# RECORD 5bf64585206ad7e7f4dd7182eea5bcbb352319dd
# TITLE: Ripple effect on housing prices. Evidence from tourist markets in Alicante, Spain
# YEAR: 2017.0  VENUE: nan  DOI: 10.3846/1648715x.2016.1241192
# AUTHORS: Paloma Taltavull de La Paz; E. Lopez; F. Juárez
# PAGES: 14  CANDIDATE TABLE PAGES (1-based): [10]
# ABSTRACT: ABSTRACTThis paper analyses the house price diffusion effect in an economic-mixed region where the costal amenities strongly attracts second home and temporal residents while the main region’s city is an administrative centre in alicante province, Spain. The region is called Vega Baja country with 2 well known foreign-Europeans destination areas are located (Orihuela costa and Torrevieja). Using geo-referenced data, the paper explores the ripple effect on house prices between the coastal and inland areas, versus Orihuela capital. To control by heterogeneity and spatial autocorrelation, the model estimates housing prices controlled by quality including 33 house characteristics and spatial autocorrelation applying an SAR-hedonic based model which is estimated yearly for the period 2007–2012. Once controlled by quality, the estimated prices are used to seek 3 evidences of ripple effect: with spatial contiguity (spatial diffusion in the short distance), without special contiguity (long distance) and constant ...


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Copyright © 2017 Vilnius Gediminas Technical University (VGTU) Press
http://www.tandfonline.com/tspm
*	Corresponding author. E-mail: paloma@ua.es
RIPPLE EFFECT ON HOUSING PRICES. EVIDENCE FROM  
TOURIST MARKETS IN ALICANTE, SPAIN
Paloma TALTAVULL de LA PAZ a,*, Enrique LÓPEZ a, Francisco JUÁREZ a
a Department of Applied Economics, University of Alicante, Campus de San Vicente del Raspeig s/n, 
03080 Alicante, Spain
Received 17 June 2015; accepted 28 October 2015
Abstract. This paper analyses the house price diffusion effect in an economic-mixed region where 
the costal amenities strongly attracts second home and temporal residents while the main region’s city 
is an administrative centre in Alicante province, Spain. The region is called Vega Baja country with 
2 well known foreign-Europeans destination areas are located (Orihuela costa and Torrevieja). Using 
geo-referenced data, the paper explores the ripple effect on house prices between the coastal and in-
land areas, versus Orihuela capital. To control by heterogeneity and spatial autocorrelation, the model 
estimates housing prices controlled by quality including 33 house characteristics and spatial autocor-
relation applying an SAR-hedonic based model which is estimated yearly for the period 2007–2012. 
Once controlled by quality, the estimated prices are used to seek 3 evidences of ripple effect: with spa-
tial contiguity (spatial diffusion in the short distance), without special contiguity (long distance) and 
constant relative prices ratio, using Lagrange Multiplier test and Moran’s I, and Spatially Weighted 
Two Stage Least Squares (SW2SLS) including spatial lag and errors in the model. Results show the 
existence of spatial autocorrelation patterns in a well-defined local clusters and highlight evidence of 
ripple effect between Orihuela city and the coastal and inland areas but with lagged effect.
Keywords: Housing prices; Ripple effect; Tourist areas; Spain
SUPPLEMENTARY MATERIAL associated with this article can be found, in the online version, at 
https://doi.org/10.3846/1648715X.2016.1241192
1. INTRODUCTION
House prices have received increasing attention 
since the start of the Global Financial Crisis (GFC) 
because many has seen in the house price sinking 
to have part of the crisis responsibility. The EU 
authorities included house price growth rate into 
the list of indicators to be followed to monitoring 
(macro) economic imbalances and it is also recog-
nized that house prices have played a role in the 
lack of household affordability to housing there-
fore, having social impacts. This interest grew af-
ter a long list of analysis deepening on how the 
housing bubble formation happened, and giving 
different evidence about how the three different 
groups of variables (the general-global influences, 
the specific-local demand shocks and the diffusion 
effects from other closer areas) affected to prices.
It is documented how housing (aggregate) pric-
es depend on the fundamental drivers associated 
to the economic and social dynamism (for instance 
migration, economic growth or the financial sys-
tem efficiency) although a relevant part of those 
influences happen at local level as a response to 
a demand shock. Local house prices also diffuse 
and interact to other prices in the closer markets 
transmitting their influences among the territory 
in the long run. It is recognized that housing prices 
maintain a weighted relationship in the long run 
with other regions’ ones showing a long term equi-
librium in the relative house price among regions 
in the long run (Meen 1999; Holmes, Grimes 2008 
among others).
The literature agrees that house prices depend 
on the local demand characteristics and that dif-
fer across markets. A controversy opinion appears 
International Journal of Strategic Property Management
ISSN 1648-715X / eISSN 1648-9179
2017  Volume  21(1): 1–14
doi:10.3846/1648715X.2016.1241192


