Moving to Work 

Retrospective

A Picture of Moving to Work

Agencies’ Housing Assistance

Moving to Work Agencies’ 

Use of Funding Flexibility

Housing Choice and SelfSufficiency Outcomes at

Moving to Work Agencies

The Impact of the Moving to

Work Demonstration on the

Per Household Costs of 

Federal Housing Assistance

Evaluating the Effects of

Santa Clara County Housing

Authority’s Rent Reform

Moving to Work Agencies’ 

Use of Project-Based 

Voucher Assistance

U.S. Department of Housing and Urban Development | Office of Policy Development and Research
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Evaluating the Effects of

Santa Clara County Housing

Authority’s Rent Reform

Final Report

Prepared for

U.S. Department of Housing 

and Urban Development

Washington, D.C.

Prepared by

Nina Castells

MDRC

April 2020
Acknowledgments

The evaluation was sponsored by the Office of Policy Development and Research in the U.S. 

Department of Housing and Urban Development (HUD) and was part of a broader Moving to Work 

(MTW) evaluation led by Diane Levy at the Urban Institute. At HUD, I am especially grateful to 

Elizabeth Rudd, the government technical representative for the MTW retrospective evaluation, 

who provided guidance and very thoughtful feedback throughout the study. Elaine Ng, regional 

economist at the HUD San Francisco office, shared helpful insights on the labor and housing 

markets of counties in the Bay Area, which provided important context for selecting appropriate 

comparison sites and interpreting study findings.

This report reflects the efforts and important contributions of the study team at MDRC. James 

Riccio and Nandita Verma—the project director and project manager—provided valuable guidance 

and support throughout, from the research design to their careful reviews of each draft of this 

report. Howard Bloom, the senior technical reviewer, worked closely with the study team on 

developing the methodology and providing guidance and advice throughout the analysis. I am 

very grateful for the critical insights and expertise that he contributed. Gordon Berlin also provided 

critical advice on the report and its findings. Audrey Yu and Kali Aloisi carefully processed and 

analyzed all the earnings data and housing subsidy data for the study and contributed many 

important insights on the data to the interpretation of the findings. Jennie Kaufman skillfully edited 

the report. David Long from Princeton Policy Associates also contributed important insights during 

the research design, analysis, and report writing phases of the study.

This report has benefited greatly from the insights of the staff at the MTW housing agencies 

included in this study, particularly the Santa Clara County Housing Authority (SCCHA). Katherine 

Harasz, the executive director of SCCHA, and Janine Burrier, the assistant director of housing, 

generously shared extensive details about the housing agency’s policies and safeguards and 

the policy and economic context in which the SCCHA rent reform was implemented. Jennifer 

Rainwater at the Housing Authority of the County of San Mateo and Dominica Henderson at the 

Oakland Housing Authority also shared important information on their agencies’ policies and the 

housing and employment contexts where their housing agencies were located.

Disclaimer

The contents of this report are the views of the contractor and do not necessarily reflect the views 

or policies of the U.S. Department of Housing and Urban Development or the U.S. Government. 

Acknowledgments

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform
Foreword

The Moving to Work (MTW) demonstration, authorized by Congress in 1996, gives selected 

public housing agencies (PHAs) and the Secretary of Housing and Urban Development (HUD) 

flexibility to implement innovative approaches to providing housing assistance. PHAs chosen to 

participate in the demonstration may enact certain policies otherwise not allowed by law, but only 

if those policies are intended to achieve one or more of the MTW demonstration’s three statutory 

objectives: to achieve greater cost effectiveness, promote self-sufficiency among assisted families, 

and increase housing choice for low-income families. Since the demonstration’s launch, housing 

authorities with MTW status have served as a laboratory for HUD policy, designing and testing 

a range of new approaches to delivering housing assistance. In 2015, HUD launched the MTW 

Retrospective Evaluation to assess the MTW demonstration as a whole. This report is one of six 

produced by that effort and is an excellent example of how MTW can be used to test variations in 

rent policy and learn from the experience.

In 2013, the Santa Clara County Housing Authority (SCCHA) faced a budget shortfall due to 

sequestration. To avoid terminating families from assistance, SCCHA sought to reduce the costs 

of housing assistance payments in its Housing Choice Voucher (HCV) program by increasing the 

proportion of income that assisted households paid toward rent. Most HUD-assisted households 

nationwide pay 30 percent of their adjusted income towards rent (as required by law), but there 

have been numerous proposals to increase that proportion so that HUD could serve more families 

at a lower cost. One concern voiced by researchers and advocates is that doing so might backfire, 

that the increased “tax” on earnings might lead assisted households to work and earn less, 

paradoxically increasing the cost per household of housing assistance. 

SCCHA initially raised the tenant contribution rate for all HCV households from 30 percent of 

adjusted income to 35 percent of gross income, then dropped the rate a year later to 32 percent of 

gross income. HUD recognized SCCHA’s actions as an opportunity to find out what could happen 

in the real world when assisted households paid more than 30 percent of their adjusted income for 

rent and funded a study of the impact of SCCHA’s new rent policy on employment, earnings, and 

housing subsidies. To detect impacts, the study compared work-able HCV recipients at SCCHA to 

HCV recipients at three nearby PHAs who were not affected by the rent reform. The study tracked 

employment, earnings, and housing subsidy for 4 years after SCCHA implemented the new rent 

policy. The comparison showed that SCCHA’s rent increase did not affect average employment 

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

iii

Foreword
and earnings of work-able HCV households, indeed, HCV households in the study PHAs worked 

and earned more over the observation period. SCCHA met its objective of serving the same 

number of families at a lower cost. The study did not assess whether families reduced spending, 

increased debt, and experienced material hardship.

MTW flexibility enabled SCCHA to respond immediately to a sudden budget shortfall by adjusting 

rent contributions, and it allowed the agency to serve the same number of families at a lower cost. 

HUD’s proposed Making Affordable Housing Work Act (MAHWA), submitted to Congress in April 

2018, would allow all PHAs similar flexibilities. Additionally, because the flexibility to tailor activities 

to local conditions and adjust rapidly to changing conditions has proven valuable to current MTW 

agencies, HUD is adding 100 new MTW agencies, including 30 in rural communities. So that we 

can learn as much as possible from the MTW expansion, participating housing agencies will be part 

of a systematic program of research to test various policies, including different rent policies and 

work requirements. The reports produced by the MTW retrospective evaluation form a foundation 

that HUD will continue to build on as we seek more cost-effective ways to house our neediest and 

lowest-income families.

Seth D. Appleton

Assistant Secretary for Policy Development and Research

U.S. Department of Housing and Urban Development

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

iv

Foreword
v

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Contents

Abstract........................................................................................................................................ ix

Executive Summary...................................................................................................................... xi

Introduction and Background....................................................................................................... 1

Introduction ....................................................................................................................................................................... 1

Background ....................................................................................................................................................................... 3

Existing Evidence About the Effects of Housing Subsidies on Employment and Earnings ........................ 7

Research Design........................................................................................................................... 11

Research Questions ....................................................................................................................................................... 11

Study Sample ................................................................................................................................................................... 15

Study Period ..................................................................................................................................................................... 17

Data Sources .................................................................................................................................................................... 17

Analytic Approach ........................................................................................................................................................... 22

Comparison Group Selection ....................................................................................................................................... 26

Findings........................................................................................................................................ 35

Impacts on Employment and Earnings ...................................................................................................................... 35

Impacts on Housing Subsidies .................................................................................................................................... 40

Households’ Housing Decisions and Rent Burden ................................................................................................ 43

Subgroup Findings .......................................................................................................................................................... 45

Discussion .................................................................................................................................... 53

Discussion of Findings ................................................................................................................................................... 53

Conclusion......................................................................................................................................................................... 56

Appendix A................................................................................................................................... 59

Appendix B................................................................................................................................... 61

Appendix C................................................................................................................................... 67

Appendix D................................................................................................................................... 71

Appendix E ................................................................................................................................... 73

Appendix F ................................................................................................................................... 75

Appendix G................................................................................................................................... 79

References ................................................................................................................................... 95

Contents
List of Exhibits

List of Exhibits

Exhibit ES.1 Impacts on Average Quarterly Employment Rate and Annual Earnings 

(Nonelderly, Nondisabled Adults) ......................................................................................................................... xiv

Exhibit ES.2 Impacts on Housing Subsidies (Nonelderly, Nondisabled Households) ......................... xv

Exhibit 1.1 The Moving to Work Retrospective Evaluation ............................................................................. 2

Exhibit 1.2 General Housing Policy Terms .......................................................................................................... 4

Exhibit 1.3 Total Tenant Payment as a Percentage of Monthly Gross Income Among 

Nonelderly, Nondisabled Households Receiving Subsidies ........................................................................ 5

Exhibit 2.1 Definitions of Housing Subsidy Measures Used in Present Study ........................................ 13

Exhibit 2.2 Definitions of Other Housing Subsidy Terms .............................................................................. 13

Exhibit 2.3 HUD Definitions of Sample Terms .................................................................................................. 16

Exhibit 2.4 Timeline of Policy Changes ............................................................................................................... 17

Exhibit 2.5 Comparison Group Selection ........................................................................................................... 27

Exhibit 2.6 Map of Santa Clara and Comparison Counties ........................................................................... 28

Exhibit 2.7 Baseline Trends in Quarterly Employment Rates of Nonelderly, Nondisabled Adults in 

the Santa Clara County Housing Authority and Selected Comparison Housing Agencies ............... 30

Exhibit 2.8 Baseline Trends in Average Quarterly Earnings of Nonelderly, Nondisabled Adults in 

the Santa Clara County Housing Authority and Selected Comparison Housing Agencies ............... 31

Exhibit 2.9 Sample Sizes and Slopes of Candidate Comparison Public Housing Agencies .............. 31

Exhibit 2.10 Characteristics of the Sample at Baseline (Nonelderly, Nondisabled Households 

and Adults) ................................................................................................................................................................... 32

Exhibit 3.1 Quarterly Employment Rates for Nonelderly, Nondisabled Adults in Santa Clara County 

Housing Authority....................................................................................................................................................... 36

Exhibit 3.2 Quarterly Employment Rates for Nonelderly, Nondisabled Adults in the Comparison 

Group Housing Authorities ..................................................................................................................................... 36

Exhibit 3.3 Quarterly Employment Rates for Nonelderly, Nondisabled Adults in the Santa Clara 

County and Comparison Group Housing Authorities ..................................................................................... 37

Exhibit 3.4 Average Quarterly Earnings of Nonelderly, Nondisabled Adults in the Santa Clara 

County Housing Authority ....................................................................................................................................... 37

Exhibit 3.5 Average Quarterly Earnings of Nonelderly, Nondisabled Adults in the Comparison 

Group Housing Authorities ..................................................................................................................................... 38

Exhibit 3.6 Average Quarterly Earnings of Nonelderly, Nondisabled Adults in the Santa Clara 

County and Comparison Group Housing Authorities ..................................................................................... 38

Exhibit 3.7 Impacts on Average Quarterly Employment Rate and Annual Earnings of Nonelderly, 

Nondisabled Adults ................................................................................................................................................... 39

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

vi
vii

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit 3.8 Impacts on Housing Subsidies (Nonelderly, Nondisabled Households) ............................ 41

Exhibit 3.9 Tenant Rent Share as a Percent of Monthly Gross Income Among Nonelderly, 

Nondisabled Households Receiving Subsidies ............................................................................................... 44

Exhibit 3.10 Characteristics of the Sample at Baseline by Policy Group (Nonelderly, Nondisabled 

Households and Adults) ........................................................................................................................................... 46

Exhibit 3.11 Impacts on Average Quarterly Employment Rate and Annual Earnings by Policy 

Change Subgroup for Nonelderly, Nondisabled Households ..................................................................... 48

Exhibit 3.12 Tenant Rent Share as a Percent of Monthly Gross Income Among Nonelderly, 

Nondisabled Households Receiving Subsidies, by Policy Subgroup in Santa Clara County 

Housing Authority ...................................................................................................................................................... 51

List of Exhibits
viii

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform
Abstract

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

ix

Abstract

This study examines the effects of a rent reform in the Santa Clara County Housing Authority 

(SCCHA) on Housing Choice Voucher (HCV) residents’ employment rates, average earnings, and 

housing subsidies using a quasi-experimental design. In the face of federal budget cuts to the 

HCV program in 2013, SCCHA reduced subsidies for all households rather than cutting some 

households from the program. The primary component of its rent reform was to increase the 

tenant rent contribution rate from 30 percent of adjusted income (equivalent to about 27 percent 

of gross income) to 35 percent of gross income (eliminating all deductions and allowances) for all 

subsidy households. A risk was that if tenants reduced their earnings in response to the higher 

“tax” rate (since they keep a smaller portion of their earnings under the new policy), their subsidies 

would increase, counteracting the housing agency’s expected savings from increasing tenant 

rent contributions. A second rent reform component changed the voucher size policy, which 

resulted in a smaller voucher size (fewer bedrooms) for some households. The findings indicate 

that, on average, the SCCHA rent reform did not affect residents’ employment rates and average 

earnings throughout the 4 years following the implementation of the rent reform. Thus, the rent 

reform reduced households’ average housing subsidies as intended, and SCCHA was able to 

meet its projected savings. Since households did not increase their earnings to compensate for 

the reduction in their subsidies, these findings suggest that households absorbed their increased 

housing costs; however, whether they did so by reducing spending on necessary goods or by 

increasing debt and whether they experienced increased material hardship is unknown.
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

x
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

xi

Executive Summary

Executive Summary

Over 2 million households receive federal 

housing subsidies that allow them to rent in 

the private rental market. The Housing Choice 

Voucher (HCV) program, funded by HUD, 

requires households to pay 30 percent of 

their income toward rent, and HUD subsidizes 

the remaining amount of the households’ 

rent up to a certain threshold based on area 

housing costs. This rent policy aims to protect 

assisted households from excessive rent 

burden, but critics argue that pegging tenant 

contributions to income creates a disincentive 

to work. A rent reform that reduces housing 

subsidies and increases households’ 

contributions to rent might therefore have 

effects on employment. This report examines 

the effects of one such reform on subsidy 

recipients’ employment rates, average 

earnings, and housing subsidies.

The HUD Moving to Work (MTW) 

demonstration, launched in 1996, grants 39 

selected public housing agencies (PHAs) the 

flexibility to implement strategies to increase 

cost-effectiveness, promote household selfsufficiency, and increase housing choice 

for assisted households.1

 These PHAs have 

special statutory authority to change many 

HCV program rules, including rent rules.2 The 

present study evaluates the impact of a rent 

reform made by one PHA, the Santa Clara 

County Housing Authority (SCCHA), using 

its MTW flexibility. In 2013, federal budget 

cuts significantly reduced the budget for 

PHAs operating HCV programs. To avoid 

having to terminate households from the 

HCV program, SCCHA chose to increase 

the tenant rent contribution rate from 30 

percent of adjusted income to 35 percent 

of unadjusted income.3

 It also changed the 

voucher size policy, which resulted in a 

1 In 2016, Congress authorized HUD to expand the MTW demonstration to grant MTW status to 100 additional PHAs. 2 Subject to public notification, approval of each PHA’s board of directors, and HUD approval. 3 This change was tempered in 2014 when the rate was reduced to 32 percent of gross income, but this is still substantially higher than the previous rate.

smaller voucher size (fewer bedrooms) for 

some households.

The results of this study suggest that the 

SCCHA rent reform did not affect residents’ 

employment rates and earnings, on 

average, throughout the 4 years following 

the implementation of the rent reform. 

The analysis also found that, as expected 

given the nature of the policy changes 

and the absence of effects on residents’ 

earnings, the SCCHA rent reform reduced 

the average housing subsidy that the PHA 

paid on behalf of households. It did not find 

any evidence of an overall effect on the 

percentage of households still receiving any 

housing subsidies during the followup period. 

The SCCHA rent reform, however, may 

have reduced earnings for a subset of this 

population—the households affected by the 

change in the voucher size policy in addition 

to the increase in the tenant contribution rate.

The Santa Clara County 

Housing Authority Rent 

Reform

SCCHA increased its tenant contribution 

rate to the level at which the total savings 

from lower subsidies would allow the PHA to 

continue to serve all households in the HCV 

program at that time. SCCHA’s projections 

of savings assumed that the increase in the 

tenant contribution rate would not cause 

residents of HCV households to work or earn 

less. They had little evidence on which to 

base these projections, however. Economic 

theory suggests multiple possibilities: On the 

one hand, increasing the tenant contribution 

rate effectively increases the “tax” on 

tenants’ earnings (in other words, tenants 

keep a smaller portion of their earnings under 

the new policy compared with the former 

policy), creating a disincentive to work. If 
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

xii

Executive Summary

tenants did reduce their earnings, it would 

have resulted in SCCHA having to increase 

the subsidy levels, effectively counteracting 

the savings in housing assistance payments 

the housing agency hoped to achieve. On 

the other hand, tenants who can work may 

increase their employment to compensate for 

the loss of net income. A third possibility is 

that households may absorb their increased 

housing costs without changing their 

employment behavior, by reducing their 

spending or incurring debt. 

The SCCHA rent reform consisted of two 

main policy changes: 

• It increased the tenant contribution rate 

from 30 percent of adjusted income 

(equivalent to about 27 percent of 

unadjusted income) to 35 percent of 

unadjusted income. After 1 year, this 

percentage was reduced to 32 percent 

of unadjusted income. This policy change 

eliminated all allowances and deductions, 

including dependent and childcare 

allowances, deductions for medical 

expenses, and utility allowances. This 

new rent policy was applied to the rent 

calculations for all HCV households.

• It changed the policy that determines 

the number of bedrooms on a 

household’s voucher. Under the former 

policy, household members of different 

generations, of the opposite sex over 

the age of 5 years old, and unrelated 

adults (other than significant others) were 

allocated separate bedrooms. The new 

policy allocated one bedroom to the head 

of household (with spouse or partner) plus 

one additional bedroom for every two 

persons regardless of age, generation, 

relationship, or gender. This policy change 

resulted in a smaller voucher size for 23 

percent of all SCCHA households (not 

including senior households or households 

with people with disabilities).

In anticipation of the potential hardship that 

HCV households might face because of the 

rent reform, SCCHA offered two safeguards: 

hardship exemptions for households that 

experienced a sharp increase in rent share 

because of the new rent calculation, and 

financial and legal assistance for households 

at risk of eviction due to the rent reform. 

The hardship exemption policy allowed 

households to have childcare or medical 

deductions temporarily included in the 

calculations for their total tenant payment 

(TTP) for a 90-day period. The eviction 

prevention assistance program provided 

financial assistance to cover unpaid rent or 

to cover a security deposit if a household 

had to move because of the rent reform. The 

program also included free legal services to 

prevent eviction. 

Data and Methods

The study sample includes the cohort of 

nonelderly, nondisabled adults who were 

receiving HCV subsidies from the SCCHA 

program or one of the three selected 

comparison PHAs at the time the SCCHA rent 

reform was implemented in July 2013. The 

comparison PHAs are the Housing Authority 

of the County of Alameda, the Housing 

Authority of the County of San Mateo, and 

San Francisco Housing Authority. The effects 

of the rent reform are examined for up to 4 

years after the rent reform. The analysis uses 

state unemployment insurance wage data 

to measure employment rates and average 

earnings and HUD’s Inventory Management 

System/PIH Information Center data to 

measure households’ housing subsidies and 

housing characteristics.

To estimate effects of the SCCHA rent 

reform on the study’s key outcomes—

employment and earnings—a comparative 

interrupted time series (CITS) analysis, a 

quasi-experimental design, is used. The CITS 

analysis uses the trends in earnings and 
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

xiii

Executive Summary

employment before the SCCHA rent reform 

for the SCCHA group and a comparison 

group and measures how each group 

deviates from its pre-rent reform trend. The 

impact is the difference between the two 

groups’ post-rent-reform deviations from 

their respective pre-rent reform trends. 

To study the effects of the SCCHA rent 

reform on housing subsidy amounts and 

the percentage of households continuing 

to receive subsidies, the study uses an 

autoregressive difference-in-difference 

method.4

 A difference-in-difference 

estimation compares the change in each 

outcome between the period before the 

SCCHA rent reform and each year following 

the rent reform for SCCHA households 

with the change for households in the 

comparison PHAs, where no rent reform was 

implemented at the time. The models used 

in the present study are autoregressive in 

that they also control for pre-intervention 

values of the outcome measures. Although 

difference-in-difference is a widely used 

quasi-experimental approach, it is less 

rigorous than CITS because it does not 

account for potentially differing baseline 

trends in outcomes for the treatment and 

comparison groups. 

Additional descriptive analyses were used to 

explore changes in housing characteristics 

before and after the rent reform that may be 

related to households’ housing decisions, 

including unit characteristics, household 

composition, neighborhood poverty, and 

rent burden.5

Key Findings

The present study primarily aims to answer 

two questions: How does an increase 

in tenant rent share affect tenants’ work 

4 It was not feasible to use the CITS method to estimate the effects of the rent reform on housing subsidy amounts and continued housing subsidy 

receipt during the followup period, because housing subsidy data were not available for the full sample for the 4 years before the rent reform. 5 It was not feasible to use a difference-in-difference analysis for these analyses because data on these outcomes were available only for households 

that were still receiving subsidies, and not all households continued to receive subsidies for the full 4 years after the implementation of the rent reform.

behavior, and how does it affect households’ 

housing outcomes? The following are key 

findings from the study’s quasi-experimental 

analyses. 

• The SCCHA rent reform did not, on 

average, affect residents’ employment 

rates and average earnings throughout 

the 4 years following the implementation 

of the rent reform. 

Exhibit ES1 presents the estimated effects 

of the SCCHA rent reform on average 

annual employment rates and average 

annual earnings for nonelderly, nondisabled 

adults for each year of the followup 

period. The results show no evidence of 

effects on the percentage of nonelderly, 

nondisabled adults who were employed 

or on their average earnings across the 4 

years of followup. In Year 1, for example, 

50.8 percent of SCCHA households had 

some earnings in a given quarter, which 

is estimated to be only 0.5 percentage 

point lower than what it would have been 

in the absence of the SCCHA rent reform, 

and the impact estimate is not statistically 

significant. If, as these findings suggest, 

households did not increase their earned 

income to compensate for the reduction in 

their housing subsidies, they would have 

experienced reductions in their net income. 

For households that did not increase their 

income over time, these reductions in 

net income could have been persistent. 

Households who did increase their income 

over time would have experienced smaller 

increases in net income compared with the 

increases they would have experienced in 

the absence of the rent reform.

• The SCCHA rent reform reduced the 

average housing subsidy that the PHA 

paid on behalf of households. 
xiv

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Executive Summary

Exhibit ES2 presents the estimated effects 

of the SCCHA rent reform on the average 

amount of housing subsidy and the 

percentage of households receiving any 

housing subsidy at the time of followup.6

The average household housing subsidy 

in the month before the implementation of 

the rent reform was $16,764 per year. As 

expected, the SCCHA rent reform reduced 

the average amount of housing subsidy that 

households received. This effect is probably 

a direct result of the increase in the tenant 

contribution rate from 30 percent of adjusted 

income to 35 percent of gross income and 

the other policy changes implemented 

as part of the rent reform. In the first year 

after the rent reform was implemented, 

the average annual household subsidy 

was estimated to be $1,593 less than it 

would have been in the absence of the rent 

reform. In the second year, when the tenant 

contribution rate was reduced to 32 percent, 

the effect was slightly smaller: The average 

6 Effects on housing subsidies were estimated for nonelderly, nondisabled households. A nonelderly, nondisabled household is defined as a household 

where the head of household and any spouse or co-head are under 62 years old and not disabled.

household subsidy was $1,548 less annually 

than it would have been in the absence of 

the rent reform. In the third year, the rent 

reform reduced the annual subsidy by $1,329. 

Overall, there is no clear evidence that 

the SCCHA rent reform influenced the 

percentage of households that lost their 

subsidies or left the subsidy program. This 

finding suggests that the increased tenant 

contribution did not drive housing subsidy 

amounts down to zero for a large proportion 

of households and that the increased rent 

burdens did not lead a large proportion of 

households to leave the housing subsidy 

program. 

• The SCCHA rent reform may have reduced 

earnings for a subset of the population—the 

households that were affected by the change 

in the voucher size policy in addition to the 

increase in the tenant contribution rate.

A subgroup analysis estimated effects of 

the SCCHA rent reform separately for the 

Exhibit ES.1 Impacts on Average Quarterly Employment Rate and Annual Earnings (Nonelderly, Nondisabled Adults)

Outcome SCCHA Rate or Average Estimated Effect P-Value

Employment Rate

Year 1 50.8 -0.5 0.604

Year 2 54.5 0.0 0.972

Year 3 56.6 0.1 0.929

Year 4 57.5 0.1 0.941

Earnings (2017 $)

Year 1 11,187 46 0.897

Year 2 13,549 143 0.763

Year 3 16,198 200 0.738

Year 4 18,538 509 0.484

Sample Size 34,075

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. The set of comparison group public housing 

agencies includes the Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of 

Alameda. Impacts were estimated using a comparative interrupted time series model. The impact estimates represent the estimated amount by which the 

SCCHA actual employment rates or average earnings deviate from the predicted employment rates or earnings levels in the absence of the rent reform. All 

earnings impacts are reported in 2017 dollars. The p-value indicates the likelihood that the estimated impact (or larger) would have been generated by an 

intervention with zero true effect. Statistical significance levels are indicated as: *** = 1 percent; ** = 5 percent; * = 10 percent.

Source: California Employment Development Department individual-level aggregate unemployment insurance data
xv

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Executive Summary

residents who were affected only by the tenant 

contribution rate change (77 percent of the 

study sample) and the residents who were 

affected by the voucher size rule change in 

addition to the tenant contribution rate change 

(23 percent).7

 The findings for the residents 

affected only by the tenant contribution rate 

increase mirror the estimated effects on the 

full sample: there was no evidence of effects 

of the rent reform on employment rates or 

average earnings through the 4 years of 

followup. The residents also affected by the 

voucher size rule change, however—who 

faced especially deep cuts in their housing 

subsidies and very high levels of rent burden if 

they did not move to smaller units—may have 

reduced their earnings in response to the rent 

reform. The negative effect on earnings for 

this subgroup is statistically significant in Years 

3 and 4 following the policy change, at about 

$2,200 and $2,340 respectively, suggesting 

that some residents affected by both policy 

changes may have reduced their employment 

by this time. Employment and earnings trends 

7 One limitation of this analysis compared with the full-group analysis is that it was only possible to include one of the three selected comparison group 

PHAs in the comparison group.

over the followup period were rising for both 

SCCHA and the comparison group, so this 

estimated negative effect on average earnings 

means that for SCCHA residents in this group, 

earnings did not increase as quickly or as 

much as they would have in the absence of 

the rent reform. Descriptive findings (which 

do not indicate causality) suggest that some 

households in this subgroup moved to units 

with fewer bedrooms after the rent reform, but 

that levels of rent burden for this subgroup 

were especially high following the rent reform. 

A tight housing market in Santa Clara may 

have made it difficult for some families to 

find new housing with fewer bedrooms at an 

affordable rent.

Conclusion

The present study of the effects of a rent 

reform implemented by SCCHA provides 

evidence, from one location, that rent policies 

that increase the tenant contribution rate 

by a moderate amount (from 30 percent of 

Exhibit ES.2 Impacts on Housing Subsidies (Nonelderly, Nondisabled Households)

Outcome SCCHA Average or Rate Estimated Effect P-Value

Total Annual Housing Subsidy ($)

Year 1 14,335 -1,593 0.000***

Year 2 13,414 -1,548 0.000***

Year 3 13,481 -1,329 0.000***

Any Housing Subsidy Receipt (%)

Year 1 99.2 0.5 0.013**

Year 2 92.9 -0.4 0.368

Year 3 87.5 -0.9 0.137

Sample (Total = 15,490) 7,109

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. The set of comparison group public housing 

agencies (PHAs) consists of the Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the 

County of Alameda. Utility allowance data were not available for San Mateo and are therefore not included in San Mateo's housing subsidy measures. 

Sample sizes may vary because of missing values. Impacts were estimated using an autoregressive difference-in-difference model, controlling for the past 

receipt of housing subsidies and other baseline characteristics of sample households. The impact estimates represent the estimated amount by which 

the SCCHA annual housing subsidy or housing subsidy receipt deviate from the predicted levels in the absence of the rent reform. To assess differences 

between the research groups, chi-square tests were used for categorical variables and two-tailed t-tests were used for continuous variables. The p-value 

indicates the likelihood that the estimated impact (or larger) would have been generated by an intervention with zero true effect. Statistical significance 

levels are indicated as: *** = 1 percent; ** = 5 percent; * = 10 percent.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
xvi

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Executive Summary

adjusted income to 35 percent of gross 

income, later to 32 percent of gross income) 

do not create a substantial disincentive to 

work or significantly increase the likelihood 

that households may lose their subsidies. 

It also provides suggestive evidence that 

implementing a voucher size policy that 

requires some households to relocate to a 

different unit (with fewer bedrooms) to avoid 

even deeper cuts in housing subsidies may 

have adverse effects on some households 

in the context of a housing market where 

affordable housing options are very limited, 

and that short-term safeguards that PHAs 

provide to households may not fully prevent 

longer-term hardship. 

The findings from the present study cannot 

predict how tenants may change their 

work behavior if the size of their tenant 

contribution rate increases by a larger 

amount than what was implemented in 

SCCHA. Although the increase from 30 

percent of adjusted income to 35 percent 

of gross income (and later 32 percent of 

gross income) did not, on average, change 

employment or earnings among SCCHA 

tenants, it is possible that a higher increase 

may affect tenants’ work behavior. The 

negative effects on earnings that were 

found for the group of households that were 

affected by both the tenant contribution rate 

increase and the voucher downsizing—and 

therefore experienced particularly deep cuts 

in their housing subsidies—are suggestive of 

this possibility.

The combination of findings that the SCCHA 

rent reform led to deep and lasting cuts 

in housing subsidies for households and 

that, on average, household members did 

not increase their earnings to compensate 

for the reduction in subsidies means that 

households absorbed their higher housing 

costs. Therefore, households’ material 

hardship is an important consideration. 

This study did not include measures of 

households’ material hardship beyond a 

measure of rent burden, and therefore 

cannot assess how this increase in rent 

burden translated into their experiences with 

material hardship. 

It is important to understand how this type 

of rent reform may be expected to vary 

based on the context, and studies in multiple 

locations that represent diverse housing and 

labor markets are needed to examine this 

question. Future studies of rent reforms that 

might result in reduced housing subsidies 

should also carefully measure households’ 

experiences with material hardship, including 

food insecurity and their ability to cover 

medical expenses. 

Nevertheless, the present study begins 

to address one aspect of housing subsidy 

policy—how increasing the tenant 

contribution rate affects households’ 

employment, earnings, and housing 

subsidies—where strong evidence is lacking. 

