argiolas, coppola & cruccas - input2012
DESCRIPTION
Michele Argiolas, Karol Coppola and Alberto Cruccas on "GIS-WEB approach to support spatial monitoring of housing market acquisition risk and urban property market dynamics definition"TRANSCRIPT
UNIVERSITA’ DEGLI STUDI DI CAGLIARI
Dipartimento di Ingegneria Civile, Ambientale ed Architettura.
ARGIOLAS M. – COPPOLA K. – CRUCCAS A.
Seventh International Conference on Informatics and Urban and Regional Planning (INPUT 2012)
10-12 May 2012 Cagliari
INTRODUCTION
This paper proposes the last implementation of a new approach to
evaluate property’s acquisition risk that does not rely on a
standardize appraisal indices analysis.
The proposed Geographical Information System is able to
investigate the historical variation of some real estate marketinvestigate the historical variation of some real estate market
indicators and to let the final user appraise the general level of
real estate investment risk, by converting and extending classical
R.E. market monitoring parameter into user-friendly spatial maps.
INTRODUCTION
Despite the heavy impact of the real estate market crisis that hit both
the U.S. and a part of European market, public real estate market
monitoring systems did not show a substantial evolution.
In addition, before the sub-prime scandal and the related fall of real
estate values, buying an home has always been considered a low riskestate values, buying an home has always been considered a low risk
investment. Today this conviction has been at least scratched by the
actual property market condition: the medium US house price is 40%
less than five years ago .
INTRODUCTION
In 2004 R. J. Schiller, surprised by the fact that did not exist an index able to
represent the historical trend of property values in the United States, has
developed an index of average market prices for the most representative
contexts U.S. cities covering the period from 1890 to nowadays . The index
has been acquired by Standard and Poor's which is currently in charge of it.
INTRODUCTION
Many economists have identified the main cause of recent global real
estate market crisis in the poor diffusion of systems capable of
monitoring the historical property values and in the lack of public
awareness about the risks of real estate investments crisis (Ref. Rocca
Bardhan).
INTRODUCTION
In 2010 a study made by TIME magazine regarding homeownership over
the world shows that homeownership is not necessarily a synonym for
economic wealth. In Switzerland, one of the world richest nations, the rate
of homes that are owner-occupied is about 34,6%. Italy and Spain have one
of the highest European rate of homeownership, but they have just the,
half of Switzerland’s GDP per capita.
In 2008, J.R. Munch et al. studying the relation between home ownership,In 2008, J.R. Munch et al. studying the relation between home ownership,
job duration, and wages claims that “positive externalities associated with
home ownership has been used to argue for favorable tax treatments of
home owners, our results suggest that there are also significant labor
market gains associated with home ownership”.
METHODOLOGY
In the last few years, it was possible to learn that, nowadays, real estate
market fluctuations associated with global variables can lead to an
immediate change in in the housing market: the risks associated with
the variable "local" is more predictable and generally tends to affect the
market with less intensity.
For these reasons, the methodology for measuring the risk connected to
property investment is multifaceted and still not consolidated. This lack
is significant, especially for housing market, because it often leads
common people to do an investment without knowing what can arise
from an accurate market analysis. (Shiller, 2008)
METHODOLOGY
An housing market bubble consists essentially in a growth of property
values far beyond the threshold of local population economic
sustainability.
Even through a simple study of the historical relationship between the
average price of a house and the median household income, it wasaverage price of a house and the median household income, it was
possible in 2006 to identify the presence of a speculative bubble in
some US metropolitan areas (Marchi, Argiolas, 2006). From this point of
view, the solid and always valid parameter of the Housing Affordability
Index (HAI) can be an absolute reference point to identify real estate
bubbles.
METHODOLOGY
The Annual Demographia International Housing Affordability Survey
(2008) identifies five different categories of purchase accessibility in
house property market. Obviously, an high ratio between the price of a
property and the average income of an household is a symptom of a
general economic unsustainability in property acquisition and,
consequently, it will be higher the possibility of a real estate housingconsequently, it will be higher the possibility of a real estate housing
market bubble. This ratio is often measured taking in account the
mortgage payment rate.
METHODOLOGY
The innovative aspect we want to analyze in this paper, concerns the
study of the ratio between different Housing Affordability Index that can
be found in the same urban environment. To achieve this target we
must assign a spatial component to HAI indicators associated with the
current market supply or to recent market sales.
By a practical perspective, this goal can be reached through the use of
GIS applications directed to the study of the real estate market. In this
case, we started from a historical study of property values in Cagliari
(Italy) during the decade between 1999 and 2009.
VALUE GIS
METHODOLOGY
Why VALUE GIS ?
-Low-cost (google fusion tables)
-User friendly interface
CASE OF STUDY
The main purpose of this application is to make a spatial analysis of
housing market property affordability over the last ten years, in the
town of Cagliari, Italy (circa 400,000 inhabitants considering the
metropolitan area).
