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Housing supply and price reaction : A comparative approach between Spanish and Italian markets

Housing supply and price reaction : A comparative approach between Spanish and Italian markets. Laura Gabrielli Paloma Taltavull. Agenda. Introduction : housing supply evolution and the role on the economies of Italy and Spain Cicles comparison Housing supply estimation

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Housing supply and price reaction : A comparative approach between Spanish and Italian markets

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  1. Housingsupply and pricereaction: A comparativeapproachbetweenSpanish and Italianmarkets Laura Gabrielli Paloma Taltavull

  2. Agenda • Introduction: housingsupplyevolution and the role on the economies of Italy and Spain • Cicles comparison • Housingsupplyestimation • Conclusions

  3. Constructionsector in Italian Economy • GDP includes investment in constructions (residential, non residential and civil engineering works), transaction costs and rents and housing services • In 2010 this sector represented the 10,24% of GPD, with a strong reduction in construction investments • Rents and imputed rents are growing: that figure overcame investment in constructions in the last two years Istat; Conti economici annuall real value

  4. Relavance of Constructions in GDP

  5. Building permits • Building permits fell sharply towards the end of 2005 – 2006 (- 50%) going back below to the level at the beginning of the last market cycle • This is associated with the end of the cycles, the oversupply, the limited number of developing area, despite a constant grow of new families Istat, yearly data Istat and Banca d’Italia

  6. ConstructionCycle in Spain Volver

  7. Type of dwellings • The average size of dwelling is increasing (104 sqm in comparison to 102 sqm of 2008), while the median value is constant at 90 sqm; • Half of the Italian families live in a dwelling of 60 – 100 sqm, while 14,5% and 18,9% live, respectively, in houses smaller than 60 sqm and bigger than 120 smq. • The average size of dwelling is positively correlated with the income: the families with a smaller income (< 20.000 €/year) live in a 70 sqm flat, while the families with a higher income (>45.000 €) live in a house with more than 145 sqm • On average, every person has 41 sqm(but that figure drops to 27 sqm for immigrants) showing a high overcrowding rate for those families • Spain is one of the Eu countries where the overcrowding rate among the population at-risk-of-poverty is below 6% (very low) Banca d’Italia, Indagini sui bilanci delle famiglie italiane Eurostat, 2010

  8. Supply • Destinándose la mayor parte a viviendas principales.

  9. Resultado: Stock de viviendas e intensidad de edificación en España, 1962-2010

  10. Prices

  11. Aim of thispaper • Describe thehousingcycle and pricedynamics in bothcountries • Approachthesupplyelasticityforcomparisonpurposes • Controllingbyregion

  12. Pre-viewresults • Strongerhousingcycle in Spainratherthan in Italy • New supply • Price increaseduring 2004-2008 • Similar responses fromsupplyside • Bothelastic responses topricesignal • Stronger in Spain (2,5) than in Italy (0,91) for 1996-2010.

  13. Fundamentals of housingsupply • Differentexperience(Meen, 2003, Barker review, 2003, Pryce, 1999, Malpezzi & Maclennan, 2001, Bramley, 2003) : • Long runelasticities in USA are >1 • Long runelasticities in Europe are < 1 • Reasons are thedifficultiesto define and estimatethewholesupplyfunction (Hanusheck & Quigley, 1979), because: • Starts are nottheonlysourceforhousingsupply • Theexistinghousessupplied as a sourceisdifficulttobeobserved (Goodman et al, 2005) • Supply function is local and specific to different regions(Glaesser, Gyurko & Sacks, 2005, DiPasquale, 1999) • Howtomeasurethesupply? • Bythe stock (DiPasquale & Wheaton, 1994, Whitehead, 2004, Mayer & Somerville, 2000, Meen, 2001) • By new unitsarrivingtothemarketorstarts(Mason, 1977, Malpezzi & Maclennan, 2001, Meen et al, 1998; Bramley, 2003) • Result… estimations of elasticitiesdifficulttobecompared