Two additional studies are currently under 

way that also evaluate changes in how 

tenant rent share is determined: The HUDfunded Rent Reform demonstration tests a 

rent reform model in four PHAs that caps the 

tenant contribution toward rent for 3 years, 

and the second cohort of the HUD study of 

the current MTW expansion is intended to 

investigate the effects of tiered rents (where 

tenant rent share is determined based on 

which income band household income falls 

into) and stepped rents (where tenant rent 

share is increased by a set amount at regular 

intervals according to a rent share schedule) 

in 10 PHAs with newly granted MTW status. 

Taken together, this set of studies will build a 

body of evidence that will inform future HUD 

and PHA decisions about the most effective 

rent policies to implement.
1

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 1. Introduction and Background

Chapter 1

Introduction and 

Background

Introduction

The HUD Housing Choice Voucher (HCV) 

program is the nation’s primary rental 

subsidy program, assisting approximately 

2.2 million low-income households in paying 

for housing in the private rental market. HCV 

households generally pay 30 percent of their 

income toward rent, and HUD subsidizes 

the remaining amount of the households’ 

rent up to a certain threshold based on 

area housing costs. This rent policy aims to 

protect assisted households from excessive 

rent burden, but critics of the policy argue 

that pegging tenant contributions to income 

can disincentivize work and that public 

housing agencies (PHAs) find it burdensome 

to administer.

HUD’s Moving to Work (MTW) 

demonstration, launched in 1996, grants 

selected PHAs the flexibility to implement 

strategies to increase cost-effectiveness, 

promote household self-sufficiency, and 

increase housing choice for assisted 

households. These PHAs have special 

statutory authority to change many HCV 

program rules, including rent rules.8 Of 

the 39 PHAs with MTW status, 20 had 

implemented rent reforms as of 2014 

(Khadduri et al., 2014). These changes to 

rent policies provide an opportunity to test 

alternatives to the traditional 30-percent-ofincome policy and better understand how 

alternative rent policies affect residents. 

For example, through HUD’s Rent Reform 

8 Subject to public notification, approval of each PHA’s Board of Directors, and HUD approval. 9 See exhibit 1.1 for a summary of other reports included in this study. 10 This change was tempered in 2014 when the rate was reduced to 32 percent of gross income, although this is still substantially higher than the 

previous rate.

demonstration, four PHAs are testing an 

alternative rent policy that lengthens the 

recertification period and simplifies the 

rent calculation, and MDRC is evaluating 

the effects on tenants’ employment and 

earnings and the PHAs’ administrative 

efficiency. In 2016, Congress authorized 

HUD to expand the MTW demonstration to 

grant MTW status to 100 additional PHAs, 

and as mandated by Congress, HUD will 

evaluate the effects of MTW innovations 

(including alternative rent policies).

The present study contributes to this 

emerging body of evidence on the effects 

of alternative rent policies in subsidized 

housing by evaluating the impact of a 

rent reform at one PHA, the Santa Clara 

County Housing Authority (SCCHA). This 

study is part of a broader HUD-sponsored 

retrospective evaluation of the MTW 

demonstration led by the Urban Institute.9

In 2013, federal budget cuts significantly 

reduced the SCCHA budget for HCVs, 

and SCCHA no longer had sufficient funds 

to continue to provide subsidies to all 

households in the HCV program at the same 

level as before. To avoid having to terminate 

households from the HCV program, 

SCCHA chose to increase the tenant rent 

contribution rate from 30 percent of adjusted 

income (equivalent to about 27 percent 

of gross income) to 35 percent of gross 

income.10 It also changed the voucher size 

policy—the set of rules used to determine 

the number of bedrooms that a household’s 

subsidy is based on—which resulted in a 

smaller voucher size for 17 percent of all the 

SCCHA HCV households.

SCCHA chose to increase its tenant 

contribution rate to the level at which the 

total savings from lower subsidies would 

allow the PHA to continue to serve all 
2

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 1. Introduction and Background

households in the HCV program at that time. 

SCCHA’s projections of savings assumed 

that the increase in the tenant contribution 

rate would not cause residents of HCV 

households to work or earn less. They 

had little evidence on which to base these 

projections, however.

Economic theory suggests multiple 

possibilities: On the one hand, increasing 

the tenant contribution rate effectively 

increases the “tax” on tenants’ earnings (in 

other words, tenants keep a smaller portion 

of their earnings under the new policy 

compared with the former policy), creating 

a disincentive to work. On the other hand, 

tenants who are able to work may increase 

their employment to compensate for the 

loss of net income. A third possibility is that 

households may absorb their increased 

housing costs without changing their 

employment behavior, by reducing their 

spending or incurring debt. Without an 

evidence base to indicate how a PHA could 

expect changes in the tenant contribution 

11 HUD defines an elderly household as one where the head of household, spouse, or co-head is at least 62 years old. HUD defines a disabled 

household as a household where at least one of the members is a disabled adult (Code of Federal Regulations, 24 CFR 888.113).

rate to affect tenants’ employment and 

earnings, SCCHA assumed no effects on 

earnings when designing its rent reform. 

The SCCHA rent reform offered an 

opportunity to assess the effects of 

increasing the tenant contribution rate on 

their employment behavior and housing 

outcomes. The present study analyzed 

employment, earnings, housing subsidy, 

and housing characteristics of the group 

of nonelderly, nondisabled SCCHA tenants 

who were receiving HCV subsidies when the 

SCCHA’s rent reform was implemented (July 

2013) for the 4 years before the rent reform 

was implemented, and then follows them for 

up to 4 years after the rent reform.11

This report begins with background on 

traditional HUD policies and details on the 

SCCHA rent reform. It then reviews existing 

evidence on the effects of housing vouchers 

and changes to the traditional HUD rent 

rules on tenants’ labor market outcomes. 

The second chapter defines the study’s 

Exhibit 1.1 The Moving to Work Retrospective Evaluation

The HUD-sponsored Retrospective MTW Evaluation includes six reports and an online data feature that examine different aspects of the 

MTW program and MTW agencies’ activities and performance under the program’s three statutory objectives. 

A Picture of Moving to Work Agencies’ Housing Assistance describes MTW agencies, the assistance they provided, and the 

characteristics of the households they served in 2008 and 2016. A related online data feature provides access to MTW agency-level 

data.

Moving to Work Agencies’ Use of Funding Flexibility examines how agencies have used MTW funding flexibility, alone and with 

regulatory waivers, and categorizes funding flexibility activities by their primary objectives—cost effectiveness, self-sufficiency of 

assisted households, or increased housing choice for low-income families. The study includes an indepth examination of funding shifts 

for a subgroup of eight agencies.

Housing Choice and Self-Sufficiency Outcomes at Moving to Work Agencies examines the extent to which MTW agencies meet two 

of the program’s three statutory objectives, increasing housing choice and promoting self-sufficiency for assisted households. 

The Impact of the Moving to Work Demonstration on the Per Household Costs of Federal Housing Assistance examines how MTW 

status affects the costs, to HUD, of providing housing assistance to households in the public housing and Housing Choice Voucher 

(HCV) programs. 

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform examines the impacts on work, earnings, and housing 

subsidies among assisted households of Santa Clara’s unique rent reform, which increased the proportion of income that households 

must pay toward rent.

Moving to Work Agencies’ Use of Project-Based Voucher Assistance examines multiple aspects of MTW agencies’ use of projectbased voucher (PBV) assistance, including the share of assistance and HCV budget authority devoted to PBVs, the relationships 

between PBVs and the Low-Income Housing Tax Credit and Rental Assistance Demonstration programs, the locations of PBV-assisted 

units, and case studies of three agencies’ MTW goals and activities.
3

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 1. Introduction and Background

research questions and the rationale behind 

hypothesized effects. It also describes 

the study’s research design, including the 

study sample definition, comparison group 

selection, study period, data sources, 

and different methods used for each set 

of research questions. The third chapter 

discusses the study’s findings, and the final 

chapter discusses their implications.

Background

Santa Clara County is a diverse and 

densely populated region in the Bay Area of 

California, located in the southern portion 

of Silicon Valley. Santa Clara has the fifth 

highest median income among U.S. counties, 

and it is part of a metropolitan area with 

a very high cost of living, including an 

expensive housing market (U.S. Census 

Bureau, 2013).

SCCHA implemented its rent reform in 

response to the particular budget situation 

caused by the federal sequestration in 2013, 

and at the time, other MTW PHAs considered 

a similar response.12 Housing authorities 

often have to respond to budget cuts, and 

in doing so they must confront the question: 

Should they cut the number of vouchers 

they provide and put many households at 

risk of homelessness and severe hardship, 

or should they instead reduce the level of 

housing assistance they provide to their 

current voucher holders, having everyone 

share the burden—potentially increasing 

hardship for many more households (albeit 

to a lesser degree)? At the federal level, 

through a 2018 proposal, HUD expressed 

interest in a rent reform similar to the SCCHA 

rent reform that would have increased the 

tenant contribution rate from 30 percent 

of adjusted income to 35 percent of gross 

income (HUD, 2018).

12 The 2013 federal budget sequestration refers to a set of cuts to federal spending that was passed as part of the Budget Control Act of 2011 and went 

into effect March 1, 2013. 13 The payment standard is the maximum subsidy a PHA can pay on behalf of a household, and payment standards are set by the PHA between 90 and 110 

percent of the area’s fair market rents (FMRs). HUD sets FMRs annually at the 40th percentile of gross rents in the area.

Questions such as the one above must be 

answered even when policymakers are 

not facing budget reductions. The HCV 

program is not an entitlement program, its 

budget is limited, and there are long waiting 

lists in most large communities served 

by the program. Discussions around rent 

reform, therefore, must consider not only 

effects on current voucher holders, but also 

effects on eligible households that are not 

yet served by the program. The present 

study contributes to the knowledge of the 

impact on assisted households of a rent 

reform that decreases the subsidy received 

by each household in order to serve more 

households.

Housing Choice Voucher Program 

Income-Based Tenant Rent Rules

The HCV program helps low-income families 

obtain decent and safe housing in the 

private rental market. Housing vouchers are 

administered locally by housing agencies 

with funding from HUD. The voucher is 

a housing subsidy paid directly to the 

landlord by the agency on behalf of the 

participating household. The household 

pays the difference between the gross rent 

(the contract rent paid to the landlord plus 

utility costs) and the subsidy amount, or 

Housing Assistance Payment (HAP). The 

voucher holder is typically responsible 

for a portion of the gross rent equal to 30 

percent of the household’s adjusted income 

(after accounting for various allowable 

deductions), plus any amount by which 

the gross rent exceeds the local payment 

standard.13 Allowable deductions include a 

deduction for each dependent, a deduction 

for having at least one household member 

who is elderly or disabled, a child care 

allowance for reasonable child care expense, 

and an allowance for medical expenses 
4

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 1. Introduction and Background

for household members who are elderly or 

disabled. The portion of the gross rent that 

is equal to 30 percent of the household’s 

adjusted income is called the total tenant 

payment (TTP), and the total amount that 

the household pays toward its gross rent is 

called the family share. As a result, when 

tenants’ earnings increase, their share of 

the rent is increased by 30 percent of the 

additional amount they earn.

The rule that households pay 30 percent 

of adjusted income predates the Section 

8 program’s enactment in 1974 and was 

based on judgment about reasonable 

housing cost burden at the time (Schwartz 

and Wilson, 2008). It was initially set at 25 

percent by the 1969 Brooke Amendment to 

the 1968 Housing and Urban Development 

Act and was raised to 30 percent in 1981. 

This 30-percent-of-income rule is also now 

known as the Brooke rent.14 Variations of 

this tenant contribution rate—such as the 

one implemented by SCCHA—have so far 

not been rigorously tested. If increasing 

the tenant portion of rent does not affect 

households’ employment decisions and 

does not significantly increase tenants’ 

material hardship, but does succeed in 

reducing HAP expenditures, this could be 

one way of providing housing assistance to 

more families within a fixed budget amount.

14 See exhibit 1.2 for definitions of general housing policy terms used in this report. 15 SCCHA has a minimum tenant rent contribution of $50 that was in place before the rent reform (and before the beginning of the study period). Under 

both traditional and new rent rules, the tenant rent share is the greater of the calculated percentage of income or the $50 minimum rent. 16 Under the traditional rent rules, for units where utilities are not included as part of the contract rent, a utility allowance is added to the contract rent 

amount to calculate the gross rent. The HAP calculation is then based on this gross rent amount rather than the contract rent amount and equals the 

gross rent minus the household’s TTP (assuming the unit does not exceed the payment standard). Using the new rent calculation rules, the HAP is 

calculated as the contract rent minus the household’s TTP (again, assuming the unit does not exceed the payment standard). 

The Santa Clara County Housing 

Authority Rent Reform

Until September 2013, SCCHA required 

its tenants to pay 30 percent of adjusted 

income for rent (plus any amount over 

the payment standard). Then, in response 

to federal budget cuts resulting from 

the sequestration in March of that year, 

SCCHA increased tenants’ share to 35 

percent of gross income. Under traditional 

rent rules, income is first adjusted by 

subtracting various allowances and 

deductions—including dependent and 

childcare allowances and deductions for 

medical expenses—and then multiplying 

the adjusted income by 30 percent to arrive 

at the TTP. Under the new rules, the TTP is 

a flat 35 percent of the household’s gross 

income with no allowances or deductions.15

SCCHA estimated that this changed 

households’ rent contribution from 27 to 

35 percent of gross income (HACSC, 2013). 

In addition to eliminating deductions and 

allowances that are subtracted from gross 

income under traditional rules, SCCHA 

also eliminated utility allowances, so that 

households do not receive any assistance 

in paying for utilities when utilities are not 

included in their contract rent.16 In effect, 

this means that those households are paying 

even more than 35 percent of their gross 

income. In September 2014, the percentage 

Exhibit 1.2 General Housing Policy Terms

Brooke Amendment: The Brooke Amendment to the 1968 Housing and Urban Development Act was enacted in 1969. It amends the 

United States Housing Act of 1937 to cap subsidy households’ tenant rent share at 25 percent of their adjusted income. This percentage 

was raised to 30 percent in 1981. 

Brooke Rent: The 30 percent of adjusted income that households pay toward their gross rent.

Section 8 Housing Choice Voucher Program: The Housing Choice Voucher (HCV) program is the federal government’s primary rental 

subsidy program, assisting approximately 2.2 million low-income households in paying for housing in the private rental market. HCV 

households generally pay 30 percent of their income toward rent, and HUD subsidizes the remaining amount of the households’ rent up 

to a certain threshold based on area housing costs. The HCV program was enacted as Section 8 of the United States Housing Act of 1974.
5

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 1. Introduction and Background

of gross income to be contributed was 

reduced from 35 to 32 percent. As a result 

of the policy change, therefore, the overall 

tenant contribution was drastically increased 

in 2013, then slightly decreased a year later. 

(Neither the required contribution nor the 

minimum voucher standard has changed 

since that time.)

Exhibit 1.3 shows the TTP as a percentage 

of gross income at baseline (the last month 

before the policy change) and over the 

followup period for the study cohort, which 

is the measure that most directly reflects 

the rent policy changes over time.17 This 

measure reflects the treatment whose effects 

are evaluated in this study. In the month 

before the rent reform was implemented, 

households were paying 30 percent of 

their adjusted income toward rent (up to 

the unit’s payment standard) under the 

traditional rent rules, which translated, on 

average, to 27 percent of gross income. The 

actual percentage during this month was 

30.6 percent because this average includes 

households for whom 30 percent of adjusted 

income (or 10 percent of gross income) is less 

than the PHA’s minimum rent. At the end of 

the first year after rent reform, tenants’ TTP 

was on average equal to 37.8 percent of 

their gross income. (Again, this percentage 

17 This measure is only available for households in the study cohort who are receiving subsidies at the time.

is higher than 35 percent because for some 

households, 35 percent of gross income 

was below the minimum rent). It decreased 

slightly to 35.1 percent in Year 2 because of 

the reduction in TTP from 35 percent to 32 

percent of gross income 1 year after the rent 

reform was first implemented.

While SCCHA increased the tenant 

contribution rate, it also changed its policy 

for determining a household’s voucher size. 

The new policy allocated one room for the 

head of household (with spouse or partner) 

plus one additional bedroom for every two 

persons regardless of age, generation, 

relationship, or gender. Before this policy 

change, the household members of different 

generations (such as grandparents and their 

grandchildren), of the opposite sex over the 

age of 5, and unrelated adults (other than 

significant others) were allocated separate 

bedrooms. For example, a household that 

included a household head, her 7-year-old 

daughter, and her 9-year-old son would 

have had a voucher size of three bedrooms 

using the old rule and a voucher size of 

two bedrooms under the new policy. This 

policy change decreased the voucher size 

for 23 percent of nonelderly, nondisabled 

households served by SCCHA. In other 

words, 23 percent of voucher households 

Exhibit 1.3 Total Tenant Payment as a Percentage of Monthly Gross Income Among Nonelderly, Nondisabled Households 

Receiving Subsidies

TTP Among Households Receiving Subsidies (% of Monthly Gross Income) SCCHA

Last Month of Baseline 30.6

Last Month of Year 1 37.8

Last Month of Year 2 35.1

Last Month of Year 3 34.3

Sample Size 7,109

SCCHA = Santa Clara County Housing Authority. TTP = total tenant payment.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary by year because of missing 

values. TTP is the minimum amount a family must contribute toward rent and utilities regardless of the unit selected. Outcomes shown describe only those 

households receiving any housing subsidies in the specified month.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
Chapter 1. Introduction and Background 

were housed in a unit where the number 

of bedrooms exceeded the number of 

bedrooms on their vouchers under the new 

policy. For these households, if they didn’t 

move before the effective date of the new 

policy, their expected tenant contribution 

would sharply increase because their subsidy 

was now based on the fair market rent (FMR) 

for a smaller unit than the one they occupied. 

In anticipation of the potential hardship 

that HCV households might face because 

of the rent reform, SCCHA offered two 

means of assistance: hardship exemptions 

for households that experienced a sharp 

increase in rent share because of the new 

rent calculation, and financial and legal 

assistance for households at risk of eviction 

due to the rent reform.

The hardship exemption policy allowed 

households to have childcare or medical 

deductions temporarily included in the 

calculations for their TTP. These expenses 

were deducted from the household’s gross 

income (the exemption did not include 

other deductions, such as the dependent 

deduction). A household was eligible to 

apply for a hardship exemption if its rent 

portion increased by at least $50 because of 

the new rent calculation method. Since the 

households with larger deduction amounts 

were most affected by the rent reform, 

eligible households consisted mostly of 

households with children under the age of 13 

that were paying for childcare, or elderly and 

disabled households. Hardship exemptions 

were granted to 414 households (out of 754 

requested), most of them immediately after 

the rent reform went into effect.18 Households 

that were granted the exemption paid the 

lower TTP for 90 days, after which it was reset 

to the regular amount under the new rent 

rules, based on 35 percent of the household’s 

gross income with no deductions.

18 The total of 414 hardship exemptions includes exemptions for all households regardless of elderly or disabled status. SCCHA did not track elderly 

and disabled status of households granted hardship exemptions, so it is unknown how many of these households are in the study sample, which only 

includes nonelderly, nondisabled households and individuals.

SCCHA also collaborated with the Law 

Foundation of Silicon Valley and other 

local organizations to create the Sequester 

Eviction Prevention Program (SEPP) to assist 

HCV households that were facing eviction 

because of the SCCHA rent reform. The 

program provided financial assistance to 

cover unpaid rent or to cover a security 

deposit if a household had to move 

because of the rent reform. The program 

also included free legal services to prevent 

eviction. While the program was primarily 

designed to assist households affected by 

the voucher size rule change, the program 

was open to any household facing eviction 

because of an inability to pay the higher 

rent under the new rent policy. Households 

that experienced a substantial increase 

in their rent share (at least $300) or that 

were otherwise at risk of eviction because 

of the rent reform were eligible to receive 

assistance from the program. The program 

assisted 293 households comprising 805 

people. Of those households, 260 were 

nonelderly, nondisabled households and 

therefore included in the household-level 

analysis sample of the present study. SCCHA 

committed $500,000 of MTW funds for SEPP, 

which was supplemented with additional 

funds from the county of Santa Clara, the 

city of San Jose, and the Housing Trust 

Silicon Valley for a total funding commitment 

of $1,820,000. Of this committed funding, 

$808,078 was spent on the program, and all 

payments were made by August 2014.

SCCHA chose to increase the tenant 

contribution rate, which reduced the size of 

the housing subsidy per household, so they 

could continue to provide housing assistance 

to all households that were in the HCV 

program at the time. The alternative would 

have been to maintain the same percentageof-income amount but reduce the number 

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

6
Chapter 1. Introduction and Background

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

7

of households already in the subsidy 

program by terminating some households’ 

participation in the program.19

The decision by SCCHA was based partly on 

the assumption that increasing the amount 

that households paid toward rent would not 

substantially reduce tenants’ employment.20

Reductions in employment would have led 

to reductions in income, which would have 

led to necessary increases in HAP amounts, 

making the policy change counterproductive. 

Without any existing empirical evidence 

on the effects of changing the tenant 

contribution rate on employment and 

earnings, however, the effects of the kinds 

of policy changes made in SCCHA on actual 

HAP expenditures, households’ employment 

decisions, and hardship were difficult to 

predict. A few years after the rent reform was 

implemented, SCCHA leadership told the 

research team that their general impression 

was that, overall, voucher households did 

not seem to have changed their employment 

behavior in response to the policy, but instead 

made do with less. Furthermore, SCCHA 

achieved the HAP savings it projected using 

the assumption that the rent reform would 

have no effects on employment. 

Existing Evidence About the 

Effects of Housing Subsidies 

on Employment and Earnings

Given the increase in the percentage of 

income that tenants paid toward rent under 

the new SCCHA rent policy, there was a risk 

that tenants might reduce their earnings, 

which would have resulted in SCCHA having 

to increase the subsidy levels, effectively 

counteracting the HAP savings the housing 

19 SCCHA also put a freeze on issuing new vouchers at the time of the 2013 rent reform, so households that left the program after the rent reform was first 

implemented were not replaced in the subsidy program for a few years. There were two exceptions: an allotment of 500 vouchers issued to waiting list 

applicants in 2015 and an allotment of 500 vouchers issued to the chronically homeless in 2016. The voucher freeze was lifted at the end of February 

2017. 20 It was confirmed in phone calls with executive staff at SCCHA that the estimates of HAP savings that they calculated before implementing the rent 

reform did not account for any potential reductions in earnings from the reform. 21 See Shroder (2012) for a discussion of these and other factors and a literature review up to 2012.

agency hoped to achieve. The economic 

theory behind these expectations is not 

straightforward, however. Economic theory 

suggests that, on the one hand, increasing 

the percentage of income that tenants pay 

toward rent can reduce employment in 

response to the increased “tax” on their 

earnings (the “substitution effect” in labor 

economics): The tenants would gain less 

disposable income with each extra hour of 

work than they would have in the absence 

of that tax. On the other hand, households 

might increase their employment to 

compensate for the reduction in their subsidy 

and maintain the level of disposable income 

they had before the policy change (the 

“income effect” in labor economics).

While there is no prior research on changing 

the percentage of income that households 

pay toward rent or total housing costs among 

households already receiving subsidies, 

some insight can be drawn from the existing 

evidence about providing housing vouchers 

to households that had not been receiving 

housing subsidies. For such households, 

both the income and substitution effects 

point to housing subsidy receipt as a work 

disincentive.21 The income effect suggests 

that providing housing subsidies can reduce 

employment among recipients by increasing 

households’ disposable income, because the 

subsidy covers a large part of the housing 

costs that households were previously paying 

for, increasing their disposable income. 

The substitution effect suggests a further 

disincentive to work by imposing an implicit 

“tax” on their earnings, since the 30-percentof-income rule for determining tenant rent 

share means that households would only 

“take home” 70 cents for every dollar they 

earn. (This tax is in addition to the explicit 
Chapter 1. Introduction and Background 

taxes earnings bring.) This “tax” is effectively 

an increase from 0 percent to about 30 

percent of the households’ income when they 

begin receiving subsidies.

Three large-scale random assignment studies 

conducted in the past decade provide 

reliable evidence on new housing subsidies’ 

effects on households’ employment behavior 

and suggest some disincentive effect on 

employment and earnings consistent with 

the economic theory described above. The 

first of these recent studies is the random 

assignment evaluation of the Welfare to Work 

Voucher (WtWV) program, which studied the 

effects of receiving housing vouchers for 

households selected from the HCV waiting 

list that were receiving or had received 

Temporary Assistance to Needy Families 

(TANF). The study found that households 

randomly assigned to receive a housing 

voucher worked less than households who 

were randomly assigned to the control 

group, but only during the first year following 

random assignment (Mills et al., 2006).

A later study leveraged a lottery used by the 

Chicago Housing Authority Corporation to 

allocate newly available housing vouchers in 

1997 (Jacob and Ludwig, 2012). This natural 

experiment found more persistent negative 

impacts on labor supply. The study found 

that receiving a voucher caused subsidy 

recipients to reduce their employment by 6 

percent (4 percentage points) and reduce 

their quarterly earnings by 10 percent ($329 

in 2007 dollars). The Chicago study found 

that the impacts were significantly larger for 

households who were not receiving TANF 

than those who were, which may be an 

important reason their results differed from 

those of WtWV (whose sample consisted of 

all TANF recipients and found less negative 

impact on employment).22

22 Both the WtWV and Chicago studies found that estimated effects varied according to several baseline characteristics, including household size and 

age of the household head. In Chicago, Jacob and Ludwig used their employment and income findings to estimate an income elasticity of -0.09 and a 

compensated wage elasticity of 0.15. In this case, the response of individuals determined by the elasticity of substitution was more important than the 

one caused by the elasticity of income.

The most recent of the three studies, the 

Family Options Study, offered vouchers 

to homeless families as one arm of the 

intervention. This study also found that 

housing vouchers reduced employment 

for voucher recipients: In the short-term, 11 

percentage points fewer households who 

were randomly assigned to receive housing 

vouchers were working than was the case 

for households that were randomly assigned 

to the study’s control group. (Fifty percent of 

the intervention group had any employment 

during the first year after random assignment 

compared with 61 percent of the control 

group.) After 3 years, this difference fell to 6 

percentage points (64 percent of treatment 

group members had any employment in 

the prior year and a half compared with 58 

percent in the control group) (Gubits et al., 

2015; 2016).

In all three of these studies, randomly 

selected households were given access 

to housing subsidy programs that used 

the traditional 30-percent-of-income rent 

rule. Therefore, as described earlier, these 

studies estimated effects of providing 

housing assistance to households that 

were not yet receiving any assistance. That 

research question is somewhat distinct from 

the question addressed by this SCCHA 

study, which examines the effects of 

changing rent policies for households that 

are already receiving housing assistance 

under the traditional rent rules. Also, while 

the earlier studies provide evidence for a 

potential work disincentive from obtaining a 

housing voucher at least in the short term, 

this evidence does not necessarily imply 

that reducing the housing subsidy (as in 

the SCCHA rent reform) would provide an 

incentive to work. Theoretically, as described 

earlier, an increase in the percentage of 

income a household pays toward rent could 

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

8
Chapter 1. Introduction and Background

9

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

lead to a reduction in earnings due to a 

higher “tax” on earnings (households would 

keep less of their earnings) or to an increase 

in earnings to compensate for lost income; 

the net outcome depends on which of the 

two effects is dominant. 

To date, there is no direct prior evidence 

to support either hypothesis, but there are 

studies currently under way that may provide 

insight on this question. Evidence from 

these studies is more directly relevant to 

the present study because they specifically 

examine the effects of changing the 

percentage of income that housing subsidyassisted households are required to pay 

toward rent. The first is the HUD-funded 

Rent Reform demonstration, which tests a 

rent reform model in four PHAs that caps 

the tenant contribution toward rent for 3 

years. During those 3 years, households’ 

contribution toward rent does not increase 

regardless of any increases in earnings 

during that period. The Rent Reform 

demonstration’s evaluation will provide 

evidence on whether this reform leads to 

increases in employment and earnings.23 An 

interim report with findings on short-term 

effects on employment and earnings and a 

final report with findings on long-term effects 

are expected to be published later this year.

The two other related studies under way are 

the HUD evaluation of the MTW expansion 

and the HUD Jobs Plus Outcomes study. 

The second cohort of the HUD study of 

the current MTW expansion is intended to 

investigate the effects of tiered rents (where 

tenant rent share is determined based on 

which income band household income falls 

into) and stepped rents (where tenant rent 

share is increased by a set amount at regular 

intervals according to a rent share schedule) 

in 10 PHAs with newly granted MTW status. 

These rent reforms are not expected to 

23 The policy, evaluation design, and PHAs’ early experiences with the new policy are described in detail in a baseline report (Riccio, Deitch, and Verma, 

2017).

directly change the percentage of income 

that households will contribute toward rent 

but will provide alternative methods of 

calculating tenant rent. The HUD Jobs Plus 

Outcomes study will assess the effects of the 

Jobs Plus program, and results may provide 

some insight into the effects of earnings 

disregards combined with employment 

services. Jobs Plus is a place-based program 

implemented in public housing developments 

that combined on-site employment-related 

services and activities (including job search 

assistance, referrals to education and training 

programs, and support services), rent-based 

financial incentives, and community support 

for work. Taken together, this set of studies 

that evaluate changes in how tenant rent 

share is determined will build a body of 

evidence that will inform future HUD and 

PHA decisions about the most effective rent 

policies to implement.

The present study is the only study to date to 

assess the effects of increasing the percent 

of income that tenants pay toward rent in a 

housing subsidy program. It examines the 

effects of this type of rent reform on tenants’ 

employment behavior and housing subsidies. 

The study’s research questions are specified 

in the next chapter.
10

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform
11

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 2. Research Design

Chapter 2

Research Design

The present study examines the effects of 

Santa Clara County Housing Authority’s 

(SCCHA) rent reform on housing subsidy 

recipients’ employment and housing 

outcomes for the cohort of nonelderly, 

nondisabled adults and households 

receiving HCVs in SCCHA at the time the 

rent reform was implemented in 2013. It uses 

three methods to investigate its research 

questions: a comparative interrupted 

time series design to estimate impacts on 

employment and earnings; an autoregressive 

difference-in-difference design to estimate 

impacts on average housing subsidies and 

continued subsidy receipt; and descriptive 

analyses to examine subsidy households’ 

housing characteristics and rent burden 

before and after the SCCHA rent reform.

Research Questions

The present study primarily aims to address 

the question: How does an increase in tenant 

rent share affect tenants’ work behavior, 

and how does it affect households’ housing 

outcomes? This question is broken down into 

the following research questions:

1. What was the effect of the SCCHA 

rent reform on household members’ 

employment and earnings?

2. What was the effect of the SCCHA rent 

reform on housing assistance receipt and 

subsidy amounts?

3. Was there any suggestion of potential 

effects of the SCCHA rent reform on 

households’ housing decisions?

