1st …. prices» P = (pop, y, w, otr, cu)

– 2nd … construction» Vivin p)

• Empirical contrast– 1st.. Isolate the effect of the unexpected demand– 2nd…. Identify impact on housing construction

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Market fundamentals• (1)

Where:• Qh: housing demand.• X vector with variables having permanent effects on the market, which are:

– Pop Population– Y: Real income per capita or measure of permanent purchase capacity – K: Capital expenditure on housing other than income

• Z: vector of variables with transitory effects on demand:– ph housing prices– Dh vacancies– Cu user costs of housing

• Of: other factors such as relative prices of other goods and tastes

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Market fundamentals

(2) Phdt = f(X, Z)t = 1 + 2 (pop)t + 3 (y)t + 4 (K)t - 5 (h)t – 6 (Cu)t + t

Pop = Δp + IR + OI

y = f(yl, ye)

Kt = Mt + Set

3) Phdt = 1 + 1 [pop + OI, (y)t , Mt] + 2 [IR, ye , Se]

- 5 (h)t – 6 (Cu)t + t

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p(y)t , Mt

Market fundamentals

IR, ye , Se]

ph ph2

ph3

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Empirical analysis

(6) Pht = 1 +1[IR] +2[ye /yi]t +3[Exr] t +

4[CPIe/CPIi] t +5 Hcgt + 6 Irpt – 5 (h) t + t

Remember that Cut = f([CPIE/CPIi], Irp, Hcg] t

Irp = Mire – Mirl (mortgate rates in Spain and the origin

country of retirees)

Hcg = Capital gains: pht/pht(-1)

-

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1st Empirical exercise• Database:

– Time series 1988....2007– Quarterly ... – Secondary data ... Aggregate at province level– British and German flow of retirees (older than

55)– Sources: Spanish National Institute of Statistics

(INE), Housing Ministery (M.Vivienda), Bank of Spain, Ministery of Fomento.

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Empirical exercise

• Methodology.• Time series....

– Integrated series– NOT cointegrated retirees migrant series– VEC.... And regression methods Stepwise LS

and 2SLS

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Stepwise regression

Method:StepwiseRegressionSample(adjusted):1988Q12007Q4Numberofsearchregressors:9Selectionmethod:Stepwiseforwards

Stoppingcriterion:p-valueforwards/backwards=0,5/0,5DependentVariable:LOG(PH) DependentVariable:LOG(PH)

Coefficient

t-Statisti

c Prob,* Coefficientt-

Statistic Prob,*

LOG(UK_55) 0,042 2,790 *** LOG(UK_55) 0,040 2,660 ***LOG(GER_55) -0,034 -2,376 ** UK_INC -0,505 -4,509 ***

UK_INC -0,548 -5,038 *** LOG(EXR_UK) -2,387 -5,675 ***

GER_INC -1,215 -6,638 *** CPI_UK/CPI_ALI -1,629 -2,952 ***LOG(EXR_UK) -2,379 -5,610 *** DUMM99 0,389 1,473 0,145

LOG(EXR_GER) -0,009 -1,129 0,263 C 13,393 31,198 ***CPI_UK/CPI_ALI -1,626 -2,923 *** GER_INC -1,248 -6,823 ***

CPI_GER/CPI_ALI -1,627 -3,959 *** CPI_GER/CPI_ALI -1,701 -4,143 ***C 13,794 41,181 *** LOG(GER_55) -0,037 -2,579 ***

LOG(EXR_GER) 0,091 1,331 0,188

R-squared 0,994 R-squared 0,994

AdjustedR-squared 0,993 AdjustedR-squared 0,994

S,E,ofregression 0,046 S,E,ofregression 0,046Sumsquaredresid 0,151 Sumsquaredresid 0,146Loglikelihood 137,394 Loglikelihood 138,615

F-statistic 1506,982 F-statistic 1361,864Prob(F-statistic) 0 Prob(F-statistic) 0Durbin-Watsonstat 1,518 Durbin-Watsonstat 1,621

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Empirical analysis.

-3

-2

-1

0

1

2

3

4

88 90 92 94 96 98 00 02 04 06

Standardized Residuals

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Empirical analysis.

-.15

-.10

-.05

.00

.05

.10

.15

.20

5.2

5.6

6.0

6.4

6.8

7.2

7.6

88 90 92 94 96 98 00 02 04 06

Residual Actual Fitted

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Empirical analysis. Cointegration test

Hypothesized Trace 0,05

Hypothesized Trace 0,05

No, of CE(s)

Eigenvalue Statistic

Critical Value Prob,**

No, of CE(s)

Eigenvalue Statistic

Critical Value Prob,**

None *  0,456573  88,63694  69,81889  0,0008 None *  0,342221  78,37250  69,81889  0,0089At most 1  0,293770  41,67772  47,85613  0,1680 At most 1  0,244123  46,11827  47,85613  0,0722At most 2  0,114020  14,89597  29,79707  0,7868 At most 2  0,158421  24,56776  29,79707  0,1775At most 3  0,051897  5,574272  15,49471  0,7452 At most 3  0,131553  11,28717  15,49471  0,1944At most 4  0,018919  1,470745  3,841466  0,2252 At most 4  0,005522  0,426375  3,841466  0,5138

