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

AN ESTIMATE OF

HOUSING DISCRIMINATION

AGAINST SAME-SEX COUPLES
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AN ESTIMATE OF 

HOUSING DISCRIMINATION 

AGAINST SAME-SEX COUPLES

Prepared for

U.S. Department of Housing and Urban Development

Office of Policy Development and Research

Prepared by

Samantha Friedman

University at Albany, SUNY

Angela Reynolds

Susan Scovill

Florence R. Brassier

Ron Campbell

McKenzie Ballou

M. Davis and Company, Inc.

Philadelphia, Pennsylvania

June 2013
Acknowledgments

Disclaimer

Many individuals contributed to this study. The work could not 

have been completed without the commitment and hard work 

of the primary research team members and various administrative and support staff. We thank the following members of the 

project team: Gregory M. Herek; Madeline Hoffman; Thomas 

Roth and David Paisley of Community Marketing; Robert 

Schwemm; Thomas Sexton; Gregory D. Squires; Bryan Tomlin; 

and Donald Kahl and John Baker of the Equal Rights Center, 

who also made contributions to the design of the project.

A panel of expert advisers made valuable contributions to the 

understanding of the housing issues faced by the lesbian, gay, 

bisexual, transgender community and of the e-mail testing 

approach. We express special thanks to Gregory M. Herek, 

Jim McCarthy, Robert Schwemm, and Gregory D. Squires; as 

well as Lee Badgett, Roger Doughty, Kate Kendall, Jerry Malitz, 

Justin Nelson, Terry Stone, and Laura Young. 

We also thank Jennifer A. Stoloff, the project’s Government 

Technical Representative from the U.S. Department of Housing 

and Urban Development, Office of Policy Development and 

Research, for providing significant guidance and support at all 

stages.

We offer special thanks to Louisa Elfman of M. Davis and 

Company, Inc., for managing the packaging of the report.

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.
An Estimate of Housing Discrimination Against Same-Sex Couples iii

Contents

Acknowledgments.................................................................. ii

Executive Summary................................................................iv

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

Fair Housing Laws .......................................................... 1

Paired Testing and Previous Housing Discrimination 

Studies..................................................................... 2

Previous Research on Discrimination Against LGBT 

People...................................................................... 3

Research Design ..................................................................... 5

Hypotheses ..................................................................... 5

E-mail Approach............................................................. 5

Methodology .......................................................................... 6

Selecting Markets............................................................ 6

Random Sample of Markets............................................. 6

Sampling Strategy ........................................................... 7

Conducting the E-mail Testing........................................ 9

Data Analysis........................................................................ 12

Gross and Net Measures of Adverse Treatment.............. 12

Findings............................................................................... 14

National-Level Estimates of Discrimination................... 14

Estimates of Discrimination by Legislative Jurisdiction.. 16

Estimates of Discrimination by Metropolitan Market 

Size........................................................................ 18

Conclusions and Implications .............................................. 20

Recommendations for Further Study............................. 21

Technical Appendixes........................................................... 22

Appendix A. Distribution of Population and Sample 

Characteristics Across Proposed Population 

Stratum.................................................................. 22

Appendix B. Weighted Results and Standard Errors ...... 23

Appendix C. List of Tester Names ................................. 24

Appendix D. E-mail Text and Subject Lines .................. 24

Appendix E. Data Dictionary......................................... 27

References............................................................................ 69

List of Tables

Table E-1. Tests Favoring Heterosexual Couples (gross 

measures) ............................................................vii

Table E-2. Tests Favoring Heterosexual Couples (net 

measures) ............................................................vii

Table 1. Number of Paired Tests in Each Stratum............... 7

Table 2. Outcome Variables.............................................. 14

Table 3. National-Level Gay Male-Heterosexual Tests....... 14

Table 4. National-Level Lesbian-Heterosexual Tests............ 15

Table 5. Gay Male-Heterosexual Tests by State Protection... 16

Table 6. Lesbian-Heterosexual Tests by State Protection...... 17

Table 7. Gay Male-Heterosexual Net Measures by 

Metropolitan Market Size....................................... 18

Table 8. Lesbian-Heterosexual Net Measures by 

Metropolitan Market Size....................................... 19

List of Figures

Figure E-1. National-Level Adverse Treatment Against 

Gay Male and Lesbian Couples, 2011................viii
An Estimate of Housing Discrimination Against Same-Sex Couples iv

Executive Summary

This is the first large-scale, paired-testing study to assess housing discrimination against same-sex couples in metropolitan 

rental markets via advertisements on the Internet. The research 

is based on 6,833 e-mail correspondence tests conducted in 

50 metropolitan markets across the United States from June 

through October 2011. For each correspondence test, two e-mails 

were sent to the housing provider, each inquiring about the 

availability of the unit advertised on the Internet. The only 

difference between the two e-mails was the sexual orientation 

of the couple making the inquiry. Two sets of correspondence 

tests were conducted, one assessing the treatment of gay male 

couples relative to heterosexual couples and one assessing the 

treatment of lesbian couples relative to heterosexual couples. 

This methodology provides the first direct evidence of discriminatory treatment of same-sex couples compared with the treatment of heterosexual couples when searching for rental housing 

advertised on the Internet in the United States.

The study finds that same-sex couples experience less favorable treatment than heterosexual couples in the online rental 

housing market. The primary form of adverse treatment is that 

same-sex couples receive significantly fewer responses to e-mail 

inquiries about advertised units than heterosexual couples. 

Study results in jurisdictions with state-level protections against 

housing discrimination on the basis of sexual orientation unexpectedly show slightly more adverse treatment of same-sex 

couples than results in jurisdictions without such protections. 

This study provides an important initial observation of discrimination based on sexual orientation at the threshold stage 

of the rental transaction and is a point of departure for future 

research on housing discrimination against same-sex couples.

Background

Federal fair housing laws, seeking to ensure equal access to 

housing, prohibit housing discrimination based on race, color, 

religion, national origin, sex, familial status, and disability. The 

Fair Housing Act, however, does not include sexual orientation 

or gender identity as protected classes. Although individual 

states and localities increasingly include sexual orientation and 

gender identity as protected classes, the fair housing laws of 

most states do not provide legal protections for the lesbian, gay, 

bisexual, and transgender (LGBT) community.

Although various studies have gathered information on prejudice and stigma against the LGBT community, little empirical 

research has examined housing discrimination based on sexual 

orientation. In community-based surveys conducted during the 

1980s and 1990s with nonprobability samples, many lesbians 

and gay men reported that they had experienced some form of 

housing discrimination. In a statewide survey of lesbians and gay 

men by the Philadelphia Lesbian and Gay Task Force, between 

9 and 16 percent of males (depending on race) and between 

5 and 11 percent of females reported housing discrimination 

(Gross and Aurand, 1996). In a 2000 Kaiser Family Foundation 

survey, 11 percent of the lesbian, gay male, and bisexual respondents said they had personally experienced discrimination in 

renting an apartment or buying a home. Another 35 percent 

said they had not personally experienced such discrimination 

but knew someone who had (Kaiser Family Foundation, 2001). 

Using data from a nationally representative sample of lesbian, 

gay male, and bisexual adults, Herek (2009a) found that 3.8 

percent of this population reports experiencing discrimination 

in the housing market at least once, with gay men experiencing 

the highest rate of housing discrimination (6.5 percent). 

Data on perceptions can miss discriminatory actions that are 

unknown to prospective renters, however. Recently, three correspondence test studies examined potential adverse treatment 

of lesbian and gay male couples, relative to heterosexual couples: 

two in Sweden (Ahmed, Andersson, and Hammarstedt, 2008; 

Ahmed and Hammarstedt, 2009) and one in Canada (Lauster 

and Easterbrook, 2011). Ahmed and colleagues did not find 

evidence of adverse treatment against lesbians, but they did 

find significant differences between gay male couples and 

heterosexual couples, with gay male couples receiving fewer 

responses and invitations to contact the provider and inspect 

the unit. Regarding a “gross” measure of adverse treatment, 

Ahmed and Hammarstedt (2009) found that in 12.3 percent 

of the correspondence tests (not matched pairs), heterosexual 

couples were favored over gay male couples in getting an e-mail 

response; the net measure was 11.4 percent and was the only 

dimension of adverse treatment that was statistically significant. 

No disparities emerged in invitations to contact the provider or 

to a showing of the unit. Lauster and Easterbrook (2011) also 

found no disparity between lesbian and heterosexual couples 

but found that gay male couples are less likely than heterosexual couples to receive positive responses from housing 

providers. No correspondence tests, however, were previously 

conducted for these groups in the United States. 
An Estimate of Housing Discrimination Against Same-Sex Couples v

Objectives of the Research

The objective of this study is to develop the first national 

estimate of the level of housing discrimination based on sexual 

orientation; that is, discrimination against same-sex couples—

men partnering with men and women partnering with 

women—at the initial stage of the rental housing transaction 

in the electronically advertised rental market. The study looks 

only at the issue of the sexual orientation of same-sex couples 

and not at other issues, such as gender identity.

The study has two unique features. First, it examines the experience and treatment of same-sex couples in their search for 

rental housing, a subject not previously observed on a national 

scale. Second, recognizing the increasing use of the Internet 

to search for housing, the study uses Internet advertising and 

matched-pair e-mails—the very threshold of the housing 

transaction—as the point of contact between the tester and 

the housing provider. The project also provides a novel, yet 

increasingly relevant, approach to a first look at barriers in the 

rental housing market for same-sex couples.

Hypotheses

Consistent with the findings of previous research outside the 

United States (for example, Ahmed, Andersson, and Hammarstedt, 2008; Ahmed and Hammarstedt, 2009; Lauster and 

Easterbrook, 2011), we expect that a disparity would exist in 

the response of housing providers to inquiries expressing interest in electronically advertised rental housing by heterosexual 

and same-sex couples. The main hypotheses for the study 

are that (1) same-sex couples will experience more adverse 

treatment than heterosexual couples, (2) gay male couples will 

experience a greater degree of adverse treatment than lesbian 

couples, and (3) same-sex couples will experience lower levels 

of adverse treatment in places with state-level housing discrimination laws inclusive of sexual orientation than in jurisdictions 

without such protections.

Methodology

The research adapts the well-established matched-pair testing 

methodology, which has been a hallmark of previous U.S. 

Department of Housing and Urban Development (HUD) 

housing discrimination studies (HDSs), for use in examining 

the electronically advertised rental housing market. A total of 

6,833 matched-pair correspondence tests were completed via 

e-mail across 50 markets. Tests were divided between those 

examining discrimination against gay men (3,424 tests) and 

those examining discrimination against lesbians (3,409 tests), 

both relative to the treatment of heterosexual couples. 

The primary objectives of the study were to obtain data that 

would produce (1) nationally representative estimates of 

various measures of housing discrimination against same-sex 

couples; (2) to the extent possible, estimates of these measures 

by whether a state had legislative protections against housing 

discrimination based on sexual orientation; and (3) to the 

extent possible, estimates of these measures by market size.

A total of 50 markets were randomly selected, proportional 

to population size (PPS), from among the 331 metropolitan 

statistical areas or primary metropolitan statistical areas, based 

on 2000 census definitions. The sampling elements were 

one-bedroom rental unit listings advertised on a national 

Internet listing site. This site was chosen as the universe from 

which to sample the electronic advertisements because the 

first contact between the prospective renter and the housing 

provider could always occur via e-mail; unlike other electronic 

search engines, the site does not require prospective renters 

to complete an online registration form asking for their phone 

numbers and current addresses; and because the format of 

the advertisements on the selected site and the nature of the 

contact between providers and prospective tenants is uniform 

throughout the country. 

For a market to be included in the sample, it had to have 

complete coverage on the selected listing site throughout the 

metropolitan area being sampled. For example, for the Washington, D.C. market to be included in our sample, the range 

of advertised units had to be spread among different areas 

throughout the metropolitan area (for example, Fairfax County, 

Virginia; Prince George’s County, Maryland; the District of Columbia; and so on). If the listing site did not completely cover a 

selected market, it was not included in the sampling frame, and 

another market was randomly selected using a PPS sampling 

approach. This procedure ensured a final sample of 50 markets 

with complete coverage. 

Each correspondence test involved sending two e-mails to the 

housing provider, each inquiring about the availability of the 

electronically advertised unit. The only difference between the 

two e-mails was whether the couple was same sex or heterosexual. Unfavorable treatment was measured based on the housing 

provider’s response to the e-mail, with the central focus being 

on whether each tester (1) received a response, (2) received 

more than one response, (3) was told the unit was available, 

(4) was told to contact the provider, and (5) was invited to 

inspect the unit.

Each correspondence test resulted in one of three potential 

outcomes: (1) the heterosexual couple is favored over the 

same-sex couple, (2) the same-sex couple is favored over the 
An Estimate of Housing Discrimination Against Same-Sex Couples vi

heterosexual couple, or (3) both couples receive equivalent 

treatment (equally favored or disfavored). The most straightforward measure, the gross measure, is the percentage of tests 

in which the heterosexual couple is favored over the same-sex 

couple. Gross measures are considered upper bound estimates 

of discrimination. Differential treatment might occur for random reasons, as well as reasons that have nothing to do with 

actual discrimination. For example, the housing provider might 

simply have forgotten to reply to the same-sex couple, or perhaps the unit was truly already rented by the time the same-sex 

couple inquired about it. To produce lower bound estimates 

of discrimination, net measures are calculated, borrowing from 

the methodology of the 2000 Housing Discrimination Study 

(HDS2000). Net measures subtract the percentage of same-sex 

couples favored on a given outcome from the percentage of 

heterosexual couples favored. The true estimate of adverse 

treatment against same-sex couples probably lies between the 

upper and lower bound estimates.

This report presents results for the five key dimensions of 

treatment discussed previously and combines these dimensions 

to create a composite measure of treatment. In particular, the 

consistency index, adopted from HDS2000, reflects the extent 

to which one tester is consistently favored over the other in 

the treatment received from housing providers based on their 

inquiry e-mails. Tests are classified as “heterosexual favored” if 

the heterosexual couple received favorable treatment on at least 

one of the five dimensions and the same-sex couple (gay male 

or lesbian) received no favorable treatment. Tests are classified 

as “gay male or lesbian favored” if the same-sex couple received 

favorable treatment on at least one of the five dimensions and 

the heterosexual couple received no favorable treatment.