4. To what extent did SCCHA households 

experience selected housing-related 

hardships after the rent reform?

These research questions are first 

addressed for the full study sample of 

nonelderly, nondisabled adults living in 

HCV-subsidized households. The study then 

explores whether these effects differ for 

households only affected by the increase in 

the tenant contribution rate (77 percent of 

the study sample) and for the households 

affected by the change in the voucher size 

policy in addition to the increase in the 

tenant contribution rate (23 percent of the 

study sample). 

The remainder of this section describes 

the rationale for each research question 

and hypotheses that lie behind these 

questions. It also describes the rationale for 

assessing effects separately for households 

only affected by the change in the tenant 

contribution rate and households also 

affected by the voucher size rule change.

Effects on Employment and Earnings

The primary research question for this study 

is: “How did the SCCHA policy changes 

affect HCV subsidy recipients’ employment 

and earnings?” Adults in subsidy households 

who were able to work could have 

responded to the rent reform by changing 

their work behavior to adjust their earnings 

(and therefore adjust their tenant contribution 

amount and net income) in three ways:

1. Households may have increased their 

employment and hours worked in response 

to the policy change. Doing so could 

increase their earnings, compensating for 

all or part of the reduction in disposable 

income so they would experience less 

change in their standards of living.

2. Households may have maintained their 

current levels of employment and hours 

worked (by choice or not), either finding 

a way to manage with less disposable 

income or perhaps experiencing increased 

material hardship.
12

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

3. Households may have reduced their 

employment and earnings in response to 

the increased disincentive to work, namely 

the increased “tax” on earnings, reflecting 

the fact that they got to keep less of each 

dollar they earned than they did under the 

former policy.

In the first two scenarios, HAP expenditures 

would have decreased in the amount 

estimated by SCCHA, and their expected 

savings would have been realized.24

If, instead, households reduced their 

employment in response to an increase in 

the percentage dedicated to rent (the third 

scenario), HAP expenditures would not have 

decreased as much as expected, and SCCHA 

would not have met its budgetary targets. 

Depending on the extent of the reduction in 

employment, HAP expenditures might even 

be greater than previous levels, and the policy 

change would have been counterproductive.

These different forces could have immediate 

effects (someone could reduce the number 

of hours worked because of the increased 

implicit tax on earnings), or they could affect 

decisions about employment later in the 

followup period (someone could choose not 

to accept an opportunity to increase working 

hours because the increase in net income 

would not be as large as it would have been 

under the previous rent policy). It is also 

possible that households responded to the 

increased tenant contribution rate differently 

over time. For example, households may have 

first responded to the unanticipated income 

shock by working more to compensate for 

the lower income and to maintain longer 

term financial commitments, but over time 

they may have reduced their employment as 

they adjusted to the change, possibly down 

24 The elimination of utility allowances may contribute to the income effect (as households may have to increase income to cover increased utility costs) 

but would not contribute to the substitution effect (reducing earnings would not increase HUD coverage of utility costs; it would only increase HAP to 

cover rent). 25 SCCHA also considered reducing the payment standard for the HCV program, but decided against it because an analysis it conducted comparing 

these two options—revising the payment standard to 90 percent of FMRs or increasing the tenant contribution rate to 35 percent of gross income—

showed that the tenant contribution rate change would have a lesser impact on lower income households (households with less than $32,000 of 

income). See appendix 5 of the SCCHA FY2014 MTW Plan for more details (HACSC, 2013). 26 See exhibit 2.1 for definitions of subsidy outcomes included in the present study. See exhibit 2.2 for definitions of other relevant housing subsidy terms.

to their pre-2013 employment level, or even 

lower, in response to the increased “tax” on 

earnings. This study estimates the effects of 

the SCCHA rent reform on employment and 

earnings for the 4 years after the rent reform 

was implemented and therefore can capture 

both immediate and longer-term effects.

Effects on Average Housing Subsidy 

Amounts and Continued Housing 

Subsidy Receipt

The primary objective of the SCCHA rent 

contribution increase in September 2013 

was budgetary. Initially, SCCHA sought to 

reduce housing assistance payments and 

associated administrative costs sufficiently to 

stay within its annual budget as constrained 

by the sequestration cuts. By increasing the 

tenant rent contribution and thereby reducing 

subsidy payment amounts for all families, 

SCCHA planned to continue to serve all the 

households in the HCV program at the time 

with the reduced budget. Therefore, the rent 

reform was expected to have a direct effect 

on housing subsidies, including the average 

TTP, average HAP, and average family share 

(TTP plus any part of the gross rent that 

exceeds the payment standard).25, 26

The increase in the tenant contribution 

rate and the decrease in housing subsidy 

payments is not necessarily a straightforward 

relationship, however. As described in the 

previous section, the SCCHA rent reform 

could have led to various changes in 

households’ employment behavior. If many 

households had reduced their earnings in 

response to the rent reform, then average 

household HAP amounts may not have 

decreased substantially. In other words, 

the rent reform could have directly affected 

Chapter 2. Research Design
13

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

households’ subsidy levels through its 

change in the tenant contribution rate and 

indirectly affected households’ subsidy levels 

through households’ employment responses 

to the changes in their housing costs.

The study also seeks to address whether 

the SCCHA rent reform caused households 

to leave the HCV program. The increase 

in the tenant contribution rate might have 

driven some households’ HAP down to zero, 

meaning that such households would be fully 

responsible for their own housing costs. If the 

rent reform did in fact increase employment 

and earnings, some households might have 

“earned their way off” housing subsidies (if 

their increased income effectively reduced 

their subsidy payments to $0). Even for 

Chapter 2. Research Design

Exhibit 2.1 Definitions of Housing Subsidy Measures Used in Present Study

Housing Assistance Payment (HAP): The amount that the public housing agency (PHA) provides in subsidy to pay for rent and utilities. 

It is calculated as the lower of (1) the payment standard for the family’s unit minus the TTP, or (2) the gross rent minus the TTP. Under the 

SCCHA new rent calculation rules, the HAP is calculated as the lower of (1) the payment standard for the family’s unit minus the TTP, or 

(2) the contract rent minus the TTP.

Total Tenant Payment (TTP): The minimum amount that the household must contribute towards rent and utilities. Under traditional rent 

rules, it is calculated as the greatest of: (1) 30 percent of monthly adjusted income, (2) 10 percent of monthly gross income, and (3) the 

PHA minimum rent. Under the SCCHA new rent rules, it is calculated as the greater of 35 percent (or 32 percent, after July 2014) of 

monthly gross income and (2) the PHA minimum rent.

Tenant Rent Share: The household’s total contribution towards the contract rent. For households living in units with contract rents at or 

below the payment standard, the tenant rent share is equal to the household’s TTP. For households with contract rents that exceed the 

payment standard, the tenant rent share is calculated as the TTP plus the amount by which the contract rent exceeds the payment standard.

Any Subsidy Receipt: A household is classified as receiving housing subsidies if their HAP amount is greater than zero (in any PHA). 

If a household’s income increases to the threshold where their HAP amount is zero because their calculated TTP is greater than the 

gross rent, they have a grace period of 180 days during which they are not receiving any subsidies but are still considered active in the 

program. If their income drops before their grace period ends, they can have their TTP recalculated and will begin receiving subsidies 

again. A household whose HAP is $0 and is in their grace period is not classified as receiving any housing subsidies at that time.

Tenant Rent Share as a Percent of Household Gross Income: Rent burden is typically defined as the portion of a household’s income 

used toward total housing costs, including rent and utilities. Because data on utility costs were not available for two PHAs in the sample, 

the present study uses an alternative measure of rent burden, which is calculated as the monthly tenant rent share (rent only, not 

including utilities) divided by the household’s monthly gross income.

Exhibit 2.2 Definitions of Other Housing Subsidy Terms

Adjusted Income: A household’s gross income minus deductions for the following: dependents, status as a senior family or family with 

members with disabilities, unreimbursed childcare expenses, unreimbursed medical expenses (for seniors and families with members 

with disabilities only), and unreimbursed disability assistance expenses. 

Fair Market Rent (FMR): The gross rent for units by number of bedrooms on which the household’s housing subsidy is based. HUD sets 

FMRs annually at the 40th percentile of gross rents in the area, based on local housing market prices for nonluxury, privately owned 

rental units that meet minimum standards of safety.

Gross Income: A household’s total income before taxes and other deductions, received by all members of the household. It includes total 

income from wages, social security payments, retirement benefits, military and veteran’s disability payments, unemployment benefits, 

welfare benefits, and asset income. It excludes certain forms of income, such as earnings from minors and income from live-in aides.

Gross Rent: The total contract rent paid to the landlord plus any utility allowances.

Payment Standard: The maximum subsidy a PHA pays on behalf of a household (before deducting the household’s TTP), which is set 

by the PHA between 90 and 110 percent of the area’s FMR.

Port-Out: A household relocating to a unit within another PHA jurisdiction.

Utility Allowance: The utility allowance is an estimate of the amount needed for a household to cover its reasonable utility costs, based 

on bedroom size, which utilities the tenant is responsible for outside the contract rent, the type of utilities (for example, gas versus oil 

heat), and other unit characteristics such as structure type.

Voucher Size: The number of bedrooms on a household’s voucher. A household’s rent calculation uses the lower of (1) the payment 

standard for the household’s voucher size, or (2) the payment standard for the household’s unit size. 

Minimum Rent: The minimum amount set by the PHA that households must contribute towards rent and utilities.
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

14

households whose HAP was significantly 

reduced, but not reduced fully to $0, some 

might have chosen to leave the HCV program 

because they found the smaller subsidy 

no longer justified the burden of staying in 

the program and complying with housing 

authority reporting requirements and other 

program rules. While there were strong 

reasons to expect direct effects on average 

household housing subsidy amounts (as 

discussed before), effects on receiving any

housing subsidy (“attrition” from the program) 

would have been less direct.

Households’ Housing Decisions While in 

the Voucher Program

Although the immediate goal of both 2013 

changes in SCCHA policies was to reduce 

HAP expenditures in response to federal 

budget cuts, the changes could also have 

had effects on decisions households made 

about whether and where to relocate and 

whether to change who was on the lease. In 

contrast with the housing subsidy outcomes, 

which are near-term outcomes of the SCCHA 

rent reform, households’ housing decisions 

are more removed and the effects on these 

outcomes are less direct.

The tenant contribution rate change could 

have encouraged households to seek 

other housing if their gross rent was above 

the payment standard, in order to offset 

the increase in housing costs. The study 

explored whether households moved to 

smaller units, moved to different types of 

neighborhoods, or relocated to units outside 

the jurisdiction of SCCHA (defined as “porting 

out”), and whether they changed their 

housing composition by adding or removing 

family members. 

Household Rent Burden While in the 

Voucher Program

Because the policy change effectively 

reduced the subsidy amounts provided to 

households for rent, an important research 

question is whether the rent reform led to 

housing-related hardship. For example, 

households may have been unable to pay 

their rent on time, leading to arrears and, in 

some cases, to eviction and termination from 

the HCV program. Whether the SCCHA rent 

reform caused increased material hardship 

is an important question, but one that this 

study was not able to answer directly or 

comprehensively. Due to data limitations, 

the study was able to examine a measure 

of households’ rent burden over time on a 

descriptive level, but it could not measure 

other aspects of material hardship, such 

as rent arrears, evictions, food insecurity, 

inability to pay utility bills or medical 

expenses, and other important expenses. The 

study relied on conversations with SCCHA 

leadership and internal agency documents 

to explore the types of assistance SCCHA 

provided to alleviate housing-related hardship 

and prevent eviction due to the rent reform.

Effects for Households Affected by the 

Tenant Contribution Rate Change Only 

Versus Households Also Affected by the 

Voucher Size Rule Change

The hypotheses described earlier relate 

to the potential effects of the tenant 

contribution rate change. As noted earlier, 

23 percent of HCV households (not including 

senior households or households headed 

by people with disabilities) in SCCHA were 

immediately affected not only by the change 

in subsidy levels but also by the new voucher 

size policy that SCCHA adopted as part 

of its rent reform. The new voucher size 

policy enforced a minimum of two family 

members per bedroom, excluding the head 

of household’s bedroom, regardless of age, 

generation, gender, or relationship of the 

household members. 

Both groups of households—that subject to 

only to the tenant contribution rate change 

Chapter 2. Research Design
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

15

Chapter 2. Research Design

and that also subject to the voucher size 

rule change—faced the same increased 

contribution rate of 35 percent of gross 

income.27 Thus, its effect on earnings and 

employment should be approximately 

the same for the two groups. Members of 

the group subject to both policy changes, 

however, faced a much larger total reduction 

in housing subsidies, especially if they 

could not readily move to a unit with fewer 

bedrooms. This larger reduction in net 

income may have produced a stronger 

incentive for adult household members 

to increase their earnings in order to 

compensate for their lost net income. On 

the other hand, if these larger rent burdens 

led to evictions or other forced moves, the 

resulting instability of their housing situations 

may have led to difficulties in maintaining the 

same job or maintaining the same level of 

work effort (especially if it was necessary to 

relocate further away from the current job).

All households whose rent exceeded the 

payment standard faced some incentive 

to move to a less expensive unit. The 

households that were affected by both 

policy changes, however, faced an especially 

large reduction in their housing subsidies 

because of both the increase in the tenant 

contribution rate and a reduction in the 

number of bedrooms on which their subsidies 

would be based. The latter increase could 

be avoided by moving to a smaller unit, 

so these households had an especially 

strong incentive to relocate. Their options 

to relocate may have been limited, however, 

because of rapidly increasing housing 

prices in the area. According to SCCHA 

staff members working with households at 

the time, these rapid changes to the local 

housing market made it very difficult for 

27 As mentioned earlier, when SCCHA eliminated all income deductions and allowances from households’ rent calculation policy change, it also 

eliminated utility allowances. Throughout this paper, references to the tenant rate contribution change include this elimination of utility allowances. 28 The study uses HUD’s definitions of elderly and disabled households and adults. See Box 2.3 for definitions of these terms. 29 The SCCHA policy changes affected all HCV households, regardless of elderly or disability status. The study focuses on nonelderly, nondisabled 

households because elderly and disabled households would not have had the same flexibility to change their work behavior in response to the policy 

changes. Although the study’s analysis plan included conducting a parallel, secondary analysis for elderly and disabled households, studying the 

effects of the rent reform on these households was not feasible due to data limitations (see Castells, Riccio, Verma, and Long, 2017). 

many households to find a smaller unit that 

was affordable; in some cases, moving to 

a smaller unit would have been even more 

expensive than remaining where they were. 

To the extent that was the case, these 

households would have been vulnerable to 

especially high rent burdens.

Study Sample

The analysis sample includes all nonelderly, 

nondisabled households and individuals who 

were receiving HCV subsidies from SCCHA 

or one of the three selected comparison 

PHAs at the time of the SCCHA policy 

change in July 2013.28, 29 These comparison 

PHAs include: the Housing Authority of the 

County of Alameda, the Housing Authority of 

the County of San Mateo, and San Francisco 

Housing Authority. The process used for 

selecting these PHAs for the comparison 

group is described later in this chapter. 

Quarterly and annual effects on employment 

were estimated for the cohort of all 

nonelderly, nondisabled individuals who 

were living in households receiving HCV 

subsidies at the time of the rent reform (July 

2013). Annual effects on household subsidy 

amounts and continued housing subsidy 

receipt were estimated for the cohort of 

all nonelderly, nondisabled households

receiving HCV subsidies from study PHAs at 

the time of the rent reform.

The SCCHA policy changes affected all 

HCV households regardless of elderly or 

disability status. The present study focuses 

on nonelderly, nondisabled tenants because 

its primary research question is how the 

rent reform affected subsidy recipients’ 

employment and earnings, and elderly 
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

16

Chapter 2. Research Design

and disabled tenants would not have had 

the same flexibility to change their work 

behavior in response to the policy changes. 

Although the present study had intended to 

conduct a parallel, secondary analysis for 

elderly and disabled households, it was not 

feasible to examine effects of SCCHA’s rent 

reform on these households due to data 

limitations. Specifically, employment trends 

for elderly adults declined over time as adults 

in these households aged. In contrast, this 

trend for disabled, nonelderly households 

increased over time, possibly because some 

members overcame temporary disabilities. 

Unfortunately, SCCHA and the comparison 

PHAs had different proportions of elderly 

households and disabled households, which 

meant that the employment and earnings 

trends for the group of elderly and disabled 

households in the comparison PHAs were not 

an appropriate counterfactual for this analysis.

The present study conducted a subgroup 

analysis that compares intervention effects 

on households that experienced only a 

change in the tenant contribution rate with 

households that were also affected by the 

voucher-size rule change. The subgroup of 

SCCHA households that were affected by 

the voucher size rule change was identified 

by comparing households’ voucher sizes 

at baseline (in early July 2013, before the 

rent reform was implemented) with their 

voucher sizes under the new policy. Using 

actual subsidy data, a simulation applied the 

new voucher size rules to each household 

according to its baseline unit size and 

household composition. A household was 

included in the subgroup of households 

affected by the voucher size rule change, 

if its new rent calculation would use the 

payment standard of a smaller voucher size 

under the new policy. All other households 

were included in the subgroup of households 

that were only affected by the tenant 

contribution rate increase.

At the time of the SCCHA rent reform, 

only one PHA in the study sample other 

than SCCHA—the San Francisco Housing 

Authority (SFHA)—had not yet moved to 

a more conservative voucher size policy. 

Therefore, only SFHA could be included 

in the comparison group for this subgroup 

analysis. The method described earlier was 

used to identify the subgroup of households 

(based on baseline voucher size, unit size, 

and household composition) in SFHA that 

would have been affected by the new 

voucher size rules if those rules had been 

applied to them. Twenty-three percent 

of nonelderly, nondisabled households 

in SCCHA and 21 percent in SFHA were 

identified for this subgroup analysis. 

The comparative interrupted time series 

(CITS) models for the main analysis were 

used to estimate effects for nonelderly, 

nondisabled individuals. For the subgroup 

analysis, they were used to estimate effects 

on adults living in nonelderly, nondisabled 

households who were affected by the voucher 

size policy change in addition to the increase 

in the tenant contribution rate. This difference 

Exhibit 2.3 HUD Definitions of Sample Terms

Adult: An individual who is 18 years of age or older or a minor under the age of 18 who has been emancipated to act on his/her own 

behalf, including the ability to execute a contract or lease. 

Individual with Disabilities: An individual who has a physical or mental impairment that substantially limits one or more of the major life 

activities. 

Household with Disabilities: A household whose head, co-head, spouse, or sole member is a person with a disability. 

Senior Individual: A person at least 62 years of age.

Senior Household: A household whose head, co-head, spouse, or sole member is at least 62 years of age.
Chapter 2. Research Design

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

17

in sample definition is due to the subgroups 

being defined using household-level variables 

(voucher size, unit size, and household 

composition at the time of the policy change) 

and receiving unemployment insurance (UI) 

data aggregated within those groupings. 

Although the unit of analysis is the same 

for both the full sample and subgroup 

analyses (individuals, aggregated to PHAlevel averages), the sample of individuals 

differs somewhat. For the main analysis, the 

sample consists of nonelderly, nondisabled 

individuals living in either nonelderly, 

nondisabled households or in elderly or 

disabled households (which were also 

subject to SCCHA’s rent reform). For the 

subgroup analysis, the individual-level 

analysis sample consists of all adults living 

in those households, regardless of their 

personal elderly or disabled status. The 

sample still consists of mostly nonelderly, 

nondisabled adults: 94.8 percent of the 

adults in the sample are neither elderly nor 

disabled. This distinction means, however, 

that 19 percent of the SCCHA adults in the 

main analysis sample are not included in the 

subgroup sample because they were living 

in elderly or disabled households, which are 

excluded from the subgroup analysis.

Study Period

The CITS design used in this study (described 

in detail later) requires a sufficient number 

of time points (ideally, at least 4 years) 

before the policy change to reliably estimate 

baseline trends. As exhibit 2.4 shows, the 

SCCHA rent reform was implemented in 

early July 2013 (when the PHA sent letters 

to subsidy households notifying them of 

the rent reform and their new tenant rent 

share under the new rent policy), and the 

baseline period is defined as the 4 years 

before the start of the SCCHA rent reform 

implementation: July 1, 2009, to June 30, 

2013. The followup period includes the 

4 years after the start of the SCCHA rent 

reform and is defined as July 1, 2013, to June 

30, 2017. In other words, the analysis used 

4 years of historical (pre-rent-reform) and 4 

years of followup (post-rent reform) data on 

the study cohort to estimate effects of the 

rent reform.

Data Sources

The study primarily relies on two data 

sources for understanding the rent reform’s 

effects on employment, earnings, housing 

subsidy receipt and amounts, plus housing 

characteristics: state UI wage data and the 

Chapter 2. Research Design

Exhibit 2.4 Timeline of Policy Changes
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

18

HUD Inventory Management System/Public 

and Indian Housing Information Center 

(IMS/PIC) data. It also uses other data 

sources—including U.S. Census Bureau 

data and internal SCCHA documents and 

discussions with SCCHA staff members—to 

provide context for these findings.

Employment and Earnings 

Employment and earnings data were 

obtained from the California Employment 

Development Department (EDD). These 

administrative data consist of employerreported UI wage data for all employment 

covered by UI in the state of California. 

These data do not, however, include 

wage data for jobs outside of California, 

federal employment, or informal or selfemployment not covered by UI.

The data are quarterly and were received 

in aggregate form (for example, average 

earnings in the third quarter of 2013 for 

all households in a group). Since this is a 

retrospective study relying on secondary 

analysis of administrative data, it was 

not feasible to obtain informed consent 

for all the members of the sample, and 

therefore the analysis relies on deidentified, 

aggregate-level earnings and employment 

data. The employment and earnings data 

for the main analysis (which estimates 

effects for all nonelderly, nondisabled adults 

receiving HCV subsidies) were grouped by 

PHA and whether individuals were elderly or 

disabled. These data were used to construct 

the two key measures in this analysis: the 

average quarterly employment rate and 

average quarterly earnings measures. Since 

CITS analysis requires the calculation of a 

trend in the outcome over time, average 

quarterly earnings were adjusted for inflation 

to 2017 dollars using the Bureau of Labor 

Statistics Consumer Price Index (CPI).30

30 All Urban Consumers (Current Series) database (https://www.bls.gov/cpi/data.htm). 31 A full list of 50058 certification types can be found in the HUD 50058 instruction booklet, available at https://www.hud.gov/sites/documents/50058I.pdf. 

For the subgroup analysis, which looks 

at effects on employment and earnings 

for adults living in households that 

were only affected by the increased 

tenant contribution rate separately from 

households also affected by the new 

voucher size policy, the sample was defined 

at the household level (as described in 

more detail in the Sample section above). 

The data were grouped by PHA, household 

elderly or disabled status, and whether 

the payment standard on which the 

household’s rent calculation was based 

was reduced because of the new voucher 

size determination rules. Therefore, this 

analysis estimated effects on earnings 

and employment for all adults (regardless 

of elderly or disabled status) living in 

nonelderly, nondisabled households 

that were subject to the voucher size 

policy change. Employment and earnings 

measures were constructed in the same 

way as for the main analysis.

Housing Subsidies and Housing 

Characteristics

The study relies on IMS/PIC data obtained 

from HUD for housing-related measures. 

At each household certification, the 

PHA must complete (or update) a HUD 

Form 50058, which includes information 

on a household’s housing subsidy 

amount, tenant rent amount, household 

characteristics, and unit characteristics. 

A certification occurs when a household 

is issued a new voucher, completes a 

regular recertification, completes an 

interim recertification due to a change 

in income or household composition, 

relocates to another unit outside of its 

regular recertification schedule, relocates 

to a different housing agency, or ends its 

program participation.31

Chapter 2. Research Design
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

19

Quarterly IMS/PIC snapshot data were used 

to identify the study sample, to describe 

household and individual characteristics 

at the time of the policy change, and to 

create covariates for the impact models. To 

identify the study sample, snapshot files 

from the second and third quarters of 2013 

were used to identify which households in 

the selected PHAs were receiving subsidies 

on July 1, 2013, just before the SCCHA 

rent reform was implemented. These 

files provide a snapshot of households’ 

information at the end of each quarter.

IMS/PIC transactional data were used to 

investigate effects on housing subsidy 

amounts and housing subsidy receipt 

and to provide descriptive information on 

other housing-related outcomes, including 

rent burden and unit characteristics. The 

transactional files include a record for 

each certification that occurred during the 

study period. Monthly measures from July 

2009 through June 2017 were created 

using these data. Data were acquired for all 

transactions recorded from January 1, 2009 

(six months before the study period) to 

establish baseline levels of all the housingrelated measures.

The IMS/PIC data for the last year of the 

followup period (July 1, 2016, to June 30, 

2017) have important limitations. The data 

for this last year of the study period did 

not benefit from updates recorded in the 

following year, or from certifications that 

were recorded in the following year but 

effective during Year 4. An analysis of years 

in the study period that had at least one full 

year of subsequent data available (2009 to 

2015) found that 12 to 25 percent (depending 

on the year) of certifications effective in 

a given year had an effective date that 

occurred after that year. In other words, it 

can be expected that only 75 to 88 percent 

32 The payment standard amounts and the household HAP, TTP, and family share amounts are included in the IMS/PIC data for traditional PHAs. 33 The selection process for the comparison group is described in detail later in this chapter.

of records in Year 4 are accurate. This issue 

is especially evident in the housing subsidy 

amounts in Year 4, which contain many more 

extreme values than the prior 3 years that 

would likely be corrected in an updated 

file. Therefore, results using the fourth year 

of IMS/PIC data are not presented in this 

report, but the overall results using Year 4 

data are reported in footnotes.

MTW agencies have fewer 50058 reporting 

requirements and use a shortened 50058 

form to collect data at each certification. 

It was necessary, therefore, to construct 

some measures that are available for 

traditional PHAs but are not included in 

HUD Form 50058 MTW: HAP, TTP, and 

family share. These measures rely on the 

payment standard at the time of the rent 

calculation (based on the smaller of the 

number of bedrooms of the voucher or 

unit), which is not included in the IMS/PIC 

data.32 MDRC collected payment standard 

amounts for the full study period from 

SCCHA and from the Housing Authority 

of the County of San Mateo (HACSM), 

one of the MTW agencies selected for 

the comparison group.33 MDRC calculated 

these measures as follows:

• TTP is the minimum amount that the 

household must contribute toward rent and 

utilities. Under traditional rent rules, it is 

calculated as the greatest of (1) 30 percent 

of monthly adjusted income, (2) 10 percent 

of monthly gross income, or (3) the PHA 

minimum rent. Under the SCCHA new rent 

rules, it is calculated as the greater of 35 

percent (or 32 percent, after July 2014) 

of monthly gross income or (2) the PHA 

minimum rent.

• HAP is the amount that the PHA provides in 

subsidy for rent and utilities. It is calculated 

as the lower of (1) the payment standard 

for the family’s unit minus the TTP or (2) 

Chapter 2. Research Design
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

20

Chapter 2. Research Design

the gross rent minus the TTP. For SCCHA 

households after the new rent policy went 

into effect, it is calculated as the lower of 

(1) the payment standard for the family’s 

unit minus the TTP or (2) the contract rent 

minus the TTP.

• The family share is the household’s total 

contribution toward the gross rent. For 

households with a gross rent at or below 

the payment standard, the family share 

is equal to the household’s TTP. For 

households with a gross rent that exceeds 

the payment standard, the family share is 

calculated as the TTP plus the amount by 

which the gross rent exceeds the payment 

standard. (This measure was constructed 

for baseline only.)

Utility allowance data were not available for 

SCCHA households for all recertifications 

after the rent reform was implemented in 

2013 because the rent reform eliminated 

utility allowances, and for HACSM after 

its tiered subsidy policy was implemented 

in 2010 because utility allowances were 

incorporated into their tiered subsidy 

schedules. Utility allowances are the 

PHAs’ estimates of the amount needed 

for a household to cover its reasonable 

utility costs, based on bedroom size, 

which utilities the tenant is responsible 

for outside the contract rent (for example, 

heat, cooking, electricity), the type of 

utilities (for example, gas, oil, electric), and 

other unit characteristics such as structure 

type (for example, apartment, singlefamily home). Utility allowances are added 

to contract rent to calculate gross rent, 

which is used to calculate family share as 

described earlier.

Utility allowances are not included in the 

calculation of HAP for HACSM in any of 

the analyses. (As described earlier, HAP 

relies on gross rent with the traditional 

rent policy.) Data on utility allowances are 

also not available for SCCHA after the 

rent reform, but because utility allowances 

were eliminated as part of the rent reform 

(and thus the calculation relies on contract 

rent instead of gross rent), these data are 

not needed to calculate HAP for SCCHA 

households after the rent reform went 

into effect. To test whether excluding 

utility allowances from HAP calculations 

for HACSM households influenced the 

impact estimates for average housing 

subsidies and continued housing subsidy 

receipt, utility allowance amounts were 

imputed, and the impact analyses were 

rerun using these imputed measures. The 

sensitivity tests suggest that the influence 

of excluding utility allowances for HACSM 

is negligible. This finding is unsurprising 

because San Mateo households comprise 

only about one-quarter of the comparison 

group sample and utility costs are not 

high for HACSM households (households 

that are responsible for paying for utilities 

outside of their contract rent have an 

average utility allowance of $97 per month 

during the time period that utility allowance 

data is available for HACSM). Imputed utility 

allowances for HACSM were also used 

for sensitivity tests of the HAP descriptive 

analyses, with similar findings. Specific 

findings of the sensitivity tests are included 

in footnotes in chapter 3 along with the 

main findings.

To impute the utility allowance amounts in 

SCCHA for the sensitivity test described 

above, a household’s utility allowance 

amount for all followup months was set 

to equal the amount of the household’s 

utility allowance in the month before the 

implementation of the SCCHA rent reform 

(the last month where utility allowance data 

was available for SCCHA households). For 

HACSM, where utility allowance data was 

only available during the first year of the 

study period, households’ utility allowance 

amounts in all the following months of 

the study period were set equal to the 
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

21

household’s utility allowance amount from 

that first year.34

A household’s family share is typically 

interpreted as a measure of the family’s 

total out-of-pocket housing costs, including 

tenant rent share and tenant-paid utilities. 

Although the SCCHA rent reform eliminated 

utility allowances from its rent calculation, 

households are still responsible for the 

tenant-paid utilities for their units. To ensure 

that a consistent measure of housing costs 

was used across PHAs and across time 

(before and after the SCCHA rent reform), 

the descriptive analysis uses a tenant rent 

share measure to analyze the amount that 

households pay toward rent, not accounting 

for utilities. 

