Argiolas, Coppola & Cruccas - input2012


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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"

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Argiolas, Coppola & Cruccas - input2012

  1. 1. 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
  2. 2. INTRODUCTIONThis paper proposes the last implementation of a new approach toevaluate property’s acquisition risk that does not rely on astandardize appraisal indices analysis.The proposed Geographical Information System is able toinvestigate the historical variation of some real estate marketindicators and to let the final user appraise the general level ofreal estate investment risk, by converting and extending classicalR.E. market monitoring parameter into user-friendly spatial maps.
  3. 3. INTRODUCTIONDespite the heavy impact of the real estate market crisis that hit boththe U.S. and a part of European market, public real estate marketmonitoring systems did not show a substantial evolution.In addition, before the sub-prime scandal and the related fall of realestate values, buying an home has always been considered a low riskinvestment. Today this conviction has been at least scratched by theactual property market condition: the medium US house price is 40%less than five years ago .
  4. 4. INTRODUCTIONIn 2004 R. J. Schiller, surprised by the fact that did not exist an index able torepresent the historical trend of property values in the United States, hasdeveloped an index of average market prices for the most representativecontexts U.S. cities covering the period from 1890 to nowadays . The indexhas been acquired by Standard and Poors which is currently in charge of it.
  5. 5. INTRODUCTIONMany economists have identified the main cause of recent global realestate market crisis in the poor diffusion of systems capable ofmonitoring the historical property values and in the lack of publicawareness about the risks of real estate investments crisis (Ref. RoccaBardhan).
  6. 6. INTRODUCTIONIn 2010 a study made by TIME magazine regarding homeownership overthe world shows that homeownership is not necessarily a synonym foreconomic wealth. In Switzerland, one of the world richest nations, the rateof homes that are owner-occupied is about 34,6%. Italy and Spain have oneof 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,job duration, and wages claims that “positive externalities associated withhome ownership has been used to argue for favorable tax treatments ofhome owners, our results suggest that there are also significant labormarket gains associated with home ownership”.
  7. 7. METHODOLOGYIn the last few years, it was possible to learn that, nowadays, real estatemarket fluctuations associated with global variables can lead to animmediate change in in the housing market: the risks associated withthe variable "local" is more predictable and generally tends to affect themarket with less intensity.For these reasons, the methodology for measuring the risk connected toproperty investment is multifaceted and still not consolidated. This lackis significant, especially for housing market, because it often leadscommon people to do an investment without knowing what can arisefrom an accurate market analysis. (Shiller, 2008)
  8. 8. METHODOLOGYAn housing market bubble consists essentially in a growth of propertyvalues far beyond the threshold of local population economicsustainability.Even through a simple study of the historical relationship between theaverage price of a house and the median household income, it waspossible in 2006 to identify the presence of a speculative bubble insome US metropolitan areas (Marchi, Argiolas, 2006). From this point ofview, the solid and always valid parameter of the Housing AffordabilityIndex (HAI) can be an absolute reference point to identify real estatebubbles.
  9. 9. METHODOLOGYThe Annual Demographia International Housing Affordability Survey(2008) identifies five different categories of purchase accessibility inhouse property market. Obviously, an high ratio between the price of aproperty and the average income of an household is a symptom of ageneral economic unsustainability in property acquisition and,consequently, it will be higher the possibility of a real estate housingmarket bubble. This ratio is often measured taking in account themortgage payment rate.
  10. 10. METHODOLOGYThe innovative aspect we want to analyze in this paper, concerns thestudy of the ratio between different Housing Affordability Index that canbe found in the same urban environment. To achieve this target wemust assign a spatial component to HAI indicators associated with thecurrent market supply or to recent market sales.By a practical perspective, this goal can be reached through the use ofGIS applications directed to the study of the real estate market. In thiscase, we started from a historical study of property values in Cagliari(Italy) during the decade between 1999 and 2009.
  11. 11. METHODOLOGY VALUE GISWhy VALUE GIS ?-Low-cost (google fusion tables)-User friendly interface