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10
P. Taltavull et al.
three spatial areas, with high explanatory capacity 
(AdjR2 > 0.8). The three regions show consistent he-
donic explanatory structure, with larger relevance 
of the neighbourhood quality in Orihuela and the 
coastal area, and more relevance of population dy-
namism and the use density to explain house prices 
in the inland region. The spatial lag parameters are 
significant in all equations and consistent results 
are at region level as well as in the case of spatial 
error parameter. Those agrees with the literature 
which identify the significance of spatial lag param-
eters as evidence of ripple effect, both in prices (rho 
parameter for spatial lagged prices) and for unob-
served heterogeneity capturing spatial-other-influ-
ences (lambda parameter for spatial error, Cameron 
et al. 2005). Spatial error parameter is not signifi-
cant in two years (2009 and 2012) for Orihuela, and 
in one (2012 and 2011) for the coastal area and the 
inland region suggesting that for those periods, the 
influence from unobserved variables at spatial level 
have not effect on housing prices.
The last step seeks to find the second evidence 
of ripple effect through fitting the model (7), that 
is, estimating the parameters which allow ap-
proach the ratio to capture the constant relation-
ship among the prices. Constancy and convergence 
to the equilibrium should be an evidence of the 
existing ripple effect between the coast and Ori-
huela capital, in one hand, the inland to Orihuela 
capital, on the other hand.
Table 2 shows the estimated parameter and the 
goodness of fit of time hedonic equation. The mod-
el has been fitted between two price series, taking 
Orihuela prices as reference. A third model is also 
estimated calculating the conditional parameters of 
prices in the three spatial dimensions relative to the 
prices in Orihuela. Those parameters serve to calcu-
late the “k” values as explained above. The estimated 
parameter values are consistent across the years.
The “k” values are reported in Table 3 and also 
reports the values of the parameters’ exponents. 
Note that the joint model contains the conditional 
Table 2. Relative price models estimation. Parameters value and explanatory capacity
log pi  =  g + x(log pj). Dependent variable log(porihuela)
2007
2008
2009
2010
2011
2012
log porihuela  =  gc + xc (log pcoast)
gc
2.415
3.162
3.198
5.037
2.032
2.291
xc
–0.207
–0.273
–0.278
–0.436
–0.179
–0.201
Adj R2
0.101
0.1407
0.166
0.321
0.111
0.124
log porihuela  =  gin + xin (log pinland)
gin
2.508
2.907
2.459
2.562
1.386
1.564
xin
–0.217
–0.254
–0.217
–0.227
–0.123
–0.139
Adj R2
0.110
0.115
0.088
0.056
0.047
0.052
Conditional coast and inland joint model
log porihuela  =  g(c+int) + x int/c (log pinland) + x c/int (log pcoast)
g(c+int)
10.277
9.875
9.657
10.316
9.334
9.947
x c/int
–0.880
–0.852
–0.841
–0.893
–0.823
–0.873
x int/c
–0.891
–0.863
–0.854
–0.913
–0.831
–0.886
Adj R2
0.882
0.829
0.846
0.885
0.829
0.877
Table 3. Relative price model constancy estimation “k” value
2007
2008
2009
2010
2011
2012
Mean
‘k’ values
Coastal area [e gc * e xc]
0.9185
0.5791
0.5612
0.1355
1.1366
0.9759
0.717
Inland [e gint * e xint]
0.8636
0.674
0.8799
0.8267
1.734
1.5245
1.083
Conditional Coastal and inland
[e g(c+int) * e x c/int * e x int/c]
1.4E-08
4.9E-08
8.6E-08
8.9E-09
2.2E-07
2.8E-08
6,7E-08
Exponent of price parameter coefficients
Coastal area [e xc]
–0.499
–0.862
–0.890
–2.197
–0.364
–0.461
–0.871
Inland [e xint]
–0.545
–0.739
–0.535
–0.581
–0.171
–0.218
–0.464
Model with conditional parameters
Coastal area [e x c/int]
–9.044
–8.411
–8.122
–9.215
–7.680
–8.688
–8.526
Inland [e x int/c]
–9.159
–8.524
–8.251
–9.414
–7.757
–8.817
– 8.653