  14. Principles of housingsupply • Housing supply theory elements • Supply could not be fixed (Meen, 2001) • It is changing on time (Pryce, 1999, Goodman, 2005) • Dependent of territorial factors, climate (Fergus, 1999) or the geographical situation (Goodman & Thibodeau, 1998). • Different market-control situations: Quasi-monopoly or monopolistic competition basis…land ownership, reduced number of building firms, land uses under control, restrictive permit system(Green & Malpezzi, 2003, Barker Review, 2003) • Control on the production process from developer, to adapt the supply to changes in the cycle (Coulson, 1999) • Others supply restrictions coming from its inputs (land available, materials, labour) • Public intervention… Housing Policy. (Murray, 1999, Malpezzi & Vandel, 2002, Whitehead, 2003). Asymmetric and disparates responses from the supply curve (Goodman, 2005, Pryce, 1999, Glaeser & Gyourko, 2005) VERY RELEVANT..

  15. Literature • H = f(p, ccost, ir), Gs[land, mpower], G[Adm, HP] Where, ‘p = housing prices (new) ‘ccost= construction costs ‘it = financial costs Gs= Spatial differences Land= availability of land Mpover= development structure, market power Adm= effect of administrative processes HP= Housing policy impacts Gs and G are not observables - impose restrictions

  16. Literature • DH = a + bp + g ccost+ dir+ m • Under • Gs • G ‘ b isthepriceelasticity of supply

  17. Relevance of housingsupply… Prices Housing starts

  18. NEW HOUSING SUPPLY ‘MOVES’ whenthereis no restrictions e=0 e<1 Housing prices e=1 e>1 Housing starts

  19. Empirical analysis • Estimatehousingsupplyelasticity of new units • Marketorientedfocus: • Prices are thesignal… afectingstarts • Share of themarketexplainedbythemodel • Theresis no ‘intervention’ onthemarket as: • Marketpower • Escarcity of land • Administrativelimits • Monopolyoroligopoly in development

  20. Model • Definition of new housing supply model according toMalpezzi & Maclenan, 2000 and Glaeser & Gyourko, 2005, Hanusheck & Quigley, 1979, DiPasquale, 1999, Malpezzi & Vandel, 2002, Goodman et al, 2005, Meen, 2001, 2003, Goodman & Thibodeau, 1998, Whitehead, 1974, Mayes, 1979, Bramley, 1996, 2003, Pryce, 1999, Swank et al. 2002, Mayo & Sheppard, 1991… • Qts = f(PH,t, Ct ,Ht-1 , Gtk , pH) = • = a1 PH,ta2 Cmta3 Csta4 ita5 Ht-1a6 [hk Gtk ]a7pHe a8 et

  21. Model Ln (Qtsn in,t) = a1 + a2 ln PH,t +a3 ln Cmt + a4 ln Cst + a5 ln it + a6 Gtk + mt with Gtkmeasured in full model (fix effects) and considering to be constant at regional level - • a2 represents the new supply elasticities • > 1 …. Elastic • < 1 …. Inelastic • Adjust R2 represents how the model explains the new supply, that is: • R2 closer to 1 … the model capture the market performance • R2 far from 1 … there are another drivers for new housing supply (construction decissions) other than the market ones.

  22. Data • Secondarysource data: Nationalinstitutes of statistics • 1995-2010 (lastavailable) • Yearly data • Byregion (14 and 17) • Pool

  23. HOUSE BUILDING PERMISSIONS

  24. Prices

  25. Methodology • Pooledleastsquares • Fixedeffectestimator • Non commonroot, adjustedbyan AR(1) process at regional level • White crossectionstandarderrors and covarianze

  26. Results

  27. Fixedeffects

  28. Conclusions (1) • Similar cycleswithstrongerhousebuilding in Spainthan in Italy • Higherhousepricegrowthalso in Spainbutduring 2004-2008 • Similar marketreacions • Verymarketoriented (adjR2>0,93)

  29. Conclusions (2) • Labourcosts has negativeeffects • Stronger in Spain • Material costsincreaseprices • Stronger in Italy • Interestrates are notstatsignificant in Spain • Itdoes in Italy, smallelasticity • Elasticreactions of house-buildingtomarketsignals… during 1997-2010 • Closethan 1 in Italy (e=0,911) • Closeto 3 in Spain(e=2,9)

  30. THANKS FOR YOUR ATTENTION

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