An alternative measure of rent burden was 

constructed for both MTW and traditional 

PHAs. Rent burden is typically defined as a 

household’s total housing cost—including 

rent share and tenant-paid utilities—as a 

proportion of household income. Because 

data on utility allowances for the entire 

study period are not available for SCCHA 

and HACSM, it was not possible to 

reconstruct family share for SCCHA during 

the followup period (or for San Mateo at 

all). To ensure that this descriptive analysis 

described later in this chapter examines 

a consistent measure of rent burden over 

time—both before and after the SCCHA 

rent reform—and that this measure is 

comparable between SCCHA and the 

comparison group PHAs—an alternative 

measure of rent burden is used. This 

measure is the tenant rent share (equal to 

the TTP plus any amount that the contract

rent, not including tenant-paid utilities, 

34 This imputation method was used based on an examination of the percent of households with utility allowances and the average utility allowance 

amounts over the 4 years of baseline. Both measures remained very stable over these 4 years (in SCCHA, 98.1 to 98.6 percent of households had 

any utility allowances with an average amount of $104 to $107 each year.) For HACSM, utility allowance data were only available in the first year of the 

study period. To the extent to which households’ unit size, household income, and other factors affect their decisions about choosing units based on 

their gross rents in relation to the payment standard, or based on the number and types of utilities the tenant is responsible for, these factors would be 

captured in their prior utility allowance levels, and this variation in utility allowance amounts is preserved using this imputation method. This imputation 

method cannot, however, account for changing utility costs when households relocate to different units with different utility costs. 35 For households whose tenant rent share (TTP plus the amount that the contract rent exceeds the unit’s payment standard) exceeds their gross income, 

this measure is set to 100 percent.

exceeds the payment standard) divided by 

the household’s gross income.35

A 40-percent rent burden is commonly 

used as the threshold for a high burden in 

the literature discussing HCV households 

(Ellen and Torrats-Espinosa, 2017; Dawkins 

and Jeon, 2017). The measure used in this 

study—the tenant rent share as proportion 

of household gross income—departs from 

this standard definition in two ways. First, 

the threshold used is typically 40 percent 

of adjusted income—which was impossible 

to measure in SCCHA after it eliminated 

deductions—which would be a lower 

threshold than 40 percent of gross income. 

Second, the measure typically uses total 

housing costs—including tenant rent share 

and tenant-paid utilities—as a proportion 

of household income. As described earlier, 

the measure used in the present study only 

uses tenant rent share (and does not include 

tenant-paid utilities).

Local Context, Neighborhood Poverty 

and Hardship Policies

The present study uses the census tract 

poverty rate as a proxy for neighborhood 

quality. Poverty rate is the most widely 

used measure of neighborhood quality 

and distress (Galvez, 2010). To measure 

neighborhood poverty, the geocoded HUD 

IMS/PIC data were merged with U.S. Census 

data. The census tract poverty rates (for 

individuals age 18 to 64 years) from either 

the 2007–2011 American Community Survey 

5-year estimates or the 2012–2016 5-year 

estimates, depending on the date that the 

record was entered, were merged with the 

census tracts in the IMS/PIC data.

Chapter 2. Research Design
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

22

The study used two additional public data 

sources during the process of selecting the 

comparison group PHAs (described later). 

Public data from the California EDD website 

was one source for measures of labor and 

housing market information for 2012–2016 for 

the Bay Area counties where the PHAs in the 

present analysis were located.36 The other 

source was 2013 data from the HUD Picture 

of Subsidized Households dataset, available 

publicly on the HUD website, to describe 

the characteristics of households living in 

candidate PHAs.

Last, the study relied on discussions with 

SCCHA leaders and internal SCCHA 

documentation to better understand PHA 

hardship policies, eviction assistance 

program, and the overall policy and 

economic context at the time the rent reform 

was implemented.

Analytic Approach

The present study uses a combination of 

analytic methods to assess the effects of 

the SCCHA 2013 rent reform. The most 

rigorous method used is a CITS analysis, 

which is a quasi-experimental design 

that was used to estimate effects on 

the study’s key outcomes, employment 

and earnings. SCCHA’s rent reform is 

particularly well suited for this method 

because the rent reform was rolled out all 

at once, the policy change affected all HCV 

households in SCCHA, and an appropriate 

comparison group of PHAs exists. These 

PHAs were subject to the same labor and 

housing market forces as SCCHA but did 

not implement a rent reform during the 

analysis period.

It was not feasible to use the CITS method 

to estimate the effects of the rent reform 

on housing subsidy amounts and continued 

36 Data were compiled from the “REPORT 400 C, Monthly Labor Force Data for Counties, Annual Average (Data Not Seasonally Adjusted)” reports, 

produced by the Labor Market Information Division of California EDD, available on the California EDD website: https://www.labormarketinfo.edd.ca.gov/

data/unemployment-and-labor-force.html.

housing subsidy receipt (“attrition”) during 

the followup period. Multiple time points 

(ideally a minimum of 4 years) of baseline 

data are needed to estimate a baseline 

trend in CITS analysis, but these housing 

subsidy measures rely on HUD IMS/PIC 

data that are available for households only 

while they are receiving subsidies. The study 

sample was defined at the point in time 

when the rent reform was first implemented, 

and since not all the study households had 

been receiving subsidies for all 4 years 

before that point, it was not possible to 

estimate a baseline trend for the full sample. 

Therefore, to study the effects of the SCCHA 

rent reform on housing subsidy amounts and 

continued receipt, the study instead uses 

an autoregressive difference-in-difference 

method for housing subsidy outcomes. 

Although difference-in-difference is a widely 

used quasi-experimental approach, it is 

less rigorous than CITS because it does not 

account for potentially differing baseline 

trends in outcomes for the treatment and 

comparison groups.

In addition, descriptive analyses, which 

cannot indicate causality, were used to 

explore changes in household decisions 

about unit size, neighborhood quality, 

changes in household composition, and 

housing-related hardships. It was not 

feasible to use CITS or difference-indifference for these analyses because data 

on these outcomes were available only 

for households who were still receiving 

subsidies, and not all households continued 

to receive subsidies for the full 4 years after 

the implementation of the rent reform. The 

results of the descriptive analyses should be 

interpreted with caution and are presented 

only to provide context for the rent-reform 

impact estimates. Each method is described 

more fully in the following.

Chapter 2. Research Design
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

23

Comparative Interrupted Time Series

The CITS analysis measures the impact of 

the SCCHA rent reform on earnings or on 

employment as the difference between the 

post rent reform SCCHA deviation from its 

pre-rent reform trend and the corresponding 

comparison group deviation from its pre-rent 

reform trend.37 This method was previously 

used to assess the effects of the Jobs 

Plus program (Bloom, Riccio, and Verma, 

2005). The focus of the present analysis is 

whether the SCCHA rent reform caused a 

deviation in predicted employment rates or 

average quarterly earnings for the cohort 

of all nonelderly, nondisabled adults in 

SCCHA’s HCV program that differed from any 

deviation from predicted employment rates 

and average annual earnings that residents 

in comparison group PHAs experienced at 

the time. Model specifications for these CITS 

models are presented in appendix A.

The SCCHA rent reform meets important 

criteria for a successful CITS analysis. 

First, the policy change or changes must 

be consequential, capable of producing a 

substantial impact in a relatively short time. 

The reform was consequential in that it was 

expected to increase the average tenant 

rent share from 27 to 35 percent of gross 

income and decrease HAP payments by 12 

percent. Second, the policy change must be 

implemented all at once for the entire study 

cohort. The rent reform affected all HCV 

households, and, according to the SCCHA, 

all households were notified and therefore 

potentially affected at the same time. Letters 

were sent out to households in the first week 

of July and the changes went into effect on 

September 1, 2013. Third, for the comparison 

with other housing authorities to be valid, 

those housing authorities’ voucher holders 

must be subject to similar labor and housing 

market forces as SCCHA (the baseline levels 

of employment and earnings do not have to 

37 See Somers et al. (2013) for a review of this method.

be the same). The study used a systematic 

comparison group selection process, 

described in the following, that identified 

comparison PHAs that faced similar local 

economic forces during the study period.

The first step in the CITS analysis was 

to measure the average earnings or 

employment trajectory of all the nonelderly, 

nondisabled adults in households receiving 

subsidies in the SCCHA HCV program over 

the 4 years before its policy changes in 

2013. This baseline trend was then used 

to extrapolate what earnings levels or 

employment rates would have looked like 

in the absence of the policy changes in 

2013. The second step was to measure the 

earnings levels or employment rates after 

these changes occurred to estimate the 

magnitude and direction of any subsequent 

deviations from this baseline trend. A parallel 

analysis was conducted for comparison 

PHAs. The final step of the design was to 

measure the magnitude and direction of the 

treatment and control group difference in 

these estimated deviations from trend. These 

observed differences represent the estimates 

of the impact of the SCCHA rent reform on 

individual earnings and rates of employment.

Autoregressive Difference-in-Difference

As noted earlier, the present study uses 

an autoregressive difference-in-difference 

model to estimate effects on the average 

amount of subsidy households received and 

the percentage of households in the sample 

still receiving subsidies each year after the 

SCCHA rent reform was first implemented. 

Difference-in-difference estimation is also 

a rigorous, quasi-experimental design, but 

unlike a CITS analysis, it does not account for 

differences in baseline trends.

While the lack of four full years of historical 

data for the full study cohort (as discussed 

Chapter 2. Research Design
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

24

previously) ruled out using a CITS analysis 

for these outcomes, the comparison group 

selection process provides a reasonable level 

of confidence that the comparison PHAs had 

similar baseline trends in housing subsidy 

receipt and amounts and were subject to 

the same labor and housing market forces. 

It is important to remember the caveat that 

if there were any differences in the trends 

of these housing outcomes before the 

rent reform, those differences, rather than 

the policy changes, could be the cause of 

estimated impacts, or they could mask a true 

effect when none is detected.

Conceptually, autoregressive difference-indifference measures the difference between 

the outcome of interest at the time of the 

policy change and the outcome at specific 

points during the followup period (for 

example, 1 year after the policy change) for 

both the treatment and comparison groups, 

and then compares those differences. Unlike 

a simple difference-in-difference model, 

however, the models used for this analysis 

are autoregressive in that they also control 

for preintervention values of the outcome 

measure. The model estimating effects 

on average HAP includes four covariates 

representing HAP amounts in the 4 years 

before the rent reform (for those households 

not yet receiving HCV subsidies in each of 

the 4 years, these values of HAP are $0), 

along with four binary covariates indicating 

whether the household was receiving any 

HCV subsidy in each year before the rent 

reform. The model specifications for these 

autoregressive difference-in-difference 

models are provided in appendix A.

Descriptive Analysis

The study looks descriptively at outcomes 

that may reflect housing decisions that 

SCCHA households made in response to the 

rent reform and that reflect any subsequent 

housing-related hardship they may have 

faced, including rent burden, number of 

bedrooms, neighborhood quality, and 

household size. Average levels of these 

outcomes for the sample households in 

Santa Clara are compared with averages 

in the comparison group PHAs at the last 

month of baseline and annually thereafter. 

Discussions with SCCHA leadership 

provided information on safeguards that 

SCCHA offered to households severely 

affected by the rent reform.

The trends in the descriptive exhibits 

should be interpreted with caution. Data 

on these housing measures were available 

for only those households still receiving 

subsidies. The households that leave the 

subsidy program each year are likely to 

differ systematically from households 

that remain. Therefore, the patterns in 

housing outcomes over the followup 

period represent only a partial picture of 

outcomes for the households in the study 

sample, and this picture gets even less 

representative later in the study period, 

as the percentage of households still 

receiving subsidies gets smaller.

The outcome levels for the comparison group 

PHAs are also presented in the descriptive 

exhibits to provide context for the patterns in 

outcomes for SCCHA in relation to patterns 

for the comparison group PHAs, which also 

have a small percentage of households 

losing their housing subsidies each year. 

The comparison group’s outcomes, however, 

should not be interpreted as a counterfactual 

representing the expected outcomes for 

SCCHA households in the absence of the 

rent reform. 

Drawing conclusions from the patterns 

of these outcomes can be especially 

problematic if the rent reform had an effect 

on the proportion of households that lost 

their subsidies. While the analysis did not 

suggest an overall effect on households 

Chapter 2. Research Design
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

25

Chapter 2. Research Design

leaving housing assistance, the SCCHA rent 

reform may have influenced which types 

of households left the subsidy program 

during the followup even if this change is 

not captured by the data on changes in 

the percentage of households receiving 

subsidies over time.

The descriptive analysis serves two main 

purposes. First, it examines the averages 

in the housing subsidy outcomes as an 

additional check on the validity of the study. 

The SCCHA rent reform is expected to 

have direct effects on households’ housing 

subsidies. If there is no clear pattern of 

an increase in TTP and reduction in HAP 

(especially 1 year after the rent reform was 

implemented), the findings might call into 

question the face validity of the study—

whether the SCCHA rent reform was 

implemented as expected and whether key 

outcomes are being measured correctly. 

Second, the analysis examines patterns in 

averages of housing outcomes during the 

followup period that may reflect households’ 

potential responses to the SCCHA rent 

reform to see whether any stark deviations 

from pre-rent reform levels are evident, 

especially if this deviation does not exist in 

the comparison group. Even if such a stark 

difference is evident, however, it alone 

would not provide compelling evidence 

that the change was caused by the SCCHA 

rent reform. Instead, it would suggest that 

the rent reform may have led to changes in 

SCCHA households’ housing decisions and 

may warrant further exploration in future 

studies with more rigorous methods directed 

to this question.

Subgroup Analysis

The subgroup analysis examines whether 

the effects of the SCCHA rent reform for 

the 77 percent of nonelderly, nondisabled 

households who were only affected by 

the tenant contribution rate increase 

(hereafter referred to as the “single policy 

change” subgroup) differed from that for 

the 23 percent of nonelderly, nondisabled 

households who were affected by both the 

increased tenant contribution rate and the 

reduction in voucher size (hereafter referred 

as the “double policy change” subgroup). 

As described in the “Study Sample” section 

above, only one PHA—SFHA—could be 

used for the subgroup analysis comparison 

group. To verify that SFHA by itself would 

provide a valid comparison group for the 

subgroup analysis, impact analyses on 

the four key study outcomes—average 

earnings, employment rates, the average 

household HAP, and whether households 

were still receiving subsidies—were rerun 

for the full nonelderly, nondisabled sample 

with only SFHA as the comparison group. 

Results of this analysis indicated no policychange effects on employment rates or 

average earnings for the full sample, which 

is comparable to results produced using all 

three comparison PHAs. This provides some 

confidence that the reduced comparison 

group sample is valid for the subgroup 

analysis for earnings and employment 

impacts, which relies on a comparative 

interrupted time-series research design. 

For the two housing subsidy outcomes, 

however, using only SFHA as the comparison 

group (and an autoregressive differencein-difference research design) produced 

impact estimates that differed appreciably 

from those based on the full comparison 

group of three PHAs. Specifically: (1) when 

using the SFHA comparison group, estimated 

impacts on the percent of households still 

receiving housing subsidies receipt rates 

were negative and statistically significant 

compared to essentially zero effects when 

using the full comparison group), and (2) 

estimated SCCHA reductions in in HAP 

amounts were larger when SFHA replaced 

the full comparison group.
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

26

These differences in the estimated impacts 

for the housing subsidy outcomes (and the 

lack of meaningful differences in impact 

estimates on employment and earnings) 

suggest that there is a difference in the 

underlying baseline trends between SCCHA 

and SFHA that is accounted for by the CITS 

analysis (used for the employment and 

earnings outcomes) but not accounted for by 

the autoregressive difference-in-difference 

analysis used to estimate effects on housing 

subsidies. Because, with SFHA as the only 

comparison group PHA, the autoregressive 

difference-in-difference design would not 

produce reliable estimates of the effects 

on average housing subsidy amounts and 

the percentage of households still receiving 

subsidies during the followup period for the 

single policy change and the double policy 

change subgroups separately, this study 

focuses on the CITS estimates of effects on 

employment rates and average earnings. 

Although the results of the validation 

analysis raise doubt about the validity of 

the impact estimates for housing subsidies 

and continued subsidy receipt for the 

single policy change subgroup alone and 

the double policy change subgroup alone, 

it is still possible to gain some insight into 

whether the rent reform affected households’ 

housing subsidies differently for these two 

subgroups. In other words, while the study 

can’t produce reliable estimates of the effects 

of the SCCHA rent reform on households 

in the double policy change group, it is 

possible to estimate how its effects differ (in 

direction and magnitude) from those for the 

single policy change group. These differential 

effects can be estimated by examining the 

difference in the separate estimated effects 

for the two subgroups. This method is known 

as a difference-in-difference-in-difference 

design and is conducted as an exploratory 

analysis for the present study.38

38 See Wing, Simon and Bello-Gomez (2018) for a description of this method.

Recognizing that the simple differencein-difference estimates for each of the 

subgroups likely contain a bias (due to a 

potentially differing underlying baseline 

trend for SFHA compared with SCCHA), the 

present difference-in-difference-in-difference 

method is based on the assumption that 

this bias is reasonably similar across both 

the single policy change subgroup and 

the double policy change subgroup and 

therefore can be “subtracted out” from the 

estimates of their differential impacts. This 

assumption seems reasonable here because 

it is unlikely that any underlying reason for 

the differing baseline trends would affect the 

double policy change group differently than 

the single policy change group. For example, 

if the difference in the underlying baseline 

trends in average housing subsidy amounts 

between SCCHA and SFHA is due to the 

differing baseline trends in employment rates 

(which are observed in exhibit 2.9, described 

later in the report), it is unlikely that the 

underlying cause of that difference—perhaps 

a somewhat slower-growing local economy—

would affect the double policy change group 

substantially differently than the single policy 

change group. Thus, one can have some 

confidence in the method used to estimate 

the difference between rent reform impacts 

on the two subgroups. 

Comparison Group Selection

One of the main conditions for a CITS design 

to be an effective method for measuring the 

impact of the SCCHA rent reform is that the 

CITS comparison group be subject to labor 

and housing market forces that are similar to 

those for SCCHA. Because the present study 

identified comparison PHAs in the Bay Area 

in counties with similar labor and housing 

markets, one can be reasonably confident 

that this condition is met. This condition is 

important for a CITS analysis because the 

Chapter 2. Research Design
Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

27

Chapter 2. Research Design

mean outcome of the comparison group does 

not serve as the counterfactual outcome for 

the treatment group, as it does in most quasiexperimental methods. Instead, the deviation

in the mean outcome of the comparison 

group from its estimated baseline trend 

serves as the counterfactual for the deviation

of the mean treatment group outcome from 

its estimated baseline trend. Consequently, 

the difference between these two deviations 

from trend identifies the impact of the 

SCCHA rent reform on the employment and 

earnings of SCCHA subsidy recipients.

In addition, it is desirable for the CITS 

comparison group to have baseline trends for 

the primary outcome measures (employment 

and earnings) that are similar to those for 

SCCHA and for the characteristics of their 

households to be similar to those of SCCHA 

residents. While these similarities are not 

necessary for a CITS analysis to produce 

valid impact estimates (because the CITS 

design implicitly controls for these baseline 

differences), the closer the alignment 

between the treatment and comparison 

groups on baseline levels and trends of 

earnings and employment, and the more 

similar the households in the two groups, the 

more one can be confident that the groups 

would respond similarly to changing local 

economic conditions. In the original Jobs Plus 

evaluation (which also used a CITS design), 

the close alignment in baseline trends of the 

primary outcome measure (earnings) of the 

program and comparison groups lent a great 

deal of credibility to the results.

In contrast, similarity of baseline trends 

is quite important for the difference-indifference method that was used to estimate 

effects on housing subsidy levels and 

whether households continued to receive 

subsidies, since this method does not 

account for any treatment and comparison 

group differences in baseline trends.

With the preceding considerations in mind, a 

three-stage process was used to identify PHAs 

to serve as the comparison group. As exhibit 

2.5 illustrates, the first stage narrowed down 

the counties considered by examining local 

labor market and housing market conditions. 

The second stage examined characteristics of 

households in the remaining candidate PHAs 

to determine which differed appreciably from 

those in SCCHA. Last, baseline earnings and 

employment trends for the remaining pool of 

PHAs were examined to select those whose 

baseline trends were most closely aligned with 

the SCCHA baseline trends.

Stage 1

Compare Local Labor and 

Housing Market Conditions

Candidate Counties: 11

Selected Counties: 5

Stage 2

Compare PHAs’ Aggregate

Household Characteristics

Candidate PHAs: 12

Selected PHAs: 11

Stage 3

Compare PHAs’ Average Baseline

Earning and Employment Trends

Candidate PHAs: 11

Selected PHAs: 3

Housing Authority of the County of Alameda

Housing Authority of the County of San Mateo,

and San Francisco Housing Authority

Exhibit 2.5 Comparison Group Selection

PHA = public housing agency.

Notes: Stage 1 conditions were calculated using county-level U.S. 

Census Bureau (2010), 2009–2013 American Community Survey 5-Year 

Estimates, and California Employment Development Department Monthly 

Labor Force Data for Counties (2012–2016) data. Stage 2 characteristics 

were calculated using HUD housing agency-level Picture of Subsidized 

Households (2013) data and HUD household-level Public and Indian 

Housing Information Center data. Stage 3 trends were calculated 

using California Employment Development Department individual level 

aggregate unemployment insurance (UI) data. Trends were calculated 

across the 4-year period from July 1, 2009, through June 30, 2013.
28

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

In the first stage, local labor and housing 

market conditions were examined for the 

12 counties in the San Jose-San FranciscoOakland combined statistical area,39

including Santa Clara, in 2013 (when the 

SCCHA rent reform was implemented). 

San Benito County was excluded early 

on at this stage because there is no PHA 

located in this county, which is served by 

the Housing Authority of the County of 

Santa Cruz. The map in exhibit 2.6 shows 

the counties’ locations in the Bay Area. In 

addition, the selection process considered 

geographical factors, such as ease of 

access to San Francisco and San Jose and 

the counties’ general proximity to Santa 

Clara. For example, if the large cities of 

San Francisco and San Jose are not easily 

accessible by public transportation, there is 

a higher likelihood that households in those 

PHAs would be subject to different labor 

market forces from households in SCCHA. 

Also, the closer a county is to Santa Clara, 

39 See appendix exhibit B.1.

the more likely it is that households in that 

county would face similar economic forces 

as SCCHA households, all other factors 

being equal.

Based on these factors, five counties were 

dropped from consideration: Napa, Sonoma, 

San Joaquin, Solano, and Marin. Napa, 

Sonoma, and San Joaquin were dropped 

because they are more rural than Santa Clara 

(as is evident by their population and housing 

density measures), and their local labor 

markets are heavily based on agriculture. 

Hence, they are probably subject to forces 

that differ substantially from those for Santa 

Clara. Labor market indicators also suggest 

dissimilarities: They all had lower household 

incomes, and San Joaquin and Solano had 

higher unemployment rates than Santa 

Clara during this period. Furthermore, there 

are indicators that housing markets differ 

significantly from Santa Clara’s: rental vacancy 

rates are higher in these counties and average 

Candidate Comparison

Group Counties

Santa Clara County

Non-Study Counties

KEY

Exhibit 2.6 Map of Santa Clara and Comparison Counties

Source: California State Association of Counties

Chapter 2. Research Design
29

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 2. Research Design

rents are lower. MDRC sought input from 

the HUD regional office in San Francisco to 

validate its initial assessment. The remaining 

counties were Alameda, Contra Costa, San 

Francisco, San Mateo, and Santa Cruz.

In the second stage of the comparison 

selection process, all PHAs in the five 

remaining counties and Santa Clara were 

identified and the aggregate household 

characteristics for the HCV populations 

of these PHAs were examined. At this 

stage, a conservative approach was used 

because it was not clear which household 

characteristics would lead households to 

respond differently to changes in the labor 

and housing markets, and only one of the 

12 PHAs in the five candidate counties was 

dropped from consideration. (A stronger 

indicator of whether the households in 

the PHAs would respond similarly to 

labor and housing market forces is their 

actual baseline trend in the outcome of 

interest, which was the basis for the third 

stage of the selection process.) Further, 

the mix of demographics in Santa Clara 

is unique (about one-third of households 

are Asian, one-third are Hispanic, and the 

remaining one-third consists of Black and 

White households), and while a mix of 

comparison PHAs can provide some level 

of representation of this racial and ethnic 

composition, there is no single PHA in the 

Bay Area that has a similar mix. Nonetheless, 

one PHA, the Livermore Housing Authority, 

was dropped at this stage because of a 

nonelderly, nondisabled HCV population 

that looked very different from Santa Clara’s 

on key outcomes. The Livermore Housing 

Authority had a much higher proportion of 

households with at least one household 

member working and a much higher average 

household income than the nonelderly, 

nondisabled HCV population in SCCHA.

Because the remaining pool of PHAs 

included two MTW PHAs (Oakland Housing 

Authority and HACSM), MTW reports were 

reviewed to assess whether those PHAs 

had implemented any rent reforms or other 

policy changes with their MTW flexibility 

during the study period that may have 

affected the study’s outcomes of interest. 

One policy change that was explored was a 

tiered subsidy rent structure in San Mateo, 

which was implemented early in the study 

period. It is unlikely that this policy created 

a work incentive or disincentive. There is 

currently no evidence that tiered rent or 

subsidy structures affect subsidy recipients’ 

work behavior; further, the income tiers 

used in San Mateo’s tiered subsidy policy 

were small ($2,500 increments). It is 

important to note that this change was 

implemented very early on in the study 

baseline period (early 2010), so even if there 

was any effect on employment or earnings, 

it would have been captured in the baseline 

trends for that PHA. 

SCCHA also implemented a rent policy 

change in early 2010 that was intended 

to encourage households to increase 

their earnings. SCCHA extended its 

recertification period from the traditional 

12 to 24 months for households that were 

not on a fixed income. This policy change 

was approved in 2009, and SCCHA began 

rolling it out in January 2010. Households 

could still request an interim recertification 

to decrease their rent share if they 

experienced a reduction in income between 

certifications but increases in income during 

this period did not result in increased TTP 

until the next scheduled recertification. If 

this extended recertification period led to an 

increase in households’ earnings, it would 

have been captured in the baseline trend 

and would not be confounded with the 

SCCHA rent reform in 2013.

In the third and final stage of selecting 

comparison PHAs, earnings and employment 

trends for the 4 years before the SCCHA 
30

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

rent reform were examined for the remaining 

11 candidate comparison PHAs using UI 

wage data. Again, similar baseline trends 

are not necessary for CITS analysis to 

produce reliable estimates, but they increase 

confidence that the two groups of households 

would respond similarly to changing 

economic conditions. This is especially 

true for baseline trends of the primary 

outcome measures. If baseline earnings and 

employment trends among comparison group 

and treatment group PHAs were closely 

aligned, despite differences in household 

characteristics such as demographics, it 

would suggest that households in both 

groups respond similarly to local labor 

and housing market forces, regardless of 

differences in their characteristics.

Based on these patterns of baseline 

employment and earnings before the 

SCCHA rent reform, the sample was 

narrowed down to the three PHAs with 

trends most similar to Santa Clara’s: 

The Housing Authority of the County of 

Alameda, HACSM, and SFHA. Exhibits 2.7 

and 2.8 compare these trends for Santa 

Clara and the selected counties. Exhibit 

2.9 shows the slopes for the pre-rent 

reform employment and earnings trends 

in each candidate PHA and the number 

of individuals in the HCV program. The 

slopes represent the average change in 

the outcome by quarter. For example, the 

SCCHA slope of 0.895 for the employment 

rate means that over the baseline period, 

the employment rate for adults in SCCHA 

increased by an average of 0.895 

percentage points each quarter. The slope 

of 47.79 for the SCCHA average earnings 

means that over the baseline period, 

average quarterly earnings increased by 

$47.79 each quarter. The closer the slope 

to the SCCHA slope, the more similar 

the PHA baseline trend is to the SCCHA 

baseline trend. Appendix exhibits B.2 

through B.7 show the baseline trends for 

0%

10%

20%

30%

40%

50%

60%

Q3/09

Q4/09

Q1/10

Q2/10

Q3/10

Q4/10

Q1/11

Q2/11

Q3/11

Q4/11

Q1/12

Q2/12

Q3/12

Q4/12

Q1/13

Q2/13

Employment Rate

Quarter

Santa Clara County HA San Mateo County HA

Alameda County HA San Francisco HA

Exhibit 2.7 Baseline Trends in Quarterly Employment Rates of Nonelderly, Nondisabled Adults in the Santa Clara County 

Housing Authority and Selected Comparison Housing Agencies

HA = housing authority.

Note: Sample consists of adults in the Housing Choice Voucher program who were not seniors or adults with disabilities. 

Source: California Employment Development Department individual-level aggregate unemployment insurance data

Chapter 2. Research Design
31

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 2. Research Design

the full set of PHA candidates along with 

the SCCHA baseline trend by county (with 

some counties combined into one graph 

for readability).

It is worth noting that two of the three 

selected comparison PHAs—those in 

Alameda and San Mateo—were already 

using voucher size determination rules 

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

Average Earnings

Q3/09

Q4/09

Q1/10

Q2/10

Q3/10

Q4/10

Q1/11

Q2/11

Q3/11

Q4/11

Q1/12

Q2/12

Q3/12

Q4/12

Q1/13

Q2/13

Santa Clara County HA San Mateo County HA

Alameda County HA San Francisco HA

Quarter

Exhibit 2.8 Baseline Trends in Average Quarterly Earnings of Nonelderly, Nondisabled Adults in the Santa Clara County 

Housing Authority and Selected Comparison Housing Agencies

HA = housing authority.

Notes: Sample consists of adults in the Housing Choice Voucher program who were not seniors or adults with disabilities. Earnings not adjusted for inflation.

Source: California Employment Development Department aggregate unemployment insurance data

Exhibit 2.9 Sample Sizes and Slopes of Candidate Comparison Public Housing Agencies

Housing Authority Number of Adults Employment Rate Slope (p.p.) Average Earnings Slope ($)

Alameda County

City of Alameda 1,732 0.625 24.24

Alameda County 7,969 0.880 43.39

City of Oakland 10,617 0.534 29.22

City of Berkeley 921 0.607 32.51

San Mateo County

San Mateo County 3,694 0.800 49.30

San Francisco County 

San Francisco 6,279 0.699 43.88

Contra Costa County 

Contra Costa County 5,989 0.617 30.73

City of Richmond 1,357 0.579 33.34

City of Pittsburg 957 0.556 26.72

Santa Cruz County 

Santa Cruz County 3,813 0.686 33.26

59,461

Notes: Sample consists of adults (who were not seniors or adults with disabilities) in the Housing Choice Voucher program. Earnings not adjusted for inflation.

Source: California Employment Development Department aggregate unemployment insurance data
32

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

that were closer to the more conservative 

rules (allowing fewer bedrooms based on a 

given household composition) that SCCHA 

implemented as part of its 2013 rent reform. 

Like the other policy changes described 

earlier that sample PHAs made between 

2009 and 2013, since these voucher size 

policies were already in place during the 

baseline period, any effects on employment 

and earnings are captured in the baseline 

trends. Since the comparison PHAs were 

selected largely based on the similarity of 

those trends, this fact should not undermine 

the validity of including these PHAs in the 

comparison group.