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11
Ripple effect on housing prices. Evidence from tourist markets in Alicante, Spain
parameters of prices between cost/inland to Ori-
huela which capture the multiple effect among 
prices in those areas.
Figure 4 represents the two “k” values-series 
for coastal/Orihuela and Inland/Orihuela, both by 
year and the period mean. As it can be seen, there 
is a dissimilar evolution of both relative ratios dur-
ing the analysed period. The first (coast/Orihuela) 
ratio returns to the equilibrium at the end of the 
period after to diverge since 2007, reducing from 
0.9 to 0.6, and in 2010, with large changes mak-
ing the ratio become highly volatile to return to 
the equilibrium in 2012. Those “k” evolve around a 
mean value of 0,71 and reverts to the mean during 
the period10.
In the case of second ratio (inland/Orihuela), 
the “k” is shown as a constant until 2010 when 
starts diverging until the end of period with no 
apparent convergence. Both periods match with 
the double-v crisis experience in Spain with a first 
shock, the GFC crisis starting in 2007, and the 
“austerity crisis” starting in 2010–11. The latter 
did strongly negatively impact on Spanish econo-
my and especially in the households demand. The 
first period seems to suggest equilibrium in house 
prices between both regions until 2010 while the 
second shows a distortion on the price relations 
where the “k” parameter strongly differs from the 
mean (1.08).
The model with conditional parameters gives 
an estimator of a combined “k” with a mean of 
6,7*e(-8), showing the same shocks effect on house 
relative prices explained above (increasing volatil-
ity since 2010), but clearly converges to the equi-
librium (Fig. 5) at the end of the period. Conver-
gence to the equilibrium is also achieved by the 
estimated parameters values and, as an illustra-
tion, is represented in Figure 7.
The results obtained give empirical evidence of 
convergence relationships among housing prices 
between areas under study which shows different 
socio-economic characteristics although located at 
close distance. The analysed period shows the ef-
fect of shocks on relative house prices which are 
consistent with the 2 waves of crisis affecting 
Spanish economy. The change in “k” value during 
the first years report a reduction in house prices 
10	 The sample period, 2007 to 2012, is too short to con-
firm without doubt that mean “k” is a good benchmark 
of long run equilibrium. However, the empirical exer-
cise gives evidence that it occurs during the analysed 
period. Further analysis with longer database should 
be develop to support the evidence in this paper. We 
acknowledge to an anonymous referee to focus in this 
point.
in the costs rather than in the capital. This sug-
gest that the impact of GFC shock at worldwide 
level (1st shock) would have reduced income (or 
purchase capacity) of foreign demander before the 
Spanish ones, lowering the foreign house demand 
and diminishing house prices in the coast where 
the demand is dominated by foreign (European) 
income level and flow of population, and modifying 
the relative to Orihuela house prices, where house 
market is reflecting the local socio-demographic 
characteristics.
The second shock (the one coming from the 
application of austerity measures in the Spanish 
Economy) had domestic effects, that is, it affected 
the income level to Spanish households influenc-
ing house prices dominated by domestic demand to 
lower. As the fall was sharp, it is consistent with 
how the relative “k” ratio jumps up and return to 
the equilibrium (average “k”) quickly. This is con-
sistent with results in Cook (2003, 2005).
Although the period of time is short to observe 
the full equilibrium, the described evolution seems 
to suggest the existence of ripple effect between 
the coast (dominated by foreign demand) and the 
0.000 
0.200 
0.400 
0.600 
0.800 
1.000 
1.200 
1.400 
1.600 
1.800 
2.000 
2007
2008
2009
2010
2011
2012 
Coastal area
 
Interior 
Fig. 4. Constant price relationship and convergence
γ
ξ
γ
ξ



=
=



 
 
* 
, 
 
* 
c
c
int
int
Coastalarea
e
e
Interior
e
e
0.000
0.050
0.100
0.150
0.200
0.250
2007
2008
2009
2010
2011
2012
Fig. 5. Constant relationship and convergence. ‘k’ value 
for the conditional model’s parameter
(
)
γ
+
ξ
ξ




  /
 
/
* 
* 
c int
c int
int c
e
e
e