Findings

Same-sex couples are significantly less likely than heterosexual 

couples to get favorable responses to e-mail inquiries about 

electronically advertised rental housing. Comparing our gross 

measures of discrimination, heterosexual couples were favored 

over gay male couples in 15.9 percent of tests and over lesbian 

couples in 15.6 percent of tests (Table E-1).

The net measures indicate that heterosexual couples are significantly more likely than their gay male and lesbian counterparts 

to receive an initial e-mail response (Table E-2). At this preliminary stage of the rental housing transaction, barriers indicate 

a rejection of the tester based solely on the sexual orientation 

information provided in the e-mail rather than on any characteristics related to qualification for the housing, thus preventing 

basic access to rental units.

Key Findings

•	 Same-sex couples experience discrimination in the online 

rental housing market, relative to heterosexual couples 

(Figure E-1).

•	 Adverse treatment is found primarily in the form of same-sex 

couples receiving fewer responses to the e-mail inquiry than 

heterosexual couples.

•	 Overall, results in states with legislative protections show 

slightly more adverse treatment for gay men and lesbians 

than results in states without protections.

•	 Adverse treatment of same-sex couples is present in all 

metropolitan areas, but no clearcut pattern exists in the 

magnitude of adverse treatment by metropolitan market size.

•	 Lower bound measures of discrimination (net measures) reveal similar results, although the magnitude of the difference 

in treatment between heterosexual and same-sex couples is 

less (that is, 2.2 percent for the gay male-heterosexual tests; 

1.3 percent for the lesbian-heterosexual tests) than for the 

gross measures and is only statistically significant in the gay 

male-heterosexual tests.

Table E-1. Tests Favoring Heterosexual Couples (gross measures)

Gross Measures Tests Favoring Heterosexual Couples Versus ... 

Gay Male Couples (%) Lesbian Couples (%)

Consistency index 15.9 15.6

Initial response provided 11.6 11.2

Net Measures Tests Favoring Heterosexual Couples Versus ... 

Gay Male Couples (%) Lesbian Couples (%)

Consistency index 2.2* 1.3

Initial response provided 3.1** 2.3**

Table E-2. Tests Favoring Heterosexual Couples (net measures)

* p ≤ .05. ** p ≤ .01. 
An Estimate of Housing Discrimination Against Same-Sex Couples vii

15.9%

13.7%

2.2*

15.6%

14.3%

1.3%

11.6%

8.5%

3.1**

11.2%

8.9%

2.3**

Heterosexual favored Gay male favored

Gay male-heterosexual tests

Net measure Heterosexual favored Lesbian favored

Lesbian-heterosexual tests

Net measure

Consistency index Reponse provided

Effect of Legislative Protections

In states with legislative protections against housing discrimination based on sexual orientation, heterosexual couples were 

consistently favored over gay male couples in 16.0 percent of 

tests and were favored over lesbian couples in 15.9 percent of 

tests. In states without such protections, however, heterosexual 

couples were favored over gay male and lesbian couples at rates 

that were 0.6 percentage points less than those in protected 

states (that is, 15.4 and 15.3 percent, respectively). Moreover, 

the net measure for gay male couples relative to heterosexual 

couples (3.1 percent) was statistically significant only in jurisdictions with state-level protections. Taken together, those 

results are surprising in that states with legislative protections 

prohibiting housing discrimination on the basis of sexual orientation do not show lower levels of adverse treatment. Several 

factors could account for this unexpected finding, including 

potentially low levels of enforcement, housing provider unfamiliarity with state-level protections, or the possibility that 

protections exist in states with the greatest need for them.

Effect of Metropolitan Market Size

When disaggregated by the size of metropolitan areas, the results 

of the paired tests continue to reveal that heterosexual couples 

were consistently favored over gay male and lesbian couples, 

although variation exists in the magnitude of the differences in 

treatment. These differences exhibit no clearcut pattern by metropolitan market size, however. The net measure is statistically 

significant only in gauging the treatment of gay male couples 

relative to heterosexual couples in the largest metropolitan areas. 

Conclusions and Implications

The findings presented in this report provide evidence that 

discrimination exists against same-sex couples in the initial 

stages of the search for electronically advertised rental housing 

in metropolitan America. The study measured the response of 

housing providers regarding the sexual orientation of couples 

and did not examine other characteristics, such as gender identity. The adverse treatment of same-sex couples stems largely 

from the fact that housing providers are less likely to respond 

to same-sex couples than to heterosexual couples. 

This study employed paired e-mail correspondence tests rather 

than in-person, paired tests, and it allowed for only one e-mail 

interaction with each housing provider. Because the observations 

are at the very threshold of the rental transaction, the estimates 

of discrimination presented here likely underestimate the extent 

to which heterosexual couples are favored over same-sex couples 

in the rental housing market. Nevertheless, the incidence of 

consistently favored treatment of heterosexual couples relative 

to gay male and lesbian couples (that is, 15.9 and 15.6 percent, respectively) is similar in magnitude to the incidence of 

Figure E-1. National-Level Adverse Treatment Against Gay Male and Lesbian Couples, 2011

* Significant at the p ≤ .05 level. **Significant at the p ≤ .01 level.
An Estimate of Housing Discrimination Against Same-Sex Couples viii

consistently favored treatment of White homeseekers relative 

to Black and Hispanic homeseekers (that is, 21.6 and 25.7 percent, respectively) found using in-person audits in HDS2000. 

This study serves as the initial step toward future research on 

same-sex housing discrimination. Although its use of paired 

testing and its national scope are strengths, the study design 

is limited to e-mail tests of rental housing in metropolitan 

markets advertised by one source on the Internet. Moreover, 

the study captures the treatment of test e-mail inquiries by 

housing providers in response to only one e-mail sent by each 

tester, and it therefore does not consider what could happen 

to testers through additional contact (via additional followup 

e-mails, phone, or in-person communication). Thus, the testing 

conducted in this study is representative of the initial stage of 

the housing search by prospective renters in the metropolitan 

rental housing market. 

The contribution of this study is to demonstrate that same-sex 

couples are less likely than heterosexual couples to gain access 

to the targeted rental unit. When same-sex couples do receive 

a response, however, the treatment by housing providers is, for 

the most part, equal—at least for a single e-mail interaction. 

This type of discrimination diverges somewhat from that which 

has been found between Whites and non-White minorities 

(Friedman, Squires, and Galvan, 2010). In large part, the disparity between Whites and non-White minorities in the initial 

access to housing units (that is, getting a response from providers) is less than the disparity observed in additional contact 

with providers (for example, getting more than one response or 

the potential to inspect the unit). 

This first set of national findings on the discrimination against 

same-sex couples in the metropolitan rental housing market 

should serve as a point of departure for future research on 

same-sex housing discrimination. In-person testing would 

provide valuable, additional information on the experiences of 

same-sex couples in the rental market, and it would replicate 

the approach of other HDS research and track the real-life 

sequence of a rental housing search. A broader sample of advertised rental units, including other electronic media and print 

advertisements, could be used for in-person testing.

Future studies could employ e-mail or in-person audits to 

further examine differences in treatment between same-sex and 

heterosexual couples in states with and without legislative protections for sexual orientation or gender identity. Local jurisdictions’ protections were not within the scope of this study, and 

examining the effect of such local protections on differential 

treatment could be very useful. In addition, this study looked 

at treatment based only on the sexual orientation of same-sex 

couples and not on gender identity or gender expression. This 

study does not explicitly capture treatment of transgender 

people or people who do not conform to stereotypical gender 

norms because it used the e-mail testing approach. Finally, 

future research could seek to obtain metropolitan-specific 

estimates of discrimination against same-sex couples. Perhaps 

this approach could shed light on the mixed findings of rental 

housing discrimination revealed across metropolitan areas in 

this study.
An Estimate of Housing Discrimination Against Same-Sex Couples 1

Introduction

This report presents the findings of the first large-scale, pairedtesting study to measure treatment of same-sex couples in the 

electronically advertised rental housing market. The study, 

sponsored by the U.S. Department of Housing and Urban 

Development (HUD) and conducted by M. Davis and Company 

(MDAC), Inc., was developed to obtain a baseline national 

estimate of housing discrimination against same-sex couples at 

the initial stage of the search for rental housing. It builds on the 

well-established matched-pair testing method used in previous 

HUD housing discrimination studies (HDSs) examining racial 

and ethnic discrimination in the housing market. The in-person 

method was adapted to reflect the increased use of the Internet 

in the housing search. The results are based on 6,833 paired 

e-mail tests conducted in 50 metropolitan areas from June 

through October 2011.

This study examines the treatment of same-sex couples seeking 

rental housing, a subject not previously observed on a national 

scale. Although the federal Fair Housing Act does not include 

sexual orientation or gender identity among its protected classes, 

evidence suggests that discrimination on the basis of actual or 

perceived sexual orientation limits housing opportunities for gay 

men and lesbians. Studies of public perception and attitudes 

toward sexual minorities show prejudice and stigma against this 

community (Herek, 2009a, 2009b). Smaller scale testing projects 

and other studies, discussed in the following section, indicate 

that same-sex couples experience prejudice based on their 

sexual orientation and encounter discrimination in their search 

for housing. State and local jurisdictions are increasingly enacting legislation prohibiting discrimination on the basis of sexual 

orientation or gender identity. Based on the existing evidence 

of discrimination experienced by lesbian, gay, bisexual, and 

transgender (LGBT) people, HUD recently issued a final rule to 

ensure that its core programs are open to all eligible individuals 

and families, regardless of sexual orientation or gender identity.1

In addition, recognizing the increasing use of the Internet to 

search for housing, this study uses Internet advertising and 

matched-pair e-mails—the threshold of the housing transaction—as the point of contact between the tester and the housing provider. In each paired test, the housing provider received 

two e-mails inquiring into an advertised rental unit: one from 

a self-identified same-sex couple and one from a self-identified 

heterosexual couple.

Fair Housing Laws

The federal Fair Housing Act (Title VIII of the Civil Rights Act 

of 1968) prohibits discrimination in the sale, rental, and financing of housing or in other housing-related transactions on the 

basis of seven protected classes: race, color, religion, national 

origin, sex, familial status (the presence of children less than 18 

years old, seeking custody of such people, or being pregnant), 

and disability. For example, housing providers are prohibited 

from considering these protected characteristics as the basis 

for rejecting or refusing to negotiate with individuals seeking 

housing or housing-related services, from misrepresenting or 

limiting housing opportunities based on these protected characteristics, or in setting different terms or conditions because of 

these protected characteristics. 

Neither sexual orientation nor gender identity is a protected 

class under the federal Fair Housing Act, although some forms 

of such discrimination against LGBT people might be prohibited 

under currently protected classes: sex discrimination (for example, 

nonconformity with gender stereotypes), sexual harassment, or 

disability (such as a provider’s perception that a gay applicant 

might have HIV/AIDS). An increasing number of states and 

local jurisdictions have enacted legislative protections against 

housing discrimination based on sexual orientation or gender 

identity. As of early 2012, 20 states and the District of Columbia have enacted legislation prohibiting housing discrimination 

based on sexual orientation or gender identity:2

California Nevada 

Colorado New Hampshire 

Connecticut (sexual orientation only)

Delaware New Jersey

 (sexual orientation only) New Mexico

Hawaii New York

Illinois (sexual orientation only)

Iowa Oregon

Maine Rhode Island

Maryland Vermont

 (sexual orientation only) Washington

Massachusetts Washington, D.C. 

Minnesota Wisconsin

 (sexual orientation only)

1

 “Equal Access to Housing in HUD Programs Regardless of Sexual Orientation or Gender Identity.” Final rule. Federal Register 77 (5662) February 3, 2012. Also 

available at http://portal.hud.gov/hudportal/documents/huddoc?id=12lgbtfinalrule.pdf.

2

 See HUD’s Fair Housing Act LGBT web page at http://portal.hud.gov/hudportal/HUD?src=/program_offices/fair_housing_equal_opp/LGBT_Housing_Discrimination.
An Estimate of Housing Discrimination Against Same-Sex Couples 2

Several states and more than 240 local jurisdictions currently 

prohibit discrimination in employment and public accommodations on the basis of sexual orientation. Many of these 

local jurisdictions also prohibit discrimination in housing 

on the basis of sexual orientation, gender identity, or gender 

expression.

On February 3, 2012, HUD published its Final Rule, “Equal 

Access to Housing in HUD Programs Regardless of Sexual 

Orientation or Gender Identity,” which prohibits making a 

determination of eligibility for HUD-assisted or HUD-insured 

housing on the basis of sexual orientation or gender identity. 

The rule applies to all HUD programs, including public housing, 

HUD-assisted or HUD-financed housing, and FHA-insured 

mortgage financing. The rule has four main provisions: It 

(1) requires providers assisted by HUD or insured by FHA to 

make housing available without regard to actual or perceived 

sexual orientation, gender identity, or marital status; (2) clarifies 

that the definitions of family and household, which are integral to 

determining who is eligible for HUD’s core programs, includes 

people regardless of actual or perceived sexual orientation, 

gender identity, or marital status; (3) prohibits HUD-assisted 

and FHA-insured entities from inquiring about an applicant’s 

or occupant’s sexual orientation or gender identity for the 

purpose of determining eligibility or otherwise making housing 

available; and (4) prohibits FHA-approved lenders from basing 

eligibility determinations for FHA-insured loans on actual or 

perceived sexual orientation or gender identity.3

Although less than one-half of all states provide state-level 

protection against housing discrimination for LGBT people, the 

effect of this lack of legislation remains unknown. Although 

most information is anecdotal, some previous formal research 

studies, described in the following section, illuminate the issue 

of housing discrimination against LGBT people. 

