Drivers of homelessness, and what works to bring people inside driver… · Drivers of...
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Drivers of homelessness, and what works to bring people inside Tedd Kelleher Senior Managing Director June 2019 1
Transcript of Drivers of homelessness, and what works to bring people inside driver… · Drivers of...
Drivers of homelessness, and what works to bring people
insideTedd Kelleher
Senior Managing Director
June 2019
1
The Department of
Commerce touches
every aspect of
community and
economic development.
We work with local
governments, businesses
and civic leaders to
strengthen communities
so all residents may
thrive and prosper.
We strengthen communities
2
Safety / Crime Victims
BusinessAssistance
Planning Infrastructure
CommunityFacilities
Housing
Energy
Commerce provides a publicly available accounting of where the homeless money goes
Project-level reporting for all projects receiving any public homeless funds (federal, state, county, city)
Information available includes: Spending from all funding sources (including all public and private spending), bed/slots, numbers served, average length of time in
project, exit destinations, % of people returning to homelessness, etc.Spending data reported by counties, client data from HMIS. First completed in 2014, updated annually, legislatively required starting in 2018 https://deptofcommerce.box.com/s/bjocxz2stmw5f0wigkbi5dw97r2bhth5
3
Commerce provides publicly available report card on county performance
State/county report card – Performance of homeless crisis response system – All projects, all funding sources. Used in state contracts; provide transparency to public/policy makers (completed 2016, updated annually)
https://public.tableau.com/profile/comhau#!/vizhome/WashingtonStateHomelessSystemPerformanceCountyReportCardsSFY2018/ReportCard
4
It’s the rent – people/families in WA are above average and getting better
• Homelessness has increased primarily because rents increased
• Part of why rents increased was housing supply did not keep pace with demand
• Other drivers or “causes” of homelessness do not appear to be meaningful drivers of the increase
• Washington is already a high performer in the areas ofjob pay, work participation, family composition/stability, lower alcohol and drug dependence, housing outcomes
5
Housing works
• Housing reduces homelessness
• Base level of other services critical…some people need services to maintain subsidized housing…but extra services don’t seem to reduce homelessness
6
Housing Prices in Washington
Source: http://www.zillow.com/home-values/
7
Rents in Spokane County
Source: http://www.zillow.com/home-values/
9
Rents in Whatcom County
Source: http://www.zillow.com/home-values/
10
Rents in King County
Source: http://www.zillow.com/home-values/
11
Rents in Yakima County
Source: http://www.zillow.com/home-values/
12
Rents in Thurston County
Source: http://www.zillow.com/home-values/
13
Rents in lower cost areas served by Sound Transit
Source: one bedroom http://www.zillow.com/home-values/
14
Rents – Alternative data source
Source: https://www.apartmentlist.com/wa/seattle#rent-report15
WA Economy: Rents are increasing while income growth lags
Median Rent +30%
-Middle incomes
+10%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
% c
han
ge in
flat
ion
ad
just
ed
$
Low incomes (bottom 20% of households)
Data sources: U.S. Census Bureau American Community Survey 1-Year estimates; inflation adjusted using the Bureau of Labor Statistics CPI-U. Median household incomes
Lowest quartile rent+20%
16
WA Economy: Rents compared to minimum wage and disability income growth
Disability income +24%
Minumum wage
Rent +49%
0%
10%
20%
30%
40%
50%
60%
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Supplemental Security Income (SSI) Minumum wage
Rent lower qunitile units Rent lower qunitile units projection
Rent data sources: U.S. Census Bureau American Community Survey 1-Year Estimates for Washington State, B25057
17
Housing affordability in King County – Rent vs. wages and disability income
18
Sources:BLS Quarterly Census of Employment and Wages, Average Annual Pay https://data.bls.gov/PDQWeb/enCensus Bureau ACS Median Contract Rent 1-Year Estimates B25058 https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_17_1YR_B25058&prodType=table
0%
10%
20%
30%
40%
50%
60%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Rent All industries
Education - local government Janitorial - private
Full service restaurants - private Supplemental Security Income
Housing affordability in Spokane County – Rent vs. wages and disability income
19
Sources:BLS Quarterly Census of Employment and Wages, Average Annual Pay https://data.bls.gov/PDQWeb/enCensus Bureau ACS Median Contract Rent 1-Year Estimates B25058 https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_17_1YR_B25058&prodType=table
0%
10%
20%
30%
40%
50%
60%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Rent All industries
Janitorial - private Full service restaurants - private
Supplemental Security Income
Housing affordability in Whatcom County – Rent vs. wages and disability income
20
Sources:BLS Quarterly Census of Employment and Wages, Average Annual Pay https://data.bls.gov/PDQWeb/enCensus Bureau ACS Median Contract Rent 1-Year Estimates B25058 https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_17_1YR_B25058&prodType=table
0%
10%
20%
30%
40%
50%