Exhibit 2.10 presents baseline characteristics 

for households and individuals in SCCHA 

and the three selected comparison PHAs in 

40 A more detailed set of baseline characteristics are presented in appendix exhibits C.1-C.3.

early July 2013, just before the rent reform 

was implemented.40 It shows that households 

in both groups have on average two adults, 

with more than one-half having more than one 

adult in the household, and 65 percent in both 

groups have children in the household. About 

62 percent of study households in SCCHA 

and 60 percent in comparison PHAs have at 

least one household member who is working. 

In both groups, 23 percent of households are 

receiving TANF.

The two groups are also quite similar at the 

individual level. The second panel in exhibit 

2.10 presents the baseline characteristics of 

nonelderly, nondisabled adults in the HCV 

program in SCCHA and the comparison 

PHAs. The sample is majority female 

(64 percent in SCCHA and 66 percent in 

Exhibit 2.10 Characteristics of the Sample at Baseline (Nonelderly, Nondisabled Households and Adults)

Characteristic SCCHA Comparison PHAs

Household characteristics

Average Number of Family Members

Adultsa 1.9 1.8

Children 1.4 1.3

Families with More than One Adult (%) 58.3 50.7

Families with Any Children (%) 64.7 64.6

Current/Anticipated Annual Family Income ($) 17,368 18,525

Income Sourcesb (%)

Wages 61.7 60.4

TANF 23.2 22.9

Social Security/SSI/Pension 12.8 16.5

Other Income Sources 29.1 35.5

Average Monthly Family Sharec

 ($) 523 561

Average Monthly Housing Subsidyd ($) 1,397 1,244

Monthly Gross Rent Exceeds Payment Standard (%) 53.2 56.7

Neighborhood Poverty Ratee

 (%)

0%–10% 41.5 41.8

11%–20% 40.1 47.2

21%–30% 14.3 8.1

More than 30% 4.1 3.0

Household Sample Size (Total = 15,499) 7,111 8,388

(continued)

Chapter 2. Research Design
33

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 2. Research Design

comparison PHAs) and the average age 

is about 36 years old in SCCHA and 35 in 

comparison PHAs. Forty-one percent of 

adults in both groups were working during 

the last month of the baseline period, and 12 

percent in both groups were receiving TANF. 

Average annual earnings were higher in the 

comparison PHAs: $19,247 compared with 

$16,840 in SCCHA.

Although both groups are racially and 

ethnically diverse, there are differences in 

their racial and ethnic compositions. SCCHA 

has a larger Asian population (35 percent 

compared with 21 percent in the comparison 

group) and a larger Hispanic population 

(40 percent compared with 20 percent in 

the comparison group). The comparison 

group PHAs have a higher White (17 percent 

compared with 9 percent in SCCHA) and 

Black (41 percent compared with 15 percent 

in SCCHA) population. As mentioned, while 

there are some differences in racial and 

ethnic composition between SCCHA and the 

comparison group, the fact that the trends 

in employment and earnings throughout the 

4-year baseline period are similar provides 

assurance that households in both groups 

respond similarly to local economic forces 

despite these differences.

The fact that households in both groups live 

in tight housing markets is evident by their 

high level of average household subsidies: 

$1,397 monthly for SCCHA households 

and $1,244 for the comparison PHAs. Also, 

Exhibit 2.10 Characteristics of the Sample at Baseline (Nonelderly, Nondisabled Households and Adults) (continued)

Characteristic SCCHA Comparison PHAs

Adult Characteristics

Female (%) 63.9 66.3

Average Age (Years) 35.6 35.4

Race (%)

White, non-Hispanic 9.4 16.7

Black, non-Hispanic 14.7 40.6

Asian or Hawaiian or Pacific Islander, non-Hispanic 34.7 21.2

Hispanic 40.4 20.1

Other Race or More than One Race, non-Hispanic 0.8 1.4

Income Sources (%)

Wages 41.1 41.4

TANF 11.5 11.9

Social Security/SSI/Pension 1.8 4.2

Other Income Sources 14.3 21.0

Average Annual Income from Wages for Individuals with Any Wage Income ($) 16,840 19,247

Individual Sample Size (Total = 34,075) 16,133 17,942

SCCHA = Santa Clara County Housing Authority; TANF = Temporary Assistance for Needy Families; SSI = Supplementary Security Income.

a

Adults are defined as individuals age 18 and older who were not classified on the HUD-50058 form as a live-in aide.

b

Income source categories are as defined on the HUD-50058 form. Wages include one’s own business, federal wages, PHA wages, military pay, and other 

wages. Other income sources include child support, medical reimbursement, Indian trust/per capita, unemployment benefits, and other nonwage sources.

c

Family share is the family’s contribution toward the gross rent. 

d

Housing subsidy is the full subsidy amount paid by the housing agency on the household’s behalf. It includes any utility allowance payments made to the 

tenant in addition to rent paid to the owner by the housing agency.

e

Poverty rate is defined as the percentage of individuals ages 18 to 64 years whose income in the previous 12 months was below the poverty threshold.

Notes: Samples consist of households and adults that were not headed by seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences. The set of comparison group public housing agencies (PHAs) includes the Housing Authority 

of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Housing subsidy characteristics 

represent monthly averages. Utility allowance data were not available for San Mateo and are therefore not included in San Mateo’s housing subsidy measures. 

Source: MDRC calculations using HUD Public and Indian Housing Information Center and 2009–2013 American Community Survey 5-Year Estimates data
34

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

53 percent of households in SCCHA and 

57 percent in comparison PHAs have a 

gross rent that is greater than the payment 

standard. On average, households pay a 

total of $523 monthly in SCCHA and $561 

in comparison PHAs toward their housing 

costs (rent plus utilities). Only a very small 

proportion of households (4 percent in 

SCCHA and 3 percent in comparison PHAs) 

live in neighborhoods with poverty rates 

greater than 30 percent. Most households 

(82 percent in SCCHA and 89 percent in 

comparison PHAs) live in neighborhoods with 

relatively low poverty, with poverty rates of 

no more than 20 percent. 

As explained previously, the validity of the 

CITS analysis that investigates the impact 

of the rent reform on employment and 

earnings is not based on how similar the 

comparison group is to the intervention 

group, but on the level of confidence that 

the comparison group PHAs are subject 

to the same labor and market forces, and 

generally respond similarly to such changes. 

The baseline trends in employment and 

earnings presented in exhibits 2.7 and 2.8 

provide a reasonable level of confidence 

that subsidy recipients in each of the two 

groups respond similarly to changing 

economic conditions. Even so, it is useful 

to note that the study households in the 

comparison PHAs are quite similar to the 

study households in SCCHA. 

Chapter 2. Research Design
35

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 3. Findings

Chapter 3

Findings

This chapter presents the study’s findings 

on the effects of the SCCHA rent reform 

on subsidy recipients’ employment rates, 

average earnings, average housing subsidy 

amounts, and continued housing subsidy 

receipt. This chapter also presents findings 

from the descriptive analysis of rent burden 

and households’ housing decisions following 

the rent reform. Findings are presented 

first for the full cohort of nonelderly, 

nondisabled households and individuals in 

the HCV program at the time of the SCCHA 

rent reform in 2013, and then presented 

separately for households that were affected 

by both the tenant contribution rate increase 

and the voucher size policy change and 

households that were affected by the tenant 

contribution rate alone. In sum, there was no 

evidence of effects of the SCCHA rent reform 

on overall employment rates or average 

earnings for the full cohort, but there was 

some indication that the SCCHA rent reform 

reduced earnings for the smaller group of 

households who were affected by both 

policy changes. The analysis found evidence 

that the SCCHA rent reform did decrease 

average housing subsidies (as intended). 

There was no indication that the rent reform, 

on average, caused households to leave 

housing assistance.

Impacts on Employment and 

Earnings

This section presents findings from the CITS 

analysis on the effects of the SCCHA rent 

reform on employment and earnings for the 

cohort of nondisabled, nonelderly adults 

in the HCV program in July 2013, when the 

SCCHA rent reform was implemented. As 

described in the “Data Sources” section in 

chapter 2, UI data were used to construct 

the employment and earnings measures 

for this analysis. Given that the SCCHA rent 

reform meets the conditions needed for a 

CITS analysis (described in the “Analytic 

Approach” section in chapter 2), this method 

provides rigorous evidence of the effects 

of the SCCHA rent reform on residents’ 

employment rates and average earnings over 

the followup period. 

As described in chapter 2, the CITS design 

tests whether the SCCHA rent reform caused 

a deviation from the predicted baseline trend 

in employment rates and average earnings 

for the nonelderly, nondisabled adults in 

the SCCHA HCV program. Exhibits 3.1 to 

3.6 graphically illustrate this analysis. To 

estimate effects of the SCCHA rent reform 

on employment, the first step in the CITS 

analysis was to use the observed quarterly 

employment rate of the adults in the SCCHA 

sample (the solid line in exhibit 3.1) over the 

4-year baseline period before the SCCHA 

rent reform—shown by the solid vertical 

line—to measure the employment rate trend 

over those 4 years, which is shown by the 

dotted line over the same baseline period. 

This baseline trend was used to extrapolate 

what employment rates would have looked 

like for this SCCHA sample in the absence 

of the 2013 rent reform (by extrapolating 

this trend into the future), as shown with 

the dotted line continuing throughout the 

4-year followup period. The second step of 

the analysis was to measure the quarterly 

employment rates after the SCCHA rent 

reform (the solid line) to estimate whether 

there was a deviation from this baseline 

trend, indicated by the distance between 

the solid line during the followup period 

and the dotted line during the followup 

period. Visually, this gap indicates that 

employment rates were slightly higher than 

the trend would predict in the first 2 years of 

implementing the new SCCHA rent policies, 

and then somewhat lower.
36

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

A parallel analysis was then conducted for 

the comparison group sample, illustrated 

in exhibit 3.2. The deviation of the actual 

employment rates from the predicted 

employment rates over the followup 

period looks similar to the deviation for 

SCCHA in exhibit 3.1. The final step of the 

analysis was to test whether the deviation 

35

40

45

50

55

60

65

30

Employment Rate (%)

Relative Quarter

-16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16

SCCHA Trend SCCHA Predicted Trend

Intervention (July 1, 2013)

Exhibit 3.1 Quarterly Employment Rates for Nonelderly, Nondisabled Adults in the Santa Clara County Housing Authority

35

40

45

50

55

60

65

30

Employment Rate (%)

Relative Quarter

-16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16

Comparison Trend Comparison Predicted Trend

Intervention (July 1, 2013)

Exhibit 3.2 Quarterly Employment Rates for Nonelderly, Nondisabled Adults in the Comparison Group Housing Authoritites

Notes: Samples consist of adults who were not seniors or adults with disabilities. The set of comparison group public housing agencies includes the Housing 

Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Impacts were estimated 

using a comparative interrupted time series model.

Source: California Employment Development Department individual-level aggregate unemployment insurance data

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of adults who were not seniors or adults with disabilities. Impacts were estimated using a comparative interrupted time series model.

Source: California Employment Development Department individual-level aggregate unemployment insurance data

Chapter 3. Findings
37

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 3. Findings

in the employment rates for SCCHA was 

statistically discernible from the deviation 

for the comparison group PHAs. In other 

words, the differences in the deviations were 

examined. Exhibit 3.3 overlays the graphs 

for the SCCHA and comparison groups. 

Exhibit 3.4 to 3.6 illustrate the same CITS 

analysis for average earnings. The difference 

35

40

45

50

55

60

65

30

Employment Rate (%)

Relative Quarter

-16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16

Intervention (July 1, 2013)

Comparison Trend Comparison Predicted Trend

SCCHA Trend SCCHA Predicted Trend

Exhibit 3.3 Quarterly Employment Rates for Nonelderly, Nondisabled Adults in the Santa Clara County and Comparison Group 

Housing Authorities

2000

2500

3000

3500

4000

4500

5000

1000

Average Earnings ($)

Relative Quarter

-16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16

SCCHA Trend SCCHA Predicted Trend

Intervention (July 1, 2013)

1500

Exhibit 3.4 Average Quarterly Earnings of Nonelderly, Nondisabled Adults in the Santa Clara County Housing Authority

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of adults who were not seniors or adults with disabilities. Impacts were estimated using a comparative interrupted time series model.

Source: California Employment Development Department individual-level aggregate unemployment insurance data

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of adults who were not seniors or adults with disabilities. The set of comparison group public housing agencies includes the 

Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Impacts were 

estimated using a comparative interrupted time series model.

Source: California Employment Development Department individual-level aggregate unemployment insurance data
38

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

2000

2500

3000

3500

4000

4500

5000

1000

Average Earnings ($)

Relative Quarter

-16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16

Comparison Trend Comparison Predicted Trend

Intervention (July 1, 2013)

1500

Average Earnings ($)

Relative Quarter

Intervention (July 1, 2013)

2000

2500

3000

3500

4000

4500

5000

1000

-16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16

1500

Comparison Trend Comparison Predicted Trend

SCCHA Trend SCCHA Predicted Trend

Exhibit 3.5 Average Quarterly Earnings of Nonelderly, Nondisabled Adults in the Comparison Group Housing Authorities

Exhibit 3.6 Average Quarterly Earnings of Nonelderly, Nondisabled Adults in the Santa Clara County Housing Authority and 

the Comparison Group Housing Authorities

Notes: Samples consist of adults who were not seniors or adults with disabilities. The set of comparison group public housing agencies includes the Housing 

Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Impacts were estimated 

using a comparative interrupted time series model.

Source: California Employment Development Department individual-level aggregate unemployment insurance data

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of adults who were not seniors or adults with disabilities. The set of comparison group public housing agencies includes the 

Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Impacts were 

estimated using a comparative interrupted time series model.

Source: California Employment Development Department individual-level aggregate unemployment insurance data

Chapter 3. Findings
39

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 3. Findings

between the gaps for the two groups was 

not statistically significant for either the 

employment rate or average earnings 

outcome throughout the followup period.

Exhibit 3.7 presents the estimated effects 

of the SCCHA rent reform on average 

employment rates and average annual 

earnings for adults for each year of 

the followup period.41 Yearly effects on 

employment rates for each year in the 

followup period were calculated by averaging 

the quarterly employment rate impact 

estimates across the four quarters in each 

followup year. Yearly effects on average 

earnings were calculated by summing 

quarterly earnings impact estimates across 

the four quarters in each followup year. 

Standard errors were computed accordingly. 

The first column of results in exhibit 3.7 

labeled “SCCHA Mean” represents the 

average outcome for the study cohort in 

SCCHA. For example, the average quarterly 

employment rate in Year 1 (which is an 

average of the quarterly employment rate 

41 See appendix exhibits D.1 and D.2 for estimated quarterly impacts on employment rates and average earnings.

for each of the four quarters in Year 1) is 

50.8 percent. In other words, in Year 1, 

50.8 percent of the SCCHA households 

had some earnings in a given quarter, on 

average, in Year 1. The second column labeled 

“Impact” represents the estimated impact 

of the SCCHA rent reform. For example, the 

50.8-percent employment rate observed for 

SCCHA is estimated to be 0.5 percentage 

point lower than what it would have been 

in the absence of the SCCHA rent reform.

This impact estimate is an estimate of the 

true effect, which is unknown. The third 

column labeled “Std. Error” presents the 

standard error of the impact estimate, which 

measures the uncertainty which exists about 

its corresponding impact estimate. The final 

column reports the p-value of the impact 

estimate, which represents the likelihood that 

an estimated effect at least as large as the 

one observed would have occurred by chance 

if there was no true effect. In this example, 

the p-value of 0.604 means that if there were 

no true effects of the SCCHA rent reform on 

the average quarterly employment rate in 

Year 1, then there would be a 60.4-percent 

Exhibit 3.7 Impacts on Average Quarterly Employment Rate and Annual Earnings of Nonelderly, Nondisabled Adults

Outcome SCCHA Mean Estimated Effect Std. Error P-Value

Employment Rate

Year 1 50.8 -0.5 0.9 0.604

Year 2 54.5 0.0 1.2 0.972

Year 3 56.6 0.1 1.5 0.929

Year 4 57.5 0.1 1.8 0.941

Earnings

Year 1 11,187 46 349 0.897

Year 2 13,549 143 474 0.763

Year 3 16,198 200 597 0.738

Year 4 18,538 509 725 0.484

Sample Size 34,075

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of adults who were not seniors or adults with disabilities. The set of comparison group public housing agencies includes the 

San Mateo County Housing Authority, the San Francisco Housing Authority, and the Alameda County Housing Authority. Effects were estimated using 

a comparative interrupted time series model. All estimated earnings effects are reported in 2017 dollars. The p-value indicates the likelihood that the 

estimated impact (or larger) would have been generated by an intervention with zero true effect. Statistical significance levels are indicated as: *** = 1 

percent; ** = 5 percent; * = 10 percent.

Source: California Employment Development Department individual-level aggregate unemployment insurance data
40

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

chance that an estimated effect of at least 0.5 

percentage point would be observed. P-values 

are marked with one or more asterisks if the 

impact estimate is statistically significant, and 

the number of asterisks corresponds with 

the level of statistical significance. (Exhibit 

3.7 doesn’t contain any asterisks because 

none of the impact estimates are statistically 

significant.) One asterisk signifies that the 

probability is 10 percent or less; two asterisks 

signify that the probability is 5 percent or 

less; and three asterisks signifies that the 

probability is 1 percent or less.

The results show no evidence of effects on 

the percentage of nonelderly, nondisabled 

adults who are employed or on their 

average earnings across the 4 years of 

followup. The estimated effects on both 

outcomes are small and not statistically 

significant. For example, in the first year 

after the rent reform, the estimated impact 

on average earnings was $46, but this 

difference was not statistically significant. 

This estimate could be interpreted to mean 

that the SCCHA average quarterly earnings 

of $11,187 for this first followup year was 

$46 higher than it would have been in the 

absence of the rent reform. The magnitude 

of the effect is very small, however, and the 

standard error and p-values are very large, 

suggesting that this small difference is very 

likely due to chance. In other words, there 

is no evidence that the SCCHA rent reform 

caused a deviation from its predicted 

average earnings trend in the first year 

after the rent reform was implemented that 

was appreciably different from deviation 

from the predicted average earnings 

trend for the comparison group during the 

same time period, where no rent reform 

was implemented. As exhibits 3.1 to 3.6 

illustrate, employment rates and average 

earnings increased steadily throughout the 

4 years following the SCCHA rent reform 

for both SCCHA and comparison group 

subsidy recipients.

Impacts on Housing Subsidies

The SCCHA rent reform intended to directly 

decrease the average household HAP by 

increasing the tenant contribution rate 

from 30 percent of adjusted income to 35 

percent of gross income and eliminating 

utility allowances for all households, and 

by reducing the voucher sizes for a smaller 

percentage of households (23 percent) by 

applying a new voucher size policy. This 

part of the analysis examines whether the 

rent reform did in fact decrease average 

household HAP, and whether HAP remained 

lower over time. If households had reduced 

their earnings in response to the rent 

reform (there was no evidence they did 

so, as discussed in the previous section), 

the SCCHA HAP savings would have been 

smaller than what it had projected. The 

analysis also tested whether the SCCHA 

rent reform increased the rate of households 

leaving the HCV program. As discussed 

earlier, the rent reform could have caused 

attrition from the HCV program if it drove 

some households’ HAPs down to zero, 

reduced subsidies to the extent that some 

households decided the subsidy no longer 

justified the burden of complying with 

program rules, or increased household rent 

burden to a level that was not sustainable 

for households.

This section describes the results of the 

autoregressive difference-in-difference 

analysis (described in chapter 2) used to 

estimate effects of the SCCHA rent reform 

on average housing subsidy amounts and 

on the percent of households leaving the 

subsidy program. As described earlier, the 

results using this method are less rigorous 

than those produced using a CITS design, 

because while this method accounts for 

pre-rent reform differences in the levels

of the outcome, if the underlying baseline 

trends in housing outcomes are different 

for the treatment and comparison groups, 

Chapter 3. Findings
41

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

it is possible that a difference detected at 

followup is attributable to those differing 

trends rather than being a true effect of the 

SCCHA rent reform. It is also possible that 

differing baseline trends could mask a true 

effect when none has been detected.

Exhibit 3.8 presents the estimated 

effects of the SCCHA rent reform on the 

average amount of housing subsidy and 

the percentage of households receiving 

any housing subsidy at followup using 

difference-in-difference estimation, which 

compares the change in each outcome 

between the time period prior to the SCCHA 

rent reform and the outcome at each 

year following the rent reform for SCCHA 

households compared with households in 

the comparison PHAs, where no rent reform 

was implemented at the time. The findings 

in this exhibit can be interpreted in the same 

way as described in the previous section 

for exhibit 3.7. Because the research design 

used to estimate impacts for exhibit 3.8 is 

42 This first-year impact estimate does not account for the households that were granted a 90-day hardship exemption that allowed them to deduct 

medical and childcare expenses from their gross income for their temporary HAP calculation. A total of 414 households were granted a hardship 

exemption, but this total includes elderly and disabled households. SCCHA did not retain data on the elderly and disabled status of these households, 

so the precise number of households in the study’s nonelderly, nondisabled sample is unknown.

weaker than that used to estimate impacts 

for exhibit 3.7, however, one can place less 

confidence in the estimates for exhibit 3.8. 

The average household housing subsidy 

in the month before the implementation 

of the rent reform was $16,764 per year, 

or $1,397 per month (as shown in exhibit 

2.10). As expected, the SCCHA rent reform 

reduced the average amount of housing 

subsidy that households received. This 

effect is probably a direct result of the 

increase in the tenant contribution rate 

from 30 percent of adjusted income to 

35 percent of gross income and the other 

policy changes implemented as part of 

the rent reform, which resulted in the PHA 

paying less of a subsidy on behalf of each 

household. In the first year, the average 

annual household subsidy was estimated to 

be $1,593 less than it would have been in 

the absence of the rent reform. This annual 

effect is equivalent to $133 monthly.42 In 

the second year after the rent reform was 

Chapter 3. Findings

Exhibit 3.8 Impacts on Housing Subsidies (Nonelderly, Nondisabled Households)

Outcome SCCHA Mean Estimated Effect Std. Error P-Value

Total Annual Housing Subsidy ($)

Year 1 14,335 -1,593 65 0.000***

Year 2 13,414 -1,548 99 0.000***

Year 3 13,481 -1,329 123 0.000***

Receipt of Housing Subsidy (%)

Year 1 99.2 0.5 0.2 0.013** 

Year 2 92.9 -0.4 0.5 0.368

Year 3 87.5 -0.9 0.6 0.137

Sample (Total = 15,490) 7,109

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of households that were not headed by seniors or adults with disabilities. The set of comparison group public housing agencies 

(PHAs) includes the Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of 

Alameda. Sample sizes may vary because of missing values. Effects were estimated using an autoregressive difference-in-differences model, controlling 

for the past receipt of housing subsidies and other baseline characteristics of sample households. To assess differences between the research groups, 

chi-square tests were used for categorical variables and two-tailed t-tests were used for continuous variables. The p-value indicates the likelihood that 

the estimated impact (or larger) would have been generated by an intervention with zero true effect. Statistical significance levels are indicated as: *** = 

1 percent; ** = 5 percent; * = 10 percent. Utility allowance data were not available for San Mateo and are therefore not included in San Mateo’s housing 

subsidy measures.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
42

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

implemented, when the tenant contribution 

rate was reduced to 32 percent, the 

effect was slightly smaller: the average 

monthly household subsidy was $1,548 

less annually, or $129 less monthly, than it 

would have been in the absence of the rent 

reform. In the third year, the rent reform 

reduced annual HAP by $1,329 and monthly 

HAP by $111.43,44,45

The bottom panel of exhibit 3.8 presents 

the estimated effects of the rent reform 

on whether households are still receiving 

subsidies at followup.46 Overall, there is 

no clear evidence that the SCCHA rent 

reform had an effect on the percentage 

of nonelderly, nondisabled households 

that lost their subsidies. There was a small 

(0.5 percentage points) but statistically 

significant increase (0.5 percentage 

point) in the percentage of households 

continuing to receive subsidies in the first 

year of followup, but this effect is probably 

inconsequential because of its small 

magnitude and the fact that it disappears 

after the first year.47 (This 0.5 percentage 

point impact estimate can be interpreted 

to mean that 99.2 percent of the cohort 

of households who were receiving HCV 

subsidies from SCCHA when the rent 

reform was implemented in July 2013 still 

received subsidies during the first year after 

the rent reform was implemented, which is 

0.5 of a percentage point more than what 

43 The effect continues to decrease in the fourth year, though this finding is likely due to the data limitation for Year 4 housing data described in the “Data 

Sources” section of chapter 2. 44 The sensitivity test described in chapter 2 that estimated these effects including imputed utility allowances for the HACSM produced very similar 

results. Impact estimates on average housing subsidies were somewhat smaller than these main findings but were still large and had the same level of 

statistical significance. 45 Results from a sensitivity test that estimated effects on HAP using utility allowance imputations for HACSM in the HAP calculations had very similar 

results. 46 Any household that is receiving a HAP amount greater than zero (in any PHA) is counted as still receiving a subsidy at that time. If a household’s income 

increases to the threshold where its HAP amount is zero because its calculated TTP is greater than the gross rent, the household has a grace period 

of 180 days during which it is still considered active in the program. If the household income drops during this period, TTP can be recalculated and 

the subsidy can resume; otherwise, the household’s participation is terminated from the HCV program and the household would have to go back on 

the waiting list to rejoin if its situation changes. Households that leave the HCV program are included in the average with a subsidy amount of $0. If 10 

percent of the sample left the HCV program and the PHA replaced them all with new households, the subsidy receipt rate for the group would be 90 

percent (not 100 percent). 47 The statistical significance for an impact estimate of such a small magnitude reflects the high precision that exists when the mean of a binary outcome 

variable is near zero or one. 48 It also remained true 4 years after the rent reform was implemented. While the data limitations with the Year 4 IMS/PIC data would have affected 

measures of average subsidy amounts more than the measures of any subsidy receipt, the overall data limitations also reduce the reliability of this 

Year 4 impact estimate. 49 As a sensitivity test, logistic regressions were run to estimate effects on this dichotomous outcome. The results were very similar. 50 Results from a sensitivity test that included utility allowance imputations for HACSM in the HAP calculations were very similar in magnitude to these 

main findings except for the Year 1 impact estimate, which was smaller (but still positive) and was not statistically significant.

the percentage would have been in the 

absence of the rent reform.) Two years after 

the implementation of the rent reform there 

was no difference between the percentage 

of households in the sample receiving 

subsidies in SCCHA and the percentage 

that would have been receiving subsidies 

in the absence of the rent reform. This 

remained true 3 years after rent reform was 

implemented.48,49,50

The patterns in household housing subsidy 

outcomes over time—presented in appendix 

exhibit E.1—align with expectations based 

on the nature and timing of the rent reform. 

The average household TTP and family 

share (TTP plus the amount by which a 

household’s gross rent exceeds the payment 

standard) increased more steeply than they 

did for comparison group PHAs when the 

tenant contribution rate changed from 30 

percent of adjusted income to 35 percent 

of gross income in the first year of the rent 

reform. The increase was tempered in the 

second year when the tenant contribution 

rate was reduced to 32 percent of gross 

income. As expected, the household HAP—

which is directly related to the TTP in that 

a household’s HAP decreases by the same 

amount that the TTP increases—mirrors 

these patterns in TTP and family share. 

Housing market trends are also reflected 

in these patterns of housing subsidy 

outcomes: housing prices were steeply 

Chapter 3. Findings
43

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 3. Findings

increasing during the followup period, so 

there is a general upward trend in subsidies 

independent of any policy change (across 

both SCCHA and comparison PHAs) as 

payment standards increased in response.

Households’ Housing 

Decisions and Rent Burden

The findings discussed so far show that 

SCCHA rent reform did not have an overall 

effect on tenants’ employment and earnings, 

and that it did lead to deep and lasting 

cuts in housing subsidies as intended. This 

section explores measures of households’ 

housing characteristics over time to gain 

further insight into how households may have 

responded to the SCCHA rent reform, and to 

describe households’ levels of rent burden in 

the years following the rent reform. The rent 

reform could have encouraged households to 

seek other, less expensive housing, possibly 

with fewer bedrooms or in higher poverty 

neighborhoods in some cases, or to transfer 

to an area in the jurisdiction of a different 

PHA that still used traditional rent rules. 

These types of housing decisions would 

have tempered the increase in households’ 

rent burden resulting from the reduction in 

housing subsidies.

As described in the “Analytic Approach” 

section in chapter 2, the findings in this 

section should be interpreted with a great 

deal of caution. The exhibits in this section 

present average housing outcomes over time, 

and causal inferences should not be drawn 

from this descriptive analysis. For example, 

as described in chapter 2, a stark difference 

in the average level of a housing outcome 

(like a neighborhood poverty rate) following 

the SCCHA rent reform compared with the 

average level before the rent reform—if this 

difference does not exist for the comparison 

group—may suggest that the rent reform 

51 See appendix exhibit F.1 for details.

led to that difference. Nonetheless, such 

an observed difference does not by itself 

warrant a definitive conclusion that the 

SCCHA rent reform caused that difference. 

Comparison group levels are presented to 

provide context for the SCCHA findings. 

Households’ Housing Decisions While 

in the Voucher Program

The patterns in measures related to 

households’ housing decisions throughout 

the followup period give no obvious 

indication that households are, on average, 

relocating to poorer quality neighborhoods, 

moving to smaller units, moving to units 

outside the jurisdiction of SCCHA, or 

changing their household composition.51

There was a general upward trend in 

households’ neighborhood poverty rate 

over the followup period, suggesting that 

households that moved tended to move to 

poorer neighborhoods, but this trend also 

existed for households in the comparison 

group PHAs. The SCCHA households’ 

average number of bedrooms dropped 

only slightly, from 2.7 to 2.6 bedrooms. (The 

comparison group’s average number of 

bedrooms remained constant throughout 

the followup period.) There is also no 

strong indication that a significant portion 

of households changed their household 

composition by adding or removing 

household members in response to the rent 

reform. Household size decreased slightly 

over the followup period, but a similar 

trend is evident for the comparison group 

households. Last, there is no indication that a 

large portion of households chose to relocate 

to a unit outside the jurisdiction of SCCHA 

to avoid the higher out-of-pocket housing 

costs (defined as “porting out”); SCCHA had 

a lower rate of port-outs than the comparison 

group PHAs throughout the study period.
44

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Household Rent Burden While in the 

Voucher Program

The lack of effects on employment and 

earnings discussed earlier in this chapter 

means that households were not increasing 

their incomes to cover their greater tenant 

rent share due to the rent reform. These 

findings suggest that households were 

absorbing their increased housing costs into 

their current budgets, either by reducing 

spending or incurring debt. Considering 

material hardship is therefore an important 

part of understanding the effects of a rent 

reform that increases the tenant contribution 

rate toward rent, but material hardship is 

only partially measured in this study. This 

section looks at patterns of a measure of 

rent burden over the study period to better 

understand the extent to which households’ 

rent burdens increased after the rent reform 

was implemented.

