1 / 48

Demand pressure and housing market expansion under supply restrictions: Madrid housing market

Demand pressure and housing market expansion under supply restrictions: Madrid housing market. Paloma Taltavull de La Paz,Universidad de Alicante Federico de Pablo Martí, Universidad de Alcalá Carlos Manuel Fernández-Otheo, Universidad Complutense Julio Rodríguez, Universidad de Alcalá. Index.

deion
Télécharger la présentation

Demand pressure and housing market expansion under supply restrictions: Madrid housing market

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Demand pressure and housing market expansion under supply restrictions: Madrid housing market Paloma Taltavull de La Paz,Universidad de Alicante Federico de Pablo Martí, Universidad de Alcalá Carlos Manuel Fernández-Otheo, Universidad Complutense Julio Rodríguez, Universidad de Alcalá

  2. Index • Introduction • Description of the demand/supply drivers in housing market in Madrid • Model • Results • Conclusions

  3. Introduction • Between 1997 and 1999, housing prices in Madrid falled in real terms without the existence of any economic crisis. • At the same time than a strong rise in other Spanish areas

  4. Introduction

  5. Introduction • With positive demand factors: • Strong increase on GDP, • the lowest interest rates in the Spanish history • Enough flow of mortgages • Affordability gains • Strong growth on housing prices in other areas • Reasons for the less dynamism in Madrid housing prices? • Market factors? • Public intervention?

  6. Introduction

  7. Introduction

  8. Introduction • Capital of Spain • Mayor city: 6 millions P • 17% of Spanish GDP • Main based on service activities and high quality jobs • Financial center • Decission center for business...

  9. Introduction • Years later, we were ask to develop a research project to explain why Madrid housing prices rise more than in the rest of Spain • In only five years everything changed in Madrid housing market • We are witness of what have happened during the period, • from an static situation to a very dynamic process

  10. Introduction – Methodology followed • 1st. Explore statistics trying to describe what has happened • Different methodologies: Time series, Panel data, GIS, combined. • 2nd. Inside a theoretical framework • Economic intuition to define the hipothesis • 3rd. Contrast the hipothesis • 4th. Need for spatial analysis

  11. Description of drivers evolution • Agreement about the fundamental reasons to explain housing prices last decade • Meen, 2001, Andrew and Meen, 2003, Case and Shiller, 2003, Case, Quigley and Shiller, 2005, • In dense cities... Gibb,and O’Sullivan, 2002, Wheaton, 1998.. • If income and financial growth process do not create restrictions • Demografics? .... Where? • Spatial effects

  12. Description of driver: total population

  13. Description of driver: population mobility (number of arrivals and departures)

  14. Description of driver: population mobility (Spanish and foreigners –all arrivals)

  15. Description of driver: population mobility (Spanish and foreigners –all departures)

  16. Description of drivers evolution • These behaviour show a double shock in basic demand of houses • From foreigners • From increase on internal mobility • Located from 2001 • Increasing the size of the housing market • Along the territory?

  17. Description of drivers: Spatial demographic movements

  18. Description of drivers: Spatial demographic movements

  19. Description of drivers: Spatial demographic movements

  20. Description of drivers: Spatial demographic movements

  21. Description of drivers: Spatial demographic movements

  22. Description of drivers: Spatial demographic movements

  23. Description of drivers: Spatial demographic movements

  24. Description of drivers: Spatial demographic movements

  25. Description of drivers: Spatial demographic movements

  26. Description of drivers: Spatial demographic movements

  27. Description of drivers: Impact on prices?

  28. Description of drivers: migration and prices

  29. Description of drivers: Supply reactions

  30. Description of drivers: Supply reactions.. Enough??

  31. Description of drivers: Supply reactions..Spatial segmentation

  32. Description of drivers: Supply reactions..Spatial segmentation

  33. Model: aggregate definition • Qvdt = f[A(pop, y,f) t, B(Pvt, tit, trt, cut)] (1) • Qvot = g[Pvt, Cmt, tit, Otrost] (2) • Pvt = G[k(pop, y,f, ht) t, m( tit, trt, cut)] (3) Where: • Qvdt is housing demand, • pop is population, • y, income • f mortgages funds • Pvt, housing prices • tit, interest rate • trt, transactions • cut housing use cost • Qvot Housing supply • Cmt, construction costs • Otrost other components, like land, developers market size, market power, administrative restrictions, housing policy, regional differences

  34. Model: Demand equation (See Andrew and Meen, 2003, DiPascuale and Wheaton, 1996 and many others references) • Phd*t = a1 + a2 (pop)t + a3 (ry)t – a4 (h)t + a5 (w)t – a6 (uc)t + a6 (ff)t +et • Identifying the role of different components of population dynamic • Pop = Dp + IR + OI