60%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Rent All industries
Education - local government Janitorial - private
Full service restaurants - private Supplemental Security Income
Housing affordability in King County – Individual income vs. rent
21
Sources:BLS Quarterly Census of Employment and Wages, Average Annual Pay https://data.bls.gov/PDQWeb/enCensus Bureau ACS Median Contract Rent 1-Year Estimates B25058 https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_17_1YR_B25058&prodType=table
17.4%
19.2%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
50.0%
55.0%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Rent burden: Jobs in King CountyMedian contract rent in Seattle-Tacoma-Bellevue MSA / Average Income
All industries Education - local government Janatorial - private Full service restaurants - private Affordable
Housing affordability in King County – Individual income vs. rent
22
Sources:BLS Quarterly Census of Employment and Wages, Average Annual Pay https://data.bls.gov/PDQWeb/enCensus Bureau ACS Median Contract Rent -Year Estimates B25058 https://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_17_1YR_B25058&prodType=table
17.4%
19.2%
130.5%
177.4%
65.2%
88.7%
10.0%
30.0%
50.0%
70.0%
90.0%
110.0%
130.0%
150.0%
170.0%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Rent burden: SSI Recipients - King CountyMedian contract rent in Seattle-Tacoma-Bellevue MSA / Average income
All industries Education - local government
Janatorial - private Full service restaurants - private
Affordable Supplemental Security Income
Supplemental Security Income - Two recipients living together
71% of WA extremely low-income renter households are severely cost burdened
Source: National Low Income Housing Coalition
23
Housing affordability in Washington State - Households
24
29%
30%
31%
32%
33%
34%
35%
36%
37%
2012 Households paying >30 percent forhousing
2017 Households paying >30 percent forhousing
Percent of owner and renter households paying >30% for housing - WA
-
100,000
200,000
300,000
400,000
500,000
600,000
2013 2015 2017
Rent burdened households - WA
Rent 30%-34.9% of income Rent > 35% of income
-
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
2013 2017
Renter households with incomes <$20,000 paying more than 50% of income to housing
Sources:Census ACS 1-Year Estimates Selected Housing Characteristics DP04Public Use Microdata Samples, Washington Housing Unit RecordsCHAS Data: https://www.huduser.gov/portal/datasets/cp.html
210,245 215,555
7.9% 8.1%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
-
50,000
100,000
150,000
200,000
250,000
2010-14 2011-15
Households with incomes <30% AMI paying >50% of income for housing
Homelessness – WA 5th highest per capita rate
WA: 0.29%, US: 0.17%
January 201921,621 people
9,599 living unsheltered
8,831 in households without children
768 people in households with children
Sources: HUD AHAR - https://www.hudexchange.info/resource/3031/pit-and-hic-data-since-2007/Census Bureau ACS 1-Year Estimates of Population
25
-
50
100
150
200
250
300
350
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019
Peo
ple
per
10
0,0
00
po
pu
lati
on
exp
erie
nci
ng
ho
mel
essn
ess
Unsheltered Sheltered
Homelessness – WA 5th highest per capita rate
0.00%
0.05%
0.10%
0.15%
0.20%
0.25%
0.30%
0.35%
0.40%
0.45%
0.50%
% of Population Experiencing Homelessness Ranked
Percentage unsheltered Percentage sheltered
26
All things being equal, as rents grow, homelessness increases
Sources:Rent: U.S. Census Bureau American Community Survey one-year estimates for Washington State, B25058, inflation adjusted using Bureau of Labor Statistics CPI-UHomelessness: WA point in time count, adjusted by : U.S. Census Bureau American Community Survey one-year population estimate for Washington State1 - Journal of Urban Affairs, New Perspectives on Community-Level Determinants of Homelessness, 20122 - Dynamics of homelessness in urban America, arXiv:1707.09380
60
70
80
90
100
110
120
$660
$680
$700
$720
$740
$760
$780
$800
$820
$840
$860
2010 2011 2012 2013 2014 2015 2016 2017
WA
un
shel
tere
d p
er 1
00
,00
0 p
op
ula
tio
n
WA
med
ian
ren
t 2
00
6 $
Median rent 2006 $ Per capita unsheltered homelessness
27
Rents vs. homelessness – 0.7 correlation
28
Alabama
Alaska
Arizona
Arkansas
California
Colorado
ConnecticutDelaware
Florida
Georgia
Hawaii
Idaho
Indiana IllinoisIowaKansas
KentuckyLouisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
MontanaNebraska
Nevada
New HampshireNew Jersey
New Mexico
New York
North Carolina
North Dakota
OhioOklahoma
Oregon
Pennsylvania Rhode Island
South Carolina
South DakotaTennessee
TexasUtah
Vermont
Virginia
Washington
West VirginiaWisconsin
Wyoming
0.00%
0.10%
0.20%
0.30%
0.40%
0.50%
0.60%
$500 $600 $700 $800 $900 $1,000 $1,100 $1,200 $1,300 $1,400 $1,500
% o
f p
op
ula
tio
n h
om
eles
s, H
UD
AH
AR
20
17
Median contract rent, Census Bureau ACS 2017 1-year
Rents vs. homelessness
$300
$500
$700
$900
$1,100
$1,300
$1,500
0.00%
0.10%
0.20%
0.30%
0.40%
0.50%
Ren
t
Per
cen
t o
f p
op
ula
tio
n h
om
eles
s
Percentage unsheltered Percentage sheltered Rent 2017 Linear (Rent 2017)
WA had second largest rent increase 2013-17
Sources: HUD AHAR - https://www.hudexchange.info/resource/3031/pit-and-hic-data-since-2007/Census Bureau ACS 1-Year Estimates of PopulationMedian contract rent, Census Bureau ACS 2017 1-year
29
Other drivers
30
Beyond rent: What about other potential drivers of the increase in homelessness?