Paired Testing and Previous Housing 

Discrimination Studies 

Testing is an investigative technique used to observe the practices 

of housing providers. Testers, who pose as individuals seeking 

housing, contact housing providers in a variety of ways to inquire about housing opportunities. The origins of paired testing 

as a method of studying housing discrimination and identifying 

differential treatment lie in fair housing enforcement, and testing was originally used to identify individual housing providers 

who were violating housing discrimination laws. HUD has used 

testing for more than 40 years to investigate discriminatory 

housing practices, because testing is a powerful tool for directly 

observing differences in the treatment that homeseekers experience. When paired testing is applied to large, representative 

samples and implemented with rigorous controls, it provides 

reliable estimates of the differences in treatment among different populations.

HUD funded three national studies using the methodology of 

matched-pair testing to measure the levels of housing discrimination based primarily on race and ethnicity.

In 1977, HUD’s Housing Market Practices Survey (HMPS1977) 

employed the auditor technique to observe differential treatment 

of Black and White homeseekers. The Black and White auditors were both male or both female and had approximately 

the same level of education, income, occupation, and family 

characteristics. Each member of the audit team responded 

separately to advertisements that were randomly selected from 

major newspapers, and then they recorded their treatment on 

standardized forms. In HMPS1977 1,609 rental and 1,655 sales 

audits were conducted in 40 metropolitan areas during May 

and June of 1977. The results revealed significant differences 

between the Black and White audits. The white auditor was 

favored 50.4 percent of the time in the sales market and 45.7 

percent of the time in the rental market. The black auditor was 

favored only 19.7 and 17.9 percent of the time, respectively. 

HUD built on the HMPS1977 experience 10 years later by 

launching a second national audit study, the 1989 Housing 

Discrimination Study (HDS1989). This study involved 3,800 

paired tests for discrimination against Black and Hispanic 

homeseekers. As in HMPS1977, both rental and sales markets 

were tested in a random sample of 25 major metropolitan 

areas. Black-White tests were conducted in 20 of these sites and 

Hispanic-non-Hispanic White tests were conducted in 13 sites. 

The HDS methodology also involved expanded sample sizes 

in 5 metropolitan areas, which supported in depth analysis of 

variations in patterns of discrimination within urban areas (Fix 

and Turner, 1998).

In HDS1989, Black renters faced a 10.7-percent chance of being 

excluded altogether from housing made available to comparable 

White renters and a 23.5-percent chance of learning about fewer 

apartments. Real estate brokers were also much more likely to 

offer financial advice to White than to Black customers. 

In HUD’s third national study, Discrimination in Metropolitan 

Housing Markets (HDS2000), the results were based on 4,600 

paired tests conducted in 23 metropolitan areas nationwide 

during the summer and fall of 2000. 

3 http://portal.hud.gov/hudportal/documents/huddoc?id=12lgbtfinalrule.pdf.
An Estimate of Housing Discrimination Against Same-Sex Couples 3

HDS2000 Phase I was designed to provide updated national 

estimates of adverse treatment against Black and Hispanic homeseekers and to measure change in the incidence of differential 

treatment since 1989. In addition, Phase I provided estimates 

of adverse treatment against Black and Hispanic homeseekers 

in 20 individual metropolitan areas and exploratory estimates 

of adverse treatment against Asian (in 2 metropolitan areas) 

and Native American (in 1 metropolitan area) homeseekers. 

The basic testing protocols replicated those implemented in 

HDS1989. Random samples of advertised housing units were 

drawn weekly from major metropolitan newspapers, and testers 

visited the sampled offices to inquire about the availability of 

these advertised units. Both minority and White partners were 

assigned incomes, assets, and debt levels to make them equally 

qualified to buy or rent the advertised housing unit. Test partners were also assigned comparable family circumstances, job 

characteristics, education levels, and housing preferences. They 

visited sales or rental agents and systematically recorded the 

information and assistance they received about the advertised 

unit or similar units, including location, quality, condition, rent 

or sales price, and other terms and conditions. Test partners 

did not compare their experiences with one another or record 

any conclusions about differences in treatment; each simply 

reported the details of the treatment he or she experienced as 

an individual homeseeker. 

As reported in the Discrimination in Metropolitan Housing Markets: National Results from Phase I HDS 2000 Final Report (HUD, 

2002), researchers found that discrimination persisted in both 

rental and sales markets of large metropolitan areas nationwide 

but that its incidence had generally declined since 1989. African Americans still faced discrimination when they searched 

for rental housing in metropolitan markets nationwide. White 

renters were consistently favored over Black renters in 21.6 

percent of the tests (the net measure, at 2.3 percent, was much 

lower). In particular, White renters were more likely to receive 

information about available housing units and had more opportunities to inspect available units. Discrimination against 

Black renters declined between 1989 and 2000 but was not 

eliminated. The overall incidence of consistent White-favored 

treatment dropped by 4.8 percentage points, from 26.4 percent 

in 1989 to 21.6 percent in 2000. 

Hispanic renters nationwide also faced significant levels of 

discrimination. Non-Hispanic White renters were consistently 

favored in 25.7 percent of tests (the net measure was 6.1 percent). Specifically, non-Hispanic White renters were more likely 

to receive information about available housing and opportunities 

to inspect available units than were Hispanic renters. Discrimination against Hispanic renters appeared to have remained 

essentially unchanged since 1989, and Hispanic renters appeared to face a greater incidence of discrimination than Black 

renters.

Previous Research on Discrimination 

Against LGBT People

None of the previous HUD housing discrimination studies included observation of the differential treatment of homeseekers 

on the basis of sexual orientation, and little empirical research 

has focused on housing discrimination against the LGBT community. 

In community-based surveys conducted during the 1980s 

and 1990s with nonprobability samples, many lesbians and 

gay men reported that they had experienced some form of 

housing discrimination. For example, in a statewide survey of 

Pennsylvania lesbians and gay men conducted by the Philadelphia Lesbian and Gay Task Force, housing discrimination was 

reported by between 9 and 16 percent of males (depending 

on race) and between 5 and 11 percent of females (Gross and 

Aurand, 1996). 

In a 2000 Kaiser Family Foundation survey, 11 percent of the 

lesbian, gay, and bisexual respondents said they had personally 

experienced discrimination in renting an apartment or buying 

a home. Another 35 percent said they had not personally 

experienced such discrimination but knew someone else who 

had (Kaiser Family Foundation, 2001). 

In a 2005 national survey of lesbian, gay male, and bisexual 

adults (Herek, 2009a), approximately 4 percent of respondents 

reported they had experienced some form of housing discrimination because of their sexual orientation. Such discrimination 

was more common among gay men (reported by 6.5 percent) 

and lesbians (5.1 percent) than among bisexual men (nearly 

2 percent) and bisexual women (1.3 percent). 

When interpreting these figures, it is important to remember 

that many lesbian, gay male, and bisexual people refrain from 

revealing their sexual orientation in a variety of social situations 

as a way of avoiding stigma (Herek, 2009b). For this reason, 

evaluating the prevalence of housing discrimination would be 

facilitated by knowledge of the extent to which sexual minority 

adults have concealed their sexual orientation from potential 

landlords and real estate agents. 

A survey of more than 6,000 transgender people by the 

National Center for Transgender Equality and the National 

Gay and Lesbian Task Force Foundation (NCTE and NGLTFF, 

2011) indicated significant levels of housing instability for 
An Estimate of Housing Discrimination Against Same-Sex Couples 4

transgender people. Of the respondents, 26 percent reported 

having to find alternative places to sleep for short periods of 

time, 11 percent reported having been evicted, and 19 percent 

reported becoming homeless because of bias.

Although stigma and prejudice based on sexual orientation 

are widespread, and employment discrimination against LGBT 

individuals has been well documented, little empirical research 

has examined housing discrimination against the LGBT community in the United States. The only published studies on 

housing discrimination against gay men and lesbians were 

conducted in Sweden (Ahmed, Andersson, and Hammarstedt, 

2008; Ahmed and Hammarstedt, 2009) and Canada (Lauster 

and Easterbrook, 2011). Ahmed and Hammarstedt (2009) 

e-mailed landlords who had advertised an available apartment 

on an Internet service comparable to the service used for this 

study. The e-mails were ostensibly sent by either a gay male 

couple or by an otherwise comparable heterosexual couple. 

The study found that the heterosexual couple was significantly 

more likely than the gay male couple to receive a response 

to the e-mail, to be asked to provide further information, 

and to be invited to an immediate showing of the apartment. 

Regarding a gross measure of adverse treatment, Ahmed and 

Hammarstedt (2009) found that heterosexual couples were 

favored over gay male couples in getting an e-mail response 

in 12.3 percent of the correspondence tests (not matched 

pairs); the net measure was 11.4 percentage points and was 

the only dimension of adverse treatment that was statistically 

significant. No disparities emerged in invitations to contact 

the provider or to a showing of the unit. Ahmed, Andersson, 

and Hammarstedt (2008) did not find comparable differences 

between the responses to a lesbian couple and a heterosexual 

couple. Lauster and Easterbrook (2011) also found no disparity 

between lesbian and heterosexual couples but found that gay 

male couples were less likely than heterosexual couples to 

receive positive responses from housing providers.

The Fair Housing Centers of Michigan, which comprises four 

local fair housing organizations, conducted a testing audit of 

housing discrimination based on sexual orientation (FHC of 

Michigan, 2007) that found disparate treatment in 32 out of 

120 (27 percent) fair housing tests it conducted. Testers posing 

as gay male or lesbian homeseekers received unfavorable treatment regarding whether housing was available, the amount of 

rent, application fees, and levels of encouragement compared 

with the treatment of testers posing as heterosexual homeseekers. 

The gay male and lesbian testers also were subjected to offensive 

comments.
An Estimate of Housing Discrimination Against Same-Sex Couples 5

Research Design

The objective of this study is to develop the first national 

estimate of the level of housing discrimination against samesex couples—that is, men partnering with men and women 

partnering with women—in the electronically advertised rental 

market.

Hypotheses

Given the findings of previous research (for example, Ahmed, 

Andersson, and Hammarstedt, 2008; Ahmed and Hammarstedt, 2009; Lauster and Easterbrook, 2011), we expect 

that a disparity will exist in the responses of housing providers 

to inquiries from heterosexual and from same-sex couples 

expressing interest in electronically advertised rental housing. 

The findings of Ahmed and his colleagues and of Lauster and 

Easterbrook suggest that disparities will be more prevalent between gay male and heterosexual couples than between lesbian 

and heterosexual couples. We expect that same-sex couples, 

and in particular gay male couples, will be less likely than 

heterosexual couples to receive responses from housing providers, invitations to contact providers, and invitations to inspect 

the advertised rental unit. We expect that states with legislative 

protections will have lower levels of discrimination against 

same-sex couples than those without protections because of the 

enforcement mechanism in place. 

E-mail Approach

The way people search for housing has changed dramatically in 

the 21st century, with much of the housing search now taking 

place via the Internet. It is estimated that between 43 and 90 

percent of renters consult the Internet to search for housing 

(Frank N. Magid Associates, Inc., 2005; Horrigan, 2008; 

Wagner, 2008). Housing in this segment of the market has not 

been scrutinized as carefully as housing advertised through 

newspapers or other printed media, however. Although fair 

housing advocates have brought attention to the discriminatory 

nature of the content of advertisements on electronic media, 

little research has brought a systematic focus to how housing 

providers actually treat prospective tenants at the initial stages 

of a housing search through e-mail inquiries. 

A small but growing literature has begun to examine the treatment of protected groups in the online housing market via correspondence testing (for example, Ewens, Tomlin, and Wang, 

forthcoming; Friedman, Squires, and Galvan, 2010; Hogan and 

Berry, 2011). E-mails that are matched on all characteristics 

except those indicating the nature of the protected group (for 

example, race or ethnicity) are sent to housing providers inquiring about the availability of the unit. The only characteristic 

of the e-mail that varies is the text used to convey the nature of 

the protected class (for example, names traditionally associated 

with a particular racial or ethnic group).

The results of an online survey conducted by Community 

Marketing, Inc. (CMI) and MDAC in March 2010 demonstrated 

that, among a sample of 297 LGBT renters who had conducted 

a search for new housing in the previous 12 months, 63 percent 

used the Internet as a primary source in their search, whereas 

18 percent used newspaper ads and articles (CMI and MDAC, 

2010). The CMI/MDAC pulse study further indicated that 77 

percent of the respondents who inquired about rental housing 

through the Internet used the listing site selected for this study. 

The other two most frequently cited websites had only about 

one-third as much usage, 27 and 25 percent.
An Estimate of Housing Discrimination Against Same-Sex Couples 6

Methodology

This study uses an e-mail, or correspondence, test methodology 

to gauge the level of discrimination against same-sex couples in 

the rental housing market, which has not previously been examined on a national scale in the United States. The researchers 

completed 6,833 tests via e-mail, divided between gay male 

couples (3,424 tests) and lesbian couples (3,409 tests). 

In this study, the matched pairs were the e-mails sent to housing providers. Each correspondence test involved sending 

two e-mails to the housing provider, both inquiring about the 

availability of the advertised unit. Each inquiry was from a 

person in a committed relationship asking about an advertised 

one-bedroom apartment. E-mails from heterosexuals referred to 

a relationship partner as “husband” or “wife”; e-mails from gay 

men and lesbians referred to a relationship partner as “partner.” 

Focus groups of gay men and lesbians indicated that the term 

“partner” was most frequently used to indicate a relationship. 

Moreover, in many states, same-sex marriage is not legally 

recognized; thus, the terms “husband” or “wife” for same-sex 

partners might be used unevenly across the country. 

The text of the matched-pair e-mails contained similar language 

asking about the housing unit for rent. The only difference 

between the two e-mails was the sexual orientation of the tester 

making the inquiry. In the case of gay male couples, male 

names were used by the individual signing the e-mail and for 

the partner of that individual. In the case of lesbian couples, 

female names were used. 

The Internet listing site used in this project was chosen as the 

universe from which to sample the electronic advertisements 

because the first contact between the prospective renter and 

the housing provider can always occur via e-mail. Several 

other electronic search engines require prospective renters to 

complete an online registration form asking for their phone 

numbers and current addresses, which would permit housing 

providers to contact prospective renters by phone rather than 

limit the contact to e-mail responses. The chosen site is also 

ideal because the format of the advertisements and the nature 

of the contact between providers and prospective tenants are 

uniform throughout the country.

