International Perspectives on Poverty, Social Exclusion, and Homelessness

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Presentation given by Professor Marybeth Shinn, Professor of Human and Organizational Development Vanderbilt University, Peabody College, Nashville, USA at a FEANTSA Research Conference on "Homelessness and Poverty", Paris, France, 2009

Transcript of International Perspectives on Poverty, Social Exclusion, and Homelessness

International Perspectives on Poverty, Social Exclusion, and

Homelessness

European Observatory on Homelessness18 September, 2009

Marybeth Shinn,Vanderbilt Universitybeth.shinn@vanderbilt.edu

Outline: Homelessness in Industrialized Countries

• Definitions & comparative numbers• Pathways into Homelessness:

– Poverty and lack of social safety net– Housing affordability and subsidies– Structural changes income and housing– Social exclusion– Individual factors– Relationship among levels of analysis

If a turtle loses its shell, is it naked, or is it homeless?

Definitions Matter

• U.S.: Literal homelessness: rough sleeping; shelters (specialized homelessness services)

• Europe: Broader focus on tenuous or inadequate ties to housing

• Australia: 3 levels– Primary = rough sleeping– Secondary = shelters and doubling up– Tertiary = inadequate housing

Focus on Literal Homelessness

• Inadequate housing is almost by definition a function of poverty

• Literal homelessness often theorized to be a function of disability

• Goal is to switch lens to focus on structural factors, including poverty and social exclusion

• Even disability may operate via poverty and access to housing

Self-Reported Homelessness Over Lifetime in US as of 1990

Literal Literal Plus Doubled Up

Percentage 7.4% 14.0%

Number 13.5 million 26.0 million

(Link et al., 1994)

% Lifetime Literal Homelessness U.S. and Europe:

Telephone Surveys

US UK Italy Belgium Germany

6.2 / 8.1 5.0 / 7.7 4.0 3.4 2.4

(Toro et al., 2007; Shinn, 2007)

Pathway: Poverty and Lack of Social Safety Net

• Income inequality

• Social benefits

• Social and subsidized housing

US UK Ital Bel Ger Fra Swe Jap Aus

% lifetime literal homelessness

6.2/

8.1

5.0/

7.7

4.0 3.4 2.4

% income for

lowest 10%

1.9 2.1 2.3 3.4 3.2 2.8 3.6 4.8 2.0

GINI coefficient

40.8 36.0 36.0 33.0 28.3 32.7 25.0 24.9 35.2

Social Policies: Income Inequality

U.N Development Report (2007/8)

Inequality and Homelessness

• Models of housing markets (O’Flaherty, 1995, 1996)

– At the bottom, increasing inequality increases demand for low-quality housing

– At the top, increasing inequality increases demand for land

– Both factors increase the price of low-quality housing, increasing homelessness

US UK Ital Bel Ger Fra Swe Jap Aus

% lifetime literal homelessness

6.2/

8.1

5.0/

7.7

4.0 3.4 2.4

% income for

lowest 10%

1.9 2.1 2.3 3.4 3.2 2.8 3.6 4.8 2.0

GINI coefficient

40.8 36.0 36.0 33.0 28.3 32.7 25.0 24.9 35.2

Social benefits as % of GDP

10.6 15.6 20.5 19.6 20.2

Family benefits as % of GDP

0.5 2.3 2.7 2.7 3.3

Social Policies: Social Benefits and Transfers

Alesina & Glaeser (2004)

Homelessness and Family Policy: U.S.

