Can Indirect Strategies Reduce Shortages, Restrain Housing ... · Includes future needs plus...

Can Indirect Strategies Reduce Shortages,Restrain Housing Cannibals, and Promote Affordability?

Dowell MyersProfessor of Policy, Planning, and Demography

Center for Applied Housing Research (CAHR) Distinguished Lecture

School of Public Affairs and Civic Engagement

San Francisco State University

October 17, 2019

Based on research supported by the Haynes Foundationand the National Multifamily Housing Council

1. Where did the housing crisis come from? How big? So many

interconnections, anomalies, and misperceptions

Themes Addressed

Dowell Myers, USC Price

5. The growing evidence for indirect solutions

2. How does housing affordability result or get measured?

3. To understand growing needs, follow the people

4. How does housing shortage exert its effects?

Nationwide

But Most Acute

in California

Includes future needs plus present unmet needs

Statewide

2017-2025 McKinsey (2016) = 3.5M (438K per year)

2017-2025 USC (HRB 1) Pop based, using 2000 norm = 2.8M (354K per year)

Key regions

2014-2022 ABAG RHNA = 188K (24K per year) only future needs?

2021-2029 SCAG RHNA = 456K (57K per year) by staff, but members vetoed

→ 1.3M (163K per year) by HCD determination 8/22/19

How Big is the Housing Shortage Really?


0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Nu

mb

er o

f H

ou

sin

g U

nit

s (T

ho

usa

nd

s)

Multifamily

Single-family

Sources: U.S. Census Bureau’s Building Permits Survey.

Slowdown in New Construction in CaliforniaAnnual Building Permits by Structure Type, California, 1960 to 2018

Expanding new construction after

bust, but still much below average

160K permitsper year for the

last 59 years

2018


An existential problem…..

Cannot measure needs or affordability for HHs that do not exist because would-be HHs cannot find enough housing units

Housing needs must be estimated from either the number of people or jobs, but not from the existing HHs

Population based, using normal household formation rates

Jobs-housing based, using “normal” relationships of permits to job growth from the past

How to Measure Needs for Households that Don’t Exist?


Strong Relations Between New Construction and Job Growth Before the Recession, Five Eras Since 1980, Largest 100 Metros

2012-17 2007-11 2000-06

1990s 1980s

Notes: New construction per year (%) = Summed annual bldg. permits (2-year lagged) / start year households x 100 / length of years; Job growth per year (%) = (end year jobs – start year jobs) / start year jobs x 100 / length of yearsSources: U.S. Census Bureau’s Building Permits Survey; Bureau of Economic Analysis (BEA)’s Employment Data; Decennial Census and American Community Survey IPUMS Microdata Files.


(a) (b) (c)

Coefficient

on Job

Growth

Constant

Term

R-squared

1980–89 0.80 0.12 0.68

1990–99 0.52 0.53 0.71

Boom (2000 Through 2006) 0.59 1.08 0.56

Bust (2007 Through 2011) 0.34 1.37 0.17

Recovery (2012 Through 2017) 0.29 0.25 0.34

Average of

80s, 90s, and Boom0.64 0.58

Relations Across 100 Metros

Strong Relations Between New Construction and Job Growth Before the Recession, Five Eras Since 1980, Largest 100 Metros


354

314

198

187

0 50 100 150 200 250 300 350 400

Include unmet since 2000

Include unmet since 2006

Only count future needs

Exclude current unmet needs

Only count future needs

20

00

Stan

dar

d2

01

7St

and

ard

Annual Housing Needs 2017 to 2025 (Thousand Units per Year)

Choices for Counting Annual Housing Needs in California, 2017 to 2025

Existing Backlog and Future Needs per Year, Population-based, 1000s,Including 5% Vacancies and 0.15% Annual Replacements

115

Avg. actual permitsin 2017 & 2018


When Growing Rental Demand Meets Limited Housing Supply

Great Recession & Aftermath

Depressed Homeownership

Millennial ArrivalIn Adulthood

IncreasedRental Demand

Other PopulationGrowth

D E M A N D

Depressed Construction

Political Resistance

Restricted Supplyof Workers

Financing & Land Constraints

S U P P L Y

Rental HousingShortage

Conceptual Diagram for Explaining the Rental Housing Shortage


Interconnections in the Housing Market with Owners at the Top While the Lowest Income Multifamily Renters at the Bottom, 2017

11.4 12.2 14.7 13.1

4.0 5.17.0

5.68.2

11.3

14.914.2

12.4

16.5

15.0

12.3

63.954.9

48.554.8

0

10

20

30

40

50

60

70

80

90

100

United States(120M HHs)

California(13M HHs)

LA Metro(4.3M HHs)

SF-Oak Metro(1.7M HHs)

Per

cen

tage

(%

)

Homeowners

SF Renters

MF Renters (80%+ AMI, Moderate or Higher-income)

MF Renters (50−80% AMI, Low-income)

MF Renters (0−50% AMI, Very Low-income)

Sources: 2017 American Community Survey IPUMS Microdata Files.