As described in the “Data Sources” section of 

chapter 2, the present study uses a measure 

52 Appendix exhibit F.2 presents alternative measures of rent burden, including average, median, and distributions of rent burden in the last month of 

baseline and of each followup year.

of rent burden that is the tenant rent share 

(equal to the TTP plus any amount that the 

contract rent, not including tenant-paid 

utilities) as a proportion of the household’s 

gross income. Exhibit 3.9 shows patterns in 

this measure of households’ rent burden from 

the last month of the baseline period (before 

the rent reform was implemented) through 

the 4 years of followup.52 In the month before 

SCCHA’s rent reform was implemented, 

the percentage of nonelderly, nondisabled 

households whose tenant rent share 

exceeded 40 percent of their gross income 

looked fairly similar to the percentage for the 

comparison group households; 12 percent in 

SCCHA and 14 percent in comparison PHAs 

were paying more than 40 percent of their 

gross income toward rent. In the first year 

following the implementation of the SCCHA 

rent reform, the percentage of households in 

SCCHA paying more than 40 percent of their 

income toward rent increased steeply from 12 

percent to 30 percent, compared with a three 

percentage points increase for households 

Exhibit 3.9 Tenant Rent Share as a Percent of Monthly Gross Income Among Nonelderly, Nondisabled Households 

Receiving Subsidies

Outcome SCCHA Comparison PHAs

Tenant Rent Share Exceeds 40% of Monthly Gross Income (%)

Last Month of Baseline 12.3 14.0

Last Month of Year 1 30.1 17.4

Last Month of Year 2 30.5 14.2

Last Month of Year 3 19.4 11.2

Tenant Rent Share Exceeds 50% of Monthly Gross Income (%)

Last Month of Baseline 8.9 9.6

Last Month of Year 1 21.4 11.9

Last Month of Year 2 21.9 9.3

Last Month of Year 3 13.9 7.7

Sample Size (Total = 15,490) 7,109 8,381

PHA = public housing agency. SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. The set of comparison group PHAs includes the 

Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Sample sizes 

may vary because of missing values. Outcomes shown describe only those households receiving any housing subsidies in the specified month. Utility 

allowance data were not available for San Mateo and are therefore not included in San Mateo’s housing subsidy measures.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data

Chapter 3. Findings
45

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 3. Findings

in comparison group PHAs. These patterns 

largely held up during the second year; the 

differences declined in the third. That decline 

may not necessarily reflect a true decline in 

this measure of rent burden, if it was at least 

in part due to households with an extreme 

rent burden leaving the subsidy program 

(voluntarily or through eviction) and therefore 

not being counted in the averages.53

Subgroup Findings

As described earlier, SCCHA implemented 

a new voucher size policy that enforced 

a minimum of two family members per 

bedroom, excluding the head of household’s 

bedroom. Before this policy change, the 

age, generation, gender, and relationship of 

other household members were considered 

when determining voucher size. The group of 

households in SCCHA that were immediately 

affected by this change constituted 

approximately 23 percent of the nonelderly, 

nondisabled voucher population. This section 

presents the findings of a subgroup analysis 

of the effects on earnings and employment 

and describes housing characteristics and 

rent burden separately for the households 

only affected by the tenant rent contribution 

increase (referred to as the “single policy 

change” subgroup) and households affected 

by the voucher policy change in addition to 

the tenant contribution rate increase (referred 

to as the “double policy change” subgroup).

As described in the “Research Questions” 

section of chapter 2, all households in both 

subgroups were affected by the tenant 

contribution rate increase; therefore, all 

households faced the potential earnings and 

employment incentives and disincentives 

described in that section for the full sample, 

and all households whose rent exceeded 

53 As described in chapter 2, this study focused on nonelderly, nondisabled households and individuals in the HCV program. Although it was not feasible 

to conduct an impact analysis for the cohort of elderly and disabled households and individuals in the HCV program due to the data limitations 

described in chapter 2, the measure of tenant rent share as a percent of gross income was available for this cohort. Appendix Table F.3 presents the 

rent burden measures for the cohort of elderly and disabled households and shows similar patterns as the nonelderly, nondisabled sample, though the 

increases in the percent of gross income these households pay toward rent are not as steep.

the payment standard faced some incentive 

to move to a less expensive unit. It is 

possible, however that the rent reform’s 

effects on employment and earnings for the 

subgroup of households affected only by the 

tenant contribution rate increase may have 

differed from the effects for the subgroup of 

households affected by both policy changes. 

Households also affected by the voucher 

size rule change might have stayed in their 

current units and faced much steeper out-ofpocket housing costs because they had to 

fully cover the difference between the new 

lower payment standard and the previous 

one, or they might have moved to a smaller 

unit whose gross rent exceeded the area 

payment standard by a larger amount than 

their previous larger unit. For these reasons, 

households in the double policy change 

subgroup could have had stronger incentives 

to change their employment behavior in 

addition to stronger incentives to move to a 

new unit. Furthermore, if double policy change 

households who did not move to smaller units 

were unable to afford their much higher rent 

shares, and this hardship led them to leave 

the subsidy program (either by voluntarily 

moving to a more affordable housing situation, 

like moving in with other family members, or 

through eviction), the turmoil of their housing 

situation may also have affected households’ 

employment and earnings.

The single policy change subgroup differed 

from the double policy change subgroup 

in some important ways. It is important to 

keep this in mind when interpreting the 

subgroup findings, as differences in effects 

between the two subgroups may not be 

entirely due to being differentially affected 

by just the tenant contribution rate versus 

both policy changes but may also reflect 

how different types of households respond 
46

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

to the policy changes. Exhibit 3.10 presents 

characteristics of households just before 

SCCHA implemented its rent reform for 

the single policy change and double policy 

change subgroups separately. As expected, 

households that were directly affected by the 

voucher size rule change tended to be larger 

and have more children than households 

that were only affected by the tenant 

contribution rate change. In SCCHA, the 

average number of household members is 

3.7 for this subgroup (compared with 3.2 for 

the single policy change subgroup), and 77 

percent of households in the double policy 

change group in SCCHA included children, 

compared with 61 percent in the single 

policy change subgroup. A slightly larger 

proportion of households in the double 

policy change subgroup in SCCHA had at 

54 See appendix G for more detailed exhibits of baseline characteristics of households in each of these subgroups.

least one adult working at baseline than 

among the single policy change subgroup: 

65 percent compared with 61 percent. The 

double policy change subgroup also had a 

higher level of out-of-pocket housing costs 

($574 monthly) than the single policy change 

subgroup ($508 monthly) and a larger 

average subsidy ($1,711 per month compared 

with $1,304).54

Subgroup Impacts on Employment 

and Earnings

The estimated effects of the SCCHA rent 

reform on employment rates and average 

earnings for the subgroup of individuals 

living in households that were affected only 

by the tenant contribution rate increase (the 

“single policy change” subgroup) were very 

Exhibit 3.10 Characteristics of the Sample at Baseline by Policy Group (Nonelderly, Nondisabled SCCHA Households and Adults)

Characteristic Single Policy Change Double Policy Change

Household Characteristics

Average Number of Family Members

Adultsa 1.8 2.2

Children 1.4 1.5

Families with More than One Adult (%) 53.6 74.1

Families with Any Children (%) 61.2 76.7

Current/Anticipated Annual Family Income ($) 16,511 20,247

Income Sourcesb (%)

Wages 60.7 65.2

Temporary Assistance for Needy Families (TANF) 22.6 25.4

Social Security/SSI/Pension 11.2 18.0

Other Income Sources 28.1 32.4

Average Monthly Family Sharec

 ($) 508 574

Average Monthly Housing Subsidyd ($) 1,304 1,711

Monthly Gross Rent Exceeds Payment Standard (%) 53.5 52.0

Neighborhood Poverty Ratee

 (%)

0%–10% 39.0 50.1

11%–20% 41.1 36.8

21%–30% 15.5 10.4

More than 30% 4.4 2.7

Household Sample Size (Total = 6,725) 5,183 1,542

(continued) 

Chapter 3. Findings
47

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 3. Findings

similar to the impact estimates for the full 

sample: there is no suggestion of positive 

or negative effects on employment rates or 

average earnings for this subgroup. This is 

unsurprising given that these households 

constitute 77 percent of the full study 

sample. As exhibit 3.11 shows, households 

affected by the change in the voucher size 

policy in addition to the tenant contribution 

rate increase (the “double policy change” 

subgroup)—the remaining 23 percent of 

the full study sample—showed a pattern of 

negative estimated effects on employment 

rates, but these estimates were not 

statistically significant. They were also not 

statistically significantly different from those 

for the single policy change subgroup. 

The impact estimates in the “single policy 

change” panel and the “double policy 

change” panel of exhibit 3.11 represent 

impact estimates using a CITS analysis 

for each subgroup separately and can be 

interpreted in the same way as the impact 

estimates in exhibit 3.7. Exhibit 3.11 contains 

an additional column labeled “Difference 

Between Groups.” This column presents the 

results of the statistical comparison between 

the difference in the impact estimates 

Exhibit 3.10 Characteristics of the Sample at Baseline by Policy Group (Nonelderly, Nondisabled SCCHA Households and Adults) 

(continued) 

Characteristic Single Policy Change Double Policy Change

Adult Characteristics

Female (%) 63.8 64.6

Average Age (Years) 36.0 34.5

Race (%)

White, non-Hispanic 9.7 8.5

Black, non-Hispanic 15.3 14.0

Asian or Hawaiian or Pacific Islander, non-Hispanic 33.1 37.6

Hispanic 41.0 39.1

Other Race or More than One Race, non-Hispanic 0.8 0.8

Income Sources (%)

Wages 41.1 41.2

TANF 11.6 11.1

Social Security/SSI/Pension 1.9 1.3

Other Income Sources 14.5 13.7

Average Annual Income from Wages for Individuals with 

Any Wage Income ($)

16,676 17,273

Individual Sample Size (Total = 15,131) 10,974 4,157

SCCHA = Santa Clara County Housing Authority. SSI = Supplementary Security Income. 

a

Adults are defined as individuals age 18 and older who were not classified on the HUD-50058 form as a live-in aide.

b

Income source categories are as defined on the HUD-50058 form. Wages include one's own business, federal wages, public housing agency (PHA) 

wages, military pay, and other wages. Other income sources include child support, medical reimbursement, Indian trust/per capita, unemployment benefits, 

and other nonwage sources.

c

Family share is the family's contribution toward the gross rent. 

d

Housing subsidy is the full subsidy amount paid by the housing agency on the household’s behalf. It includes any utility allowance payments made to the 

tenant in addition to rent paid to the owner by the housing agency.

e

Poverty rate is defined as the percentage of individuals ages 18 to 64 years whose income in the previous 12 months was below the poverty threshold.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences. The set of comparison group PHAs includes the Housing Authority of the County of 

San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Housing subsidy characteristics represent monthly 

averages. Utility allowance data were not available for San Mateo and are therefore not included in San Mateo's housing subsidy measures.

Source: MDRC calculations using HUD Public and Indian Housing Information Center and 2009–2013 American Community Survey 5-year estimates data
48

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

between the two subgroups. The numbers 

in the column represent the p-values, and 

the daggers represent the levels of statistical 

significance of the estimate of the difference 

in impacts.

The estimated impacts on average earnings 

by subgroup in exhibit 3.11 suggest that 

the SCCHA rent reform also did not affect 

average earnings for the households 

affected only by the tenant contribution rate 

increase. The impact estimates are small 

and not statistically significant. There is 

some evidence, however, that the household 

members also affected by the voucher 

size rule change may have reduced their 

earnings in response to the rent reform. 

For this double policy change subgroup, 

average annual earnings were estimated to 

be lower in the first 2 years after the rent 

reform was implemented than they would 

have been in the absence of the rent reform, 

though these estimated effects were not 

statistically significant from zero. By the third 

year, SCCHA residents in this subgroup 

were earning $2,220 less annually on 

average than they would have been in the 

absence of the rent reform, and this effect 

was sustained in the fourth year (when the 

estimated decrease was $2,341). These 

third- and fourth-year effects are statistically 

significant at the 0.05 level. They are also 

statistically significantly different from the 

impact estimates for the single policy change 

subgroup at the 0.05 level.

As exhibits 3.1 to 3.6 from the full sample 

analysis illustrated, employment rates 

and average earnings increased over the 

followup period for both SCCHA and the 

comparison group. In the context of these 

earnings trends, an estimated negative effect 

on average earnings means that although 

average earnings did increase over time 

for SCCHA subsidy residents, they did not 

increase as quickly or as much as they would 

Exhibit 3.11 Impacts on Average Quarterly Employment Rate and Annual Earnings by Policy Change Subgroup for Nonelderly, 

Nondisabled Households

Single Policy Change Group Double Policy Change Group

Outcome SCCHA 

Mean

Estimated 

Effect

Std. 

Error

P-Value SCCHA 

Mean

Estimated 

Effect

Std. 

Error

P-Value Difference 

Between Groups

Employment Rate

Year 1 49.9 -0.2 1.4 0.881 51.0 -1.3 1.3 0.323 0.573

Year 2 53.1 -0.2 1.9 0.907 54.6 -1.7 1.7 0.322 0.560

Year 3 54.9 -0.6 2.4 0.801 56.4 -3.5 2.2 0.112 0.374

Year 4 55.6 -0.4 2.9 0.886 57.7 -4.2 2.6 0.112 0.334

Earnings

Year 1 11,223 111 496 0.824 11,572 -663 521 0.208 0.284

Year 2 13,206 212 674 0.755 13,761 -960 695 0.172 0.228

Year 3 15,618 223 859 0.796 16,206 -2,220 875 0.014** 0.048††

Year 4 17,606 736 1,046 0.484 18,487 -2,341 1,058 0.031** 0.041††

Sample Size 12,439 4,438

SCCHA = Santa Clara County Housing Authority. 

Notes: The comparison group public housing agency in this exhibit is the San Francisco Housing Authority. Effects were estimated using a comparative 

interrupted time series model. All estimated earnings effects are reported in 2017 dollars. The p-value indicates the likelihood that the estimated impact 

(or larger) would have been generated by an intervention with zero true effect. Statistical significance levels are indicated as: *** = 1 percent; ** = 5 percent; 

* = 10 percent. A two-tailed t-test was applied to differences between the outcomes of the policy subgroups. Statistical significance levels for differences 

across subgroup impacts are indicated as: ††† = 1 percent; †† = 5 percent; † = 10 percent.

Source: California Employment Development Department household-level aggregate unemployment insurance data

Chapter 3. Findings
49

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 3. Findings

have in the absence of the rent reform. 

An estimated negative effect on average 

earnings could be caused either by some 

SCCHA residents reducing their employment 

in response to the rent reform, or by some 

SCCHA residents not obtaining employment 

or not increasing their hours or wages 

because of the rent reform. 

This negative effect of the rent reform 

on average earnings for the households 

affected by both the tenant contribution 

rate change and the voucher size rule 

change seems at least partly due to the 

decrease in employment rates that the 

impact estimates (though not statistically 

significant) on employment rates suggest. 

The negative effect on employment and 

earnings for this subset of the sample did not 

occur immediately after the rent reform was 

implemented, suggesting that residents did 

not reduce their employment right away. 

An exploratory analysis examined whether 

these employment and earnings effects may 

also be related to the double policy change 

households’ housing experiences following 

the rent reform. As described in the “Analytic 

Approach” section of chapter 2, using the 

difference-in-difference approach with a 

reduced comparison group (described in 

the “Sample” section of the same chapter) 

for the subgroup analysis does not allow 

for reliably estimating effects on housing 

subsidy outcomes for the single and double 

policy change subgroups separately, but 

the exploratory analysis overcomes much 

of these limitations. The difference-indifference-in-difference method used for 

this analysis is described in the “Analytic 

Approach” section of chapter 2. Because 

these analyses are considered exploratory, 

the results for this analysis are presented in 

the appendix exhibit G.7. The column labeled 

“Difference Between Subgroup Impacts” 

can be interpreted as the difference in 

impact estimates (the double policy change 

subgroup impact estimate minus the single 

policy change subgroup impact estimate). 

The column to the right of that column 

contains their p-values, which are marked 

with daggers to indicate the level of statistical 

significance.

The findings of this analysis do suggest 

that the households in the double policy 

change subgroup experienced much 

larger reductions in HAP than the single 

policy change group. Households in 

the double policy change subgroup 

experienced reductions in subsidies that 

were more than $4,000 larger than the 

single policy change group in the first 

2 years following the rent reform, and 

this difference declined somewhat in the 

third year. These differences in effects on 

average HAP are statistically significant at 

the 0.01 significance level. The differential 

effects on continued subsidy receipt are 

not statistically significant between the 

two groups (though approach statistical 

significance by the third year), but the 

pattern of these differential effects may 

suggest that the SCCHA rent reform led 

a small percentage of households in the 

double policy change group to leave the 

subsidy program or lose their housing 

subsidies. The timing of these estimated 

impacts on continued subsidy receipt 

align with the timing of the estimated 

negative impacts on employment and 

earnings for this double policy change 

subgroup, suggesting that they may be 

related. The patterns in housing subsidies 

for each of the subgroups (in relation to 

their corresponding comparison groups) 

aligns with these suggestive findings. HAP 

decreased significantly more, and tenant 

rent share increased significantly more for 

the double policy change subgroup than 

for the single policy change subgroup. 

By the third year after the SCCHA rent 

reform was implemented, 86 percent of 

SCCHA households in the double policy 
50

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

change subgroup were still receiving 

subsidies compared with 91 percent in the 

comparison group.55

Households’ Housing Decisions and 

Rent Burden While in the Voucher 

Program by Subgroup

Households affected by only the tenant 

contribution rate increase may have had 

an incentive to move to a more affordable 

unit (whose contract rent exceeds the 

payment standard by a lesser amount than 

their current unit) to offset increases in 

housing costs. In addition to this incentive, 

households affected by the voucher size 

rule change in addition to the tenant 

contribution rate increase also have a very 

strong incentive to relocate to smaller units 

to avoid the steeper out-of-pocket housing 

cost they would have faced if they remained 

in their units.

Especially in a tight housing market, finding a 

unit that is affordable may require moving to 

a more affordable neighborhood. The trend 

among both single policy change households 

and double policy change households looks 

similar to each other: a slight increase in 

neighborhood poverty over the 3 years 

following the SCCHA rent reform that mirrors 

the full sample results. Similar to the full 

sample findings, the differences between 

each subgroup of SCCHA households and 

their corresponding comparison group 

households (whose trends fluctuates only 

slightly) are not stark, and it is impossible 

to draw any conclusion about effects from 

these purely descriptive data. The trends in 

number of bedrooms over time suggest more 

strongly that households in the double policy 

change group moved to smaller units, with 

households’ average unit size dropping from 

3.4 to 3.2 bedrooms in the first year after the 

SCCHA rent reform was implemented, and 

55 See appendix exhibits G.8 and G.9 for more details. 56 See appendix exhibits G.10 and G.11 for details.

then continuing to drop to 3.1 bedrooms by 

the end of the third year, compared with the 

comparison group, whose average remains 

steady at 3.1 starting before the SCCHA rent 

reform was implemented and remaining at 

3.1 throughout the 3 years following the rent 

reform. For the single policy change group, 

the number of bedrooms remains steady 

both for SCCHA and comparison group 

households. There is no apparent pattern 

of households changing their household 

composition following the policy changes for 

either subgroup.56

One particularly striking pattern is that the 

double policy change households’ tenant 

rent share (as measured by TTP plus the 

amount that the contract rent exceeds the 

payment standard) increased very steeply 

in the year following implementation of the 

rent reform for households continuing to 

receive subsidies compared with the single 

policy change subgroup. Tenants’ rent 

shares increased slightly in the comparison 

groups for both the single policy change 

households and the double policy change 

households. The SCCHA households’ 

tenant rent share in the single policy 

change subgroup increased from $447 

to $529 between the month before the 

SCCHA rent reform and 1 year later (which 

was a larger increase than the single policy 

change comparison group, as expected.) 

In contrast, the SCCHA households’ tenant 

rent share in the double policy change 

subgroup rose from $511 per month just 

before the implementation of the rent 

reform to $810 per month 1 year later. (Only 

a tiny fraction of households in the double 

policy change subgroup—0.3 percent—

stopped receiving housing subsidies 

between these two time points, so these 

averages are a relatively reliable measure 

of the sample’s housing costs.) Tenant rent 

shares did decrease in subsequent years 

Chapter 3. Findings
51

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 3. Findings

(in part because of the reduction in tenant 

share from 35 percent to 32 percent of 

gross income), but they remained high. 

This might suggest that while many double 

policy change subgroup households moved 

to smaller units, many other households 

stayed in place and paid the much higher 

housing costs as a result.

The increase in tenant rent share for double 

policy change households from $511 to $810 

per month is quite large for this subset of 

SCCHA households, which have an average 

household income of $1,687 per month. 

This apparent hardship is explored more 

formally in exhibit 3.12, which presents 

a measure of households’ rent burden 

(defined in the present study as the tenant 

rent share as a percentage of gross income) 

just before the SCCHA implementation 

of the rent reform and throughout the 

followup period.57 The levels of average 

tenant rent share as a percentage of gross 

income demonstrate that this subset of 

households experienced very high levels 

of housing-related hardship after the rent 

reform was implemented. Just before the 

57 Additional measures of rent burden are presented in appendix exhibits G.12 and G.13.

rent reform was implemented, just 6 percent 

of these households had tenant rent shares 

that exceeded 40 percent of their gross 

income. The percentage jumped to 61 

percent 1 year after the rent reform was first 

implemented. (In contrast, this percentage 

only increased from 15 percent to 21 percent 

for single policy change households.) This 

percentage then decreased over the rest 

of the followup period, to 50 percent by 

the end of the second year and 33 percent 

by the end of the third. This decrease 

reflects the tenant contribution rate being 

reduced from 35 percent to 32 percent 

of gross income in the second year of its 

implementation, but may also reflect the 

fact that some households may have moved 

to smaller or more affordable units after 

the end of the first year, or that households 

with the highest levels of rent burden may 

have left the subsidy program following the 

rent reform. It is notable that the downward 

trend in the percentage of households 

exceeding this 40-percent threshold also 

decreased for the comparison group (SFHA) 

in this subsample, possibly also because of 

Exhibit 3.12 Tenant Rent Share as a Percent of Monthly Gross Income Among Nonelderly, Nondisabled Households Receiving 

Subsidies, by Policy Subgroup in Santa Clara County Housing Authority

Outcome Single Policy Change Double Policy Change

Tenant Rent Share Exceeds 40% of Monthly Gross Income (%)

Last Month of Baseline 14.9 5.8

Last Month of Year 1 21.4 60.5

Last Month of Year 2 24.5 50.2

Last Month of Year 3 15.6 32.9

Tenant Rent Share Exceeds 50% of Monthly Gross Income (%)

Last Month of Baseline 10.9 4.1

Last Month of Year 1 14.0 47.3

Last Month of Year 2 16.8 38.7

Last Month of Year 3 10.9 25.0

Sample Size (Total = 6,723) 5,181 1,542

SCCHA = Santa Clara County Housing Authority.

Notes: Sample sizes may vary because of missing values. Outcomes shown describe only those households receiving any housing subsidies in the 

specified month.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
52

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

the changing composition of households 

continuing to receive subsidies over time. 

The same pattern is evident using a higher 

threshold. The percentage of households in 

the single policy change subgroup paying 

over one-half of their gross incomes toward 

rent rose only slightly from 11 to 14 percent, 

but for households in the double policy 

subgroup, this percentage rose steeply 

from 4 percent just before the start of 

implementation to 47 percent 1 year later.

Chapter 3. Findings
53

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 4. Discussion

Chapter 4

Discussion

This chapter summarizes the study’s 

findings and discusses their implications. It 

also discusses the study’s limitations and 

next steps for future research in the area of 

rent reform.

Discussion of Findings

In response to federal budget reductions in 

2013, SCCHA implemented a rent reform that 

increased the tenant contribution rate for 

all households from 30 percent of adjusted 

income to 35 percent of unadjusted income 

and changed voucher size rules for these 

households. A central question of the present 

study is how the rent reform implemented by 

SCCHA affected households’ employment 

and earnings. As discussed earlier in the 

“Research Questions” section of chapter 

2, there were three such possible effects 

of the rent reform: (1) The increased tenant 

contribution rate would act as a disincentive 

that would cause households to decrease 

their earnings, (2) households would 

increase earnings to cover their increased 

housing costs, or (3) there would be no 

effect on earnings or employment because 

households would adjust spending in other 

areas to cover their higher housing costs, 

increase their debt, or experience increased 

material hardship.

The present study found no evidence that 

these policy changes had any effects, on 

average, with respect to the employment 

and earnings of nonelderly, nondisabled 

SCCHA residents. The absence of an overall 

reduction in household earnings meant that 

SCCHA was able to realize its projected 

HAP savings. (If there were to have been a 

reduction in household earnings, it would 

have led to an increase in HAP amounts, 

counteracting the intended savings from 

the increase in the tenant contribution 

rate.) Nonelderly, nondisabled households 

received approximately $1,600 less in 

housing subsidies, on average, during the 

first year, $1,550 less in the second, and 

$1,330 less in the third year after the rent 

reform than they would have received 

without the rent reform. There was also 

no evidence that the rent reform caused 

households to lose their housing subsidies.

There are two factors specific to the SCCHA 

context that might have strengthened any 

incentive inherent in the rent reform’s policy 

change to increase their employment and 

earnings. First, Santa Clara County and 

its surrounding counties had a robust job 

market during the study period. It is worth 

noting that even in this job market with many 

employment opportunities, households did 

not increase their employment or earnings in 

response to an increased tenant contribution 

rate. Second, SCCHA has a 24-month 

recertification period, which is longer than 

the typical 12-month recertification period 

used in traditional PHAs. SCCHA households 

that were considering increasing their 

income in response to the rent reform (to 

compensate for lost net income) may have 

had a stronger incentive to do so than 

they would have in a PHA with a 12-month 

recertification period. If positive effects 

had been estimated on employment and 

earnings, these two factors would have 

needed to be taken into consideration when 

interpreting results. With no evidence of 

effects on employment and earnings, it is 

unknown whether this potential incentive 

may have been a factor in balancing out a 

disincentive to earn more.

The combination of findings that overall 

the SCCHA rent reform did not increase 

residents’ average earnings levels and that 

it did, as intended, reduce households’ 

housing subsidies means that households 
54

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

experienced reductions in their net income. 

For households that did not increase their 

income over time, these reductions in 

net income could have been persistent. 

Households who did increase their income 

over time would have experienced smaller 

increases in net income compared with the 

increases they would have experienced 

in the absence of the rent reform. This 

interpretation is consistent with SCCHA 

leadership’s impression that voucher 

households generally did not change their 

employment behavior but instead absorbed 

their increased housing costs. This study 

did not include measures of households’ 

material hardship beyond a measure of rent 

burden, and therefore cannot assess how 

this increase in rent burden translated into 

their experiences with material hardship. 

It is an important consideration, however, 

because increased housing costs for 

households without increased income 

to cover those costs could mean that 

households are reducing spending on other 

necessary goods and services, which may 

lead to increased material hardship, or are 

increasing their debt.

One study—the Rent Reform demonstration—

that is currently underway in four PHAs can 

provide some context for potential effects 

on households’ material hardship. A baseline 

survey of the households participating in the 

demonstration—a population comparable to 

the sample for the present study, consisting 

of nonelderly, nondisabled households in the 

Housing Choice Voucher (HCV) program—

revealed that even households receiving 

housing subsidies under traditional rent rules 

commonly experience material hardship: 

almost 70 percent of survey respondents 

said they had experienced at least one form 

of material hardship during the last year. 

Forty-six percent said they were not able 

to pay a utility bill, 34 percent said they 

were not able to pay a telephone bill, and 

20 percent said they were not able to pay 

the (subsidized) rent in at least one month 

of the past year. Furthermore, 28 percent 

said they were not able to buy food and 23 

percent said they were not able to see a 

doctor or buy prescription drugs they needed 

during at least one month in the past year 

(Riccio, Deitch, and Verma, 2017). Given that 

HCV households in SCCHA were likely to 

be experiencing similar material hardship 

before the rent reform, there is a risk that the 

increase in housing costs and consequent 

decrease in net income caused by the rent 

reform may have worsened such hardship.

A subgroup analysis explored how the 

SCCHA rent reform may have affected 

households subject to only the change in 

the tenant contribution rate differently from 

households who were also affected by the 

voucher size rule change. Like the findings 

for the full sample, there was no evidence 

that the rent reform had any effects on 

employment or earnings for the subgroup 

only affected by the tenant contribution rate 

change. There was, however, some evidence 

that the SCCHA rent reform reduced 

earnings for the subgroup of households 

that was affected by both policy changes. 

These households experienced particularly 

high levels of rent burden following the 

rent reform (measured as the tenant rent 

share as a proportion of household gross 

income). The negative effect on earnings 

for this subgroup did not occur immediately 

after the rent reform was implemented, 

suggesting that residents did not reduce 

their employment right away, but perhaps 

struggled with their increased housing 

costs before reducing their earnings. 

An exploratory analysis shows that, as 

expected, the SCCHA rent reform led to 

especially deep cuts in housing subsidies 

for this double policy change subgroup. 

To the extent that the steep increases 

in households’ housing costs led some 

households to leave the subsidy program 

(of which there is only suggestive evidence), 

Chapter 4. Discussion
55

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 4. Discussion

this housing instability might partially 

explain the employment and earnings 

effects for this subgroup of households, if 

having to relocate to a new unit or leave the 

subsidy program destabilized a person’s 

employment situation. The true drivers 

of these delayed negative effects on 

household earnings for this subgroup cannot 

be definitively explained within the scope of 

the present study.

These findings hint at some potential 

consequences of implementing a voucher 

size policy that causes steep increases in 

households’ housing costs if they don’t 

move to a smaller unit. The scarcity of 

affordable housing in Santa Clara meant 

that households had fewer options for less 

expensive units. Although the trends in the 

average number of bedrooms over time 

suggest that some households in this group 

did move to smaller units, it is likely that many 

were unable to, or that if they did, those 

units may not have been as affordable as 

their previous units.58 In a location with more 

affordable housing options, it is possible that 

households that have to move to a smaller 

unit may have an easier time doing so. 