WA economy: Above average and improving
2012 to 2018:
Ranked #1 in GDP growth – two years in a row• Per capita GDP ranked #9
More people working• Percent of population employed increasing - ranked #25
Incomes increasing• Median household income ranked #10• Median household income growth ranked #1• Lowest quintile household income rank #9• Lowest quintile household income growth ranked #5
31
WA economy: Employment rate is above average and increasing
Source: U.S. Department of Labor, Bureau of Labor Statistics, Employment status of the civilian noninstitutional population, percent of population employed
56
57
58
59
60
61
62
63
64
65
66
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Percent of people working
WA US
32
WA economy: More prime-age people work
Source: U.S. Department of Labor, Bureau of Labor Statistics, Employment status of the civilian noninstitutional population, percent of ages 25-54 employedhttps://www.bls.gov/lau/ex14tables.htm
67.00%
69.00%
71.00%
73.00%
75.00%
77.00%
79.00%
81.00%
83.00%
19
70
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
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87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
20
17
Prime Age Employment - Ages 25-54
WA USA
33
Services: WA similar rate of employment to high and low service states
Source: U.S. Department of Labor, Bureau of Labor Statistics, Employment status of the civilian non-institutional in states, percent of population employed
58
.3
21
.5
55
.7
77
.0
78
.5
76
.3
63
.0
18
.9
60
.8
28
.3
63
.8
76
.5
78
.9
78
.8
63
.0
18
.5
60
.9
35
.6
66
.2
75
.9
80
.6
77
.7
63
.5
19
.0
60
.1
30
.3
66
.0
78
.3
79
.8
77
.8
62
.5
18
.6
T O T A L 1 6 - 1 9 2 0 - 2 4 2 5 - 3 4 3 5 - 4 4 4 5 - 5 4 5 5 - 6 4 6 5 +
2017 PERCENTAGE OF POPULATION EMPLOYED BY AGE GROUP
NY Texas WA USA
34
Services: More people working compatible with higher levels of housing assistance
Housing vouchers for low income households:1
• Reduce earned income by $109 a month ($12,452 to $11,140 annually)
• Reduce employment by 4 percentage points (61% to 57%) first eight years, no significant impact >8 years2
Permanent vouchers vs. temporary rent assistance for homeless families:3
• Reduce families living homeless or doubled up by 16 percentage points (16% vs. 32%)
• No long term significant impact on earned income or having a job
Sources: https://www.oecd.org/els/family/PH3-1-Public-spending-on-housing-allowances.pdfhttps://data.oecd.org/emp/employment-rate-by-age-group.htm#indicator-charthttps://www.cbpp.org/sites/default/files/atoms/files/4-13-11hous-WA.pdf1 – The Effects of Housing Assistance on Labor Supply, Jacob et al, 2008, http://www.nber.org/papers/w14570.pdf2 - The Impact of Housing Assistance on Child Outcomes: Evidence From a Randomized Housing Lottery, Jacob el al, 2015, https://harris.uchicago.edu/files/inline-files/QJE%20housing%20vouchers%20and%20kid%20outcomes%202015.pdf3 – HUD Family Options Study 3-Year Impacts, pages 76 and 81, https://www.huduser.gov/portal/sites/default/files/pdf/Family-Options-Study-Full-Report.pdf
France
Finland
Germany
Denmark
New ZealandSweden
The Netherlands
Czech RepublicAustralia
Austria
United States
NorwayPoland
LatviaKorea Lithuania
Portugal
EstoniaChileSpain
Washington
-0.05%
0.05%
0.15%
0.25%
0.35%
0.45%
0.55%
0.65%
0.75%
0.85%
72.0% 74.0% 76.0% 78.0% 80.0% 82.0% 84.0% 86.0% 88.0%
% o
f G
DP
sp
en
t o
n r
en
t as
sist
ance
Percent of people ages 25-54 working
Moderate positive relationship between spending on rent assistance and % of people working
35
Taxes and transfers to reduce poverty not associated with less work
Sources:OECD prime age employment 2017 - https://data.oecd.org/emp/employment-rate-by-age-group.htm#indicator-chartOECD pre and post taxes and transfers, poverty line 50% - https://stats.oecd.org/Index.aspx?DataSetCode=IDD
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0%