5.1 8.0 10.0 6.4

14.0

46.034.6

42.3

9.0 25.1

49.8

38.6 37.030.3

43.8

0

10

20

30

40

50

60

70

80

90

100

LA SF New York Chicago

Per

cen

tage

(%

)Breakdown of Total Housing Stock, By Tenure and Subsidy, Cities of LA, San Francisco, New York, and Chicago


Sources: Graphs based on Table 2 ofMetcalf, G. (2018). Sand Castles Before the Tide? Affordable Housing in Expensive Cities. Journal of Economic Perspectives. 32(1) : 59–80.

Subsidized Rental

Owner-occupied

Unregulated Rental

Rent Regulated

76.566.0

8.8

12.6

7.29.1

7.4 12.3

0

10

20

30

40

50

60

70

80

90

100

LA SF

Perc

enta

ge (

%)

34.0% of Low-cost Rentals* Were Taken by Relatively Higher-income Renters in the Cities of LA and San Francisco, 2017

Low-Cost Successfully Occupied by Very Low-income (0−50% AMI)Either Subsidized or Rent Regulated/Unregulated Market-rate

Taken by Low-income (50−80% AMI)

Taken by Middle-income (80−120% AMI)

Taken by Higher-income (120%+ AMI)

Sources: Analysis by JungHo Park, 2017 American Community Survey IPUMS Microdata Files.


* Low-cost rental units in the City of San Francisco are defined for THIS analysis by gross rents lower than $1,388/month (2017$) which is 30%-rent-burden-ceiling for very low-income San Franciscan HH (<50% of City of SF median HH income, $111,000 in 2017); For City of LA, low-cost rental units are defined lower than $750/month (2017$) based on the city’s median HH income of $60,000 in 2017.

Long-term Homeownership Rates, US and California, 1960 to 2018

US

CA

40.0

45.0

50.0

55.0

60.0

65.0

70.0

1960 1970 1980 1990 2000 2010 2020


Sources: 1960 to 2000 Decennial Census IPUMS Microdata Files; 2006 through 2018 American Community Survey.

Homeownership Rates By Age Group, California, 1980 to 2018

10

20

30

40

50

60

70

80

90

1980 1990 2000 2010 2020

Perc

enta

ge All Ages

65+

25 to 34

35 to 44

45 to 54



Big consequences of falling homeownership rates for the rest of the housing market

Increasing Homeownership Gap, California, 1980 to 2018

Gap Between Homeownership Rate ofAge 35-44 Minus Age 65+, Percentage Point Difference


-1.6

-16.9

-20.2

-25.1

-27.8-30.0

-25.0

-20.0

-15.0

-10.0

-5.0

0.0

1980 1990 2000 2010 2018

Perc

enta

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oin

t D

iffe

ren

ce


Affordability Problems

Are Everywhere

But Not Measured Effectively

Long-term Trend of Rent Burden, United States, 1980 to 2017

Paying more than 30% of Income on Rent

Sources: 1980 to 2000 Decennial Census and 2006 through 2017 American Community Survey IPUMS Microdata Files.

Paying more than 50% of Income on Rent

10

15

20

25

30

35

40

45

50

55

1980 1985 1990 1995 2000 2005 2010 2015

Perc

enta

ge (

%)


Surprisingly Similar Rent Burden Across Regions,Plus Curious Anomalies of SF-Oakland and Washington D.C.

0.0

10.0

20.0

30.0

40.0

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60.0

70.0

Un

ited

Sta

tes

Riv

ers

ide

-SB

Los A

ng

ele

s

SC

AG

SA

ND

AG

Sacra

men

to

FC

OG

De

nve

r

Las V

eg

as

Port

lan

d

AB

AG

Pho

enix

San

Jose

Sea

ttle

SF

-Oa

kla

nd

Salt L

ake

City

Chic

ago

Detr

oit

Milw

auke

e

Cle

ve

land

Ind

ian

ap

olis

St. L

ou

is

Min

nea

polis

Colu

mb

us

Kan

sa

s C

ity

Cin

cin

nati

Mia

mi

Ne

w O

rle

an

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Orla

ndo

Ta

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a

Me

mp

his

Baltim

ore

San

An

tonio

Virg

inia

Be

ach

Ja

ckson

vill

e

Atlan

ta

Housto

n

Austin

Dalla

s

Ric

hm

on

d

D.C

.