  12. 12. CASE OF STUDYThe main purpose of this application is to make a spatial analysis ofhousing market property affordability over the last ten years, in thetown of Cagliari, Italy (circa 400,000 inhabitants considering themetropolitan area).As noted previously, the analytical method used in this work is the resultof a continuous development. The last one, described in this paper, hasextended the area under study by adding more data related to theneighboring municipalities of Cagliari.This extension has made it possible to check the levels of residentialproperties’ purchase affordability both in the intermediate andperipheral zones of the metropolitan context. This goal was achievedanalyzing the correlation between the buying power of the richestmunicipalities inhabitants and the market values of the most prestigiousareas in the whole metropolitan context.
  13. 13. CASE OF STUDY Monserrato SelargiusPirri Quartucciu Quartu S.Elena Cagliari
  16. 16. CASE OF STUDY - REAL ESTATE MARKET VALUES2.300,002.100,001.900,001.700,00 Cagliari1.500,00 Monserrato Pirri1.300,00 Quartu Quartucciu1.100,00 Selargius 900,00 700,00 500,00 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010Sources:-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 diCagliari
  17. 17. CASE OF STUDYTo calculate Spatial Housing Affordability is therefore necessary to knowboth the average property market values that the medium familyincome. The last dataset was built using various sources:- Data from Italian Department of Economy and Finance, processed by IlSole 24 Ore ( Data published by the website site-www.comuni and CentroStudi LUnione SardaStarting from the average gross revenues it is possible to obtain theaverage net income by applying the corresponding rate tax.
  18. 18. SOCIAL CATEGORIES AVERAGE INCOME AND RELATIVE PROPERTY TARGET young male bi-income Male Bi-income single single young single and worker worker couple worker wealthywho buys (low- with 1 (medium- couple a 60 sqm income) child who income) that buyapartment with a wife buys an with a wife an and 1 child apartment and 2 sons apartment who buys of 90 sqm who buys of 90 sqm an 80 sqm an apartment apartment of 90 sqm
  19. 19. CASE OF STUDY - AVERAGE INCOME22.000,0020.000,0018.000,00 Cagliari/Pirri Monserrato16.000,00 Quartucciu Quartu Selargius14.000,0012.000,0010.000,00 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
  20. 20. RESULTSThe results show that the Housing Affordability Index express aconsiderable difficulty of the local community in the acquisition of ansuitable housing unit. This feature is due to the fact that during theperiod from 1999 to 2010 property prices rose by about 109,4% whilethe average income (+34%), population (-6,8%) and constructioncosts(+37,7%).
  21. 21. RESULTS
  22. 22. RESULTS
  23. 23. RESULTS
  24. 24. RESULTS
  25. 25. CONCLUSIONS (1/4)From a market appraisal point of view, results show that theanalyzed housing market is slowed down and its future will dependfrom the short/medium-term economic trend: if the economic crisiswill be resolved quickly the market will slowly take a breath andsettle down to values sustainable by the local community,otherwise it will be a significant decline in average selling pricesthat could lead to a local real estate market crisis, absolutelyunimaginable until few years ago.If we consider the 1999 HAI as the normal ratio between medianincome and house price, market price need to drop by almost a 40percent.
  26. 26. CONCLUSIONS (2/4)With the introduction of IMU, the new italian real estate tax,it is possible to expect a 20% average property market pricefall , with picks up to 50%.This quite alarming synthesis, obtained from a recent issue ofthe magazine ”Outlook sui Consumi”, a pubblication of amayor italian institute of statistic (Censis Confcommercio),from a sample of 1200 households.
  27. 27. CONCLUSIONS (3/4)From a methodological point of view, the proposed system allows toaccess to the created information in an easy and quick way and toperceive the real estate market conditions and risk. However, futuredevelopments will allow to improve the quality of the informationcollected.In particular, among the future goals, it plays a crucial role the study ofthe spatial dimensions of the Housing Affordability Index. In fact, it willbe possible to study not only the specific value of HAI reported to eachhomogeneous area, but it will be possible to quantify the riskconsidering the whole urban center, analyzing the historical variation ofthe quota of "affordable" areas by adding a space component to theHousing Affordability Index.
  28. 28. CONCLUSIONS (4/4)In this way, the final user will be able to understand how much of theurban area is available for purchase depending to the social categoryconsidered. This implementation will allow an easy comparison betweendifferent municipalities’ inhabitants and may therefore be perceivedlevel of "openness" in buying properties offered by various cities.The next step in this study will permit a study of the market offer by aweb related application that allows to extract, in a semi-automated waydigital data banks containing the market values of items offered on themarket. This system will let the final user to be aware of the actualmarket situation of an urban center in real time.