5%
10%
15%
20%
25%
30%
35%
40%D
enm
ark
Cze
ch R
epu
blic
Fin
lan
d
No
rway
Fran
ce
Net
her
lan
ds
Slo
vak
Rep
ub
lic
Slo
ven
ia
Swed
en
Swit
zerl
and
Bel
giu
m
Irel
and
Au
stri
a
Ger
man
y
Po
lan
d
New
Ze
alan
d
Luxe
mb
ou
rg
Un
ited
Kin
gdo
m
Au
stra
lia
Can
ada
Po
rtu
gal
Ital
y
Ko
rea
Gre
ece
Spai
n
Jap
an
Esto
nia
Latv
ia
Lith
uan
ia
Isra
el
Un
ited
Sta
tes
Pri
me
age
em
plo
yme
nt
po
pu
lati
on
rat
io a
ges
25
-54
Po
vert
y ra
te
Poverty rate before taxes and transfers Poverty rate after taxes and transfers
Prime age employment
Taxes and transfers to reduce poverty not associated with less work, correlation -0.04
Sources:OECD prime age employment 2017 - https://data.oecd.org/emp/employment-rate-by-age-group.htm#indicator-chartOECD pre and post taxes and transfers, poverty line 50% - https://stats.oecd.org/Index.aspx?DataSetCode=IDD
65%
70%
75%
80%
85%
90%
0% 5% 10% 15% 20% 25% 30% 35%
Emp
loym
en
t p
op
ula
tio
n r
atio
age
s 2
5-5
4
Percent of poverty reduction through taxes and transfers
Taxes and transfers to reduce poverty not associated with less productivity
Sources:OECD pre and post taxes and transfers, poverty line 50% - https://stats.oecd.org/Index.aspx?DataSetCode=IDDOECD GDP per hour worked 2017 - https://stats.oecd.org/Index.aspx?DataSetCode=PDB_LV#
$0
$10
$20
$30
$40
$50
$60
$70
$80
$90
$100
0%
5%
10%
15%
20%
25%
30%
35%
GD
P p
er
ho
ur
wo
rke
d
Po
vert
y ra
te r
ed
uct
ion
via
tax
es
and
tra
nsf
ers
Poverty rate reduction via taxes and transfers GDP per hour worked 2017
Taxes and transfers to reduce poverty not associated with less productivity
Sources:OECD pre and post taxes and transfers, poverty line 50% - https://stats.oecd.org/Index.aspx?DataSetCode=IDDOECD GDP per hour worked 2017 - https://stats.oecd.org/Index.aspx?DataSetCode=PDB_LV#
$0
$20
$40
$60
$80
$100
$120
0% 5% 10% 15% 20% 25% 30% 35%
GD
P p
er
ho
ur
wo
rke
d
Percent of poverty reduction through taxes and transfers
Families: WA families above average and improving
2012 to 2017:
Family stability increasing
• Divorce, domestic violence, and teenage pregnancy declined
• Percentage of children in married couple households increased -WA ranked #8
• Percentage of married couple households increased – WA ranked #14
40
Alcohol and drug dependence: A mixed picture
Since 2012:
WA ranks 18th in substance use disorder 2
1. Alcohol use disorder declined, ranked 29th 2
2. Overall illicit drug dependence may be stable, ranked 11th 1, 2
3. Ranked 13th in pain reliever use disorder, and 12th in heroin use 2
4. Opioids continue to be a crisis, WA ranks 32nd in prevalence of drug overdose deaths 4
Sources: 1 - SAMHSA, Center for Behavioral Health Statistics and Quality, National, Survey on Drug Use and Health, Table 106, Washington State, 2010-11 report compared to 2014 report 2 – Rank derived from 2015-2016 National Survey on Drug Use and Health: Model-Based Prevalence Estimates 50 States; trend derived from National Survey on Drug Use and Health: Comparison of 2008-2009 and 2014-2015 Population Percentages 50 States3 – DOH: https://www.doh.wa.gov/Portals/1/Documents/Pubs/346-083-SummaryOpioidOverdoseData.pdf4 - CDC: https://www.cdc.gov/mmwr/volumes/65/wr/mm655051e1.htm
0
200
400
600
800
2012 2013 2014 2015 2016
Opioid-related overdose deaths3
All opioid related deaths
Prescription opioid overdose deaths
Heroin overdose deaths
Synthetic opioid overdose deaths
Relationship between prevalence of opioid use and homelessness
Sources: Increases in Drug and Opioid-Involved Overdose Deaths – United States, 2010-2015: https://www.cdc.gov/mmwr/volumes/65/wr/mm655051e1.htmHUD Annual Homeless Assessment Report AHAR: https://www.hudexchange.info/homelessness-assistance/ahar/#2017-reports
42
Alabama
Colorado
ConnecticutGeorgia
Illinois
Maine
Maryland
Massachusetts
Minnesota
Missouri
Nevada
New HampshireNew Mexico