Charl

otte

Birm

ing

ham

Lou

isvill

e

Nashvill

e

Okla

ho

ma

City

Rale

igh

Phila

de

lph

ia

New

York

Hart

ford

Buff

alo

Bosto

n

Pro

vid

en

ce

Pitts

bu

rgh

Share of Renters Paying More than 30 (or 50) Percent of Income, US and 50 Largest Metros, 2017

More than 50.0% 30.1 to 50.0%

WEST MIDWEST SOUTH NORTHEASTUS

Sources: 2017 American Community Survey IPUMS Microdata Files. Dowell Myers, USC Price

Faults with the Traditional Rent Burden Indicator

1. These metros can’t really be all so similar on affordability

2. The Bay Area and Washington, DC, CANNOT be more affordable

than the national average – that is nonsensical

3. Rent burden DISGUISES the problem: is it rent’s too high

or income’s too low? What has been changing the most?

4. Rent burden averages all income groups together, so we can’t

tell if the incidence of high rent burden is driven by only the

lowest income group or middle income groups as well


New Method of Tracking Growing Mismatch of Incomes and Rents

The idea of the Myers-Park (2019) method is to show the changing rent distribution,

marking it into four equal quartiles in 2000, and then see in future years how many of

the rental units have shifted over time into the top quartile

Separately, we show the changing income distribution of renters, marking that also

into four equal quartiles in 2000, and then seeing how incomes of renters also shift into

higher or lower quartiles

How great is the mismatch?

Here, we see how the new Constant Quartile Mismatch indicator helps disentangle

rent and income effects, and how it can reveal the true variation of affordability

problems across regions


25%

11

25%

14

25%

20

25%

54

2000 2016

25%17

25%

20

25%

24

25%39

2000 2016

Soaring Rent Relative to Sluggish Income of Renters,United States and Los Angeles Metro, 2000 to 2016

U.S.Los

Angeles

25% 25

25% 23

25%23

25% 29

0

25

50

75

100

2000 2016

Perc

enta

ge o

f R

ente

rs

25% 26

25% 25

25% 23

25% 26

0

25

50

75

100

2000 2016

U.S.Los

Angeles

Sources: Myers and Park (2019) https://www.huduser.gov/portal/periodicals/cityscpe/vol21num1/article7.html


Renter Income Gross Rent

https://www.huduser.gov/portal/periodicals/cityscpe/vol21num1/article7.html

Metropolitan Areas Where Incomes Are Growing,While Rents Are Growing Even Faster, 2000 to 2016

24

19

23

34

Renter Income

16

13

23

49

Gross Rent

29

18

22

32

Renter Income

17

14

20

49

Gross Rent

27

19

23

31

Renter Income

11

11

20

58

Gross Rent


Sources: Myers and Park (2019) https://www.huduser.gov/portal/periodicals/cityscpe/vol21num1/article7.html

San JoseSF-Oakland Washington, D.C.


Where Does Housing Need Come From?

Follow the People!

% of Population Each Year that Moved into a Housing Unit, 2006 to 2018

A Small Amount of Housing Growth is from OutsidersMoving into California, Los Angeles, and the Bay Area

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

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14

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16

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18

Perc

enta

ge

Moved fromdifferent state

Moved fromabroad

California

Sources: 2006 through 2018 American Community Survey.

LA Metro SF-Oak Metro


Growth by Age in California: Then and Now


Sources: Dowell Myers, Census Bureau decennial census of 1990 and 2010, and CA DOF 2017 vintage projections

Birthplace Origins of Residents, By Age Group, 2017

More than Half of Young California and Bay Area ResidentsAre Homegrown

California

Sources: 2017 American Community Survey.