Selecting Markets

The primary objective of the sampling plan was to obtain data 

that would (1) produce nationally representative metropolitanmarket estimates of various measures of housing discrimination 

against same-sex couples; (2) to the extent possible, produce 

estimates of these measures by whether a state had legislative 

protections prohibiting housing discrimination on the basis of 

sexual orientation; and (3) to the extent possible, produce estimates of these measures for individual markets, by market size.

Random Sample of Markets

The sampling frame used a proportional-to-population-size 

(PPS) approach to randomly select 50 markets from among 

the 331 metropolitan statistical areas (MSAs) or primary metropolitan statistical areas (PMSAs), based on the 2000 census 

definitions. The selection of these areas permitted inclusion of 

larger and smaller markets for the sample, facilitating a more 

nationally representative sample. 

Using information available in the 2005–2009 American Community Survey (ACS) 5-year estimates, we estimated the total 

population for each market by applying the county allocation 

to MSAs and PMSAs available in MABLE/Geocorr. The markets 

selected for inclusion in the sampling frame are those with a 

population of at least 100,000, which is sufficient to (1) ensure 

adequate coverage on the Internet listing service so that enough 

unique housing providers could be sampled and (2) support a 

systematic testing effort on same-sex couples. Selecting markets 

with populations of 100,000 or more substantially increases 

the likelihood of choosing an area with a sufficient number and 

percentage of same-sex couples to support the proposed number of tests.4

 Of the 331 MSAs,5 94 percent (312) had sufficient 

total populations to be eligible for inclusion in the sampling 

population.6 The sampling process then selected markets with 

PPS sampling. 

4

 The estimated number of same-sex households is highly correlated with estimated total population size (r = 0.97). The likelihood within each stratum of selecting 

a market with at least 250 same-sex households (based on 2005–2009 ACS 5-year estimates) is as follows: less than 100,000, 21 percent; 100,000 to 250,000, 69 

percent; 250,000 or more, 100 percent.

5

 The analysis uses 2000 census definitions for MSAs and PMSAs. We estimate population and same-sex households using the 2007–2009 ACS 3-year estimates for 

county-level data aggregated to the MSA level.

6

 The analysis eliminates six MSAs and PMSAs in Puerto Rico from the sampling frame.
An Estimate of Housing Discrimination Against Same-Sex Couples 7

Sampling Strategy

Allocation of Tests Across Markets

In the first stage of the sampling procedure, we classified selected markets by stratum, which distinguishes markets by the 

size of the total population. We defined various strata based on 

population size: insufficient population to support a systematic 

testing effort (less than 100,000), small (100,000 to 249,999), 

medium (250,000 to 399,999), medium-to-large (400,000 to 

749,999), large (750,000 to 1,499,999), very large (1,500,000 

to 4,999,999), and largest (5,000,000 or more). The PPS 

sample yields a higher representation of larger markets, thus 

reducing concerns about sampling adequate numbers of unique 

housing providers and permitting within-market exploration 

of housing market discrimination against gay male and lesbian 

couples. Achieving the targeted number of tests in the small

stratum was not possible in the relatively short study period 

(14 weeks) without duplicating providers and running the risk 

of detection. Given this difficulty, we collapsed the small and 

medium strata to create a small-to-medium stratum and renamed 

the medium-to-large stratum medium. The result was five strata 

for market size analysis. 

In the second stage of the procedure, we sampled advertised 

rental units from online listings. After randomly selecting a 

market using the PPS approach, we identified whether the 

market was covered by the selected listing service. For a market 

to be included in the sample, it had to have complete coverage 

throughout the metropolitan area being sampled. For example, 

for the Washington, D.C. market to be included in our sample, 

the range of advertised units had to be in areas throughout 

the metropolitan area (for example, Fairfax County, Virginia; 

Prince George’s County, Maryland; the District of Columbia; 

and so on) and not in only one of those jurisdictions. If the 

listing service did not cover all of a selected market, it was 

not included in the sampling frame, and another market was 

randomly selected using PPS sampling. This process ensured a 

final sample of 50 markets with complete coverage. 

Table 1 shows the distribution of the sampled listings representing unique housing providers (landlords) across population 

size strata. The distribution of listings sampled generally conformed proportionally to population across strata. The goals 

for the size and composition of the sample were 9,100 tests 

across the 50 sampled markets, with the number of tests within 

a market divided between gay male couple-heterosexual couple 

matched-pair tests and lesbian couple-heterosexual couple 

matched-pair tests. Appendix A provides a table illustrating 

the distribution of the originally proposed 9,100 tests. Table 1 

reflects the distribution of the actual sample of 6,833 tests.

We originally chose a target of 9,100 tests to ensure a reasonable margin of error—within 1 percentage point, at 95 percent 

confidence—for the national gross measure of discrimination 

against same-sex couples. Because we could not sample duplicate providers and the timeframe for conducting the testing was 

relatively short (14 weeks), we achieved 6,833 tests across the 

50 sampled markets. We estimate the overall consistency measure for gay male-heterosexual tests and lesbian-heterosexual 

tests within 1.7 percentage points. Therefore, despite the difference between the originally proposed number of tests and the 

number of achieved tests, our estimates of differential treatment 

remain within a reasonable range.

One of the strategies of the data collection was to sample 

housing providers only once within each metropolitan area to 

minimize the chances that the provider would detect the testing 

in the study. The listing service used for this study contains 

multiple advertisements from the same housing providers. 

Some are easy to identify and others are not. For example, in 

housing markets where real estate agencies list available rental 

units, such agencies can post multiple ads by multiple agents 

within the same company. If those agents see similar e-mail 

messages for different available rental units, they might detect 

the testing, which could bias the results of the study. 

To minimize the chances of detection, an automated scraping 

tool was used to scrape, or select, the ads from each of the 50 

Table 1. Number of Paired Tests in Each Stratum

a

 Based on the population residing in micropolitan or metropolitan markets with populations of at least 100,000. Less than 1 percent of all people reside in markets with 

populations of 100,000 or less.

Population Size Stratum

Percent of 

Populationa

(%)

Matched-Pair Tests 

Gay Male

(N)

Lesbian

(N)

Total

(N) 

Percent of

Total Tests

(%)

100,000 to 400,000 (small-to-medium) 15 124 122 246 4

400,000 to 750,000 (medium) 14 250 253 503 7

750,000 to 1,500,000 (large) 14 387 373 760 11

1,500,000 to 5,000,000 (very large) 39 1,763 1,761 3,524 52

5,000,000 or more (largest) 18 900 900 1,800 26

Total 100 3,424 3,409 6,833 100
An Estimate of Housing Discrimination Against Same-Sex Couples 8

markets. The scraping tool is an existing computer software 

program, modified to meet the needs of this study. On a given 

day, the tool created a partially complete entry for each ad 

by extracting some data from its page. The tool then filtered 

the information so that the sampling frame included only 

one-bedroom apartments for rent. The tool also used filters to 

exclude ads that did not provide the address, cross street, rent, 

or reply-to e-mail for the unit. These scrape files were loaded 

daily into a Microsoft Access database. Within a market, the 

Access database would then screen out any new advertisement 

for which the housing provider was already in the database 

(that is, contained a duplicate phone number, address, agent or 

owner name, e-mail address, and so on). Files that remained in 

the database were considered to be unique housing providers. 

These files were provided at random to test administrators, 

who then reviewed the partial data entry (correcting if necessary) and completed it with the information that the scraper 

was not designed to extract (for example, the kind of unit, 

presence of discriminatory statements, and so on). The test 

administrator would then submit the posting to the e-mail 

scheduling program. The Access database would run a second 

check for duplicate information on the newly completed posting entry and, if the entry was not from a duplicate landlord, 

the e-mail address associated with the posting entry would 

have a paired e-mail test scheduled. This selection process was 

continued until the targeted number of listings within each 

market for each stratum was reached. Listings within each 

stratum were divided equally between gay male-heterosexual 

tests and lesbian-heterosexual tests.

Post Sampling: Identify LGBT Protections

For each listing in the final sample, we determined whether the 

location for the listing is subject to state-level legislative protections against housing discrimination on the basis of sexual 

orientation. We classified listings for which the location of the 

housing unit is covered by such protections as “Legislatively 

Protected,” while we classified other listings as “Not Legislatively Protected.” Only state-level protections were determined; 

local jurisdiction protections were not identified.

Although the purpose of the study was to obtain statistically 

valid national estimates, sample sizes within subgroupings 

permitted statistically valid gross or net measures of housing 

discrimination against gay men and lesbians for three primary 

factors: (1) legislative protections (covered by protection for 

sexual orientation or not), (2) MSA population size stratum, 

and (3) individual markets for metropolitan areas with populations exceeding 5 million. 

Selection of Housing Providers

After the 50 study areas were selected, the selection of housing 

providers or landlords commenced. This sampling was completed in two stages. 

The first stage used an automated scraping tool or gather ads 

within each of the 50 study areas for one-bedroom apartments 

for rent. The tool took all the ads from a given regional website, screened them based on criteria provided, and stored the 

information from the ads in a searchable database. The software 

was programmed to navigate through the metropolitan areas 

listed in the sampling frame and save each newly added rental 

posting (advertising one-bedroom units) to a local server. This 

group of listings was then scraped to extract textual information contained within each posting. This scraping process 

involved two different kinds of extraction: 

1. Structured extraction entails identifying textual information 

that is entered into categorized forms at the time of the 

posting’s creation or generated by the website. Structured 

items are associated with tags the listing service creates upon 

generation and are therefore readily identified with simple 

programming techniques. Structured information includes 

items such as the address or cross streets of a listing, “Posting ID,” and the date and time of the original posting. 

2. Unstructured extraction entails identifying information that 

is not associated with predetermined tags but is likely to be 

in a posting. Phone numbers and e-mail addresses are often 

present in the body of the text generated by the poster. The 

program is cued to this information by the presence of “-” 

(dashes), “@” (at signs), and other patterns. These cues are 

not 100 percent accurate but, when used in conjunction 

with other known language patterns (that is, the number of 

digits associated with a telephone number), can yield high 

accuracy in the extraction of data from free-form text.

In the second stage, newly saved postings and the corresponding data that were scraped from these postings were provided 

daily. The data provided were from a query that was filtered 

to retain only one-bedroom units that had address or crossstreet information. These queried datasets were loaded to the 

Audit-Level Database in Microsoft Access. These data did not 

constitute complete audit-level entries, but they were screened 

by the scraper tool for a minimum level of data to constitute a 

useable listing. Test administrators reviewed the scraped data 

against the original listing and completed the coding of the listing. These data were screened twice by the Access database for 

duplicate landlords (once before the test administrator’s review 

and coding and once after).
An Estimate of Housing Discrimination Against Same-Sex Couples 9

For each study area, a new scrape file was loaded to the Access 

database from the Internet listing service each day (for 6 days 

of a given week). The sampling of landlords took place during a 

14-week period to allow for a comprehensive representation of 

landlords and available one-bedroom rental units within each 

metropolitan area. Manual processing of Internet listings in 

Access took place 6 days a week, although scraping took place 

7 days a week (two scrape files were loaded each Monday). 

Conducting the E-mail Testing

Overview

After the markets to be sampled were selected and advertisements were scraped, postings from each of those markets were 

loaded to the database and matched-pair e-mail testing commenced. During the 14-week data collection period, from June 

through October 2011, postings processed in the audit-level 

database were randomly assigned to matched pairs of e-mails 

from gay male and heterosexual couples or from lesbian and 

heterosexual couples. The procedures in the following list were 

used in executing the tests and in collecting the resulting data 

to minimize the risk of detection by housing providers involved 

in the correspondence tests. 

Procedures for Executing the E-mail Tests

1. Names. First names and e-mail accounts were created for 

the e-mails from prospective gay male, lesbian, and heterosexual renters. In addition, names were created for partners 

of the gay male and lesbian renters and for spouses of the 

heterosexual renters. Eight lists of names were created:

a. Heterosexual renters inquiring about the unit who are 

female.

b. Heterosexual renters inquiring about the unit who are male.

c. Heterosexual renters’ husbands.

d. Heterosexual renters’ wives.

e. Lesbian renters inquiring about the unit.

f. Lesbian renters’ partners.

g. Gay male renters inquiring about the unit.

h. Gay male renters’ partners.

The names appearing on these lists came from the Social Security Administration’s website of popular baby girls’ and boys’ 

names.7 The top 20 girls’ names and the top 20 boys’ names in 

the United States from 1970 through 1985 (between ages 25 

and 40 at the time of the study; that is, individuals who were 

likely to be in the market for rental housing) were retrieved from 

this site. These boys’ and girls’ names were then consolidated 

into two master lists. The names on each of these master lists 

were then filtered to eliminate duplicates, gender-neutral names 

(for example, “Shannon”), and to include race-neutral names.

After the master lists of male and female first names were created, within each study area the two sets of 20 names (40 total 

names) were randomly divided into the eight conditions of a 

2 (Gender) X 2 (Sexual Orientation) X 2 (e-mail sender/sender’s 

partner) counterbalance. The result was eight lists of 5 names 

each, falling into the listed conditions, a through h, described 

in the preceding list. Appendix C provides the full list of male 

and female names.

2. E-mail Accounts. After the lists of names were completed, 

the e-mail addresses were developed. Each of the 20 names 

was randomly assigned to a Yahoo!, Hotmail, or Gmail e-mail 

address in each of the 50 study areas to create 1,000 unique 

e-mail addresses. Thus, in each study area, each name that was 

used to sign the e-mails from prospective renters had a unique 

e-mail account. We assigned an account that closely resembled 

the first name selected but made some modifications (for example, inserting numbers after the name) because of existing 

accounts. So, for example, the name “Jennifer” for heterosexual 

female renters could appear on the list for both the New York 

and Chicago metropolitan areas. Each of these Jennifers would 

be randomly assigned to a different e-mail account. For example, Jennifer in New York would have the e-mail account, 

jennifer312@gmail.com, but Jennifer in Chicago would be 

assigned jennifer65@yahoo.com. This one-time randomization 

of names to e-mail domains was critical to facilitating the tracking of e-mails that were sent to and received from housing 

providers.