SCCHA provided crucial safeguards for 

these households by partnering with local 

organizations to provide legal and financial 

assistance to prevent eviction. It is important 

for any PHA that implements a rent reform 

to identify the households that might be 

most adversely affected by the policy 

changes and provide them with adequate 

protections from severe hardship. This study 

provides evidence that can help inform that 

assessment for other PHAs considering these 

changes to the rent policy. For example, 

the SCCHA eviction prevention assistance 

program (SEPP) provided an important 

support that likely helped many households 

avoid eviction during the time that it was 

58 A new unit with fewer bedrooms under the new policy could be less affordable than the former unit with more bedrooms if the new unit’s gross rent 

exceeded the payment standard for the smaller voucher size more than the former unit’s gross rent exceeded the payment standard for the larger 

voucher size.

being operated. An attorney working in 

the program (and now a staff member of 

SCCHA) recalled that of the 293 households 

that SEPP assisted, only two cases at most 

resulted in an actual eviction. Other PHAs 

considering a similar policy change in a 

similar context (where finding an affordable 

smaller unit may be difficult) might consider 

that households who are vulnerable to 

adverse effects because of the policy 

change may greatly benefit from an effective 

safeguard such as the SEPP program that is 

offered over an extended period of time. 

Study Limitations

Findings from this study contribute to the 

emerging body of evidence on how changing 

the rent policy for households receiving 

housing assistance can affect employment 

and earnings. Still, the study has some 

limitations that should be kept in mind 

when interpreting the results. An important 

limitation, as discussed earlier, is that aspects 

of material hardship beyond rent burden, 

such as food insecurity and difficulty covering 

medical expenses or rent and utilities, are 

not measured in this study. A full assessment 

of the implications of increasing the tenant 

contribution rate—or any other rent reform 

that effectively reduces housing subsidy 

levels—should consider the effects on the 

level of material hardship that households 

experience in response to the policy change.

Another limitation is that the study does 

not examine how the effects of the rent 

reform may vary for different types of 

individuals and households. It includes a 

subgroup analysis that compares effects 

for households only affected by the tenant 

contribution rate and households affected 

by both policies, but there may be other 

sources of variation that the study was not 

able to explore. It is possible, for example, 
56

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

that nonelderly, nondisabled adults who were 

already working at the time the SCCHA rent 

reform was implemented would have more 

flexibility than those who were not employed 

to increase or reduce their employment and 

earnings in response to the increased tenant 

contribution rate. Nonelderly, nondisabled 

individuals who are not yet working may have 

less of an incentive to begin a new job with 

the higher tenant contribution rate. The study 

was not able to estimate effects separately 

for these subgroups due to data limitations.

The primary analytic method in this study is 

a rigorous one: a CITS to examine the effects 

of the SCCHA rent reform on employment 

and earnings. As described in chapter 2, the 

rent reform meets important conditions for 

CITS in that it was a consequential change 

that occurred for the full study cohort all 

at once, and there were data available for 

a comparison group that was subject to 

the same economic forces as SCCHA. As 

noted in the Analytic Approach section of 

chapter 2, it was not feasible to use CITS 

to examine effects on households’ average 

housing subsidies or continued subsidy 

receipt because 4 years of historical housing 

subsidy data were not available for the full 

study sample and therefore baseline trends 

could not be estimated for these measures. 

The autoregressive difference-in-difference 

design used to study effects of the rent reform 

on these outcomes is not as rigorous as CITS 

because it does not account for potentially 

differing baseline trends in housing subsidy 

measures. Furthermore, it was not feasible to 

use either CITS or autoregressive differencein-difference to examine effects on housing 

characteristics (including number of bedrooms 

in the unit or neighborhood poverty) or 

household composition, because these data 

were not available for households that were 

no longer receiving subsidies. The descriptive 

analysis used to explore these outcomes can 

only provide suggestive evidence of potential 

effects on these outcomes. 

This analysis relies on UI wage data to assess 

effects on employment and earnings, and 

these data do not capture earnings from 

employment that is not covered by UI. While 

there is no strong reason to believe that the 

SCCHA rent reform would have affected 

informal employment differently from formal 

employment, this study cannot formally test 

that assumption. It is possible, however, that 

the increased rent contribution rate could 

strengthen the incentive to underreport 

earnings to the PHA, and underreporting 

would be easier with informal employment, 

especially if the worker is not paying taxes on 

the earnings.

Finally, the present study focused on only 

one PHA in one location, Santa Clara County, 

that has a tighter housing market and a more 

robust job market than most of the country, 

though there are many PHAs in comparable 

situations—such as PHAs in New York 

City, Boston, Los Angeles, Seattle, Denver, 

Washington, and San Diego—serving large 

numbers of households. These findings 

provide an important contribution to the 

literature on the effects of rent reform on 

labor market outcomes; still, the estimated 

effects should not be interpreted as effects 

that one should necessarily expect if this 

rent reform were implemented elsewhere. 

Additional studies in multiple locations with 

diverse contexts are needed to draw more 

broadly applicable conclusions.

Conclusion

The present study of the effects of a rent 

reform implemented by SCCHA provides 

evidence, from one location, that a public 

housing agency can increase the tenant 

contribution rate by a moderate amount (30 

percent of adjusted income to 35 percent 

of gross income, later to 32 percent of 

gross income) without creating a substantial 

disincentive to work and without significantly 

increasing the likelihood that households 

Chapter 4. Discussion
57

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Chapter 4. Discussion

may lose their subsidies. It also provides 

suggestive evidence that implementing 

a voucher size policy that requires some 

households to relocate to a different unit 

(with fewer bedrooms) to avoid even deeper 

cuts in housing subsidies may have adverse 

effects on some households in the context of 

a housing market where affordable housing 

options are very limited, and that short-term 

safeguards that PHAs provide to households 

may not fully prevent longer term hardship. 

The results of this study should not be 

interpreted as conclusive evidence of 

expected effects in any context, given that 

the study focuses on only one location. 

Further research is needed in multiple 

locations that represent diverse housing 

markets and labor markets to examine 

how the effects of this type of rent reform 

may be expected to vary based on the 

context. Studies with a random assignment 

design would help overcome many of the 

methodological limitations of this study 

described above, for example, by providing 

a reliable counterfactual for outcomes where 

multiple years of pre-intervention data are 

not available for the full sample. Finally, future 

studies of rent reforms that might result in 

reduced housing subsidies for households 

should carefully measure households’ 

experiences with material hardship, including 

food insecurity and their ability to cover 

medical expenses, in response to the rent 

reform. Nevertheless, the present study 

begins to address one aspect of housing 

subsidy policy—how increasing the tenant 

contribution rate affects households’ 

employment, earnings, and housing 

subsidies—where strong evidence is lacking.
58

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform
59

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix A

Model Specifications

Comparative Interrupted Time Series 

Model

The following comparative interrupted time series (CITS) model 

was used to estimate effects on quarterly employment rates 

and average quarterly earnings:

Where:

Yi = the value of the outcome variable for observation i, where 

observation i is defined as the value of the outcome variable for 

PHA p in quarter q,

PHA = a series of four indicator variables, one for each PHA p,

α = a series of four intercepts for baseline trends, one for each 

PHA p,

Q = the quarter (a continuous variable),

β0 = a series of coefficients representing the slope of the 

baseline trend for each of the four PHAs,

F = an indicator value for followup quarter f,

β1

 = a series of coefficients representing the comparison group 

deviation from its baseline trend for each followup quarter f,

S = 1 if the PHA is SCCHA (the treatment group) and 0 

otherwise,

β2 = a series of coefficients representing the treatmentcomparison group difference between their deviations from 

their baseline trends for each followup quarter f, and

e = a random error term.

59 The background household characteristics included in the model as covariates include: the head of household’s gender, age, race and ethnicity, and 

receipt of wage, Temporary Assistance for Needy Families (TANF), or Social Security/Supplementary Security Income/Pension (SSIP) income; number 

of adults in a household; age of the youngest child; annual household wage earnings; monthly family share; and whether the household’s monthly 

gross rent exceeds the payment standard.

Autoregressive Difference-inDifference Model

The following autoregressive difference-in-difference (DinD) 

model was used to estimate effects on housing subsidy outcomes:

Where:

Yh = the value of the outcome variable for sample household h,

α = the intercept, representing the conditional mean outcome 

for the three comparison PHAs combined,

S = 1 if household h was in SCCHA (the treatment group) at the 

time of the rent reform and 0 otherwise,

β1

 = estimate of the effect of the SCCHA rent reform on outcome Y, 

Ybh = a set of four variables representing the lagged value of the 

outcome variable Y for the four baseline years prior to the rent 

reform for household h

β2 = a series of four regression coefficients, one for each of the 

four variables representing the lagged values of the outcome 

for the four baseline years prior to the rent reform,

R = a set of four variables representing whether the household 

received any subsidies in each of the four baseline years prior 

to the rent reform,

β3

 = a series of four regression coefficients for the four baseline 

years’ indicators of any housing subsidy receipt,

X = a set of background characteristics for household h,

59

β4

 = the set of regression coefficients for the background characteristics,

e = a random error term.

Appendix A

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform 75

Autoregressive Difference-in-Difference Model

The following autoregressive difference-in-difference (DinD) model was used to estimate effects on 

housing subsidy outcomes:

Y9 = α + /*:9 + % /5;

<(

;) <*

Y;9 + % /=;

<(

; ) <*

R;9 + % /(

?

@)*

X@9 + 89

Where:

Y9 = the value of the outcome variable for sample household h, 

α = the intercept, representing the conditional mean outcome for the three comparison PHAs 

combined,

S = 1 if household h was in SCCHA (the treatment group) at the time of the rent reform and 0 

otherwise,

β1 = estimate of the effect of the SCCHA rent reform on outcome Y, 

Y;9 = a set of four variables representing the lagged value of the outcome variable Y for the four 

baseline years prior to the rent reform for household h 

β2 = a series of four regression coefficients, one for each of the four variables representing the 

lagged values of the outcome for the four baseline years prior to the rent reform,

R = a set of four variables representing whether the household received any subsidies in each of 

the four baseline years prior to the rent reform,

β3 = a series of four regression coefficients for the four baseline years’ indicators of any housing 

subsidy receipt,

X = a set of background characteristics for household h,

59 

β4 = the set of regression coefficients for the background characteristics,

e = a random error term.

59 The background household characteristics included in the model as covariates include: the head of household’s

gender, age, race and ethnicity, and receipt of wage, Temporary Assistance for Needy Families (TANF), or Social 

Security/Supplementary Security Income/Pension (SSIP) income; number of adults in a household; age of the 

youngest child; annual household wage earnings; monthly family share; and whether the household’s monthly gross 

rent exceeds the payment standard.

70 Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix A

Model Specifications

Comparative Interrupted Time Series Model

The following comparative interrupted time series (CITS) model was used to estimate effects on quarterly 

employment rates and average quarterly earnings: 

Y" = %α'

(

')*

PHA'" + %/0'

(

')*

PHA'"Q" + %/*2

*3

2)*

F2" + %/52

*3

2)*

F2" ∗ S" + 8"

Where:

Y" = the value of the outcome variable for observation i, where observation i is defined as the value of the 

outcome variable for PHA p in quarter q, 

PHA = a series of four indicator variables, one for each PHA p,

α = a series of four intercepts for baseline trends, one for each PHA p, 

Q = the quarter (a continuous variable), 

β0 = a series of coefficients representing the slope of the baseline trend for each of the four PHAs,

F = an indicator value for followup quarter f, 

β1 = a series of coefficients representing the comparison group deviation from its baseline trend for each 

followup quarter f,

S = 1 if the PHA is SCCHA (the treatment group) and 0 otherwise,

β2 = a series of coefficients representing the treatment-comparison group difference between their 

deviations from their baseline trends for each followup quarter f, and

e = a random error term.
60

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform
61

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix B

Supplemental Exhibits for Comparison Group Selection

Exhibit B.1 Local Labor and Housing Market Conditions, Bay Area Counties

Characteristic Alameda County Contra Costa 

County

Marin County Napa County San Francisco 

County

Total 

population (%) 1,510,271 1,049,025 252,409 136,484 805,235

White 33.7 47.2 72.7 55.8 41.7

Black 11.8 8.8 2.6 2.0 5.6

Asian 26.6 14.5 5.6 6.9 33.1

Hispanic 22.5 24.5 15.5 32.6 15.2

Median household 

rent ($) 1,289 1,365 1,628 1,350 1,488

Median household 

income ($) 72,112 78,756 90,839 70,443 75,604

Persons with 

income below the 

poverty level (%)

12.5 10.5 7.7 10.1 13.5

Bachelor’s 

degree 

attained (%)

41.8 39.0 54.6 31.3 52.4

Unemployment in 

2012 (%)

8.7 8.9 6.3 8.4 6.8

Unemployment in 

2013 (%)

7.2 7.5 5.2 6.9 5.5

Unemployment in 

2014 (%)

5.8 6.2 4.3 5.7 4.4

Unemployment in 

2015 (%)

4.7 5.0 3.5 4.6 3.6

Unemployment in 

2016 (%)

4.2 4.4 3.2 4.3 3.3

Population density 

(per sq. mi) 2,043.6 1,465.2 485.1 182.4 17,179.2

Housing unit 

density (per sq. mi) 788.3 559.1 213.7 73.2 8,041.8

Rental vacancy 

rate (%) 4.3 5.2 3.4 6.4 3.7

(continued)

Appendix B
62

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix B

Exhibit B.1 Local Labor and Housing Market Conditions, Bay Area Counties (continued)

Characteristic San Joaquin 

County

San Mateo 

County

Santa Clara 

County

Santa Cruz 

County

Solano County Sonoma County

Total 

population (%) 685,306 718,451 1,781,642 262,382 413,344 483,878

White 35.4 41.9 34.7 59.2 40.5 65.8

Black 6.8 2.5 2.4 0.9 13.7 1.4

Asian 14.0 25.1 32.3 4.1 14.3 3.9

Hispanic 39.3 25.3 26.8 32.4 24.5 25.2

Median 

household rent 

($)

1,026 1,602 1,566 1,385 1,264 1,265

Median 

household 

income ($)

53,380 88,202 91,702 66,519 67,177 63,356

Persons with 

income below 

the poverty level 

(%)

18.2 7.6 10.2 14.6 13.0 11.9

Bachelor’s 

degree 

attained (%)

18.1 44.4 46.5 37.0 24.3 32.2

Unemployment in 

2012 (%) 14.4 6.4 7.9 11.8 10.7 8.9

Unemployment in 

2013 (%) 12.3 5.3 6.5 10.3 9.1 7.1

Unemployment in 

2014 (%) 10.5 4.2 5.2 8.8 7.5 5.6

Unemployment in 

2015 (%) 8.9 3.4 4.2 7.5 6.1 4.5

Unemployment in 

2016 (%) 8.1 3.0 3.8 5.3 5.3 3.8

Population 

density (per sq. 

mi)

492.6 1,602.2 1,381.0 589.4 503.0 307.1

Housing unit 

density (per sq. 

mi)

168.0 604.4 489.8 234.7 185.8 129.8

Rental vacancy 

rate (%) 6.3 3.1 3.1 4.0 6.8 4.8

Note: No PHAs are located in San Benito County, so the county is not shown.

Sources: 2010 U.S. Census Bureau; 2009–2013 American Community Survey 5-year estimates; California Employment Development Department monthly 

labor force data for counties (2012–2016)
63

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Employment Rate

Quarter

Santa Clara

County HA

City of

Alameda HA

City of

Oakland HA

Alameda

County HA

City of

0% Berkeley HA

10%

20%

30%

40%

50%

60%

Q3/09

Q4/09

Q1/10

Q2/10

Q3/10

Q4/10

Q1/11

Q2/11

Q3/11

Q4/11

Q1/12

Q2/12

Q3/12

Q4/12

Q1/13

Q2/13

$0

$500

$1,000

$1,500

$2,000

$2,500

Average Earnings

Q3/09

Q4/09

Q1/10

Q2/10

Q3/10

Q4/10Q1/11

Q2/11

Q3/11

Q4/11

Q1/12

Q2/12

Q3/12

Q4/12

Q1/13

Q2/13

Quarter

Santa Clara

County HA

City of

Alameda HA

City of

Oakland HA

Alameda

County HA

City of

Berkeley HA

Exhibit B.2 Baseline Trends in Quarterly Employment Rates of Nonelderly, Nondisabled Adults in the Santa Clara and Alameda 

County Comparison Candidate Housing Agencies

Exhibit B.3 Baseline Trends in Average Quarterly Earnings for Nonelderly, Nondisabled Adults in the Santa Clara and Alameda 

County Comparison Candidate Housing Agencies

Note: Samples consists of adults who were not seniors or adults with disabilities in the Housing Choice Voucher program.

Source: California Employment Development Department individual-level aggregate unemployment insurance data

Notes: Samples consists of adults (who were not seniors or adults with disabilities) in the Housing Choice Voucher program. Earnings not adjusted for inflation.

Source: California Employment Development Department individual-level aggregate unemployment insurance data 

Appendix B
64

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix B

0%

10%

20%

30%

40%

50%

60%

Employment Rate

Quarter

Santa Clara

County HA

City of

Richmond HA

City of Pittsburg

HA

Contra Costa

County HA

Q3/09

Q4/09

Q1/10

Q2/10

Q3/10

Q4/10

Q1/11

Q2/11

Q3/11

Q4/11

Q1/12

Q2/12

Q3/12

Q4/12

Q1/13

Q2/13

$0

$500

$1,000

$1,500

$2,000

$2,500

Average Earnings

Quarter

Santa Clara

County HA

City of

Richmond HA

City of Pittsburg

HA

Contra Costa

County HA

Q3/09

Q4/09

Q1/10

Q2/10

Q3/10

Q4/10

Q1/11

Q2/11

Q3/11

Q4/11

Q1/12

Q2/12

Q3/12

Q4/12

Q1/13

Q2/13

Exhibit B.4 Baseline Trends in Quarterly Employment Rates of Nonelderly, Nondisabled Adults for Santa Clara and Contra 

Costa County Comparison Candidate Housing Agencies

Note: Samples consists of adults (who were not seniors or adults with disabilities) in the Housing Choice Voucher program. 

Source: California Employment Development Department individual-level aggregate unemployment insurance data

Exhibit B.5 Baseline Trends in Average Quarterly Earnings of Nonelderly, Nondisabled Adults for Santa Clara and Contra Costa 

County Comparison Candidate Housing Agencies

Notes: Samples consists of adults (who were not seniors or adults with disabilities) in the Housing Choice Voucher program. Earnings not adjusted for inflation.

Source: California Employment Development Department individual-level aggregate unemployment insurance data
65

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix B

0%

10%

20%

30%

40%

50%

60%

Employment Rate

Quarter

Santa Clara

County HA

San Mateo

County HA

San Francisco

HA

Q3/09

Q4/09

Q1/10

Q2/10

Q3/10

Q4/10

Q1/11

Q2/11

Q3/11

Q4/11

Q1/12

Q2/12

Q3/12

Q4/12

Q1/13

Q2/13

Exhibit B.6 Baseline Trends in Quarterly Employment Rates, Nonelderly, Nondisabled Adults Santa Clara, and San Mateo 

County and San Francisco County Comparison Candidate Housing Agencies

Note: Samples consists of adults (who were not seniors or adults with disabilities) in the Housing Choice Voucher program. 

Source: California Employment Development Department individual-level aggregate unemployment insurance data

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

Quarter

Santa Clara

County HA

San Mateo

County HA

San Francisco

HA

Q3/09

Q4/09

Q1/10

Q2/10

Q3/10

Q4/10

Q1/11

Q2/11

Q3/11

Q4/11

Q1/12

Q2/12

Q3/12

Q4/12

Q1/13

Q2/13

Average Earnings

Exhibit B.7 Baseline Trends in Average Quarterly Earnings, Nonelderly, Nondisabled Adults, Santa Clara, and San Mateo 

County and San Francisco County Comparison Candidate Housing Agencies 

Notes: Samples consists of adults (who were not seniors or adults with disabilities) in the Housing Choice Voucher program. Earnings not adjusted for inflation.

Source: California Employment Development Department individual-level aggregate unemployment insurance data
66

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform
67

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix C

Appendix C

Supplemental Baseline Characteristics Exhibits

Exhibit C.1 Household Composition and Income at Baseline

Characteristic SCCHA Comparison PHAs

Average Number of Family Members

Adultsa 1.9 1.8

Children 1.4 1.3

Families with More than One Adult (%) 58.3 50.7

Number of Children in Family (%)

None 35.3 35.4

1 Child 23.3 27.7

2 Children 20.3 19.7

3 or More 21.1 17.2

For Families with Children, Age of Youngest Child (%)

0–5 Years 36.6 34.9

6–12 Years 39.6 40.4

13–17 Years 23.8 24.6

Current/Anticipated Annual Family Income ($) 17,368 18,525

Current/Anticipated Annual Family Income (%)

$0 3.5 4.1

$1–4,999 16.9 12.3

$5,000–9,999 22.1 20.2

$10,000–19,999 23.4 26.6

$20,000 or More 34.0 36.9

Income sourcesb (%)

Wages 61.7 60.4

TANF 23.2 22.9

Social Security/SSI/Pension 12.8 16.5

Other Income Sources 29.1 35.5

(continued)
68

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix C

Exhibit C.1 Household Composition and Income at Baseline (continued)

Characteristic SCCHA Comparison PHAs

Average Annual Income from Wages, for Families 

with Any Wage Income ($)

22,278 24,281

Annual Income from Wages, for Families with Any Wage Income (%)

$1–4,999 11.1 6.1

$5,000–9,999 15.0 12.8

$10,000–19,999 26.9 29.1

$20,000–29,999 19.8 20.2

$30,000 or More 27.3 31.8

Sample Size (Total = 15,499) 7,111 8,388

SCCHA = Santa Clara County Housing Authority. SSI = Supplementary Security Income. TANF = Temporary Assistance for Needy Families. 

a

Adults are defined as individuals age 18 and older who were not classified on the HUD-50058 form as a live-in aide.

b

Income source categories are as defined on the HUD-50058 form. Wages include one’s own business, federal wages, PHA wages, military pay, and other 

wages. Other income sources include child support, medical reimbursement, Indian trust/per capita, unemployment benefits, and other nonwage sources.

Notes: Samples consists of households that were not headed by seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences. The set of comparison group public housing agencies (PHAs) includes the Housing 

Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
69

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit C.2 Characteristics of Adults at Baseline

Characteristic SCCHA Comparison PHAs

Female (%) 63.9 66.3

Age (%)

18–24 32.2 31.3

25–34 18.7 19.8

35–44 18.0 18.7

45 or Older 31.1 30.1

Average Age (Years) 35.6 35.4

Race (%)

White, non-Hispanic 9.4 16.7

Black, non-Hispanic 14.7 40.6

Asian or Hawaiian or Pacific Islander, 

non-Hispanic 34.7 21.2

Hispanic 40.4 20.1

Other Race or More than One Race, 

non-Hispanic 0.8 1.4

Income Sourcesa

 (%)

Wages 41.1 41.4

TANF 11.5 11.9

Social Security/SSI/Pension 1.8 4.2

Other Income Sources 14.3 21.0

Average Annual Income from Wages for 

Individuals with Any Wage Income ($) 16,840 19,247

Annual Income from Wages for Individuals with Any Wage Income ($)

$1–$4,999 19.8 9.9

$5,000–$9,999 18.7 18.9

$10,000–$19,999 27.9 32.4

$20,000–$29,999 16.7 18.3

$30,000 or More 16.9 20.4

Individual Sample Size (Total = 34,075) 16,133 17,942

SCCHA = Santa Clara County Housing Authority. SSI = Supplementary Security Income. TANF = Temporary Assistance for Needy Families. 

a

Income source categories are as defined on the HUD-50058 form. Wages include one’s own business, federal wages, PHA wages, military pay, and other wages. 

Other income sources include child support, medical reimbursement, Indian trust/per capita, unemployment benefits, and other nonwage sources. 

Notes: Samples consists of adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. Rounding may cause slight 

discrepancies in sums and differences. The set of comparison group public housing agencies (PHAs) includes the Housing Authority of the County of San Mateo, 

the San Francisco Housing Authority, and the Housing Authority of the County of Alameda.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data

Appendix C
70

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix C

Exhibit C.3 Characteristics of Households at Baseline

Characteristic SCCHA Comparison PHAs

Average Monthly Family Sharea ($) 523 561

Average Monthly Family Share (%)

$0 0.0 0.2

$1–$299 38.8 33.3

$300–$599 26.9 28.7

$600–$899 16.3 17.6

$900 or More 18.0 20.2

Family Share as a Proportion of Monthly Gross Income (%)

0%–20% 1.1 1.1

21%–30% 47.8 42.4

31%–40% 29.2 32.8

41%–50% 7.5 9.1

51% or Above 14.4 14.5

Average Monthly Housing Subsidyb ($) 1,397 1,244

Average Monthly Housing Subsidy (%)

$0–$599 5.8 9.7

$600–$899 10.0 13.6

$900–$1,199 19.1 23.7

$1,200 or More 65.0 53.0

Payment Standard Reduced with New Rulesc

 (%) 22.9 20.6

Monthly Gross Rent Exceeds Payment Standard (%) 53.2 56.7

Neighborhood Poverty Rated (%)

0%–10% 41.5 41.8

11%–20% 40.1 47.2

21%–30% 14.3 8.1

More than 30% 4.1 3.0

Sample Size (Total = 15,499) 7,111 8,388

SCCHA = Santa Clara County Housing Authority

a

Family share is the family’s contribution toward the gross rent. 

b

Housing subsidy is the full subsidy amount paid by the housing agency. It includes any utility allowance payments made to the tenant in addition to rent 

paid to the owner by the housing agency.

c

The Comparison Group value for “Payment Standard Reduced with New Rules (%)” measure is calculated for the San Francisco Housing Authority only.

d

Poverty rate is defined as the percentage of individuals ages 18 to 64 years whose income in the previous 12 months was below the poverty threshold.

Notes: Samples consists of households that were not headed by seniors or adults with disabilities. Sample sizes may vary because of missing values. The 

set of comparison group public housing agencies (PHAs) includes the Housing Authority of the County of San Mateo, the San Francisco Housing Authority, 

and the Housing Authority of the County of Alameda. Housing subsidy characteristics represent monthly averages. Utility allowance data were not available 

for San Mateo and are therefore not included in San Mateo’s housing subsidy measures. A sensitivity test that used imputed utility allowance values to 

calculate housing subsidy measures for San Mateo caused only slight change in levels.

Sources: MDRC calculations using HUD Public and Indian Housing Information Center; 2009–2013 American Community Survey 5-year estimates data
71

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix D

Appendix D

Quarterly Impacts on Employment and Earnings

Exhibit D.1 Impacts on Quarterly Employment Rates (Nonelderly, Nondisabled Adults)

Outcome SCCHA Mean Estimated Effect Std. Error P-Value

Average Year 1 50.8 -0.5 0.9 0.604

Q3 of 2013 49.9 -0.4 0.8 0.631

Q4 of 2013 51.2 -0.5 0.9 0.613

Q1 of 2014 50.2 -0.6 1.0 0.556

Q2 of 2014 51.7 -0.5 1.1 0.662

Average Year 2 54.5 0.0 1.2 0.972

Q3 of 2014 54.3 0.3 1.1 0.814

Q4 of 2014 55.3 0.5 1.2 0.704

Q1 of 2015 53.8 -0.4 1.3 0.740

Q2 of 2015 54.8 -0.1 1.3 0.933

Average Year 3 56.6 0.1 1.5 0.929

Q3 of 2015 56.3 0.2 1.4 0.885

Q4 of 2015 57.2 0.1 1.5 0.954

Q1 of 2016 56.1 0.1 1.6 0.938

Q2 of 2016 56.9 0.1 1.7 0.937

Average Year 4 57.5 0.1 1.8 0.941

Q3 of 2016 57.5 0.0 1.8 0.996

Q4 of 2016 57.8 0.0 1.8 0.992

Q1 of 2017 56.8 0.3 1.9 0.891

Q2 of 2017 57.6 0.3 2.0 0.873

Sample Size 34,075

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consists of adults who were not seniors or adults with disabilities. The set of comparison group public housing agencies includes the 

Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Effects were 

estimated using a comparative interrupted time series model. The p-value indicates the likelihood that the estimated impact (or larger) would have been 

generated by an intervention with zero true effect. Statistical significance levels are indicated as: 

*** = 1 percent; ** = 5 percent; * = 10 percent.

Source: California Employment Development Department individual-level aggregate unemployment insurance data
72

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit D.2 Impacts on Average Quarterly Earnings (Nonelderly, Nondisabled Adults)

Outcome SCCHA Mean Estimated Effects Std. Error P-Value

Year 1 11,187 46 349 0.897

Q3 of 2013 2,618 -6 77 0.936

Q4 of 2013 2,861 37 88 0.678

Q1 of 2014 2,744 -56 91 0.543

Q2 of 2014 2,963 71 98 0.472

Year 2 13,549 143 474 0.763

Q3 of 2014 3,150 51 108 0.638

Q4 of 2014 3,477 44 122 0.721

Q1 of 2015 3,338 27 124 0.830

Q2 of 2015 3,584 22 131 0.869

Year 3 16,198 200 597 0.738

Q3 of 2015 3,799 34 139 0.805

Q4 of 2015 4,259 50 145 0.733

Q1 of 2016 3,906 20 153 0.895

Q2 of 2016 4,234 95 162 0.557

Year 4 18,538 509 725 0.484

Q3 of 2016 4,591 163 169 0.338

Q4 of 2016 4,625 52 178 0.773

Q1 of 2017 4,596 173 187 0.358

Q2 of 2017 4,725 123 195 0.531

Sample Size 34,075

SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of adults who were not seniors or adults with disabilities. The set of comparison group public housing agencies includes the 

Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Impacts 

were estimated using a comparative interrupted time series model. All estimated earnings effects are reported in 2017 dollars. The p-value indicates 

the likelihood that the estimated impact (or larger) would have been generated by an intervention with zero true effect. Statistical significance levels are 

indicated as: *** = 1 percent; ** = 5 percent; * = 10 percent.

Source: California Employment Development Department individual-level aggregate unemployment insurance data

Appendix D
73

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix E

Appendix E

Supplemental Exhibits for Housing Subsidies

Exhibit E.1 Outcomes Related to Housing Assistance (Nonelderly, Nondisabled Households)

Outcome SCCHA Comparison PHAs

Received Any Housing Subsidies (%)

Baselinea 100.0 100.0

Year 1 99.2 98.3

Year 2 92.9 92.4

Year 3 87.5 86.9

Total Tenant Payment (TTP), Among Households Receiving Subsidiesb ($)

Last Month of Baseline 420 448

Last Month of Year 1 494 468

Last Month of Year 2 489 529

Last Month of Year 3 541 579

Housing Assistance Payment (HAP), Among Households Receiving Subsidiesc

 ($)

Last Month of Baseline 1,419 1,262

Last Month of Year 1 1,206 1,257

Last Month of Year 2 1,258 1,282

Last Month of Year 3 1,401 1,361

Total Tenant Rent Share, Among Households Receiving Subsidiesd ($)

Last Month of Baseline 455 471

Last Month of Year 1 590 504

Last Month of Year 2 602 553

Last Month of Year 3 611 594

Sample Size (Total = 15,490) 7,109 8,381

PHAs = public housing agencies. SCCHA = Santa Clara County Housing Authority.

a

The subsidy receipt status reported in HUD’s quarterly snapshot data files differed slightly from the status reported in HUD’s transactional data files. The 

baseline subsidy receipt status in this exhibit is based on Q2 to Q3 2013 quarterly snapshot data, while the status in the followup years are based on 

transactional data.

b

TTP is the minimum amount a family must contribute toward rent and utilities regardless of the unit selected. For MTW households, TTP has been 

calculated to reflect the minimum rents in Santa Clara and San Mateo.

c

Housing subsidy is the full subsidy amount paid by the housing agency on the household’s behalf and includes any utility allowance payments made to the 

tenant in addition to rent paid to the owner by the housing agency.

d

Total tenant rent share is the family’s contribution toward the contract rent.