New York
North CarolinaOhioOklahoma
Oregon
Rhode Island
South Carolina
Tennessee
Utah
Vermont
Virginia
Washington
West VirginiaWisconsin
-
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
0.0035
0.0040
0.0045
0.0050
0 5 10 15 20 25
Rat
e o
f h
om
ele
ssn
ess
20
17
Prevalence of opioid dependence as measured by opioid deaths per 100,000 - CDC 2015
Relationship between prevalence of opioid use and homelessness
Sources: 2016-17 NSDUH: https://www.samhsa.gov/data/report/2016-2017-nsduh-state-prevalence-estimates HUD Annual Homeless Assessment Report AHAR: https://www.hudexchange.info/homelessness-assistance/ahar/#2017-reports
43
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut Delaware
Florida
Georgia
Hawaii
Iowa
Idaho
Illinois
IndianaKansasKentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
MontanaNebraska
Nevada
New HampshireNew Jersey
New Mexico
New York
North Carolina
North Dakota
OhioOklahoma
Oregon
PennsylvaniaRhode Island
South Carolina
South DakotaTennessee
Texas Utah
Vermont
Virginia
Washington
West VirginiaWisconsin
Wyoming
-
0.0010
0.0020
0.0030
0.0040
0.0050
0.0060
0.00% 0.10% 0.20% 0.30% 0.40% 0.50% 0.60% 0.70% 0.80% 0.90%
Rat
e o
f h
om
eles
snes
s 2
01
7
Prevalence of past-year herion use age 12+, 2016-17 National Survey on Drug Use and Health
Drug and homelessness trends – USA vs. WA
Sources: Drug Overdose Deaths in the United States, 1999-2016: https://www.cdc.gov/nchs/products/databriefs/db294.htmIncreases in Drug and Opioid-Involved Overdose Deaths – United States, 2010-2015: https://www.cdc.gov/mmwr/volumes/65/wr/mm655051e1.htmDrug Overdoes Death Data: https://www.cdc.gov/drugoverdose/data/statedeaths.htmlHUD Annual Homeless Assessment Report AHAR: https://www.hudexchange.info/homelessness-assistance/ahar/#2017-reports
30
40
50
60
70
80
90
100
110
120
6
8
10
12
14
16
18
20
2010 2011 2012 2013 2014 2015 2016
Un
shel
tere
d p
er 1
00
,00
0 p
eop
le
Dru
g d
eath
s p
er 1
00
,00
0 p
eop
le
USA: Drug overdose deaths increased, unsheltered homelessness
decreased
USA Drug overdose death rate
USA unsheltered homeless per 100,000 people
30
40
50
60
70
80
90
100
110
120
6
8
10
12
14
16
18
20
2010 2011 2012 2013 2014 2015 2016
Un
shel
tere
d p
er 1
00
,00
0 p
eop
le
Dru
g d
eath
s p
er 1
00
,00
0 p
eop
le
WA: Drug overdose deaths increased less than in US, unsheltered
homelessness increased
WA Drug overdose death rate
WA unsheltered homeless per 100,000 people
44
DRAFT/Experimental Measure:
WA Homeless Crisis Response System Performance: Above Average
Sources: 2017 Data https://www.hudexchange.info/resource/5691/system-performance-measures-data-since-fy-2015/
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Length of timehomeless
Exits toPermanent
Housing
Returns tohomelessness
WA Homeless Crisis Response System Performance vs. Other States
Percentile Rank
Hig
her
Per
form
ance
Low
er Perfo
rman
ce
Average Performance
45
DRAFT/Experimental Measure:
WA Homeless Crisis Response System Performance: Ranked 9th
Sources: 2017 Data https://www.hudexchange.info/resource/5691/system-performance-measures-data-since-fy-2015/
Length of
time
homeless
percentile
Exits to
Permanent
Housing
Percentile
Returns to
homelessness
Percentile
Combined
Percentile Rank TN 70% 88% 90% 83% 1
LA 67% 90% 84% 80% 2
MT 22% 100% 100% 74% 3
ID 56% 78% 88% 74% 4
PA 37% 82% 86% 68% 5
VT 26% 98% 80% 68% 6
VA 74% 69% 59% 68% 7
OH 82% 92% 25% 66% 8
WA 45% 57% 92% 65% 9 NM 87% 29% 65% 60% 10
IN 59% 61% 55% 59% 11
WI 80% 84% 12% 59% 12
AR 83% 24% 67% 58% 13
WV 89% 80% 6% 58% 14
MI 91% 76% 8% 58% 15
MD 32% 65% 78% 58% 16
SC 54% 47% 69% 57% 17
NH 30% 63% 74% 55% 18
NC 41% 67% 57% 55% 19
GA 33% 53% 76% 54% 20
NY 58% 71% 31% 53% 21
OK 19% 59% 82% 53% 22
OR 78% 27% 53% 52% 23
HI 13% 96% 47% 52% 24
DE 76% 51% 29% 52% 25
MA 20% 37% 94% 50% 26
46
Lack of housing supply is a factor
47
Why are rents increasing?