3. Randomization. After the names were assigned to the e-mail 

domains on the four lists, tables were developed in the Access 

database to randomize each of the following necessary elements 

of all the tests to be conducted:

a. The names given to the testers in each test.

b. The names given to the partner referred to in each e-mail 

text. (Note: this one-time randomization meant that the 

names of the renter and partner/spouse were always 

paired together. This procedure made the inquiries more 

realistic and lessened the chances of detection.)

c. The e-mail subject line and text (including the greeting 

and closing). Appendix D reproduces the e-mail subject 

lines and text.

d. Which e-mail was sent first to the provider.

7 http://www.ssa.gov/oact/babynames/state/index.html.
An Estimate of Housing Discrimination Against Same-Sex Couples 10

The e-mail text was developed to vary such that the wording 

realistically conveyed to the housing provider that the person 

inquiring about the unit came from a heterosexual, gay male, 

or lesbian couple. The remaining text in the e-mail inquiries 

and in the subject lines, however, was designed not to differ in 

any other significant ways. This methodology was employed as 

another way to reduce the potential for detection if a housing 

provider was accidentally sampled more than once. Randomizing the order in which the heterosexual and the same-sex 

couple e-mails were sent decreased the likelihood that the 

treatment of these couples was because of the order in which 

the e-mails were received. 

4. Preparing the e-mails to be sent. Using a “mail merge” 

feature, all the randomized elements were combined into the 

messages sent to the housing providers. The text of the e-mails 

was constructed based on the components created in steps 2 

and 3. 

5. Sending the e-mails. Test administrator staff sent the e-mail 

inquiries to the landlord of the identified housing unit. The 

inquiries were made 1 day after the posting of the advertisement. In addition, the staff left about a 2-hour gap between the 

times when the e-mails were sent to the provider from each 

of the two parties in the matched-pair test. This procedure reduced the likelihood that landlords or housing providers would 

suspect that they were being tested. Initially, the software utility 

package called “Letter Me Later” was used by staff to automate 

the process, but it was later discontinued, and an add-on for 

Access with the same function was used instead. This software 

enabled the staff to schedule the e-mails to be sent at particular 

times and ensured that the order in which landlords received 

inquiries was properly varied, with each e-mail having a 50-50 

chance of being sent first.

Procedures for Coding the Data

The data coded for the project came from four sources: (1) the 

scraping tool, (2) items about the advertised unit or landlord 

that could not be gleaned from the scraping tool, (3) the 

process by which the correspondence test was conducted (the 

time of day the e-mail was sent, which couple sent their e-mail 

first, and so on), and (4) the response or nonresponse from the 

landlord. Also, the data gathered from sources 1 and 2 on the 

address of the unit were geocoded to the census tract level so 

that census data could be merged with the data collected in this 

study. Appendix E contains the complete data dictionary, and 

the following list presents each set of items in more detail.

1. The test administrator responsible for conducting the 

correspondence tests was also charged with coding the data 

for each test. The first set of data, on the housing unit and 

the landlord, came directly from the scraping tool. These 

data were included in an Access database for the geographic 

area in which the correspondence tests were conducted. 

Such data included the metropolitan area (area searched 

to find ad), subject line of the ad, posting ID, listing date, 

listing time, listing category (fee, no fee, by owner, “n/a”), 

monthly rent, size of largest image file (in number of pixels), 

site-specific e-mail (that is, reply-to e-mail), and information 

associated with the following Internet listing service tags 

(XXTAGS): “xstreet1” (that is, address or first cross street), 

“xstreet2” (that is, second cross street), “city,” “state,” 

“catsAreOK” (cats allowed), “dogsAreOK” (dogs allowed), 

“feedisclosure,” and “company name.” 

2. The second set of data was coded based on other aspects 

of the advertisement or the landlord not directly available 

from the scraping tool: real estate or management company, 

agent name, name of owner, reference number, e-mail 

address (from body of text), phone numbers, street address, 

cross streets, city or town, ZIP code, state, additional unit 

information, broker fee, broker fee amount, application 

fee, security deposit, security deposit amount, other fee, 

other fee amount, rent discount offered, description of 

rent discount, lease in ad, lease term, equal opportunity 

statement, protected class restriction, links to external 

URLs, full text of listing, and the presence or absence of 

the following key words and phrases: “equal opportunity 

housing,” “female,” “senior,” “section 8,” “vacation,” “per 

week,” “weekly,” “move in special,” “immediately,” and 

“before the first of the next month.” 

3. The test administrator coded data in the Access database 

about the process by which the correspondence tests were 

conducted. These data included the name of the prospective 

renters used in the test, the names of their spouses or partners, the sexual orientation depicted in the e-mail, the 

specific e-mail text, the subject line, the e-mail domain, the 

order in which the e-mails were sent (that is, whose e-mail 

was sent to the provider first), and the time and date when 

the e-mail was sent. 

4. The final set of data that each test administrator coded into 

the Access database included the response that each test 

e-mail received (or did not receive) from the housing provider. 

After test administrators conducted the correspondence test, 

they coded the data from the housing provider responses 
An Estimate of Housing Discrimination Against Same-Sex Couples 11

as they came into the prospective renters’ e-mail inboxes 

during a 2-week period. The response was linked to the 

Access spreadsheet, and the content of the response was 

coded. The data collected on the responses included—

a. Whether each prospective renter received a response.

b. Whether they received more than one response.

c. Whether they were told the advertised unit is available.

d. Whether they were invited to inspect the unit.

e. Whether they were advised to call the housing provider.

f. Whether they were asked to provide additional information regarding their quality as an applicant (for example, 

their credit score or income).

g. Whether they were reminded about qualifications they 

must possess to rent the unit.

h. Whether they were given a reason for the unit not being 

available (if the unit was not available).

i. Whether they were sent an ambiguous sign of availability 

(for example, “The unit is technically available, but an 

application has been filled out and we’re pretty sure it’s 

going to go through”).

j. Whether they were encouraged to look at a different unit 

owned by the same landlord (for example, “This unit 

actually isn’t available, but I have another unit in the 

same building you might be interested in”).
An Estimate of Housing Discrimination Against Same-Sex Couples 12

Data Analysis

The study provides national-level estimates of gross and net 

adverse treatment separately for gay male and lesbian couples, 

by legislative status (whether the advertised unit is in an area 

covered by state-level protections for gay men and lesbians) 

and by the size of metropolitan areas. The results provide 

margin-of-error estimates for the gross and net measures. 

Each test consisted of an e-mail inquiry from the same-sex 

couple and the heterosexual control couple. Results from the 

e-mail tests were analyzed to determine whether the gay male 

or lesbian prospective renter was treated unfavorably relative to 

the control, heterosexual prospective renter. Previous studies of 

housing market discrimination showed that housing providers 

can respond in various ways, both favorable and unfavorable. 

The study looked at five response outcomes, starting with 

whether the test e-mails received any response at all from the 

housing provider and continuing through increasing levels of 

contact and encouragement. More specifically, the outcomes 

included whether the test renter (1) received a response, 

(2) received more than one response, (3) was told the unit 

was available, (4) was invited to inspect the unit, and (5) was 

told to contact the provider. (Although 10 potential response 

variables were contemplated, only these 5 had sufficient 

responses to be included in the analysis.)

For each test, the response to the e-mail inquiry from each couple 

was categorized by whether the inquiry received a favorable 

response. We consider a favorable response to mean a response 

in which the tester received affirmative values on any of the five 

outcomes listed previously (for example, received a response 

and was told the unit was available).

Gross and Net Measures of Adverse 

Treatment 

The gross measure of adverse treatment is the proportion of tests 

in which the heterosexual control couple’s inquiry receives favorable treatment and the gay male or lesbian couple’s inquiry 

receives unfavorable treatment during the housing transaction. Let Yij denote the audit outcome of favorable (Y = 1) or 

unfavorable (Y = 0) for test i for couple j (j = 0 if heterosexual 

[control] and j = 1 if gay male or lesbian for test i). Differential 

treatment that is unfavorable to the gay male or lesbian tester 

will occur when Yi0 = 1, Yi1 = 0. The gross measure of adverse 

treatment is expressed as: 

Gross Measure = P[Yi0 = 1, Yi1 = 0].

We estimate the gross measure of adverse treatment at the 

national level for:

1. Gay male and lesbian couples. 

2. State-level protections against housing discrimination based 

on sexual orientation.

a. Markets with protections.

b. Markets without protections.

3. Market size.

a. Small-to-medium (100,000 ≤ population < 400,000).

b. Medium (400,000 ≤ population < 750,000).

c. Large (750,000 ≤ population < 1,500,000).

d. Very large (1,500,000 ≤ population < 5,000,000).

e. Largest (population ≥ 5,000,000).

We provide estimates of the gross measure and the associated margin of error at a 95-percent level of confidence. The 

estimated standard errors associated with the measures vary 

because of the differing sample sizes within each group. The 

corresponding margin of error is computed as:

Margin of ErrorGross = zc x σ

n

σ

n

,

where 

Margin of ErrorGross = zc x σ

n

σ

n is the standard error and zc

 = 1.96 at 95 percent 

confidence.

The gross measure of discrimination only estimates the likelihood that the control couple is favored relative to the gay male 

or lesbian couple and could overstate incidences of discrimination. In addition to the gross measure, we compute the net 

measure of discrimination, the difference in the proportion of 

tests in which the control couple’s (that is, the heterosexual 

couple’s) inquiry receives a favorable outcome relative to the 

same-sex couple’s inquiry and the proportion of tests in which 

the same-sex couple’s inquiry is favored over the control couple’s 

inquiry. The net measure of adverse treatment is expressed as:

Net Measure = P[Yi0 = 1, Yi1 = 0] - P[Yi0 = 0, Yi1 = 1].

Whereas the gross measure represents a test of one proportion, 

the net measure represents a test of differences in proportions; 

thus, the standard error and resulting margin of error estimates 

differ.
An Estimate of Housing Discrimination Against Same-Sex Couples 13

The margin of error estimate for the net measure is represented as:

Margin of ErrorGross = zc x σp2

 – p2

σp2

 – p2

,

where zc = 1.96 at 95 percent confidence and 

Margin of ErrorGross = zc x σp2

 – p2

σp2

 – p2

 represents the standard error of the difference in the proportions and is 

expressed as:

+

P[Yi0 = 1, Yi1 = 0] x 1 – P[Yi0 = 1, Yi1 = 0]

n1

P[Yi0 = 0, Yi1 = 1] x 1 – P[Yi0 = 0, Yi1 = 1]

n2 .

consistency index if the heterosexual couple received favorable 

treatment on at least one of the five outcomes measures and the 

corresponding same-sex couple received no favorable treatment. 

Tests are classified as “gay male favored” or “lesbian favored” if 

the same-sex couple received favorable treatment on at least 

one of the five outcomes and the heterosexual couple received 

no favorable treatment. Each of these consistency measures 

represents the gross measures. The net measure of the consistency index is calculated by taking the difference between the 

heterosexual-favored index and the gay male-favored or lesbianfavored index.

For a matched-pair test, the number of tests for heterosexual 

and same-sex couples are equal (that is, n1 = n2 = n).

The overall objective of the study was to estimate gross measures 

of adverse treatment of same-sex couples. We also calculate 

composite measures of housing discrimination against gay male 

and lesbian prospective renters. Similar to previous HDS studies, we estimate consistency measures, which reflect the extent 

to which one tester is consistently favored over the other in 

the treatment received from housing providers based on their 

inquiries. Tests are classified as “heterosexual favored” on the 
An Estimate of Housing Discrimination Against Same-Sex Couples 14

Findings

This section presents the findings from the data analysis, focusing on the gross and net measures of discrimination and on the 

consistency indexes. First, we present the national-level estimates 

of the adverse treatment of gay male and lesbian couples, relative 

to heterosexual couples. We then calculate estimates of adverse 

treatment by legislative status (whether the advertised unit is 

in an area covered by state-level protections against housing 

discrimination on the basis of sexual orientation) and the size 

of the metropolitan area in which the unit is advertised. The 

data were gathered from June through October 2011. For the 

five dependent variables of interest, each correspondence test 

could result in one of four outcomes: (1) both testers received 

equivalent responses, (2) neither tester is favored, (3) the heterosexual couple is favored, or (4) the gay male or lesbian couple 

is favored. As discussed in the previous section, the gross measure of adverse treatment refers to when the correspondence test 

favors heterosexual couples. The net measure takes the difference between the proportion of tests favoring the heterosexual 

couple and the proportion of tests favoring the gay male or 

lesbian couple. The consistency index is a summary measure 

of the treatment of heterosexual couples relative to gay male 

and lesbian couples on all five variables.

Table 2 presents the variables of interest and their definitions. 

Table 2. Outcome Variables

Variable Definition

(1) Response provided Whether each prospective renter 

received a response.

(2) More than one response Whether they received more than one 

response.

(3) Available Whether they were told the advertised 

unit was available.

(4) Inspect Whether they were invited to inspect 

the unit.

(5) Contact Whether they were advised to call the 

housing provider.

National-Level Estimates of 

Discrimination

Treatment of Gay Male Couples as 

Compared With Heterosexual Couples

Table 3 presents the outcomes of the e-mail correspondence tests 

between gay male and heterosexual couples at the national level. 

Table 3 shows that, in 49.3 percent of the e-mail correspondence 

tests between heterosexual and gay male couples (column 1), 

both couples received a response from the housing provider. In 

30.6 percent of the tests (column 2), neither the heterosexual 

couple nor the gay male couple received a response from the 

housing provider. Thus, in 79.9 percent of the correspondence 

tests, heterosexual and gay male couples received equal treatment.

On the gross and net measures of adverse treatment in terms of 

the “response provided” variable (columns 3, 4, and 5), heterosexual couples were significantly more likely than gay male 

couples to get a response from housing providers. In 11.6 percent of the correspondence tests, only the heterosexual couple 

received a response from housing providers compared with the 

8.5 percent of tests in which only the gay male couple received 

a response. The net measure (3.1 percent) was statistically 

significant. 