• ¼ of all episodes of poverty begin with birth of a child (Waldfogel, 2001)

• Homelessness among families associated with childbirth (Weitzman, 1989)

• Infancy is the age at which risk of shelter use is highest (HUD Annual Homeless Assessment Report, 2007)

US UK Ital Bel Ger Fra Swe Jap Aus

% lifetime literal homelessness

6.2/

8.1

5.0/

7.7

4.0 3.4 2.4

GINI coefficient

40.8 36.0 36.0 33.0 28.3 32.7 25.0 24.9 35.2

GINI Market Income (Luxembourg)

45 45 50 43 49 44 45

% Reduction by Taxes and Benefits

18 24 48 42 47 43 31

Effects of Taxes and Benefits on GINI

Smeeding (2000)

Poverty: United States• Highest income inequality in OECD• Greatest increase in inequality over past 2-3

decades• Transfers do least to redistribute• Both low social benefits and low wages lead

to poverty (Smeeding, 2000)

Attitudes Towards Social Spending

• Belief that poverty is society’s fault explains variance in social spending– 82% of variance among nations with 1998

per capital GDP > $15,000– 43% of variance among 30 nations

– Alesina & Glaser (2004)

Alesina & Glaeser (2004)

Housing Affordability• There is no State in the United States:

– Where a full-time minimum wage worker can afford a two-bedroom apartment

– Where a person on disability benefits can afford a studio apartment (NLIHC: Waldrip, Pelletiere, & Crowley, 2009)

78

74

109

89 70

12491

CT:108

DE:99DC :131

109

90

HI:163

79

8967

82

77 73

92

83

MD:130

MA:115

78

92

77

73

71

77111

NH:108

NJ:129

69

130

81

66

72

76

69

86

RI:101

79

70

94

86

VT:87

111

79

63

87

80

Work Hours/Week at Minimum Wage Needed to Afford 2 Bedroom Apartment (NLIHC, 2009)

= >120= >80 and <120= <80

Housing Affordability and Homelessness: Economic Models• Rise in homelessness in U.S. corresponded to

rising gap in housing affordability (Shinn & Gillespie, 1994)

• Homelessness is higher when– Rental costs are higher relative to incomes– Vacancy rates are lower (Quigley et al. 2001)

– (Problem: quality of homelessness data)

• Recessions associated with rise in

homelessness in New York City (O’Flaherty & Wu, 2006, Cragg & O’Flaherty, 1999)

Housing Subsidies and Homelessness: Economic Models• Studies of rates of subsidized housing and

rates of homelessness are not convincing• Some find clear benefits to subsidies (Mansur et

al, 2002)

• Housing subsidies may be poorly targeted (Early, 2002, 2003; Early & Olsen, 2002)

• Size of social housing sector is not closely related to rates of homelessness

US UK: Eng

Ital Bel Ger Fra Swe Jap Aus

% lifetime literal homelessness

6.2/

8.1

5.0/

7.7

4.0 3.4 2.4

Social Rental Sector as % of Stock

3.2 18-- 7-- 17.3 17.7 4.9

Housing: Size of Social Rental Sector

Fitzpatrick & Stephens (2007)

Housing Subsidies and Homelessness: Interventions

• Vouchers reduced shelter entry for families in national randomized study (US) (Wood et al., 2008)

• Subsidies for families exiting NYC shelter associated with:– Lower returns to shelter (Wong et al., 1997)

– Long-term stability (Shinn et al., 1998)

– Lower shelter populations (O’Flaherty & Wu, 2006, Cragg & O’Flaherty, 1999)

• Subsidized housing & entitlement benefits associated with exits from homelessness for adults and families in California (Zlotnick et al., 1999)

Structural Changes and Homelessness

• Japan – Loss of lifetime employment, tied accommodations (Okamoto, 2007)

• Central Europe – Change to market economy and social disruption (Hradecky & Hladikova, 2007; Fitzpatrick & Stephens, 2007)

• France – Industrial restructuring (Firdion & Marpsat, 2007)

• Global Economic Crisis

Pathway: Social Exclusion• Homelessness more common

among socially excluded groups– U.S.: African Americans, Native

Americans (Burt et al., 1999)

– Japan: Ainu, Koreans, Okinawans; Eta and Hinin (Okamoto, 2007)

– France: Africans and people from overseas departments (Firdion & Marpsat, 2007)