Since 2005 in WA: Population +21%, Housing units +17%
Source: American Community Survey 1-Year Estimateshttp://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_14_1YR_DP04&prodType=tablehttps://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_16_1YR_B25001&prodType=tablehttps://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_16_1YR_S0101&prodType=table
Housing unit deficit: 91,713
0%
1%
2%
3%
4%
5%
6%
7%
-
100,000
200,000
300,000
400,000
500,000
600,000
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Ren
tal v
acan
cy r
ate
New
ho
usi
ng
un
its
Deficit of new housing units necessary to maintain 2005 ratio of people to housing units
Actual additional units since 2005 Deficit of units Rental Vacancy rate
48
WA rental vacancy lowest in the US in 2017 1
Sources: American Community Survey 1-Year Estimates, Table DP041 – U.S. Census Bureau Vacancy and Homeownership rates by State2 - http://www.jchs.harvard.edu/sites/jchs.harvard.edu/files/w07-7.pdfhttp://pages.jh.edu/jrer/papers/pdf/past/vol32n04/03.413_434.pdf
A vacancy rate between 5% and 7% is considered the balanced, or “natural” rate 2
2010 2012 2014 2015 2016 2017
United States 8.2% 6.8% 6.3% 5.9% 5.9% 6.2%California 5.9% 4.5% 3.9% 3.3% 3.3% 3.5%
Massachusetts 5.8% 4.5% 4.0% 3.5% 4.0% 3.9%Oregon 5.6% 4.7% 3.6% 3.6% 3.2% 3.8%
Texas 10.6% 8.5% 7.3% 7.0% 7.7% 8.5%
Washington 5.8% 5.3% 4.2% 3.3% 3.2% 3.7%Clark County 8.2% 3.4% 2.4% 2.2% 3.0% 3.7%
Clallam County 11.4% 11.3% 6.1% 3.5% 1.8% 3.2%
King County 5.2% 4.1% 2.5% 2.6% 2.7% 3.5%Pierce County 6.6% 5.4% 5.7% 3.3% 2.0% 4.7%
Spokane County 4.0% 7.2% 5.5% 3.7% 3.7% 2.4%Yakima County 3.1% 4.5% 5.1% 3.6% 2.2% 2.3%
Whatcom County 3.9% 5.5% 4.1% 1.8% 1.8% 2.6%Thurston County 4.0% 5.5% 5.9% 3.5% 4.7% 4.3%
Seattle 4.0% 3.5% 1.2% 2.7% 2.5% 3.9%San Francisco 4.4% 2.8% 2.5% 2.5% 3.0% 3.5%
Atlanta 16.4% 8.6% 9.3% 6.6% 6.4% 7.6%Houston 15.9% 11.2% 7.2% 7.7% 7.7% 10.4%
49
Vacancy rates and rent increases are inversely related
Source: American Community Survey 1-Year Estimates, two year running average
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
3.0%
3.5%
4.0%
4.5%
5.0%
5.5%
6.0%
6.5%
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
An
nu
al r
ent
chan
ge
Vac
ancy
rat
e
Relationship between vacancies and rents - WA
Vacancy rate Median contract rent change
50
Higher incomes associated with higher rents – 0.83 correlation all MSAs income vs. lower quartile rents
Source: American Community Survey 1-Year Estimates
Higher incomes associated with higher rents – 0.87 correlation growing high income MSAs
Source: American Community Survey 1-Year Estimates
$-
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Top 25 median income MSAs with above average population growth
Median Household Income 2017 Median Lower Quartile Rent 2017 Linear (Median Lower Quartile Rent 2017)
Lower quartile rents strongly associated with median incomes – 0.80 correlation above average growth MSAs
Source: American Community Survey 1-Year Estimates, 2017
$-
$200
$400
$600
$800
$1,000
$1,200
$1,400
$1,600
$- $20,000 $40,000 $60,000 $80,000 $100,000 $120,000 $140,000
Incomes vs. Rents – Differences between lower and higher rent burdened communities
Sources: American Community Survey 1-Year Estimates, 2017
Lower quartile rents as percent of median income among top 50 high income above average growing MSAs
Rochester, MN Metro Area $ 71,985 9.3%Appleton, WI Metro Area $ 65,990 9.4%
Ogden-Clearfield, UT Metro Area $ 71,629 10.3%Worcester, MA-CT Metro Area $ 69,412 10.8%
California-Lexington Park, MD Metro Area $ 81,495 10.8%Des Moines-West Des Moines, IA Metro Area $ 68,649 10.9%Bridgeport-Stamford-Norwalk, CT Metro Area $ 91,198 11.4%
Midland, TX Metro Area $ 75,266 11.4%Bismarck, ND Metro Area $ 66,087 11.5%
Greeley, CO Metro Area $ 68,884 11.7%
10 Lowest rent burdens
Boulder, CO Metro Area $ 80,834 15.5%
Vallejo-Fairfield, CA Metro Area $ 77,133 15.6%Santa Rosa, CA Metro Area $ 80,409 15.9%
Naples-Immokalee-Marco Island, FL Metro Area $ 66,048 16.5%San Luis Obispo-Paso Robles-Arroyo Grande, CA Metro $ 71,880 16.7%
Salinas, CA Metro Area $ 71,274 17.1%Oxnard-Thousand Oaks-Ventura, CA Metro Area $ 82,857 17.3%
Santa Maria-Santa Barbara, CA Metro Area $ 71,106 17.4%Los Angeles-Long Beach-Anaheim, CA Metro Area $ 69,992 17.4%
San Diego-Carlsbad, CA Metro Area $ 76,207 17.6%
10 Highest rent burdens
Variation in % of income for rent partially explained by quality of weather: 0.51 correlation Seattle-Tacoma-Bellevue MSA lower quartile rent +8% higher than would be predicted by quality of weather
Sources: American Community Survey 1-Year EstimatesCities with the best and worst weather, WalletHub, https://wallethub.com/edu/cities-with-the-best-worst-weather/5043/
8%
9%
10%
11%
12%
13%
14%
15%
16%
17%
18%
0 10 20 30 40 50 60 70 80 90 100
% o
f m
edia
n in
com
e fo
r lo
wer
qu
arti
le u
nit
Weather quality percentile
Variation in % of income for rent partially explained by quality of weather: 0.60 correlation Seattle-Tacoma-Bellevue MSA lower quartile rent +2% higher than would be predicted by quality of weather
Sources: American Community Survey 1-Year EstimatesZillow Pleasant Days, https://www.zillow.com/research/pleasant-days-methodology-8513/
8%
10%
12%
14%
16%
18%
20%
22%
24%
26%
28%
0 50 100 150 200 250 300
% o
f m
edia
n in
com
e fo
r lo
wer
qu
arti
le r
enta
l un
it
Pleasant days per year
57
What works to reduce homelessness?