SF-Oak Metro

0% 25% 50% 75% 100%

Total

under 5

5-17

18-24

25-34

35-44

45-54

55-64

65-74

75+

0% 25% 50% 75% 100%

Total

under 5

5-17

18-24

25-34

35-44

45-54

55-64

65-74

75+


Tripling Ratio of Seniors to Workers in the Bay Area Since 2010

Upsurge After 2010 in SF-Oakland, LA, California, and U.S. Overall

Sources: Census 1960, 1970, 1980, 1990, 2000, and 2010; Census Bureau’s 2017-vintage National Population Projections 2017-2060; CA DOF’s 2017-vintage State and County Population Projections 2010-2060.

Why the Rising Ratio Matters

❑ Growing weight of pensions and health care

❑ Weakened base of taxpayers

❑ Relatively fewer workers

❑ More potential home sellers than potential buyers

❑ Elderly dominant society could have more volunteers


0

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70

19

60

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70

19

80

19

90

20

00

20

10

20

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20

30

20

40

20

50

20

60

Ratio ofPop 65+per 100

Age 25-64

LA Metro

SF-Oak Metro

CA

US

Children-to-Grandparent Ratios* LA, SF-Oakland, CA, and US, 1960 to 2060

* Number Children Under Age 10

Compared to Elderly Age 65 +

How does the Falling Ratio Matter?

❑ Surge of children in 1990s & 2000s meant more schools and a bigger budget share

❑ Now the dwindling number of children means fewer young adults in coming decades

❑ Fewer new workers, taxpayers and potential homebuyers

❑ How to raise the skills of local youth so that we can do more with less?


0.0

0.5

1.0

1.5

2.0

2.5

3.0

19

60

19

70

19

80

19

90

20

00

20

10

20

20

20

30

20

40

20

50

20

60

Rat

io

US

CA

LA Metro

SF-Oak Metro

Below this line means fewer children than elderly

Sources: Census 1960, 1970, 1980, 1990, 2000, and 2010; Census Bureau’s 2017-vintage National Population Projections 2017-2060; CA DOF’s 2017-vintage State and County Population Projections 2010-2060.

These population dynamics—and others as well—shape the politics surrounding housing problems and potential solutions.

Demographics also shape housing demand and housing needs itself. Using a housing demographic approach we can estimate needs that are not directly measurable through housing units or household income.

Old ideas of housing demography are finding new relevant applications……

Payoff from Following the People


How Doesthe Housing Shortage

Exert Its Effects on People?

Too much competition for too little supply

= Pressure cooker on prices and displacement


But what exactly are the mechanics on that?

Diverted Homeowners Pancake into the Rental Market, California



10

20

30

40

50

60

70

80

90

1980 1990 2000 2010 2020

Perc

enta

ge All Ages

65+

25 to 34

35 to 44

45 to 54

Increasing Homeownership Gap = Greater Rental Demand

Gap Between Homeownership Rate ofAge 35-44 Minus Age 65+, Percentage Point Difference


-1.6

-16.9

-20.2

-25.1

-27.8-30.0

-25.0

-20.0

-15.0

-10.0

-5.0

0.0

1980 1990 2000 2010 2018

Perc

enta

ge P

oin

t D

iffe

ren

ce


Multitudes of Millennials Trying to Form Households: Peak is Now Age 29

4.2 M in 1990

2.0

2.5

3.0

3.5

4.0

4.5

19

60

19

62

19

64

19

66

19

68

19

70

19

72

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74

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16

U.S

. Bir

ths

(Mill

ion

s)

32% greater than in 1976

Peak Millennial Births, Annual Births in the US, 1960 to 2017


Sources: Graphs based on Figure 1 of Myers, D. (2016). Peak Millennials: Three Reinforcing Cycles That Amplify the Rise and Fall of UrbanConcentration by Millennials. Housing Policy Debate, 26(6), 928–947; National Vital Statistics Reports, Vol. 67, No. 8, November 7, 2018

Declining Household Formation in California

Sources: Graphs based on Figure 5 of Myers, D. (2016). Peak Millennials: Three Reinforcing Cycles That Amplify the Rise and Fall of Urban Concentration by Millennials. Housing Policy Debate, 26(6), 928–947.0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+

Rat

io t

o 2

00

0 In

cid

ence 2000

2006

2011

2018

Total Household Formation (HHs per capita)Compared to the Same Age in 2000


Ratchet Downwardfor Millennials


0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+

Rat

io t

o 2

00

0 In

cid

ence 2000

2006

2011

2018

Sharply Declined Homeowner Households

Formation of Owner HHs (per capita)Compared to the Same Age in 2000, California

Sources: Graphs based on Figure 5 of Myers, D. (2016). Peak Millennials: Three Reinforcing Cycles That Amplify the Rise and Fall of Urban Concentration by Millennials. Housing Policy Debate, 26(6), 928–947.

