1. Housing rent market: the relevance of a micromarket Paloma Taltavull de La Paz University of Alicante, Spain ERES Yearly Conference Eindhowen, June, 2011 1June, 2011

2. Paper topic Rent market in Spain is very small: 11,2% of total family homes (census 2001) Perception of a tiny market: –Retrictions to mobility –Inefficiencies in housing market Is that true? Has the market balance in some way to develop micro markets on rent? June, 20112

3. Agenda Introduction Aim of the paper General overview of Spanish rent market Data Models: factorial analysis Discussion and conclusions 3June, 2011

4. Research questions Small rent market.. To who?. House mkt segmented? Type of house rented The role of a small rent market to: Cover mobility needs of population/work market Cover housing needs June, 20114

5. Findings Small in average but larger in urban areas Covering mobility needs 2 main types of houses rented 5 types of household renting homes Factors affecting mobility and quality.. Supply June, 20115

6. Data description Census 2001, microdata 92088 observations for all Spain, –Statistically significant of all market Information including: –House characteristics… 33, 31 usable –Construction history – Demand features of households renting houses June, 20116

7. Methodology 2 steps: –Cluster analysis to define the typical house rented –Factor analysis to find the ‘typical’ household renting homes in Spain June, 20117

8. RENT MARKET IN SPAIN June, 20118

9. Introduction 9June, 2011

10. General overview 10June, 2011

11. General overview June, 201111

12. General overview. Spatial distribution June, 201112 Main provinces Smaler rent market’s provinces

13. General overview June, 201113

14. General overview: Segmentation June, 201114

15. Covering mobility RENT AND MOBILITY RANKING (Ratio between new residents and rented houses) Source: INE 2000200120002001 ProvincesProvincias 19-Guadalajara2,082,4005-Ávila0,870,91 03-Alicante/Alacant1,571,8325-Lleida0,660,90 45-Toledo1,441,5635-Palmas (Las)1,000,89 04-Almería1,491,5040-Segovia0,810,87 26-Rioja (La)1,371,4041-Sevilla0,930,86 16-Cuenca1,371,3509-Burgos0,720,84 46-Valencia/València1,221,3420-Guipúzcoa0,770,82 44-Teruel1,101,3427-Lugo0,770,79 12-Castellón/Castelló1,191,2921-Huelva0,880,79 31-Navarra1,241,2638-Santa Cruz de Tenerife0,810,77 30-Murcia1,251,2107-Balears (Illes)0,750,74 01-Álava1,061,1637-Salamanca0,900,70 39-Cantabria1,151,1334-Palencia0,800,69 43-Tarragona1,241,1336-Pontevedra0,690,66 42-Soria1,081,1024-León0,65 48-Vizcaya1,071,0923-Jaén0,780,65 28-Madrid1,09 15-Coruña (A)0,680,64 22-Huesca0,841,0414-Córdoba0,63 13-Ciudad Real0,921,0110-Cáceres0,640,59 02-Albacete0,931,0008-Barcelona0,540,56 32-Ourense1,070,9706-Badajoz0,590,49 49-Zamora1,000,9751-Ceuta0,530,48 17-Girona0,870,9533-Asturias0,490,46 29-Málaga0,930,9211-Cádiz0,490,44 47-Valladolid0,740,9150-Zaragoza0,430,44 18-Granada0,900,9152-Melilla0,350,32 June, 201115

16. General overview: Distribution and mobility June, 201116

17. Stable living house? June, 201117 YEAR OF ARRIVAL TO RENT HOUSE, SPANISH MARKET 2001 15,5 10,39 10,19 7,34 5,12 4,20 10,48 12,50 10,74 7,27 4,73 1,51 0,0 2,0 4,0 6,0 8,0 10,0 12,0 14,0 16,0 18,0 2001200019991998199719961991-19951981-19901971-19801961-19701941-1960Antes de 1941 RENT ( % of total family houses in rentr) Source. INE, Censo

18. June, 201118

19. SOME RENT HOUSIGN SUPPLY CHARACTERISTICS June, 201119

20. June, 201120 Distributed along groups with lower size

21. June, 201121 RENT STOS BY AGE OF THE BUILDING. SPANISH HOUSING STOCK 2001 0,00 10,00 20,00 30,00 40,00 50,00 60,00 70,00 80,00 90,00 TOTAL 01- Á lava 02-Albacete 03-Alicante/Alacant 04-Almer í a 33-Asturias 05- Á vila 06-Badajoz 07-Balears (Illes) 08-Barcelona 09-Burgos 10-C á ceres 11-C á diz 39-Cantabria 12-Castell ó n/Castell ó 51-Ceuta 13-Ciudad Real 14-C ó rdoba 15-Coru ñ a (A) 16-Cuenca 17-Girona 18-Granada 19-Guadalajara 20-Guip ú zcoa 21-Huelva 22-Huesca 23-Ja é n 24-Le ó n 25-Lleida 27-Lugo 28-Madrid 29-M á laga 52-Melilla 30-Murcia 31-Navarra 32-Ourense 34-Palencia 35-Palmas (Las) 36-Pontevedra 26-Rioja (La) 37-Salamanca 38-Santa Cruz de 40-Segovia 41-Sevilla 42-Soria 43-Tarragona 44-Teruel 45-Toledo 46-Valencia/Val è ncia 47-Valladolid 48-Vizcaya 49-Zamora 50-Zaragoza Before 1971 1971-1990 After 1991 ( % total rent houses) Source. INE, Censo 2001