Prediction vs. reality of rents and related homelessness in Washington
58
Correlation between median rents and homelessness: 0.70• WA Predicted homelessness based on current median
rents: 0.23%• WA Actual homelessness: 0.29%• Difference between predicted and actual homelessness:
+20%
Correlation between median incomes and median rents: 0.85• WA Predicted median rents based on median household
incomes: $1,024• WA Actual median rent: $1,087• Difference between predicted and actual median rents:
+6%
Prediction vs. reality of rents and related homelessness in Washington
59
If WA rents matched national income/rent correlation
AND
WA homelessness matched rent/homelessness correlation
WA homelessness would be:• -27%• 0.21% of population
Model of increased unit production: Housing Prices -4.3%
60Source: Smart Growth scenario, page 19, https://www.upforgrowth.org/sites/default/files/2018-09/housing_underproduction.pdf
Model of deregulation: Citywide rent -24%
61Source: Up For Growth, Seattle Housing Policy and Affordability Calculator
Assuming the following deregulation of midrise development in the City of Seattle:
Citywide rent one-bedroom unit: $2,297 -> $1,743 (-24%)New mid-rise project rent one-bedroom: $2,460 -> $2,127 (-14%)
Model of “incremental pro-housing polices”: Citywide rent -6%
62Source: Up For Growth, HOUSING POLICY AND AFFORDABILITY CALCULATOR, page 8
Assuming the following deregulation in the City of Seattle:
Citywide rent one-bedroom unit: $2,351 -> $2,209 (-6%)New project rent one-bedroom: $2,460 -> $2,270 (-8%)
Model of “incremental pro-housing polices”: Citywide rent -6%
63Source: Census ACS
“What community should we emulate to get low rents?”
Houston and Dallas are often offered as examples, but their lower quintile rent/median income ratios are 13.1% and 13.2% respectively.
King-Snohomish-Pierce lower quintile rents are 14.0%, or $957/month.
13.1% in King-Snohomish-Pierce would be $890/month (-6%, -$60; about one year of rent inflation).
What works: Subsidized housing for low income households
Permanent subsidized housing (vouchers or facility based) for low-income households:
• ~$8,000 per household/per year
• Prevents 74% of homelessness (12.5% -> 3.3%)
• Not an effective use of limited homeless housing resources
64
Source: Vouchers for low income families reduced being families from becoming unsheltered or living in temporary homeless housing by 74% (12.5% -> 3.3%). No significant long impact on employment and earnings Change over five years. .http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.530.3116&rep=rep1&type=pdf.
What works: Short-term rent assistance for people at-risk of being evicted
• 76% decrease: (2.1% -> 0.5%)
• ~$33,000 per household prevented from becoming homeless
• Not an effective use of limited homeless housing resources
65
Source: Vouchers for low income families reduced being families from becoming unsheltered or living in temporary homeless housing by 74% (12.5% -> 3.3%). No significant long impact on employment and earnings. Change over one year. .http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.530.3116&rep=rep1&type=pdf.
…the finding in more depth
Numbers from a study of a homeless prevention program in Chicago: The impact of homelessness prevention programs on homelessness, Science, August 12, 2016, Volume 353https://nlihc.org/sites/default/files/Impact-of-homelessness-prevention.pdf
“We find that those calling when funding is available are 76% less likely to enter a homeless shelter….
For our main sample, fund availability led to a…1.6-percentage point decrease in the probability of entering a shelter within 6 months.”
People who did not receive prevention admitted to shelter within six months of calling: 2.1%
People who did receive prevention admitted to shelter within six months of calling: 0.5 %
76% decrease: (2.1% - 1.6%)/2.1% = 76%
Homelessness prevention: 2.2% effective at reducing entry into shelter
100
2.2
Households provided rentassistance to prevent
homelessness
Households prevented fromentering shelter in the six
months after receiving rentassistance
Numbers from a study of a homeless prevention program in Chicago: The impact of homelessness prevention programs on homelessness, Science, August 12, 2016, Volume 353https://nlihc.org/sites/default/files/Impact-of-homelessness-prevention.pdf
Cost to prevent one household from entering shelter: $33,000Cost to shelter one household: $2,400
Numbers from a study of a homeless prevention program in Chicago: The impact of homelessness prevention programs on homelessness, Science, August 12, 2016, Volume 353https://nlihc.org/sites/default/files/Impact-of-homelessness-prevention.pdf
3
417
Prevention: 3 households prevented fromentering shelter
Shelter: 417 households sheltered
Results of spending $100,000 on...