Trend assumption: Linear deterministic trendSeries: (PH) UK_55 UK_INC EXR_UK Lags interval (in first differences): 1 to 2

Unrestricted Cointegration Rank Test (Trace)

 Trace test indicates 1 cointegrating eqn(s) at the 0,05

Trend assumption: Linear deterministic trendSeries: PH GER_55 GER_INC EXR_GER Lags interval (in first differences): 1 to 2

 Trace test indicates 1 cointegrating eqn(s) at the 0,05  * denotes rejection of the hypothesis at the 0,05 level  * denotes rejection of the hypothesis at the 0,05 level

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Results – VEC

VEC estimation - Long term relationship, permanent effects Sample (adjusted): 1988Q4 2007Q4. t-statistics in [ ]2 lags minimize the akaike information criteria

British Retirees Germans RetiressPh Ph

Long term relationship.PH(-1)  1,000000 PH(-1)  1,000000

UK_55(-1) -0,336479 GER_55(-1)  2,261621[-6,66515] [ 6,78487]

UK_INC(-1)  411,4650 GER_INC(-1) -1558,026[ 1,53587] [-5,67546]

EXR_UK(-1)  596,5349 EXR_GER(-1)  16,09998[ 1,91570] [ 6,67797]

CPI_UK(-1)/CPI_ALI(-1)  1367,335 CPI_GER(-1)/CPI_ALI(-1)  4684,761[ 2,15552] [ 7,00781]

C -3789,909 C -3824,387Convergence parameter -0,130567 -0,034242

[-9,33098] [-2,32681] Adj, R-squared  0,602701  0,204156 Sum sq, resids  13630,53  27303,80 S,E, equation  14,48104  20,49533 Log likelihood -308,54 -335,29 Determinant resid covariance (dof adj,)  0,000232  59,80247 Determinant resid covariance  9,93E-05  25,63494 Log likelihood -191,43 -671,18

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Results – VEC

VEC estimation - Short term relationship Sample (adjusted): 1988Q4 2007Q4. t-statistics in [ ]2 lags minimize the akaike information criteria

British Retirees Germans RetiressPh Ph

Short term adjustmentD(PH(-1)) -0,275404 D(PH(-1))  0,290411

[-2,78775] [ 2,56026]D(PH(-2)) -0,493741 D(PH(-2))  0,154706

[-4,97485] [ 1,25002]D(UK_55(-1)) -0,022268 D(GER_55(-1))  0,102995

[-2,79498] [ 3,21204]D(UK_55(-2)) -0,013172 D(GER_55(-2))  0,088809

[-1,71847] [ 3,13090]D(UK_INC(-1))  9,398806 D(GER_INC(-1)) -105,5441

[ 0,15222] [-2,33373]D(UK_INC(-2))  17,81924 D(GER_INC(-2)) -102,1527

[ 0,30365] [-2,39451]D(EXR_UK(-1))  14,26544 D(EXR_GER(-1))  0,458533

[ 0,14212] [ 1,51187]D(EXR_UK(-2))  142,1646 D(EXR_GER(-2))  0,408872

[ 1,44588] [ 1,46568]D(CPI_UK(-1)/CPI_ALI(-1))  102,4153 D(CPI_GER(-1)/CPI_ALI(-1)) 468,3522

[ 0,49915] [ 1,69006]D(CPI_UK(-2)/CPI_ALI(-2))  121,9284 D(CPI_GER(-2)/CPI_ALI(-2)) 570,3255

[ 0,62340] [ 1,97545]C  35,97652 C  14,61494

[ 9,39070] [ 3,57147]

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Long term relationship. Britons

-800

-600

-400

-200

0

200

400

90 92 94 96 98 00 02 04 06

Cointegrating relation 1

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Cholenski impulse-response. Britons HOUSING PRICES RESPONSES IN ALICANTE TO CHANGES ON......

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

UK_55

UK_INC

EXR_UK

CPI_UK/CPI_ALI

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Long term relationship. Germans

-800

-600

-400

-200

0

200

400

600

90 92 94 96 98 00 02 04 06

Cointegrating relation 1

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Cholenski impulse-response. Germans HOUSING PRICES RESPONSES IN ALICANTE TO CHANGES ON......

-30

-25

-20

-15

-10

-5

0

5

10

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

GER_55

GER_INC

EXR_GER

CPI_GER/CPI_ALI

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Results• As expected according to the literature

– Housing price atractiveness – relative housing prices between two countries

– purchase capacity differentials explain the housing demand, and also the monetary effect through exchange rates

– British flow of migration affects housing prices in the long-run with permanent effect

– Germans only have short-run temporary effect

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Conclusions• Retiree migration flows would be expected to

create a shock to the housing market in Alicante– Because of the intensity of flow of Britons, not of

Germans– AND economic characteristics of the migrants

• Recent process... Concentrated during late 90s• With general impacts on local economy through

housing market– Relevant implications... Economy and society

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THANKS FOR YOUR ATTENTION