22. General overview: Quality June, 201122

23. SOME DEMAND CHARACTERISTICS OF RENT MARKET June, 201123

24. Model 2- data description June, 201124

25. Model 2- data description June, 201125

26. Model 2- data description June, 201126

27. Model 2- data description June, 201127

28. Model 2- data description June, 201128

29. Model 2- data description. Rent by nationality RENT TENENCY AND NATIONALITY (% of total population living in rent) Spanish79,60 European without Spanish4,81 Áfricans4,87 Latinamericans9,80 Asians0,92 Others0,02 Source. INE, Censo 2001 June, 201129

30. Model 2- data description RENT TENENCY AND NATIONALITY (% of total population living in rent) Spanish79,60 European without Spanish4,81 Áfricans4,87 Latinamericans9,80 Asians0,92 Others0,02 Source. INE, Censo 2001 June, 201130

31. Model 2- data description. Mobility and rent market June, 201131

32. Model 2- data description June, 201132

33. Model Rent market suplly/demand –… 44 variables..profile of household in rent –22 about the head of household –22 about structure of the household –With 22 house characteristics –92,088 observations microdata Cluster analysis … types? Supply groups of houses by characteristics Households…Demand groups Factorial analysis… Determinants of rent June, 201133

34. Supply. Rent house type Average house… characteristics –Rented since 1992 –Good neighbourhood quality –Good communications, enough public services –Low delinquency –Low green areas –Around 81 m2, 4 bedrooms, new –Good quality June, 201134

35. Model 1. Supply. 2 cluster identified: 2 types of houses: June, 201135

36. Model 1. Supply. Centroids June, 201136

37. Model 2 Factors explaining supply side of rent market Factors explaining housing rent. The supply side Factor 1- Type of building Númber of floors0,88 Factor 7 – Water system KMO and Bartlett's Test Floor of the apartment0,79Water system0,82 Kaiser-Meyer-Olkin Measure of Sampling Adequacy.0,75 Type of building0,75Water distribution network0,78 Bartlett's Test of SphericityApprox. Chi-Square14724,87 Type of owner0,59Factor 8 – Building quality df378 Number of garaje parking0,51Building quality0,71 Sig.0 Factor 2- Problems in the neighbourhoodBad road network0,52 Contamination0,66 Matrix Determinant0,012 Not well cleaned streets0,64Factor 9- Accesibility Noises0,63Vehicles availabilty (cars..)0,7 Delinquency, insecurity0,58 Total Varianza explicada No green space0,47 Componentes- FactoresInitial Eigenvalues Bad accesibility0,3 Total% de la varianze% Acc Factor 3- Size 13,8513,75 Nº of rooms0,87 21,997,1120,86 Surface0,86 31,685,9926,85 Factor 4- Year of arrival 41,595,6932,55 Year of arrival to city0,83 51,314,6737,22 Year of arrival to house0,77 61,224,3741,59 Factor 5- Energy 71,134,0445,63 Type of energy used0,77 81,093,8949,52 Gas0,59 91,083,8553,36 Factor 6- Facilities Telephone0,64 Hitting0,61 *Coeficientes de la matriz de componentes rotados Método de extracción: componentes principales, rotación: Varimax con normalización de Kaiser June, 201137

38. Demand Household renting house ‘average-type’ –Spanish, male, around 35 years old –Living in hte municipality from more than one decade –Married, 3 – 4 people: couple plus children –Working in the same municipality. 2 workers 20 minutes commuting Permanent contract, working for other –Bachelor level –Good quality in the house June, 201138

39. Model 1. Demand…5 Clusters identified Three foreign households –1.- Single immigrant men (Latinoamerica) living with others, young, medium education level High mobility, commuting 1.5 hours Recent arrived, working more hours than average Good quality in house neighbourhood, 80 m2 –3.- Single female also immigrant (Latinoamerica), medium age, low education level Living with other person (child or partner) No recent arrived (moving from other city), working little hours No so good quality in neighbourhood –2. Married man, from Europe (main UK) High education level, working in services Working in the city, stable work High quality in living conditions, large houses June, 201139

40. Model 1. 5 Clusters identified 2 Spanish rent households. –4. Single man, 37 years old, medium education Not migrant (living in the municipality from long time) Working in companies link to services, medium level salary Good quality in the neighbourhood, 70 m2 –5. Single man, 45 years old, high level of education Moved to municipality long time ago Commuting in own car Good or very good quality in neighbourhood June, 201140

41. Model 2: Household factors determinants of rent a house. Demand side June, 201141

42. Model 2: factor analysis June, 201142

43. Conclusions Rent market in Spain –Census 2001 data: stock&population, no other sources –Microdata Two level of analysis: –Typology of houses supplied in rent –Typology of rent house demanders Cluster and factorial analysis Including information about mobility for labour reasons June, 201143

44. Conclusions Micro rent market in Spain but with relevance in capitals Most associated to mobility needs for labour purposes –Direct and possitive relationship statistically significant Rent houses not statistically distinct from owned homes … Good quality.. Similar conditions Smaller than the owned stock June, 201144

45. Conclusions Relevant to cover immigrants’ demand –From all income ranges Not homogeneous for Spanish households There is no a ‘Rent typology’ for Spanish households Main role for single households, both foreign as well as Spanish Not relevant for traditional households… ownership rate June, 201145

46. Conclusions Very relevant in some provinces/cities, with rent rates similar to the international ones –Ceuta, Melilla, Canary Islands, Baleares, Barcelona, Cádiz, León, Coruña… Limitations in housing mkt in other: –Madrid, Housing needs has been covered by ownership June, 201146

47. Future Rent market in Spain changes during 2000’s June, 201147