HOUSING DEMAND, TENURE CHOICE HOUSING DEMAND, TENURE CHOICE AND HOUSING POLICY IN BRAZILAND HOUSING POLICY IN BRAZIL

Maria da Piedade MoraisMaria da Piedade MoraisBruno de Oliveira CruzBruno de Oliveira Cruz

InstituteInstitute of of AppliedApplied EconomicEconomic ResearchResearch, , BrazilBrazilFourth Urban Research Symposium 2007

World Bank,Washington, DC, May 14, 2007

Paper OverviewPaper OverviewI. IntroductionII. Survey of the Literature on Tenure ChoiceIII. Brief Retrospect of Housing Policy in BrazilIV. The Data and MethodologyV. Empirical Models and ResultsVI. Conclusions and Policy ImplicationsVII. Bibliography

APPENDIX- A model of tenure choice: the case of formal and informal housing markets

Paper MotivationPaper MotivationHousing Policy in Brazil and Latin America withemphasis on the promotion of homeownership

Lack of studies on the tenure choice of the Brazilian households

Housing accounts for 30% of the total stock of physical capital in Brazil (IPEADATA, 2004)

Housing corresponds to the main asset in household´s portfolio

Housing tenure conditions vary deeply acrosscountries, irrespective of income patterns, region of globe and levels of development

OwnershipOwnership RatiosRatios in in SeletectedSeletected CountriesCountries of of EuropeEurope andand LatinLatin AmericaAmerica

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

Nicaragu

a

Spain

Irelan

dVen

ezue

laHond

uras

Trinidad

e To

bago

México

Argenti

na

Brazil

Belgium

United King

dom

Bolívia

Portug

alEl S

alvad

orUrug

uay

Finlan

d

France

Holland

Jamaic

aGerm

any

Source: CEPAL, IBGE and Housing European Statistics 2002

Paper ObjectivesPaper Objectives

Analyze the main determinants of tenurechoice in Brazil in formal and informal housing markets using micro-econometric techniques

Help in the design of housing policies betteradapted to housing demand and incomelevels, and more effective to meet the housingneeds of the Brazilian population

Questions Explored in the PaperQuestions Explored in the PaperThe study tries to elaborate on:

1) What are the driving forces behind the housing tenure choice of households?

2) What are the tenure options faced by households either in developed or developing countries?

3) Do poor households have tenure choice or squatting and precarious rental and sharing arrangements in informal settlements are the only options open to them to satisfy their housing needs?

4) What kind of housing policies should be promoted by the government in order to meet housing demand?

Housing Policy in BrazilHousing Policy in BrazilUntil the 1930s the private rental sector was crucial in the provision of housing for fast growing population in Rio and SPAfter the 1940s official housing policies start to advogate the benefits of homeownershipDesincentive to rental housing and urban renovation projects in central areas, under rapid urbanization, led to the emergence of slums andperipheral settlements in main MAsThe official policy for informal settlements until the 70s was erradicationand relocation to the peripheryGoverment Housing Policies with poor performance and regressiveimpacts in the reduction of housing shortageLoans to medium and high income class absorbed the bulk of credit to self-owned housing (from 1964-1986 BNH financed only 25% of theincrement of the housing stock and less than 20% of beneficiaries have income below 5 minimum wages)Recently, promotion of social housing through slum upgrading, mutual-help and urban regularization, but accounting for less than 10% of Housing FundingLow income population with little payment capacity what restricts theiraccess to formal finantial, rental and owner-occupied housing markets