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

15-24 25-34 35-44 45-54 55-64 65-74 75-84 85+

Rat

io t

o 2

00

0 In

cid

ence 2000

2006

2011

2018


Rental Competition Multiplies from GenXers

Formation of Renter HHs (per capita)Compared to the Same Age in 2000, California

Sources: Graphs based on Figure 5 of Myers, D. (2016). Peak Millennials: Three Reinforcing Cycles That Amplify the Rise and Fall of Urban Concentration by Millennials. Housing Policy Debate, 26(6), 928–947.

When Growing Rental Demand Meets Limited Housing Supply

Great Recession & Aftermath

Depressed Homeownership

Millennial ArrivalIn Adulthood

IncreasedRental Demand

Other PopulationGrowth

D E M A N D

Depressed Construction

Political Resistance

Restricted Supplyof Workers

Financing & Land Constraints

S U P P L Y

Rental HousingShortage

Conceptual Diagram for Explaining the Rental Housing Shortage


How Does the ShortageGet Resolved?

Would-be homeownersdiverted into rentals

1.2 M Dislodged

Luxury New Rentals

Older Luxury Rentals

Middle Class Rentals

Working Class Rentals

$$

$$

$

$$$

Millennials coming of ageand forming households

Higher-income renterstaking medium-cost rentals

thinning the ranks of lower income residents who are forced to double-up or worse

Shortage Breeds Downward Raiding and Cannibalization


20.3% of 2017 actual renters;9.2% of 2017 actual HHs

California

Growing Evidence Suggesting Need for Indirect Solutions

Massive Solutions Are Needed


Beginning with 200,000 subsidized units targeted to very low-income HHs with the worst housing needs,

but extending to many times more low-income HHs living in market rate housing and burdened with excessive rents,

and including also a great many middle class HHs facing their own affordability problems or burdened by their grown children who are camped at home for lack of suitable entry-level housing.

Whether or not its exactly 3.5 Million homes that are needed,how in the world are we to deliver on that goal?

Limited Budget Capacity for Direct Solutions

Federal Government

$782 billion deficit for Fiscal Year

2018, about 17 percent ($116 billion)

greater than the deficit for FY 2017

and projected to keep falling deeper

in debt, with no new room for funding

housing needs

State Government

$21 billion surplus in January 2019,

enough to build 42,000 new units

or to subsidize 105,000 units for 20

years (at $10k per unit per year)

Congressional Budget Office, June 2019

No relief in sight for Federal budget deficits


Advantages of Indirect Solutions

Direct solutions are attractive, but expensive and grossly inadequate in scale.

Solutions to problems don’t always lie where the problems appear.

Indirect solutions may go to the root causes, be more economical, and also more sustainable.

We need to leverage the rest of the housing market to produce more favorable opportunities for lower income households as well as the middle class.


Consider These 4 Indirect Solutions

• Solution 1 — get the diverted homeowners OUT of rental competition—most are in apartments, not SF rental

• Solution 2 — multiply the vacancy chains stemming from newly built units

• Solution 3 — siphon demand OUT of working/middle class family homes and into newly built housing

• Solution 4 — use filtering to grow future opportunities for low-income HHs by producing more middle-income housing today


New Attention to Vacancy Chains

Old idea that every new unit stimulates a chain of moves, creating opportunities for 3 or more additional HHs. (Kristof 1965; Lansing 1969)

Chain is broken when the inmover does NOT leave a vacant unit behind (due to HH formation, in-migration from another metro, etc.)

Newest work is using the Infutor marketing database to trace residential histories. Not clear that vacancies are left behind—could just be roommates or partners leaving.

Evan Mast (2019) estimates migrants from out of MSA fill 45% of newly built units in his sample of metros. Note that centrally located new housing has special attraction for migrants lacking local familiarity.


Market Rate Housing Can Save the Working Class

Evan Mast (2019) shows new market rate housing stimulates 20 moves from low-income neighborhoods for every 100 new units built. Or 50 moves from below-median neighborhoods.

Middle income construction will have more impact on working class than luxury—because it is a closer substitution—but all housing serves to absorb excess demand that otherwise would scavenge downward in income level.

These indirect linkages may be hard to prove to neighborhood activists. Case examples and role playing exercises might help.

An excess of market rate housing would facilitate filtering opportunities, but how much can that be believed? see next!


Can Filtering Increase Low-income Opportunities?