Be wary of research abstracts
Numbers from a study of a homeless prevention program in Chicago: The impact of homelessness prevention programs on homelessness, Science, August 12, 2016, Volume 353https://nlihc.org/sites/default/files/Impact-of-homelessness-prevention.pdf
Abstract“Despite the prevalence of temporary financial assistance programs for those facing imminent homelessness, there
is little evidence of their impact. Using data from Chicago from 2010 to 2012 (n = 4448), we demonstrate that the
volatile nature of funding availability leads to good-as-random variation in the allocation of resources to individuals
seeking assistance. To estimate impacts, we compare families that call when funds are available with those who
call when they are not. We find that those calling when
funding is available are 76% less likely to
enter a homeless shelter. The per-person cost of averting homelessness
through financial assistance is estimated as $10,300 and would be much less with better targeting of benefits to
lower-income callers. The estimated benefits, not including many health benefits, exceed $20,000.”
What works: Temporary housing or rent assistance for people who are unsheltered
70
Source: WA Homeless Report Card 2019 https://public.tableau.com/profile/comhau#!/vizhome/WashingtonStateHomelessSystemPerformanceCountyReportCardsSFY2018/ReportCard
What works: Permanent supportive housing
Some (not most) people living unsheltered need behavioral health and other supports to remain stably housed (a subsidy alone is not sufficient)
• 77% to 96% remain housed
71
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3969126/https://www.rand.org/blog/rand-review/2018/06/supportive-housing-reduces-homelessness-and-lowers.html
King County vs. places with extensive subsidized housing or shelter
72
% unsheltered vs. King County Unsheltered Population
King County 0.24% 5,288 2,189,000
London 0.02% -91% 3,103 14,187,146
Germany 0.06% -74% 52,000 83,000,000
Dublin 0.01% -96% 128 1,345,402
Australia 0.03% -89% 6,314 24,600,000
New York 0.04% -82% 3,675 8,623,000
What does not apparently meaningfully reduce homelessness
• Increasing earned income through welfare to work, work training, employment navigation – Does increase earned income 1
• Treatment for behavioral health illnesses such as substance use disorders and depression – Does reduce use/dependence 2 - May help a person retain subsidized housing
• Housing linked to more intensive services intended to improve self-sufficiency 3
Sources:
1 - The most successful welfare to work program in the study increased annual income from by $374 per year (page 137)No program produced a positive reduction in participants living in “Other housing,” which includes temporary housing and homelessness (page 189) https://www.mdrc.org/sites/default/files/full_391.pdf2 - Treatment for major depression increased lifetime earnings by $1,523 (about +$51 in annual earnings assuming 30 years of work post treatment). http://www.wsipp.wa.gov/BenefitCost/Program/494The multi-site adult drug court evaluation: The impact of drug courts, Urban Institute, Justice Policy Center. “We found no differences in the rates of homelessness and in the average level of interest in receiving housing services between the drug court and comparison groups. These results remained stable between the 6- and 18-month marks.”https://www.urban.org/sites/default/files/publication/27381/412357-The-Multi-site-Adult-Drug-Court-Evaluation-The-Impact-of-Drug-Courts.PDFWashington State Medication Assisted Treatment – Prescription Drug and Opioid Addiction Project, Preliminary Outcomes through Year Two, April 2019 https://www.dshs.wa.gov/sites/default/files/SESA/rda/documents/research-4-102.pdf3 - Family Options Study 3-Year Impacts on Housing and Services Interventions for Homeless Families, October 2016, page 72.
What does not apparently meaningfully reduce dependence
Abstinence-contingent housing:
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1449349/
What does not apparently meaningfully reduce homelessness
Treatment tied to the threat of incarceration for non-participation (Drug Courts):
Reduces at 18th month:• Any drug use 17 percentage points (28% vs. 45%)• Serious drug use by 8 percentage points (17% vs. 28%)• Heavy alcohol by 10 percentage points (13% vs. 23%)• Heroin use by 0% (2% vs. 2%)
No significant improvement in:• Employment rates• Income• Depression• Homelessness
Source: https://www.urban.org/research/publication/multi-site-adult-drug-court-evaluation-impact-drug-courts/view/full_report
What does not apparently meaningfully reduce homelessness
Medication assisted treatment for opioid use disorder:
• Does not significantly reduce homelessness or housing instability
Source: Washington State Medication Assisted Treatment – Prescription Drug and Opioid Addiction Project, Preliminary Outcomes through Year Two, April 2019 https://www.dshs.wa.gov/sites/default/files/SESA/rda/documents/research-4-102.pdf
www.commerce.wa.gov
Presented by:
Tedd KelleherManaging [email protected]
https://www.commerce.wa.gov/serving-communities/homelessness/
77