– Australia: Aboriginals and Torres Strait Islanders (Homelessness Task Force, 2008)

Social Exclusion

• Racial and linguistic heterogeneity are inversely associated with social welfare spending– Across nations (total spending)– Across states in U.S. (welfare benefit)

– Alesina & Glaser (2004)

Alesina & Glaeser (2004)

Mechanisms Linking Social Exclusion to Homelessness

• Current discrimination – income, employment

• Past discrimination – wealth (housing)

• Current discrimination – housing access

• Differential rates of imprisonment

Mechanisms of Social Exclusion (U.S. Black vs. White)

• Median family income 55% as high

• Median household net worth 1/8 as high– Conley (1999)

• Ongoing residential discrimination in tests – Turner et al. (2002)

• Male imprisonment 7.1 times higher – Harrison & Karberg (2004)

Imprisonment Rates per 100,000

0

100

200

300

400

500

600

700

800

U.S. NZ UK Aus Italy Germ Fran Jap

Source: International Centre for Prison Studies, 2006

Individual Pathways

• Economic capital

• Human capital/ Disability

• Social capital

• Life transitions

• All have implications for poverty and housing needs

Economic Capital

• Current poverty

• Poverty in family of origin– Culture of poverty?– Inability to assist young adults– Health and mental health problems– Differential access to human capital

Poverty and Homelessness : NYC Families

• Poverty in family of origin– Predicted shelter entry– Unrelated to post-shelter housing stability,

after subsidized housing controlled– (Shinn et al., 1998)

• Implications:– Lack of resources, not “culture” important– Social policy can counteract individual

vulnerability

Human Capital/ Disability

• Education and skills to get employment• Mental health, substance abuse problems

– Higher for single adults than for families– Bi-directional relationship: Risk amplified by

homelessness (Johnson & Chamberlain, 2009)

– Important minority

• Physical health (also bi-directional)

• All related to ability to earn income

Social Capital• Bi-directional relationship with

homelessness (Firdion & Marpsat, 2007)

• Particularly important for groups who may be dependent on others– Older adults– Women in some societies– Adolescents

• Negative relationships: conflict, violence (Philippot et al., 2007)

Social Capital Evidence: NYC Families

• Families entering shelter reported MORE social ties than other poor families

• Also more negative relationships– Domestic violence– Foster care, other childhood disruptions

(Shinn et al., 1998)

• Domestic violence paradox

Cures for Individual Factors: Housing Important for All

• Poor people: Subsidized housing– New York: Homeless families same level of

stability as other poor families (Shinn et al., 1998)

• Adolescents: French foyer model• Adults with mental illnesses:

– Supported housing; housing first model (Tsemberis et al., 2003, 2004)

Relationships Among Levels• Policy, socio-cultural, structural factors:

– rates of homelessness – social groups at risk

• Individual vulnerability factors: – who becomes homeless (Musical chairs)

• Implications for prevention– General social policy– Support for vulnerable groups

Relationships Among Levels

• Risk amplification over time– Adolescents (Whitbeck & Hoyt, 1999)

– Older adults (Shinn et al., 2007)

• Implications for prevention– Intervene quickly – “Break the cycle” – (Homeless Task Force, 2008)

Interactions Across Levels

• Policies and services can compensate for individual vulnerabilities

– Single parenthood: U.S. vs Belgium – Subsidized housing for families in NYC– Supported housing, especially housing

first programs for individuals with mental illnesses

Summary: Pathways & Cures

• Poverty & Structural Change– Reduce inequality via wages, tax and

transfer programs– Provide social benefits, housing subsidies

• Social exclusion– Identify and counteract mechanisms– Enforce anti-discrimination policies– Compensate for discrimination

Summary: Pathways & Cures

• Individual factors– Social policy to counteract individual

vulnerabilities– Support for transitions

• Young people (families)• People leaving institutions

– Ongoing supported housing, housing first• People with mental illnesses• Older adults