On the other four variables (that is, whether the tester received 

more than one response, was told the unit was available, was 

invited to inspect the unit, and was told to contact the provider), 

the results in columns 3 and 4 of Table 3 demonstrate that, 

except for the “contact” variable, a slightly greater share of tests 

favored heterosexual couples over gay male couples. The net 

measures in column 5, however, show that none of the differences on these four variables is statistically significant.

Table 3. National-Level Gay Male-Heterosexual Tests

NA = not applicable.

* p ≤ .05. ** p ≤ .01. 

Note: The results are weighted to normalize the population levels. Unweighted results are substantially the same and are available upon request.

Outcome

Percent Tester Favored

Both (%) None (%) Heterosexual (%) Gay Male (%) Net Measure (%) N

(1) Response provided 49.3 30.6 11.6 8.5 3.1** 3,424

(2) More than one response 6.1 88.8 2.6 2.6 0.0 1,681

(3) Available 71.9 22.0 3.5 2.6 0.9 1,681

(4) Inspect 66.9 24.1 4.7 4.3 0.4 1,681

(5) Contact 49.4 39.0 5.7 6.0 – 0.3 1,681 

(6) Consistency index NA NA 15.9 13.7 2.2* 3,424
An Estimate of Housing Discrimination Against Same-Sex Couples 15

The consistency index in the last row of Table 3 mirrors the 

findings for each of the five outcomes analyzed separately. In 

15.9 percent of the correspondence tests, the heterosexual 

couple was favored on at least one of the five outcomes and 

the gay male couple was favored on none of the outcomes. In 

13.7 percent of the tests, the gay male couple was favored on 

at least one of the five outcomes and the heterosexual couple 

was favored on none of the outcomes. The difference between 

the two indexes, or net measure (column 5), is statistically 

significant. 

In sum, the results of the correspondence tests between heterosexual and gay male couples demonstrate that the most consistent form of adverse treatment against gay male couples is the 

lack of an initial e-mail response from housing providers. Gay 

male couples were significantly less likely than heterosexual 

couples to receive a response from the housing provider, a 

result that suggests discriminatory barriers at the very threshold 

of the rental housing search. No significant difference emerged 

between gay male and heterosexual couples regarding the other 

four variables, which gauge different aspects of the interaction 

that take place deeper into the search for rental housing.

Treatment of Lesbian Couples as 

Compared With Heterosexual Couples

Table 4 presents the outcomes of our e-mail correspondence 

tests between lesbian and heterosexual couples at the national 

level. The pattern of results is similar to that of the correspondence tests between gay male and heterosexual couples. Table 4 

shows that, in 49.4 percent of the tests (column 1), both couples 

received a response from the housing provider. In 30.5 percent 

of the tests (column 2), neither the heterosexual couple nor the 

lesbian couple received a response from the housing provider. 

Thus, in 79.9 percent of the correspondence tests, heterosexual 

and lesbian couples received equal treatment.

On the gross and net measures of adverse treatment in terms 

of the “response provided” variable (columns 3, 4, and 5), 

heterosexual couples clearly were significantly more likely 

than lesbian couples to get a response from housing providers, 

although the magnitude of the difference was slightly less than 

in the tests between heterosexual and gay male couples. In 

11.2 percent of the correspondence tests, only the heterosexual 

couple received a response from housing providers compared 

with the 8.9 percent of tests in which only the lesbian couple 

received a response. The net measure (2.3 percent) was statistically significant but of less magnitude than the net measure on 

the same variable in the gay male-heterosexual tests. 

On the other four variables of interest, the results in columns 3 

and 4 of Table 4 show that, by contrast to the gay maleheterosexual tests, the lesbian couples were favored in a slightly 

greater share of the tests than the heterosexual couple. The 

net measures in column 5 show that the “contact” variable is 

significant in the negative direction, indicating that the lesbian 

couple receives favorable treatment compared with that of the 

heterosexual couple. Although this result is unexpected, the 

magnitude is quite small (1.6 percent). On the other hand, 

the result for the variable “more than one response” is in the 

expected direction, with heterosexual couples significantly 

more likely to be favored than lesbian couples. With respect 

to the consistency measures in the last row of Table 4, in 15.6 

percent of the correspondence tests, the heterosexual couple 

was favored on at least one of the five outcomes and the lesbian 

couple was favored on none of the outcomes. In 14.3 percent 

of the tests, the lesbian couple was favored on at least one of 

the five outcomes and the heterosexual couple was favored on 

none of the outcomes. The difference between the two indexes 

(column 5) is not statistically significant.

In sum, the results of the correspondence tests between 

heterosexual and lesbian couples reveal that the most prevalent 

form of adverse treatment against lesbian couples is not getting an e-mail response from housing providers as often as 

heterosexual couples. Lesbian couples were significantly less 

likely than heterosexual couples to receive a response from 

the housing provider, a result that, as for gay male couples, 

Table 4. National-Level Lesbian-Heterosexual Tests

NA = not applicable.

* p ≤ .05. ** p ≤ .01.

Note: The results are weighted to normalize the population levels. Unweighted results are substantially the same and are available upon request.

Outcome

Percent Tester Favored

Both (%) None (%) Heterosexual (%) Lesbian (%) Net Measure (%) N

(1) Response provided 49.4 30.5 11.2 8.9 2.3** 3,409

(2) More than one response 7.3 86.2 4.1 2.4 1.7** 1,679

(3) Available 71.7 21.3 3.4 3.6 – 0.2 1,679

(4) Inspect 67.3 24.5 3.6 4.7 – 1.1 1,679

(5) Contact 49.0 41.3 4.1 5.7 – 1.6* 1,679

(6) Consistency index NA NA 15.6 14.3 1.3 3,409
An Estimate of Housing Discrimination Against Same-Sex Couples 16

suggests discriminatory barriers at the threshold of the rental 

housing search. Although lesbian couples are also significantly 

less likely to have received more than one response from the 

housing provider, they are significantly more likely to be 

advised to contact the housing provider. This mixed pattern is 

worthy of further investigation. 

Estimates of Discrimination by 

Legislative Jurisdiction

Effect of Legislative Protections for Gay 

Male Couples

Table 5 presents the outcomes of our e-mail correspondence 

tests between gay male and heterosexual couples, disaggregated 

by whether the advertised unit was in a state with legislative 

protections against housing discrimination based on sexual 

orientation. The results in the table present the gross and net 

measures and the consistency indexes. The level of equal treatment is about the same as that shown in Table 3. 

On the gross and net measures of adverse treatment in terms 

of the “response provided” variable (the first row of Table 5), 

legislative protections appear to do little to change the overall 

pattern of results found in Table 3. In states both with and 

without protections for sexual orientation, heterosexual couples 

were significantly more likely than gay male couples to get a 

response from housing providers. In protected states, in 11.6 

percent of the correspondence tests, only the heterosexual 

couple received a response from housing providers compared 

with the 8.3 percent of tests in which only the gay male couple 

received a response. The net measure (3.2 percent) was statistically significant. In unprotected states, in 11.5 percent of the 

tests, only the heterosexual couple received a response from 

housing providers, compared to 8.3 percent of tests in which 

only the gay male couple received a response. The net measure 

(3.2 percent) was statistically significant. 

On the other four variables of interest, the results in Table 5 

indicate that, in states with protections, a slightly greater share 

of tests favored heterosexual couples over gay male couples. 

The net measures for Legislatively Protected, however, show 

that none of the differences on these four variables is statistically significant. In unprotected states, a slightly greater share 

of tests favored heterosexual couples over gay male couples on 

the variables “available” and “inspect.” On the variables “more 

than one response” and “contact,” however, a slightly greater 

share of tests favored gay male couples over heterosexual 

couples. The net measures for Not Legislatively Protected show 

that none of these differences is statistically significant. 

The results for the consistency indexes in the last row of Table 5 

illustrate a negative effect of legislative protections. In 16.0 percent of the Legislatively Protected correspondence tests, the 

heterosexual couple was favored on at least one of the five 

outcomes and the gay male couple was favored on none of the 

outcomes. In 12.9 percent of the tests, the gay male couple was 

favored on at least one of the five outcomes and the heterosexual 

couple was favored on none of the outcomes. The difference 

between the two indexes, or net measure (column 4), is statistically significant. The Not Legislatively Protected columns in 

Table 5, however, reveal that the net measure (1.6 percent) is 

not statistically significant in states with no state-level protections 

against housing discrimination based on sexual orientation. 

The slightly greater prevalence of gay male-favored treatment 

on the “more than one response” and “contact” variables likely 

accounts for the lack of significance of the net measure in 

unprotected states.

The results of the correspondence tests between heterosexual 

and gay male couples, disaggregated by legislative protections, 

demonstrate that adverse treatment against gay male couples, 

regardless of legislative jurisdiction, consists of whether they 

received an initial e-mail response from housing providers. 

Legislative protections appear not to confer an advantage to gay 

male couples by protecting them from adverse treatment in 

this respect. Several factors could account for this unexpected 

Table 5. Gay Male-Heterosexual Tests by State Protection

** p ≤ .01. 

Outcome

Percent Tester Favored

Legislatively Protected Not Legislatively Protected

Heterosexual 

(%)

Gay Male

(%)

Net Measure 

(%) N Heterosexual (%)

Gay Male

(%)

Net Measure 

(%) N

(1) Response provided 11.6 8.3 3.2** 1,548 11.5 8.3 3.2** 1,876

(2) More than one response 2.7 2.6 0.1 780 2.8 2.9 – 0.1 901

(3) Available 3.6 2.6 1.0 780 3.4 2.6 0.9 901

(4) Inspect 4.1 3.6 0.5 780 5.4 4.4 1.0 901

(5) Contact 6.0 5.6 0.4 780 4.9 4.1 – 1.2 901

(6) Consistency index 16.0 12.9 3.1** 1,548 15.4 13.9 1.6 1,876
An Estimate of Housing Discrimination Against Same-Sex Couples 17

finding, including potentially low levels of enforcement, housing provider unfamiliarity with state-level protections, or that 

protections exist in states with the greatest need for them.

Effect of Legislative Protections for 

Lesbian Couples

Table 6 presents the outcomes of our e-mail correspondence 

tests between lesbian and heterosexual couples, disaggregated 

by whether the advertised unit was in a state with legislative 

protections against housing discrimination based on sexual 

orientation. The results in the table present the gross and net 

measures and the consistency indexes. The level of equal treatment is about the same as that shown in Table 4.

On the gross and net measures of adverse treatment in terms 

of the “response provided” variable (the first row of Table 6), 

legislative protections appear to affect the overall pattern of 

results found in Table 4. In protected states, the percentage of 

tests favoring heterosexual couples (10.8) and those favoring 

lesbian couples (9.2) exhibit no difference in terms of receiving 

a response from housing providers. The net measure (1.7 percent) is not statistically significant. In unprotected states, however, heterosexual couples were significantly more likely than 

lesbian couples to get a response from housing providers. In 

unprotected states, in 11.3 percent of the correspondence tests, 

only the heterosexual couple received a response from housing 

providers compared with the 9.1 percent of tests in which only 

the lesbian couple received a response. The net measure (2.3 

percent) was statistically significant.

Another pattern in Table 6 that diverges from the pattern at the 

national level of analysis is that, in unprotected states, a slightly 

greater share of the correspondence tests favored heterosexual 

couples over lesbian couples in terms of receiving more than 

one response from housing providers. In 3.9 percent of the Not 

Legislatively Protected correspondence tests, only the heterosexual couple received more than one response from housing 

providers compared with the 1.8 percent of tests in which only 

the lesbian couple received more than one response. The net 

measure (2.1 percent) is statistically significant. In protected 

states, the net measure for “received more than one response” 

is not significant. 

On the other three variables of interest, the results in Table 6 

show no statistically significant differences. In states with protections, a slightly greater share of tests favor heterosexual couples 

over lesbian couples on the variables “available,” “inspect,” and 

“contact.” The net measures for Legislatively Protected, however, 

reveal that none of the differences on these three variables is 

statistically significant. In unprotected states, a slightly greater 

share of tests favor lesbian couples over heterosexual couples 

on the variables “available,” “inspect,” and “contact.” The net 

measures for Not Legislatively Protected show that none of 

these differences is statistically significant, however. 

By contrast to the results for “response provided” and “more 

than one response” examined individually, the results for the 

consistency indexes in the last row of Table 6 show no effect 

of legislative protections. In 15.9 percent of the Legislatively 

Protected correspondence tests, the heterosexual couple was 

favored on at least one of the five outcomes and the lesbian 

couple was favored on none of the outcomes. In 14.5 percent 

of the tests, the lesbian couple was favored on at least one of 

the five outcomes and the heterosexual couple was favored on 

none of the outcomes. The difference between the two indexes, 

or net measure, is not statistically significant in protected or 

unprotected states. In sum, the results of the correspondence 

tests between heterosexual and lesbian couples, disaggregated 

by legislative protections, reveal that adverse treatment against 

lesbian couples, in terms of getting an initial e-mail response 

from housing providers and getting more than one response, is 

more prevalent in states without legislative protections. Unlike 

the case with gay male couples, legislative protections do appear to confer some advantages to lesbian couples in preventing 

them from experiencing adverse treatment, consistent with our 

hypothesis.

Table 6. Lesbian-Heterosexual Tests by State Protection

Outcome

Percent Tester Favored

Legislatively Protected Not Legislatively Protected

Heterosexual 

(%)

Lesbian

(%)

Net Measure 

(%) N Heterosexual (%)

Lesbian

(%)

Net Measure 

(%) N

* p ≤ .05. ** p ≤ .01. 