Notes: Samples consist of households that were not headed by seniors or adults with disabilities. The set of comparison group PHAs includes the Housing 

Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Sample sizes may vary 

because of missing values. Outcomes shown describe only those households receiving any housing subsidies in the specified month. Utility allowance data 

were not available for San Mateo and are therefore not included in San Mateo’s housing subsidy measures. 

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
74

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform
75

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix F

Appendix F

Supplemental Exhibits for Households’ Housing Decisions

Exhibit F.1 Outcomes Related to Households’ Housing Decisions Among Nonelderly, Nondisabled Households 

Receiving Subsidies

Outcome SCCHA Comparison PHAs

Neighborhood Poverty Ratea

Last Quarter of Baseline 11.5 12.0

Last Quarter of Year 1 11.7 12.1

Last Quarter of Year 2 12.0 12.4

Last Quarter of Year 3 12.2 12.6

Number of Bedrooms

Last Month of Baseline 2.7 2.4

Last Month of Year 1 2.7 2.4

Last Month of Year 2 2.6 2.4

Last Month of Year 3 2.6 2.4

Took a Port-Out Action (%)

Baseline 1.4 2.9

Year 1 1.7 4.3

Year 2 2.0 3.2

Year 3 1.8 2.7

Household Size

Last Month of Baseline 3.3 3.1

Last Month of Year 1 3.3 3.0

Last Month of Year 2 3.3 3.0

Last Month of Year 3 3.3 3.0

Sample Size (Total = 15,490) 7,109 8,381

SCCHA = Santa Clara County Housing Authority.

a

Poverty rate is defined as the percentage of individuals ages 18 to 64 years whose income in the previous 12 months was below the poverty threshold.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. The set of comparison group public housing 

agencies (PHAs) includes the Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County 

of Alameda. Sample sizes may vary because of missing values. Outcomes shown describe only those households receiving any housing subsidies in the 

specified month.

Sources: MDRC calculations using HUD Public and Indian Housing Information Center data; American Community Survey 5-year estimates, 2007–2011 and 

2012–2016
76

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit F.2 Tenant Rent Share as a Percent of Monthly Gross Income Among Nonelderly, Nondisabled Households Receiving Subsidies

Outcome SCCHA Comparison PHAs

Median Tenant Rent Share as a Percent of Monthly Gross Income (%)

Last Month of Baseline 29.1 29.3

Last Month of Year 1 35.0 29.5

Last Month of Year 2 32.0 29.3

Last Month of Year 3 32.0 29.3

Average Tenant Rent Share as a Percent of Monthly Gross Income (%)

Last Month of Baseline 33.8 33.4

Last Month of Year 1 45.7 34.7

Last Month of Year 2 44.2 33.2

Last Month of Year 3 39.6 32.3

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Baseline (%)

0–25% 16.5 16.5

26–30% 62.6 57.2

31–35% 6.1 8.7

36–40% 3.1 4.2

41–50% 3.0 4.1

51% and Above 8.7 9.4

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 1 (%)

0–25% 0.5 15.3

26–30% 1.2 55.0

31–35% 60.0 8.9

36–40% 10.0 4.3

41–50% 7.6 5.0

51% and Above 20.7 11.5

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 2 (%)

0–25% 0.7 14.4

26–30% 2.1 62.4

31–35% 58.7 6.1

36–40% 9.7 3.6

41–50% 7.6 4.3

51% and Above 21.3 9.2

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 3 (%)

0–25% 1.0 13.5

26–30% 3.1 68.3

31–35% 71.7 4.8

36–40% 5.9 2.8

41–50% 4.8 3.1

51% and Above 13.5 7.5

Sample Size (Total = 15,490) 7,109 8,381

PHAs = public housing agencies. SCCHA = Santa Clara County Housing Authority.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. The set of comparison group PHAs includes the 

Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the Housing Authority of the County of Alameda. Sample sizes 

may vary because of missing values. Rounding may cause slight discrepancies in sums and differences. Outcomes shown describe only those households 

receiving any housing subsidies in the specified month. Utility allowance data were not available for San Mateo and are therefore not included in San Mateo’s 

housing subsidy measures.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data

Appendix F
77

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit F.3 Tenant Rent Share as a Percent of Monthly Gross Income Among Elderly and Disabled Households 

Receiving Subsidies

Outcome SCCHA Comparison PHAs

Tenant Rent Share Exceeds 40 Percent of Monthly Gross Income (%)

Last Month of Baseline 8.5 10.0

Last Month of Year 1 20.7 11.5

Last Month of Year 2 20.3 9.2

Last Month of Year 3 10.9 6.4

Tenant Rent Share Exceeds 50 Percent of Monthly Gross Income (%)

Last Month of Baseline 4.1 5.0

Last Month of Year 1 10.4 6.2

Last Month of Year 2 11.4 5.1

Last Month of Year 3 6.4 3.8

Median Tenant Rent Share as a Percent of Monthly Gross Income (%)

Last Month of Baseline 29.1 29.4

Last Month of Year 1 35.0 29.5

Last Month of Year 2 32.0 29.4

Last Month of Year 3 32.0 29.3

Average Tenant Rent Share as a Percent of Monthly Gross Income (%)

Last Month of Baseline 31.6 29.1

Last Month of Year 1 39.5 29.6

Last Month of Year 2 37.9 28.7

Last Month of Year 3 35.1 28.0

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Baseline (%)

0–25% 3.2 14.0

26–30% 75.6 62.9

31–35% 9.0 9.2

36–40% 4.1 4.5

41–50% 4.1 4.6

51% and Above 3.9 4.7

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 1 (%)

0–25% 0.1 13.6

26–30% 1.0 62.5

31–35% 68.7 8.3

36–40% 11.6 5.0

41–50% 8.9 4.7

51% and Above 9.6 5.9

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 2 (%)

0–25% 0.1 13.5

26–30% 1.8 68.8

31–35% 68.6 5.6

36–40% 10.5 3.4

41–50% 8.3 3.8

51% and Above 10.7 4.8

(continued)

Appendix F
78

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix F

Exhibit F.3 Tenant Rent Share as a Percent of Monthly Gross Income Among Elderly and Disabled Households 

Receiving Subsidies (continued)

Outcome SCCHA Comparison PHAs

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 3 (%)

0–25% 0.1 13.6

26–30% 2.5 74.1

31–35% 82.8 3.8

36–40% 4.2 2.4

41–50% 4.2 2.4

51% and Above 6.1 3.7

Sample Size (Total = 20,004) 9,410 10,594

PHAs = public housing agencies. SCCHA = Santa Clara County Housing Authority.

Notes: The set of comparison group PHAs includes the Housing Authority of the County of San Mateo, the San Francisco Housing Authority, and the 

Housing Authority of the County of Alameda. Sample sizes may vary because of missing values. Rounding may cause slight discrepancies in sums and 

differences. Outcomes shown describe only those households receiving any housing subsidies in the specified month. Utility allowance data were not 

available for San Mateo and are therefore not included in San Mateo’s housing subsidy measures. 

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
79

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Appendix G

Supplemental Exhibits for Subgroup Analysis

Exhibit G.1 Household Composition and Income at Baseline, Single Policy Change Nonelderly, Nondisabled Households

 Characteristic SCCHA SFHA

Average Number of Family Members

Adultsa 1.8 1.8

Children 1.4 0.9

Families with More Than One Adult (%) 53.6 53.9

Number of Children in Family (%)

None 38.8 48.4

1 Child 21.6 25.5

2 Children 16.5 13.7

3 or More 23.1 12.3

For Families with Children, Age of Youngest Child (%)

0–5 Years 40.5 28.3

6–12 Years 37.6 40.4

13–17 Years 21.8 31.2

Current/Anticipated Annual Family Income ($) 16,511 18,583

Current/Anticipated Annual Family Income (%)

$0 3.9 5.1

$1–4,999 18.4 9.5

$5,000–9,999 22.0 21.2

$10,000–19,999 23.5 26.2

$20,000 or More 32.1 38.0

Income Sourcesb (%)

Wages 60.7 63.0

TANF 22.6 17.2

Social Security/SSI/Pension 11.2 15.3

Other income sources 28.1 46.4

(continued)
80

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit G.1 Household Composition and Income at Baseline, Single Policy Change Nonelderly, Nondisabled Households 

(continued)

 Characteristic SCCHA SFHA

Average Annual Income from Wages, for Families with 

Any Wage Income ($) 21,557 23,898

Annual Income from Wages, for Families with Any Wage Income (%)

$1–4,999 11.4 5.6

$5,000–9,999 15.4 14.7

$10,000–19,999 27.5 27.6

$20,000–29,999 20.1 21.7

$30,000 or More 25.5 30.5

Sample Size (Total = 6,915) 5,183 1,732

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority. SSI = Supplementary Security Income. TANF = Temporary 

Assistance for Needy Families.

a

Adults are defined as individuals age 18 and older who were not classified on the HUD-50058 form as a live-in aide.

b

Income source categories are as defined on the HUD-50058 form. Wages include one’s own business, federal wages, PHA wages, military pay, and other 

wages. Other income sources include child support, medical reimbursement, Indian trust/per capita, unemployment benefits, and other nonwage sources.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data

Appendix G
81

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Exhibit G.2 Characteristics of Nonelderly, Nondisabled Adults at Baseline in Single Policy Change Households

Characteristic SCCHA SFHA

Female (%) 63.8 62.0

Age (%)

18–24 30.6 28.4

25–34 19.1 18.6

35–44 18.4 14.9

45 or Older 31.9 38.1

Average Age (Years) 36.0 37.5

Race (%)

White, non-Hispanic 9.7 16.0

Black, non-Hispanic 15.3 32.7

Asian or Hawaiian or Pacific Islander, non-Hispanic 33.1 25.8

Hispanic 41.0 23.8

Other Race or More Than One Race, non-Hispanic 0.8 1.7

Income Sourcesa

 (%)

Wages 41.1 42.4

TANF 11.6 8.2

Social Security/SSI/Pension 1.9 6.4

Other Income Sources 14.5 27.4

Average Annual Income from Wages for Individuals 

with Any Wage Income ($)

16,676 18,596

Annual Income from Wages for Individuals with Any Wage Income ($)

$1–$4,999 19.5 10.0

$5,000–$9,999 18.9 21.0

$10,000–$19,999 28.4 32.4

$20,000–$29,999 17.0 18.5

$30,000 or More 16.2 18.2

Individual Sample Size (Total = 15,050) 10,974 4,076

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority. SSI = Supplementary Security Income. TANF = Temporary 

Assistance for Needy Families.

a

Income source categories are as defined on the HUD-50058 form. Wages include one’s own business, federal wages, PHA wages, military pay, and other 

wages. Other income sources include child support, medical reimbursement, Indian trust/per capita, unemployment benefits, and other nonwage sources.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
82

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit G.3 Characteristics of Nonelderly, Nondisabled Households at Baseline, Single Policy Change Households

Characteristic SCCHA SFHA

Average Monthly Family Sharea ($) 508 589

Average Monthly Family Share (%)

$0 2.1 2.3

$1–$299 40.5 31.2

$300–$599 26.5 28.5

$600–$899 15.9 17.7

$900 or More 17.1 22.2

Family Share as a Proportion of Monthly Gross Income (%)

0%–20% 1.3 1.2

21%–30% 46.8 29.0

31%–40% 28.3 39.1

41%–50% 7.5 11.7

51% or Above 16.1 19.1

Average Monthly Housing Subsidyb ($) 1,304 1,367

Average Monthly Housing Subsidy (%)

$0–$599 6.9 6.3

$600–$899 11.8 10.1

$900–$1,199 22.4 18.7

$1,200 or More 58.9 64.9

Payment Standard Reduced with New Rules (%) 0.0 0.0

Monthly Gross Rent Exceeds Payment Standard (%) 53.5 63.5

Neighborhood Poverty Ratec

 (%)

0%–10% 39.0 22.9

11%–20% 41.1 59.1

21%–30% 15.5 11.3

More than 30% 4.4 6.8

Sample Size (Total = 6,915) 5,183 1,732

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority. SSI = Supplementary Security Income. TANF = Temporary 

Assistance for Needy Families. 

a

Family share is the family’s contribution toward the gross rent.

b

Housing subsidy is the full subsidy amount paid by the housing agency. It includes any utility allowance payments made to the tenant in addition to rent 

paid to the owner by the housing agency.

c

Poverty rate is defined as the percentage of individuals ages 18 to 64 years whose income in the previous 12 months was below the poverty threshold. 

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences. Housing subsidy characteristics represent monthly averages. 

Sources: MDRC calculations using HUD Public and Indian Housing Information Center; 2009–2013 American Community Survey 5-Year Estimates data

Appendix G
83

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Exhibit G.4 Household Composition and Income at Baseline, Nonelderly, Nondisabled Double Policy Change Households

Characteristic SCCHA SFHA

Average Number of Family Members

Adultsa 2.2 2.3

Children 1.5 1.0

Families with More than One Adult (%) 74.1 73.5

Number of Children in Family (%)

None 23.3 33.0

1 Child 29.4 35.0

2 Children 32.9 29.2

3 or More 14.3 2.9

For Families with Children, Age of Youngest Child (%)

0–5 Years 26.0 11.6

6–12 Years 44.8 46.5

13–17 Years 29.2 41.9

Current/Anticipated Annual Family Income ($) 20,247 22,326

Current/Anticipated Annual Family Income (%)

$0 2.2 4.2

$1–4,999 11.9 8.9

$5,000–9,999 22.5 16.3

$10,000–19,999 23.2 24.3

$20,000 or More 40.2 46.3

Income Sourcesb (%)

Wages 65.2 68.4

TANF 25.4 20.3

Social Security/SSI/Pension 18.0 22.9

Other Income Sources 32.4 46.3

Average Annual Income from Wages, for Families 

with Any Wage Income ($) 24,536 26,612

Annual Income from Wages, for Families with Any Wage Income (%)

$1–4,999 10.0 5.2

$5,000–9,999 13.4 13.0

$10,000–19,999 25.1 27.0

$20,000–29,999 18.7 17.9

$30,000 or More 32.7 36.8

Sample Size (Total = 1,991) 1,542 449

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority. SSI = Supplementary Security Income. TANF = Temporary 

Assistance for Needy Families. 

a

Adults are defined as individuals age 18 and older who were not classified on the HUD-50058 form as a live-in aide.

b

Income source categories are as defined on the HUD-50058 form. Wages include one’s own business, federal wages, PHA wages, military pay, and other 

wages. Other income sources include child support, medical reimbursement, Indian trust/per capita, unemployment benefits, and other nonwage sources.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
84

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit G.5 Characteristics of Nonelderly, Nondisabled Adults at Baseline in Double Policy Change Households

Characteristic SCCHA SFHA

Female (%) 64.6 62.9

Age (%)

18–24 35.9 34.5

25–34 17.7 17.3

35–44 17.6 13.8

45 or Older 28.8 34.4

Average Age (Years) 34.5 35.6

Race (%)

White, non-Hispanic 8.5 11.2

Black, non-Hispanic 14.0 34.0

Asian or Hawaiian or Pacific Islander, non-Hispanic 37.6 28.3

Hispanic 39.1 25.2

Other Race or More than One Race, non-Hispanic 0.8 1.4

Income Sourcesa

 (%)

Wages 41.2 40.9

TANF 11.1 8.2

Social Security/SSI/Pension 1.3 6.2

Other Income Sources 13.7 24.5

Average Annual Income from Wages for Individuals 

with Any Wage Income ($) 17,273 19,126

Annual Income from Wages for Individuals with Any Wage Income ($)

$1–$4,999 20.8 9.2

$5,000–$9,999 18.2 23.9

$10,000–$19,999 26.5 30.3

$20,000–$29,999 15.7 15.6

$30,000 or More 18.9 21.1

Individual Sample Size (Total = 5,491) 4,157 1,334

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority. SSI = Supplementary Security Income. TANF = Temporary 

Assistance for Needy Families. 

a

Income source categories are as defined on the HUD-50058 form. Wages include one’s own business, federal wages, PHA wages, military pay, and other 

wages. Other income sources include child support, medical reimbursement, Indian trust/per capita, unemployment benefits, and other nonwage sources.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data

Appendix G
85

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Exhibit G.6 Characteristics of Households at Baseline, Nonelderly, Nondisabled Double Policy Change Households

Characteristic SCCHA SFHA

Average Monthly Family Sharea ($) 574 702

Average Monthly Family Share (%)

$0 2.3 2.6

$1–$299 33.3 22.3

$300–$599 28.1 28.5

$600–$899 17.5 19.4

$900 or More 21.1 29.6

Family Share as a Proportion of Monthly Gross Income (%)

0%–20% 0.5 0.2

21%–30% 51.0 32.7

31%–40% 31.9 35.2

41%–50% 7.7 13.8

51% or Above 8.9 18.0

Average Monthly Housing Subsidyb ($) 1,711 1,811

Average Monthly Housing Subsidy (%)

$0–$599 2.2 3.1

$600–$899 4.3 2.2

$900–$1,199 8.2 5.4

$1,200 or More 85.3 89.3

Payment Standard Reduced with new Rules (%) 100.0 100.0

Monthly Gross Rent Exceeds Payment Standard (%) 52.0 63.7

Neighborhood Poverty Ratec

 (%)

0%–10% 50.1 29.4

11%–20% 36.8 60.4

21%–30% 10.4 7.6

More than 30% 2.7 2.7

Sample Size (Total = 1,991) 1,542 449

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority. SSI = Supplementary Security Income. TANF = Temporary 

Assistance for Needy Families. 

a

Family share is the family’s contribution toward the gross rent. 

b

Housing subsidy is the full subsidy amount paid by the housing agency. It includes any utility allowance payments made to the tenant in addition to rent 

paid to the owner by the housing agency.

c

Poverty rate is defined as the percentage of individuals ages 18 to 64 years whose income in the previous 12 months was below the poverty threshold.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences. Housing subsidy characteristics represent monthly averages. 

Sources: MDRC calculations using HUD Public and Indian Housing Information Center; 2009–2013 American Community Survey 5-year estimates data
86

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Exhibit G.7 Estimated Effects on Housing Subsidies by Subgroup, Nonelderly, Nondisabled Households in SCCHA and SFHA

Outcome Difference Between Subgroup Estimated Effects 

(Double Policy Change minus Single Policy Change) P-Value

Total Annual Housing Subsidy ($)

Year 1 -4,032 0.00†††

Year 2 -4,461 0.00†††

Year 3 -3,340 0.00†††

Receipt of Housing Subsidy (%)

Year 1 0.7 0.17

Year 2 -1.8 0.28

Year 3 -3.3 0.12

Sample (Total = 8,901)

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Outcomes shown describe only those households receiving any housing subsidies in the specified month. Effects were estimated using an autoregressive 

difference-in-differences model, controlling for the past receipt of housing subsidies and other baseline characteristics of sample households. The 

estimates in the “Difference Between Subgroup Estimated Effects (Double Policy Change minus Single Policy Change)” column are calculated by 

subtracting the estimated effects for the single policy change subgroup from the estimated effects of the double policy change subgroup. The H-statistic is 

used to assess whether the difference in estimated effects between the subgroups is statistically significant. The “P-Value” column represents the p-value 

for the H-statistic. Significance levels are indicated as follows: ††† = 1 percent; †† = 5 percent; † = 10 percent.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
87

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Exhibit G.8 Outcomes Related to Housing Assistance, Nonelderly, Nondisabled Single Policy Change Households

Outcome SCCHA SFHA

Received Any Housing Subsidies (%)

Baselinea 100.0 100.0

Year 1 99.1 98.1

Year 2 93.2 94.9

Year 3 87.9 89.7

Total Tenant Payment (TTP), Among Households Receiving Subsidies ($)

Last Month of Baselineb 403 450

Last Month of Year 1 484 452

Last Month of Year 2 481 522

Last Month of Year 3 529 548

Housing Assistance Payment (HAP), Among Households Receiving Subsidies ($)

Last Month of Baselinec 1,320 1,389

Last Month of Year 1 1,194 1,381

Last Month of Year 2 1,244 1,406

Last Month of Year 3 1,377 1,461

Total Tenant Rent Share, Among Households Receiving Subsidies ($)

Last Month of Baselined 447 500

Last Month of Year 1 529 504

Last Month of Year 2 554 550

Last Month of Year 3 575 578

Sample Size (Total = 1,989) 5,181 1,731

a

The subsidy receipt status reported in HUD’s quarterly snapshot data files differed slightly from the status reported in HUD’s transactional data files. The 

baseline subsidy receipt status in this exhibit is based on Q2 to Q3 2013 quarterly snapshot data, while the status in the followup years are based on 

transactional data.

b

TTP is the minimum amount a family must contribute toward rent and utilities regardless of the unit selected. For MTW households, TTP has been 

calculated to reflect the minimum rents in Santa Clara and San Mateo.

c

Housing subsidy is the full subsidy amount paid by the housing agency on the household’s behalf and includes any utility allowance payments made to the 

tenant in addition to rent paid to the owner by the housing agency.

d

Total tenant rent share is the family’s contribution toward the contract rent.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Outcomes shown describe only those households receiving any housing subsidies in the specified month.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data
88

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit G.9 Outcomes Related to Housing Assistance, Nonelderly, Nondisabled Double Policy Change Households

Outcome SCCHA SFHA

Received Any Housing Subsidies (%)

Baselinea 100.0 100.0

Year 1 99.7 98.2

Year 2 92.2 95.3

Year 3 85.7 91.1

Total Tenant Payment (TTP), Among Households Receiving Subsidies ($)

Last Month of Baselineb 497 539

Last Month of Year 1 539 543

Last Month of Year 2 534 671

Last Month of Year 3 596 721

Housing Assistance Payment (HAP), Among Households Receiving Subsidies ($)

Last Month of Baselinec 1,715 1,825

Last Month of Year 1 1,240 1,775

Last Month of Year 2 1,293 1,748

Last Month of Year 3 1,473 1,746

Total Tenant Rent Share, Among Households Receiving Subsidies ($)

Last Month of Baselined 511 579

Last Month of Year 1 810 621

Last Month of Year 2 784 727

Last Month of Year 3 753 797

Sample Size (Total = 1,989) 1,542 447

a

The subsidy receipt status reported in HUD’s quarterly snapshot data files differed slightly from the status reported in HUD’s transactional data files. The 

baseline subsidy receipt status in this exhibit is based on Q2 to Q3 2013 quarterly snapshot data, while the status in the followup years are based on 

transactional data.

b

TTP is the minimum amount a family must contribute toward rent and utilities regardless of the unit selected. For MTW households, TTP has been 

calculated to reflect the minimum rents in Santa Clara and San Mateo.

c

Housing subsidy is the full subsidy amount paid by the housing agency on the household’s behalf and includes any utility allowance payments made to the 

tenant in addition to rent paid to the owner by the housing agency.

d

Total tenant rent share is the family’s contribution toward the contract rent.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Outcomes shown describe only those households receiving any housing subsidies in the specified month. 

Source: MDRC calculations using HUD Public and Indian Housing Information Center data

Appendix G
89

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Exhibit G.10 Outcomes Related to Households’ Housing Decisions Among Households Receiving Subsidies, Nonelderly, 

Nondisabled Single Policy Change Households

Outcome SCCHA SFHA

Neighborhood Poverty Ratea

Last Quarter of Baseline 11.9 15.3

Last Quarter of Year 1 12.0 15.3

Last Quarter of Year 2 12.3 15.0

Last Quarter of Year 3 12.5 15.1

Number of Bedrooms

Last Month of Baseline 2.5 2.2

Last Month of Year 1 2.5 2.2

Last Month of Year 2 2.5 2.2

Last Month of Year 3 2.5 2.2

Took a Port-Out Action (%)

Baseline 1.6 0.8

Year 1 1.6 3.1

Year 2 1.9 2.1

Year 3 1.9 1.6

Household Size

Last Month of Baseline 3.2 2.8

Last Month of Year 1 3.2 2.8

Last Month of Year 2 3.2 2.7

Last Month of Year 3 3.2 2.7

Sample Size (Total = 6,912) 5,181 1,731

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority.

a

Poverty rate is defined as the percentage of individuals ages 18 to 64 years whose income in the previous 12 months was below the poverty threshold.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Outcomes shown describe only those households receiving any housing subsidies in the specified month.

Sources: MDRC calculations using HUD Public and Indian Housing Information Center data; 2007–2011 and 2012–2016 American Community Survey 5-year 

estimates
90

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit G.11 Outcomes Related to Households’ Housing Decisions Among Households Receiving Subsidies, Nonelderly, 

Nondisabled Double Policy Change Households

Outcome SCCHA SFHA

Neighborhood Poverty Ratea

Last Quarter of Baseline 10.1 13.2

Last Quarter of Year 1 10.8 12.8

Last Quarter of Year 2 11.1 13.2

Last Quarter of Year 3 11.3 13.4

Number of Bedrooms

Last Month of Baseline 3.4 3.1

Last Month of Year 1 3.2 3.1

Last Month of Year 2 3.2 3.1

Last Month of Year 3 3.1 3.1

Took a Port-Out Action (%)

Baseline 1.4 1.6

Year 1 1.9 2.0

Year 2 2.3 1.6

Year 3 1.4 1.1

Household Size

Last Month of Baseline 3.7 3.3

Last Month of Year 1 3.6 3.3

Last Month of Year 2 3.6 3.2

Last Month of Year 3 3.6 3.2

Sample Size (Total = 1,989) 1,542 447

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority. 

a

Poverty rate is defined as the percentage of individuals ages 18 to 64 years whose income in the previous 12 months was below the poverty threshold.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Outcomes shown describe only those households receiving any housing subsidies in the specified month.

Sources: MDRC calculations using HUD Public and Indian Housing Information Center data; American Community Survey, 5-year estimates (2007–2011 and 

2012–2016)

Appendix G
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Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Exhibit G.12 Tenant Rent Share as a Percent of Monthly Gross Income Among Households Receiving Subsidies, Nonelderly, 

Nondisabled Single Policy Change Households

Outcome SCCHA SFHA

Median Tenant Rent Share as a Percent of Monthly Gross Income (%)

Last Month of Baseline 29.1 29.5

Last Month of Year 1 35.0 29.5

Last Month of Year 2 32.0 29.3

Last Month of Year 3 32.0 29.4

Average Tenant Rent Share as a Percent of Monthly Gross Income (%)

Last Month of Baseline 35.2 37.0

Last Month of Year 1 42.3 37.5

Last Month of Year 2 41.8 34.4

Last Month of Year 3 38.2 34.0

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Baseline (%)

0–25% 15.5 8.0

26–30% 59.7 62.5

31–35% 6.9 9.0

36–40% 3.6 4.7

41–50% 3.6 3.9

51% and Above 10.6 11.9

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 1 (%)

0–25% 0.4 8.3

26–30% 1.1 61.8

31–35% 68.9 8.5

36–40% 9.9 4.0

41–50% 6.1 4.1

51% and Above 13.6 13.3

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 2 (%)

0–25% 0.7 6.9

26–30% 2.0 76.4

31–35% 64.8 3.6

36–40% 9.5 2.2

41–50% 6.5 2.7

51% and Above 16.4 8.2

(continued)
92

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit G.12 Tenant Rent Share as a Percent of Monthly Gross Income Among Households Receiving Subsidies, Nonelderly, 

Nondisabled Single Policy Change Households (continued)

Outcome SCCHA SFHA

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 3 (%)

0–25% 1.0 7.2

26–30% 3.0 78.1

31–35% 76.3 2.8

36–40% 5.2 1.7

41–50% 4.0 2.2

51% and Above 10.5 8.0

Sample Size (Total = 6,912) 5,181 1,731

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences. Outcomes shown describe only those households receiving any housing subsidies in 

the specified month.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data

Appendix G
93

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Appendix G

Exhibit G.13 Tenant Rent Share as a Percent of Monthly Gross Income Among Households Receiving Subsidies, Nonelderly, 

Nondisabled Double Policy Change Households

Outcome SCCHA SFHA

Median Tenant Rent Share as a Percent of Monthly Gross Income (%)

Last Month of Baseline 29.1 29.5

Last Month of Year 1 35.0 29.5

Last Month of Year 2 32.0 29.3

Last Month of Year 3 32.0 29.4

Average Tenant Rent Share as a Percent of Monthly Gross Income (%)

Last Month of Baseline 30.5 34.5

Last Month of Year 1 57.6 37.2

Last Month of Year 2 52.3 34.9

Last Month of Year 3 44.7 36.0

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Baseline (%)

0–25% 17.6 6.4

26–30% 70.9 66.8

31–35% 4.3 9.4

36–40% 1.6 5.9

41–50% 1.5 2.3

51% and Above 4.0 9.2

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 1 (%)

0–25% 0.6 7.1

26–30% 1.6 59.7

31–35% 28.4 12.0

36–40% 11.1 3.3

41–50% 12.6 3.3

51% and Above 45.8 14.6

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 2 (%)

0–25% 0.8 5.1

26–30% 2.4 71.8

31–35% 38.2 6.9

36–40% 10.1 3.7

41–50% 10.8 3.7

51% and Above 37.7 8.8

(continued)
94

Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

Exhibit G.13 Tenant Rent Share as a Percent of Monthly Gross Income Among Households Receiving Subsidies, Nonelderly, 

Nondisabled Double Policy Change Households (continued)

Outcome SCCHA SFHA

Average Tenant Rent Share as a Percent of Monthly Gross Income in the Last Month of Year 3 (%)

0–25% 0.9 3.8

26–30% 3.6 71.1

31–35% 55.5 4.9

36–40% 8.4 5.4

41–50% 7.5 4.9

51% and Above 24.2 10.0

Sample Size (Total = 1,989) 1,542 447

SCCHA = Santa Clara County Housing Authority. SFHA = San Francisco Housing Authority.

Notes: Samples consist of households headed by adults who were not seniors or adults with disabilities. Sample sizes may vary because of missing values. 

Rounding may cause slight discrepancies in sums and differences. Outcomes shown describe only those households receiving any housing subsidies in 

the specified month.

Source: MDRC calculations using HUD Public and Indian Housing Information Center data

Appendix G
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Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform

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Evaluating the Effects of Santa Clara County Housing Authority’s Rent Reform
April 2020

U.S. Department of Housing and Urban Development

Office of Policy Development and Research

Washington, DC 20410-6000