Brazil – Tenure Conditions of urban and rural Private Dwellings 1940-2000

74,4

20,9

35,4

43,7

69,8

61,760,357,452,2

14,323,1

22,5 19,022,5

16,411,4

24,7

20,1 20,715,8 13,8

0

10

20

30

40

50

60

70

80

1940 1950 1960 1970 1980 1991 2000

Owner Renter Other Condition and Without tenure declaration

Source: IBGE – Demographic Census

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 até 400Reais

400 a600 reais

600 a1000

1000 a1200

1200 a1600

1600 a2000

2000 a3000

3000 a4000

4000 a6000

Acima de6000

Aquisiçao de imovel Ref orma ou melhoria do imovel

Pagament o de f inanciament o de imovel Renda Tot al

Renda do Trabalho Renda não monet ar ia

Housing Expenditures inequality in Brazil is even higher than income inequality

Housing purchase Housing ImprovementMortgage Downpayment Total IncomeLabor Income Non-monetary Income

The Data and MethodologyThe Data and MethodologyThe data comes from the Brazilian CensusBureau (IBGE) 2005 National HouseholdSurvey (PNAD)

Sample selected through an extendedconcept of “urban areas” (3 urban sectorsas classifief by IBGE and rural of urbanextension)

After Weightening microdata to berepresentative of the country as a whole, our sample covers 44,949,283 households

The Data and MethodologyThe Data and MethodologyBased on information regarding modes of occupancyof the dwelling unit, property rights over land andtype of sector (substandard or not) we have defined 4 categories of tenure:

1) Formal ownersFormal owners: owns the house, owns the land and the dwelling unit is not located in a substandard area;

2) Formal RentersFormal Renters: Rents or rent-free outside substandard area

3) Informal OwnersInformal Owners: owns the house but not the land or has other tenure condition such as squatter, owns in a substandard area (slum dweller) or both

4) Informal RentersInformal Renters: rents or rent-free in a substandard area.

The Data and MethodologyThe Data and Methodology

Tenure Condition Frequency Percentage Valid

Percentage Cumulative Percentage

Valid Formal Owner 2,999,3897 66.7 7.9 7.9

Formal Renter 8,067,093 17.9 19.6 92.5

Informal Owner 2,907,590 6.5 7.1 99.5

Informal Renter 191,112 0.4 0.5 100.0

Total 41,159,692 91.6 100.0 Missing System* 3,789,591 8.4 Total 44,949,283 100.0

Source: the authors, based on PNAD microdata

72.9 72.9

The Data and MethodologyThe Data and MethodologyWe have used four main blocks of explanatory variables:

1) Life Cycle and Household CharacteristicsLife Cycle and Household Characteristics: Age of the Household Head, Household size, Marital Status

2) Wealth and Permanent IncomeWealth and Permanent Income: Per capita income, Household income, Years of schooling of head, Wealth proxy

3) Social Vulnerability and Credit ConstraintSocial Vulnerability and Credit Constraint: Gender (single women with kids under 14), Migrant (up to 4, 4 to 9, 9 or + years), race (non-afrodescent), Economic dependency (head income/total income), Labor Market status (formal employees, public servants, employers)

4) Location variablesLocation variables : metropolitan areas, large cities, macroregions

The Data and MethodologyThe Data and MethodologyWe have constructed a proxy forproxy for household wealth wealth based on housing conditions and access to durable goods

Adequate housing conditionsAdequate housing conditions (UN-Habitat definition)-decrease by 1 point for each attribute missing :

piped water from public network,sewage network or septic tankelectricitypermanent wallsPermanent ceilingNot overcrowded (less than 3 people per dormitory)

The Data and MethodologyThe Data and MethodologyAccess to Access to durabledurable goodsgoods : increase in 1 point for each desirable good

Fridge (1.5 point for 2 doors)TVFreezerComputerInternetWashing Machine

Size/qualitySize/quality of of thethe dwellingdwelling unitunit- number of bathrooms per person :decreasing 0.5 point per each quartile, 1st 1, 4th -1

TENURE TENURE CHOICECHOICE

Informal Owner

Formal Renter

LifeCycle

IncomeWealth

Social Vulnerability

LocationalVariables

Informal Renter

Formal Owner

Empirical Model and ResultsEmpirical Model and ResultsCross-Section Logit e Multinomial LogitModels:

Logit (owners vs. renters)

Multinomial Logit 1 (formal owners, formal renters and informal dwellers)

Multinomial Logit 2 (formal owners, formal renters, informal owners andinformal renters)

Empirical Model and ResultsEmpirical Model and ResultsThe forecast performance of the Multinomial Logit Models that include informal arrangements in the dependent variable is superior to the simple Logit Model

Life cycle variables such as age of head, household size and marital status increase the probability of homeownership

Migration has a negative impact on homeownership but this impact dissipates over time

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

90,0%

100,0%

Less than18

18 a 24 24 a 30 30 a 35 35 a 45 45 a 55 55 a 65 more than65

formal owner formal renter Informal Owner Informal Renter

Brazil 2005: Impact of Age on tenure choice

LogitLogit Model: Model: Impact of Age and Migration over homeownership

0

0,2

0,4

0,6

0,8

1

1,2

Prob

abili

ty

Native or other condition Recent Migrant

age

Empirical Model and ResultsEmpirical Model and ResultsLocational variables are significant and presentthe expected signs: living in large citiesdecreases the probability of homeownership

Education increases the probability of being in formal housing markets, either as an owner or a renter

An employment in the Public Sector increasesthe probability of becoming a homeowner in formal housing markets. Formal employeespresent a negative sign, contra-intuitive result

Impact of Education on tenure choice

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00 9,00 10,00 11,00 12,00 13,00 14,00 15,00

Formal Owner Formal Renter Informal Owner Informal Renter

Empirical Model and ResultsEmpirical Model and ResultsWealth is a good predictor for formal ownership

Current income is statistically significant buthas little impact

More vulnerable households such as thepoor, the afro-descendents or single womenwith children under 14 have a higherprobability to beeing in informal sector, showing that they have limited tenurechoices, confirming results in the literature(Gilbert, 1993; Cocatto, 1996; Nenochea, 1987)

0

0,1

0,2

0,3

0,4

0,5

0,6

-7,5 -5 -2,5 0 2,5 5 7,5 10

Prob

abili

ty

wealth

Logit Model: Impact of Wealth on the probability of homeownership

Policy ConsequencesPolicy ConsequencesPolicy makers in Brazil, should considerwealth and income distribution and pointin the life cycle in the design of housing programmes, such as incentives for first homeownership or subsidies to rental housing for young people

The pattern of expenditures of the Brazilian households on home improvement shows the opportunity for microfinanceprogrammes for progressive housing

Policy ConsequencesPolicy ConsequencesPolicy makers should not focus exclusively on owner-occupied housingA wider range of housing options with different modalities, prices, qualities and locations should be availableRenting must be recognized as both a respectable and necessary housing optionRental housing can offer good housing solutions for young people and newly arrived migrants in search of employment,with importance of rental markets to aleviate housing shortage increasing in urban agglomerations and fast growing urban areas

Recommended Future ResearchRecommended Future ResearchEstimate separate models for each metropolitan areaor estimate tenure choice at intra-city level, takinginto account location and tenure choice decisionsbased on Gibb (2000) or Elder and Zumpano (1991)Developed a dynamic analyses of tenure choicebased on pseudo pannels from the 1992-2005 PNAD series, to take into account effects of inflation ontenure user cost of owing vs. renting. The effects of tenure insecurity can also be better captured on a dynamic framework. Improve information on tenure security and propertyrights in PNAD and further refining of social vulnerability and credit constraint variablesStudy the impacts of precarious insertion in the labor markets in new households formation rates (Sharing, Late Stayers)

ContactsContactsIPEA Homepage: https//: www.ipea.gov.br

Maria Maria dada PiedadePiedade MoraisMoraisE-mail: piedade@ipea.gov.br

Bruno de Oliveira CruzBruno de Oliveira CruzE-mail: bruno@ipea.gov.br