(1) Response provided 10.8 9.2 1.7 1,558 11.3 9.1 2.3* 1,851

(2) More than one response 3.6 3.5 0.1 796 3.9 1.8 2.1** 883

(3) Available 4.0 3.6 0.4 796 3.2 3.7 – 0.6 883

(4) Inspect 4.5 4.3 0.3 796 3.6 4.3 – 0.7 883

(5) Contact 5.3 4.4 0.9 796 4.2 6.2 – 2.0 883

(6) Consistency index 15.9 14.5 1.4 1,558 15.3 14.1 1.2 1,851
An Estimate of Housing Discrimination Against Same-Sex Couples 18

Estimates of Discrimination by 

Metropolitan Market Size

Table 7 presents the outcomes of our e-mail correspondence 

tests between gay male and heterosexual couples, disaggregated 

by five categories of metropolitan area based on the total population: (1) small to medium (100,000 to 399,999), (2) medium 

(400,000 to 749,999), (3) large (750,000 to 1,499,999), (4) very 

large (1,500,000 to 4,999,999), and (5) largest (5,000,000 or 

more). For the sake of brevity, the results in the table focus on 

the net measures and consistency indexes. 

Table 7 presents no clear-cut pattern in the effect of metropolitan market size on the net measures of adverse treatment of 

gay male couples relative to heterosexual couples. The results 

for the “response provided” variable appear to indicate that 

a greater share of tests favored heterosexual couples over gay 

male couples. Only the net measure for the largest stratum (6.0 

percent) is statistically significant, however (see column 5). 

In the very large stratum, a slightly greater share of tests favored 

heterosexual couples over gay male couples on the variables 

“available” and “inspect.” The net difference measures in column 4 

(1.7 and 1.9 percent, respectively) are statistically significant. 

None of the net measures in the other categories of metropolitan 

market size for the other four variables is statistically significant. 

The results for the consistency indexes in the last row of Table 7 

also do not reveal any clear-cut pattern of adverse treatment. 

Only in the case of the largest stratum is the net measure (4.9 

percent) statistically significant. The greater prevalence of 

heterosexual-favored treatment on the “response provided” 

variable in that stratum likely accounts for the significance of 

the net measure for the consistency index.

In sum, the results of the correspondence tests between heterosexual and gay male couples, disaggregated by metropolitan 

market size, reveal that the effect of metropolitan market size 

on adverse treatment is not straightforward. In the largest 

stratum, consistent with the national-level results, the adverse 

treatment of gay male couples existed in the form of not getting 

an e-mail response (the results are insignificant for the other 

market sizes). In the very large stratum, heterosexual couples 

were significantly more likely than gay male couples to be told 

that the unit was available (that is, the difference is 1.7 percentage points) and to be invited to inspect the unit (that is, the 

difference is 1.9 percentage points). 

Table 8 presents the outcomes of our e-mail correspondence 

tests between lesbian and heterosexual couples, disaggregated 

by categories of metropolitan market size. Like the results for 

the gay male-heterosexual correspondence tests, the results in 

Table 8 reveal no clear-cut pattern in the effect of metropolitan 

market size on the net measures of adverse treatment of lesbian 

couples, relative to heterosexual couples. The results for the 

“response provided” variable (the first row in Table 8) appear 

to indicate that a greater share of tests favored heterosexual 

couples over lesbian couples. Only the net measure for the 

small-to-medium stratum (8.2 percent) is statistically significant, however (see column 1). 

On the other four variables of interest, the results in Table 8 

show that, in the large stratum, a slightly greater share of tests 

favored heterosexual couples over lesbian couples on the 

variable “more than one response.” The net measure for this 

variable reveals that the difference (4.5 percentage points) is 

statistically significant. Contrary to our expectations, within 

the same metropolitan market size category, the results show 

that a slightly greater share of tests favored lesbian couples over 

heterosexual couples on the variable “contact.” The net measure 

(-5.1 percent) for this variable is statistically significant. None 

of the net measures in the other categories of metropolitan market size for the other four variables is statistically significant. 

Consistent with the results disaggregated by legislative protections, the results for the consistency indexes in the last row of 

Table 8 show that none of the net measures are statistically significant. Taken together, the results of the correspondence tests 

between heterosexual and lesbian couples, disaggregated by 

metropolitan market size, reveal that the effect of metropolitan 

market size on adverse treatment is not straightforward.

Table 7. Gay Male-Heterosexual Net Measures by Metropolitan Market Size

Outcome

Net Measure (%)

Small-to-Medium 

(100,000–400,000)

Medium

(400,000–750,000)

Large

(750,000–1.5 million)

Very Large

(1.5–5 million)

Largest

(5+ million)

(1) Response provided 4.0 1.2 3.9 1.9 6.0**

(2) More than one response 3.1 0.8 – 1.1 – 0.8 1.4

(3) Available – 3.1 0.8 1.6 1.7* – 0.2

(4) Inspect – 1.6 0.8 – 1.6 1.9* – 0.2

(5) Contact – 7.8 3.0 0.5 – 0.1 – 1.6

(6) Consistency index 0.0 2.8 2.3 1.0 4.9**

Total audits/audits in which both testers 

received response

124/64 250/133 387/182 1,763/877 900/425

* p ≤ .05. ** p ≤ .01.
An Estimate of Housing Discrimination Against Same-Sex Couples 19

Table 8. Lesbian-Heterosexual Net Measures by Metropolitan Market Size

Outcome

Net Measure (%)

Small-to-Medium 

(100,000–400,000)

Medium

(400,000–750,000)

Large

(750,000–1.5 million)

Very Large

(1.5–5 million)

Largest

(5+ million)

(1) Response provided 8.2* 2.8 2.7 1.2 2.2

(2) More than one response 5.4 2.1 4.5* 0.7 – 0.2

(3) Available 1.8 1.4 – 2.3 0.0 – 0.2

(4) Inspect 3.6 – 5.7 – 2.8 – 0.5 2.6

(5) Contact – 5.4 – 3.6 – 5.1* 0.0 1.4

(6) Consistency index 8.2 0.8 0.3 0.8 2.0

Total audits/audits in which both testers 

received response

122/56 253/140 373/177 1,761/880 900/426

* p ≤ .05.
An Estimate of Housing Discrimination Against Same-Sex Couples 20

Conclusions and Implications

This is the first national-scale, paired-testing study to assess 

rental housing discrimination against same-sex couples in 

metropolitan rental markets that selects properties via Internet 

advertising. In addition, the study calculates estimates of 

adverse treatment by state-level protections and by the size of 

metropolitan areas. 

From June through October 2011, same-sex couples 

experienced significant levels of adverse treatment relative to 

comparable heterosexual couples when they responded to 

electronically advertised rental housing in metropolitan rental 

housing markets nationwide. Our gross estimates of discrimination, which reflect the extent to which heterosexual couples 

were consistently favored over gay male or lesbian couples, 

are 15.9 and 15.6 percent, respectively. These estimates from 

2011, which are based on e-mail correspondence tests, are 

comparable to, but lower in magnitude than, the incidence 

of consistently White-favored treatment, relative to Black and 

Hispanic homeseekers, found through in-person audits in 

HDS2000 (that is, 21.6 and 25.7 percent, respectively). The 

net measures (or lower bound estimates of discrimination) 

reported in this study, as based on the consistency indexes, 

are 2.2 percent (gay male-heterosexual tests) and 1.3 percent 

(lesbian-heterosexual tests), and only the former is statistically 

significant. Although the magnitude of the level of discrimination reflected by the net measure is considerably lower than 

that conveyed by the gross measure, it is nearly the same as 

the net measure reflecting the treatment of White prospective 

renters relative to Black prospective renters in HDS2000 (that 

is, 2.3 percent, not statistically significant). 

Discrimination against gay men and lesbians appears to take a 

relatively consistent form in the rental housing market. Adverse 

treatment of same-sex couples stems largely from the lower 

likelihood that housing providers will respond to their initial 

e-mail compared with the greater likelihood that heterosexual 

couples will receive a response. Given that this study employed 

the use of paired correspondence tests rather than in-person, 

paired tests, and given that it allowed for only one e-mail interaction between each tester and the housing provider, the estimates of discrimination presented here could underestimate the 

extent to which heterosexual couples are favored over same-sex 

couples in the rental housing market. In addition, relatively 

few tests were conducted in smaller metropolitan areas, where 

some researchers hypothesize that more discrimination occurs. 

Nevertheless, it is helpful to know that the results of this study 

are reasonably consistent with the results from HDS2000, 

which examined racial and ethnic disparities in access to rental 

housing and conducted in-person tests rather than e-mail correspondence tests. 

Disaggregating the results by state-level legislative protections reveals some findings that run contrary to our main 

expectation. The results of the correspondence tests between 

heterosexual and gay male couples show that adverse treatment against male couples in the form of getting an initial 

e-mail response from housing providers exists in states with 

and without legislative protections. Legislative protections for 

sexual orientation appear not to confer an immediate advantage 

to gay male couples in whether they experience adverse treatment. By contrast, for lesbian couples, the results imply that 

adverse treatment in the form of whether an e-mail response 

was received from housing providers and in whether more than 

one response was received is more apparent in states without 

legislative protections. Unlike what the results suggest for gay 

male couples, legislative protections do appear to confer a 

slight advantage to lesbian couples in preventing them from 

experiencing adverse treatment, a finding that is consistent with 

expectations. It could be that places with legislative protections 

have higher levels of discrimination against same-sex couples 

than those without protections. It is possible that a historically 

higher level of discrimination in such places necessitated the 

protections. Such protections take time to work, and it is possible that disparities could be higher in places with protections 

because of this adjustment period, given the recent passage of 

many of the protections. 

The results of the correspondence tests between heterosexual 

and same-sex couples, disaggregated by metropolitan market 

size, are not straightforward for either gay male or lesbian couples. Consistent with the national-level results, we find some 

adverse treatment of gay male and lesbian couples regarding 

their getting an initial e-mail response. For gay male couples, 

the adverse treatment exists only in the very large stratum of 

markets. For lesbians, it exists only in the small-to-medium 

stratum. It is not clear what accounts for this pattern of results. 

Although its use of paired testing via correspondence tests and 

its national scope are strengths, the study design is limited 

to tests of rental housing that is in metropolitan markets and 

advertised by one source on the Internet. Moreover, it captures 

the treatment of testers by housing providers in response to 
An Estimate of Housing Discrimination Against Same-Sex Couples 21

only one e-mail sent by each tester and, therefore, does not 

consider what could happen to testers through additional 

contacts with the housing provider (via additional followup 

e-mails, by phone, or in person). Thus, the testing conducted 

in this study is representative of only the initial stage of the 

housing search process. 

The contribution of this study is that it demonstrates that 

same-sex couples are significantly less likely than heterosexual 

couples to be able to access the targeted rental unit. When 

same-sex couples do receive a response, however, their treatment by housing providers relative to that of heterosexual 

couples is roughly equivalent. This type of discrimination is 

somewhat divergent from that which has been found between 

White and non-White renters. In large part, the disparity 

between White and non-White applicants is less in terms of 

receiving a response from providers or initial access to the unit 

than it is in terms of subsequent potential contact with providers (for example, more than one response or the potential to 

inspect the unit). 

Recommendations for Further Study

Because these data are the first national-scale findings about 

discrimination against same-sex couples in the metropolitan 

rental housing market, the study serves as a point of departure 

for future research on same-sex housing discrimination. Future 

research should conduct further testing, including e-mail and 

in-person testing, and look at a variety of specific aspects of 

disparate treatment that were beyond the scope of this project. 

This study provides an initial look at how same-sex couples are 

treated relative to heterosexual couples at the threshold of the 

rental housing search—the initial e-mail contact. It sampled 

only rental housing advertised on one Internet listing service. 

Because of the limited universe of available rental properties 

and the single initial contact, this study possibly underestimates 

the extent to which same-sex couples face discrimination in 

the rental housing market compared with the treatment of 

heterosexual couples. The study was conducted via e-mail 

correspondence tests, and the e-mails contained information 

to ensure that the housing provider knew if the couple seeking 

housing was of the same sex or heterosexual. In-person audits 

might, however, yield higher levels of discrimination against 

same-sex couples because providers would observe visual cues 

that would unequivocally establish the sexual orientation of the 

homeseekers and could result in discriminatory actions. 

Other areas for future inquiry include a deeper look at the next 

steps in the rental process, through follow-up e-mail communication to confirm interest in the unit and, more importantly, 

to request an appointment; telephone contacts to confirm an 

appointment; and in-person visits to housing providers by 

testers. In-person testing would provide valuable, additional 

information on the experiences of same-sex couples in the 

rental market, replicate the approach of other HDS research, 

and track the real-life sequence of a rental housing search. 

A broader sample of advertised rental units, including other 

electronic media and print advertisements, could be used for 

in-person testing.

In addition, future studies should employ e-mail or in-person 

audits to further examine differences in treatment of same-sex 

and heterosexual couples in states with and without legislative 

protections for sexual orientation or gender identity. Local 

jurisdiction protections were not within the scope of this study, 

and examining their effect on differential treatment could be 

very useful. In addition, this study looked only at treatment 

based on sexual orientation and not at treatment based on gender identity or gender expression, so it did not capture other 

forms of discrimination that LGBT people might experience.

Finally, future research should seek to obtain metropolitan 

area-specific estimates of discrimination against same-sex 

couples. Perhaps this approach could shed light on the mixed 

findings observed across metropolitan areas in this study. 
An Estimate of Housing Discrimination Against Same-Sex Couples 22

Technical Appendixes

Appendix A. Distribution of Population and Sample Characteristics Across 

Proposed Population Stratum

MSA = metropolitan statistical area. PMSA = primary metropolitan statistical area.