HUD declares filtering is the traditional means of creating lower-income housing opportunity. Over time properties obsolesce and are made less competitive, commanding lower rents.

Many people have lost faith in “trickle down” strategies. Filtering requires a surplus supply if this favorable sorting is going to work. Under shortage conditions, its effects could be reversed.

A current research project supported by the research foundation of the National Multifamily Housing Council (NMHC) is tracing apartment filtering between 1980 and 2017 in the largest metros. Filtering is measured by an increased occupancy by very low-income tenants (income < 50% of MSA median).


Success of Filtering in Apartments of Each VintageMedian Rent Percent Very Low-income Tenants

Dowell Myers, USC PriceSources: 1980 to 2000 Decennial Census and 2006 through 2017 American Community Survey IPUMS Microdata Files.

Preliminary Preliminary

0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Nu

mb

er o

f H

ou

sin

g U

nit

s (T

ho

usa

nd

s)

Multifamily

Single-family

Sources: U.S. Census Bureau’s Building Permits Survey.

Slowdown in New Construction in CaliforniaAnnual Building Permits by Structure Type, California, 1960 to 2018

Forgone filtered housing of today and the future

2018


and the future

Thank you

Dowell Myers

Visit USC PopDynamicshttps://sites.usc.edu/popdynamics/housing/

https://sites.usc.edu/popdynamics/housing/

Haynes Supported Housing Research Briefs (HRBs), 2018–2019

HRB 1 – Myers, D., Park, JH., & J. Li. (August 2018). How Much Added Housing is Really Needed in California? Housing Research Brief 1. Los Angeles, CA: USC Population Dynamics Research Group. https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2017/02/HRB-1-How-Much-Added-Housing-is-Really-Needed-in-California-1okfauc.pdf

HRB 2 – Myers, D., Park, JH., & E. Mendoza. (August 2018). How Much Added Housing is Really Needed in Los Angeles? Housing Research Brief 2. Los Angeles, CA: USC Population Dynamics Research Group. https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2017/02/HRB-2-How-Much-Added-Housing-is-Really-Needed-in-Los-Angeles-1zumxf6.pdf

HRB 3 – Myers, D., Park, JH., & E. Mendoza. (September 2018). How Much Worse is Affordability in LA than Before? Housing Research Brief 3. Los Angeles, CA: USC Population Dynamics Research Group. https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2017/02/HRB-3-How-Much-Worse-Is-Affordability-in-LA-than-Before-x09qkr.pdf

→ See updated and expanded study in HUD's Cityscape: https://www.huduser.gov/portal/periodicals/cityscpe/vol21num1/article7.html

HRB 4 – Myers, D. & JH. Park. (January 2019). Who Lives in New Housing in Los Angeles? Housing Research Brief 4. Los Angeles, CA: USC Population Dynamics Research Group. https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2019/01/HRB-4-Who-Lives-in-New-Housing-in-Los-Angeles-2ev2t3l.pdf

HRB 5 – Park, JH. & D. Myers. (January 2019). Where Do Low-Income Angelenos Live? Housing Research Brief 5. Los Angeles, CA: USC Population Dynamics Research Group. https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2017/02/HRB-5-Where-Do-Low-Income-Angelenos-Live-1glbw1d.pdf

HRB 6 – Myers, D. & JH. Park. (August 2019). Do Shortages Lead to Dislodgment of Disappearing Renters in Los Angeles? Housing Research Brief 6. Los Angeles, CA: USC Population Dynamics Research Group. https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2019/08/HRB-6-How-Do-Shortages-Lead-to-Dislodgement-and-Disappearing-Renters.pdf

https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2017/02/HRB-1-How-Much-Added-Housing-is-Really-Needed-in-California-1okfauc.pdf

https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2017/02/HRB-2-How-Much-Added-Housing-is-Really-Needed-in-Los-Angeles-1zumxf6.pdf

https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2017/02/HRB-3-How-Much-Worse-Is-Affordability-in-LA-than-Before-x09qkr.pdf


https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2019/01/HRB-4-Who-Lives-in-New-Housing-in-Los-Angeles-2ev2t3l.pdf

https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2017/02/HRB-5-Where-Do-Low-Income-Angelenos-Live-1glbw1d.pdf

https://cpb-us-e1.wpmucdn.com/sites.usc.edu/dist/6/210/files/2019/08/HRB-6-How-Do-Shortages-Lead-to-Dislodgement-and-Disappearing-Renters.pdf

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