As noted previously, the analytical method used in this work is the result
of a continuous development. The last one, described in this paper, hasof a continuous development. The last one, described in this paper, has
extended the area under study by adding more data related to the
neighboring municipalities of Cagliari.
This extension has made it possible to check the levels of residential
properties’ purchase affordability both in the intermediate and
peripheral zones of the metropolitan context. This goal was achieved
analyzing the correlation between the buying power of the richest
municipalities inhabitants and the market values of the most prestigious
areas in the whole metropolitan context.
CASE OF STUDY
QuartucciuQuartucciu
SelargiusSelargius
MonserratoMonserrato
PirriPirri
CagliariCagliari
Quartu S.ElenaQuartu S.Elena
CASE OF STUDY - REAL ESTATE MARKET VALUES
CASE OF STUDY - REAL ESTATE MARKET VALUES
CASE OF STUDY - REAL ESTATE MARKET VALUES
1.100,00
1.300,00
1.500,00
1.700,00
1.900,00
2.100,00
2.300,00
Cagliari
Monserrato
Pirri
Quartu
Quartucciu
Selargius
500,00
700,00
900,00
1.100,00
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Selargius
Sources:
-Data published from public official sources like “Agenzia del Territorio”
and Cagliari’s Chamber of Commerce
-Data processed by Laboratorio di Estimo Facoltà di Ingegneria di
Cagliari
CASE OF STUDY
To calculate Spatial Housing Affordability is therefore necessary to know
both the average property market values that the medium family
income. The last dataset was built using various sources:
- Data from Italian Department of Economy and Finance, processed by Il
Sole 24 Ore (http://www.ilsole24ore.com/)
- Data published by the website site-www.comuni italiani.it and Centro - Data published by the website site-www.comuni italiani.it and Centro
Studi L'Unione Sarda
Starting from the average gross revenues it is possible to obtain the
average net income by applying the corresponding rate tax.
SOCIAL CATEGORIES AVERAGE INCOME AND RELATIVE PROPERTY TARGET
young single
worker who buys a 60 sqm
apartment
male single
worker (low-
income) with a wife and 1 child who buys an 80 sqmapartment
bi-income young couple with 1
child who buys an
apartment of 90 sqm
Male single
worker (medium-income)
with a wife and 2 sons who buys
an apartment of 90 sqm
Bi-income and
wealthy couple
that buy an
apartment of 90 sqm
CASE OF STUDY - AVERAGE INCOME
18.000,00
20.000,00
22.000,00
Cagliari/Pirri
10.000,00
12.000,00
14.000,00
16.000,00
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Monserrato
Quartucciu
Quartu
Selargius
RESULTS
The results show that the Housing Affordability Index express a
considerable difficulty of the local community in the acquisition of an
suitable housing unit. This feature is due to the fact that during the
period from 1999 to 2010 property prices rose by about 109,4% while
the average income (+34%), population (-6,8%) and construction
costs(+37,7%).
RESULTS
RESULTS
RESULTS
RESULTS
CONCLUSIONS (1/4)
From a market appraisal point of view, results show that the
analyzed housing market is slowed down and its future will depend
from the short/medium-term economic trend: if the economic crisis
will be resolved quickly the market will slowly take a breath and
settle down to values sustainable by the local community,
otherwise it will be a significant decline in average selling pricesotherwise it will be a significant decline in average selling prices
that could lead to a local real estate market crisis, absolutely
unimaginable until few years ago.
If we consider the 1999 HAI as the normal ratio between median
income and house price, market price need to drop by almost a 40
percent.
CONCLUSIONS (2/4)
With the introduction of IMU, the new italian real estate tax,
it is possible to expect a 20% average property market price
fall , with picks up to 50%.
This quite alarming synthesis, obtained from a recent issue ofThis quite alarming synthesis, obtained from a recent issue of
the magazine ”Outlook sui Consumi”, a pubblication of a
mayor italian institute of statistic (Censis Confcommercio),
from a sample of 1200 households.
CONCLUSIONS (3/4)
From a methodological point of view, the proposed system allows to
access to the created information in an easy and quick way and to
perceive the real estate market conditions and risk. However, future
developments will allow to improve the quality of the information
collected.
In particular, among the future goals, it plays a crucial role the study of
the spatial dimensions of the Housing Affordability Index. In fact, it will
be possible to study not only the specific value of HAI reported to each
homogeneous area, but it will be possible to quantify the risk
considering the whole urban center, analyzing the historical variation of
the quota of "affordable" areas by adding a space component to the
Housing Affordability Index.
CONCLUSIONS (4/4)
In this way, the final user will be able to understand how much of the
urban area is available for purchase depending to the social category
considered. This implementation will allow an easy comparison between
different municipalities’ inhabitants and may therefore be perceived
level of "openness" in buying properties offered by various cities.
The next step in this study will permit a study of the market offer by a
web related application that allows to extract, in a semi-automated way
digital data banks containing the market values of items offered on the
market. This system will let the final user to be aware of the actual
market situation of an urban center in real time.