  35. Model: empirical exercise (ECM model) • Dln(PHt) =L0 [X1] + L1[ln(PHt-1) +l1 lnRYt-1 +l2 lnDPOBt-1+ +l3 lnFFt-1 +l4 lnInft-1 +l5 lnrit-1+l6 lnDHt-1] + + d1DlnPH,t-i +d2DlnRYt-i + d3D lnDPOBt-i + + d4 D lnFFt-i+d5 DlnInft-i+ d6 Dlnrit-i+ d7DlnDHt-i + mt • PHt Housing prices in the moment t • RYt real income • POBt Existing population in the Madrid region. • FFt Mortgage finance flows • Inft Madrid inflation rate • rit Real interest rate. • Ht Housing stock. • [X1] matrix of exogenous variables • L0, L1, li, di parameters to be estimated • T time Identifying the impact of different demographics component: DPop is population in differences EVRAL is household arrivals with house EVRALEXT those coming from foreign countries DEVR is arrivals in differences

  36. Model: demand equation results • HOUSING DEMAND MODELS FOR MADRID MARKET • Variable dependiente D(LRPRV) D(LRPRV) D(LRPRV) D(LRPRV) • Mod 1 Mod. 2 Mod.3 Mod. 4 • Long term relationship  1988-2007 • lt lt lt lt • LRPRV(-1) 1 1 1 1 • LRY(-1) -0,75 -1,53 -1,99 1,22 • t-stud [-2,64182] [-6,63478] [-4,27342] [1,72930] • LDPOB(-1) -0,13 • t-stud [-2,33740] • LEVRAL(-1)0,31 • t-stud [4,81938] • LEVRALEXT(-1) 0,42 • t-stud [5,25553] • LDEVR(-1) -0,11 • t-stud [-3,01786] • LFF(-1) -0,36 -0,19 0,56 0,02 • t-stud [-4,58717] [-2,67231] [3,47261] [0,14267] • LINF(-1) 0,24 -0,22 -0,55 0,44 • t-stud [3,20846] [-3,86900] [-4,95648] [3,66203] • LRI(-1) -0,06 0,18 0,63 0,049 • t-stud [-1,54677] [4,76728] [6,39406] [0,56357] • LDH(-1) 0,42 0,04 -0,64 0,37 • t-stud [7,10577] [0,72742] [-4,63171] [4,21846] • C -9,76 • [-3,39184] • Convergence coefficient • -0,23 -0,11 -0,05 -0,085 • t-stud [-6,16575] [-3,22361] [-3,68685] [-6,00824]

  37. Model: demand equation results

  38. Model: fundamentals’ effect Madrid

  39. Model: fundamental effects in all Spain

  40. Model: demand equation results • Long term components explain the price evolution, • in the general model (all population) • Negative impact of income, finance, changes on population and interest rates (increase on prices, reduces the demand) • Short run impacts of income (2 lags) and changes on population, finance and interest rates (3 lags) • Positive impact on prices from inflation and available stock • Short run effects for stock (4 lags) and inflation (3 lags) • Strong dynamic relationships

  41. Model: demand equation results • Migration models: • Higher sensibility to changes on income • Migration is positive correlated with changes on prices: arrivals stress the prices (both cases, total and foreign) • Total inmigration is positivelly correlated with interest rates but not with existing stock, so, household movements could stress construction outside Madrid • Foreign inmigration is positive correlated with finance and interest rates, and negativelly with housing availability. • These could suggest that their arrival depends of income but also of the existent stock available, purchase capacity and the availability to have finance. • From 2000, banks in Spain start to give mortgages masivelly to inmigrans with permanent job....

  42. Model: demand equation results • Migration models (cont): • Positive correlation among stock and prices in presence of foreign movers suggest that there is a lack on supply for this demand • Negative correlation in the case of all movers (most are previous residents, spanish and foreigners) suggest that they could decide move to other market in the case of good condicions. • This also suggest that higher prices or other factors expulse this demand to other housing markets.

  43. Model: Supply equation • Goodman, 2005, Meen, 2003, Malpezzi y Maclenan, 2000 y Glaeser y Gyourko, 2005 • Qts = f(PH,t, Ct ,Ht-1 , Gtk , pH) = • =ea1 PH,ta2 Cmta3 Csta4 ita5 pta6 Ht-1a6 [hk Gtk ]a7pHe a8 et • Where: • - PH,t housing prices • - Cmt materials costs • - Cst cost of salaries • .- it interest rates • - pt cpi • - Ht-1 existing stock • - hk Gtk regional caracteristics matrix • - pHeinflation expectations in housing • - et random component • a1..8 estimated parameters

  44. Model: Supply equation • Ln (Vivin,t) = a1 + a2 ln PH,t +a3 ln Cmt + a4 ln Cst + a5 ln it + a6 ln pt + a8hk Gtk + nt • Looking for the supply elasticity a2 • Method: 2 stages regression 2SLS • 1988-2007

  45. Model: Supply Elasticity

  46. Model: Supply Elasticity and model explanation capacity

  47. Model: Supply Elasticity results • High supply elasticity which suggest rapid reactions of the developers when prices rise • Low capacity of explanation, which suggest that the share of the market performing as a market is small • Also suggest that there are other variables affecting the new supply decissions process, • The existence of supply restrictions in Madrid markets • Lack on supply... Expulse demand • And increase prices in a market segment

  48. Conclusions

More Related