Population Size Stratum

Population Characteristics (%) Sample Characteristics (%)

Percent of

Total

MSA/PMSA

Percent of 

Population

Percent of

Same-Sex 

Households

Market Within

Stratum Percent 

of Sample

Total

Target Number of 

Paired Tests

Within Stratum

Percent of

Total Target

Number of Paired

Tests Within Stratum

Less than 100,000 5.7 0.7 0.6 0.0 — 0.0

100,000 to 250,000 37.8 8.6 7.4 5.9 180 2.0

250,000 to 400,000 14.8 6.4 5.9 11.8 720 7.9

400,000 to 750,000 18.7 13.6 12.2 21.6 1,364 15.0

750,000 to 1,500,000 9.7 14.1 13.4 13.7 1,400 15.4

1,500,000 to 5,000,000 11.5 38.6 41.6 35.3 3,636 40.0

5,000,000 or more 1.8 18.0 18.9 11.8 1,800 19.8

Total 100 100 100 100 9,100 100
An Estimate of Housing Discrimination Against Same-Sex Couples 23

Appendix B. Weighted Results and Standard Errors

Weighted Computed S.E. Number 

of Paired 

Tests

Percent 

Heterosexual 

Favored

Percent 

Same-Sex 

Favored

Net 

Measure N

Gross Measure Net Measure

Label in Word File Test Type S.E. MOE

[95%]

MOE

[90%] S.E. MOE[95%]

MOE

[90%]

p-Value 

(2-Tailed

t Test)

(1) Response 

 provided

Lesbian-heterosexual 3,409 11.2 8.9 2.3 6,818 0.004 0.007 0.006 0.007 0.014 0.012 0.002**

Gay male-heterosexual 3,424 11.6 8.5 3.1 6,848 0.004 0.008 0.006 0.007 0.014 0.012 0.000**

(2) More than one 

 response

Lesbian-heterosexual 1,679 4.1 2.4 1.7 3,358 0.003 0.007 0.006 0.006 0.012 0.010 0.005**

Gay male-heterosexual 1,681 2.6 2.6 0.0 3,362 0.003 0.005 0.005 0.005 0.011 0.009 1.000

(3) Available Lesbian-heterosexual 1,679 3.4 3.6 – 0.2 3,358 0.003 0.006 0.005 0.006 0.012 0.010 0.753

Gay male-heterosexual 1,681 3.5 2.6 0.9 3,362 0.003 0.006 0.005 0.006 0.012 0.010 0.129

(4) Inspect Lesbian-heterosexual 1,679 3.6 4.7 – 1.1 3,358 0.003 0.006 0.005 0.007 0.013 0.011 0.110

Gay male-heterosexual 1,681 4.7 4.3 0.4 3,362 0.004 0.007 0.006 0.007 0.014 0.012 0.576

(5) Contact Lesbian-heterosexual 1,679 4.1 5.7 – 1.6 3,358 0.003 0.007 0.006 0.007 0.015 0.012 0.032*

Gay male-heterosexual 1,681 5.7 6.0 – 0.3 3,362 0.004 0.008 0.007 0.008 0.016 0.013 0.711

(6) Consistency 

 index

Lesbian-heterosexual 3,409 15.6 14.3 1.3 6,818 0.004 0.009 0.007 0.009 0.017 0.014 0.132

Gay male-heterosexual 3,424 15.9 13.7 2.2 6,848 0.004 0.009 0.007 0.009 0.017 0.014 0.010*

MOE = margin of error. S.E. = standard error.

* p ≤ .05. ** p ≤ .01.
An Estimate of Housing Discrimination Against Same-Sex Couples 24

Appendix C. List of Tester Names

Male Female Male Female Male Female Male Female

Adam Amanda

Andrew Amber

Anthony Amy

Brandon Angela

Brian Ashley

Christopher Brittany

Daniel Christina

David Christine

Eric Crystal

James Danielle

Jason Dawn

Jeffrey Elizabeth

Jeremy Heather

John Jamie

Jonathan Jennifer

Joseph Jessica

Joshua Julie

Justin Karen

Kevin Kimberly

Mark Laura

Matthew Lauren

Michael Lisa

Nicholas Mary

Richard Megan

Robert Melissa

Ryan Michelle

Scott Nicole

Steven Rachel

Thomas Rebecca

Timothy Sarah

William Stephanie

Susan

Tammy

Tiffany

Tina

Appendix D. E-mail Text and Subject Lines (1 of 3)

Format 1 Format 2 Format 3

E-mail 1 Hello.

I saw your 1 br apt ad on [WEBSITE] 

at <specify address>. My <relationship 

identifier>, <partner name>, and I are 

looking for a place that matches this 

description. Is it available and, if so, can 

we see it?

Thanks, <sender name>

Hello.

I saw your 1 br apt ad on [WEBSITE] 

at <specify address>. My <relationship 

identifier>, <partner name>, and I are 

looking for a place that matches this 

description. Is it available and, if so, can 

we see it? 

Thanks, <sender name>

Hello. 

I saw your 1 br apt ad on [WEBSITE] at 

<specify address>. My <relationship identifier>, <partner name>, and I are looking 

for a place that matches this description. 

Is it available and, if so, can we see it? 

Thanks, <sender name>

E-mail 2 Hi, 

My <relationship identifier>, <partner 

name>, and I are very interested in your 

1br apt (located at <specify address>). 

Could you let us know if it is still available and when a convenient time to view 

it would be? 

Thank you. <sender name>

Hi, 

My <relationship identifier>, <partner 

name>, and I are very interested in your 

1br apt (located at <specify address>). 

Could you let us know if it is still available and when a convenient time to view 

it would be? 

Thank you. <sender name>

Hi, 

My <relationship identifier>, <partner 

name>, and I are very interested in your 

1br apt (located at <specify address>). 

Could you let us know if it is still available 

and when a convenient time to view it 

would be? 

Thank you. <sender name>

E-mail 3 Hello. 

I am interested in your 1 br apt on 

<specify address> for me and my <relationship identifier>, <partner name>. Is it 

available? Is there a time we could come 

by and see it? 

Thank you. <sender name>

Hello. 

I am interested in your 1 br apt on 

<specify address> for me and my <relationship identifier>, <partner name>. Is it 

available? Is there a time we could come 

by and see it? 

Thank you. <sender name>

Hello. 

I am interested in your 1 br apt on 

<specify address> for me and my <relationship identifier>, <partner name>. Is it 

available? Is there a time we could come 

by and see it? 

Thank you. <sender name>

E-mail 4 Hello. 

Your apartment (<specify address>) 

seems to be what my <relationship 

identifier>, <partner name>, and I had 

in mind. Is it still available? We’d like to 

come by and view the apartment; could 

you contact me with an available time to 

do so? 

Thanks, <sender name>

Hello. 

Your apartment (<specify address>) 

seems to be what my <relationship 

identifier>, <partner name>, and I had 

in mind. Is it still available? We’d like to 

come by and view the apartment; could 

you contact me with an available time 

to do so? 

Thanks, <sender name>

Hello. 

Your apartment (<specify address>) 

seems to be what my <relationship identifier>, <partner name>, and I had in mind. 

Is it still available? We’d like to come by 

and view the apartment; could you contact me with an available time to do so? 

Thanks, <sender name>

E-mail 5 Hello, 

My <relationship identifier>, <partner 

name>, and I are writing in response to 

your listing for the 1 bedroom apartment 

located at <specify address>. Is it available? May we come and see it? 

Thank you for your time, <sender 

name>.

Hello, 

My <relationship identifier>, <partner 

name>, and I are writing in response to 

your listing for the 1 bedroom apartment 

located at <specify address>. Is it available? May we come and see it? 

Thank you for your time, <sender 

name>.

Hello, 

My <relationship identifier>, <partner 

name>, and I are writing in response to 

your listing for the 1 bedroom apartment 

located at <specify address>. Is it available? May we come and see it? 

Thank you for your time, <sender name>.
An Estimate of Housing Discrimination Against Same-Sex Couples 25

Appendix D. E-mail Text and Subject Lines (2 of 3)

Format 1 Format 2 Format 3

E-mail 6 Hello, 

I just saw your ad on [website] for the 

apartment at <specify address> and I 

am definitely interested. Is it still available? Is there a time that my <relationship identifier>, <partner name> and I 

can stop by and look it over? 

Thank you for your help, <sender name>

Hello, 

I just saw your ad on [website] for the 

apartment at <specify address> and I 

am definitely interested. Is it still available? Is there a time that my <relationship identifier>, <partner name> and I 

can stop by and look it over? 

Thank you for your help, <sender name>

Hello, 

I just saw your ad on [website] for the 

apartment at <specify address> and I am 

definitely interested. Is it still available? Is 

there a time that my <relationship identifier>, <partner name> and I can stop by 

and look it over? 

Thank you for your help, <sender name>

E-mail 7 Hi. 

My <relationship identifier>, <partner 

name>, and I would like to set an appt. 

to see your apartment (at <specify address>). Is this particular apartment still 

available? If it is, can you tell me when 

you would be available to show it? 

Thanks, <sender name>

Hi. 

My <relationship identifier>, <partner 

name>, and I would like to set an appt. 

to see your apartment (at <specify address>). Is this particular apartment still 

available? If it is, can you tell me when 

you would be available to show it? 

Thanks, <sender name>

Hi. 

My <relationship identifier>, <partner 

name>, and I would like to set an appt. 

to see your apartment (at <specify address>). Is this particular apartment still 

available? If it is, can you tell me when you 

would be available to show it? 

Thanks, <sender name>

E-mail 8 I saw your ad for a 1Br apartment on 

[website] located at <specify address>. 

Is this apartment still available? My <relationship identifier>, <partner name>, 

and I would like to set a time to see it. 

Can you tell me what hours you would 

be available so we can schedule a visit? 

I can be reached at this return email. 

Thanks, <sender name>

I saw your ad for a 1Br apartment on 

[website] located at <specify address>. 

Is this apartment still available? My <relationship identifier>, <partner name>, 

and I would like to set a time to see it. 

Can you tell me what hours you would 

be available so we can schedule a visit? 

I can be reached at this return email. 

Thanks, <sender name>

I saw your ad for a 1Br apartment on 

[website] located at <specify address>. 

Is this apartment still available? My <relationship identifier>, <partner name>, and I 

would like to set a time to see it. Can you 

tell me what hours you would be available so we can schedule a visit? I can be 

reached at this return email. 

Thanks, <sender name>

E-mail 9 Hello, 

My <relationship identifier>, <partner 

name>, and I are interested in the one 

bedroom apartment that you currently 

have for rent at <specify address>. Is it 

still available and is there a specific time 

we could check it out? Please contact 

me at this email address. 

Thank you in advance, <sender name>

Hello, 

My <relationship identifier>, <partner 

name>, and I are interested in the one 

bedroom apartment that you currently 

have for rent at <specify address>. Is it 

still available and is there a specific time 

we could check it out? Please contact 

me at this email address. 

Thank you in advance, <sender name>

Hello, 

My <relationship identifier>, <partner 

name>, and I are interested in the one 

bedroom apartment that you currently 

have for rent at <specify address>. Is it 

still available and is there a specific time 

we could check it out? Please contact me 

at this email address. 

Thank you in advance, <sender name>

E-mail 10 Hi. 

My <relationship identifier>, <partner 

name>, and I would like to see the apartment on <specify address>. I realize 

places go fast; is this apartment still 

available? When would be a good time 

for us to meet to see it? Please reply to 

this email address as soon as possible. 

Thank you for your time, <sender name>

Hi. 

My <relationship identifier>, <partner 

name>, and I would like to see the 

apartment on <specify address>. I realize places go fast; is this apartment still 

available? When would be a good time 

for us to meet to see it? Please reply to 

this email address as soon as possible. 

Thank you for your time, <sender name>

Hi. 

My <relationship identifier>, <partner 

name>, and I would like to see the apartment on <specify address>. I realize 

places go fast; is this apartment still 

available? When would be a good time for 

us to meet to see it? Please reply to this 

email address as soon as possible. 

Thank you for your time, <sender name>

E-mail 11 Hello, 

My <relationship identifier>, <partner 

name>, and I would like set up a time to 

see the place you advertised on <specify 

address>. We were wondering, is this 

apartment still available? Also, is there 

any particular time that works best for a 

showing? Please let me know when you 

might be able to show us the apartment. 

Best regards, <sender name>

Hello, 

My <relationship identifier>, <partner 

name>, and I would like set up a time 

to see the place you advertised on 

<specify address>. We were wondering, 

is this apartment still available? Also, 

is there any particular time that works 

best for a showing? Please let me know 

when you might be able to show us the 

apartment. 

Best regards, <sender name>

Hello, 

My <relationship identifier>, <partner 

name>, and I would like set up a time to 

see the place you advertised on <specify 

address>. We were wondering, is this 

apartment still available? Also, is there any 

particular time that works best for a showing? Please let me know when you might 

be able to show us the apartment. 

Best regards, <sender name>
An Estimate of Housing Discrimination Against Same-Sex Couples 26

Appendix D. E-mail Text and Subject Lines (3 of 3)

Format 1 Format 2 Format 3

E-mail 12 I saw your [website] ad for the 1 bedroom located at <specify address> and 

would like to make an appointment for 

my <relationship identifier>, <partner 

name> and I to come by and see the 

apartment. Could you let us know 

whether or not it is still available and if 

it is, what time(s) work best for you to 

show it to us? 

Thank you for your time, <sender name>

I saw your [website] ad for the 1 bedroom located at <specify address> and 

would like to make an appointment for 

my <relationship identifier>, <partner 

name> and I to come by and see the 

apartment. Could you let us know 

whether or not it is still available and if 

it is, what time(s) work best for you to 

show it to us? 

Thank you for your time, <sender name>

I saw your [website] ad for the 1 bedroom located at <specify address> and 

would like to make an appointment for my 

<relationship identifier>, <partner name> 

and I to come by and see the apartment. 

Could you let us know whether or not it is 

still available and if it is, what time(s) work 

best for you to show it to us? 

Thank you for your time, <sender name>

Subject Line

1 One bedroom apartment

2 Apartment for rent

3 Unit for rent

4 [Website] - 1br apartment

5 [Website] Rental

6 Unit availability

7 Apartment posted on [website]

8 [website] apartment posting

9 Inquiry about your apartment

10 Saw your [Website] Apartment ad

11 In response to your [website] listing
An Estimate of Housing Discrimination Against Same-Sex Couples 27

Appendix E. Data Dictionary

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

1 AuditID Audit ID Number assigned 

for the audit

2 strata Metro Size Strata 1 = small (100,000 to 249,999)

2 = medium (250,000 to 

3999,999)

3 = medium-to-large (400,000 

to 749,999)

4 = large (750,000 to 1,499,999)

5 = very large (1,500,000 to 

4,999,999)

6 = largest (5,000,000 or more)

strata Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 110 1.61 110 1.61

2 136 1.99 246 3.60

3 503 7.36 749 10.96

4 760 11.12 1,509 22.08

5 3,524 51.57 5,033 73.66

6 1,800 26.34 6,833 100.00

3 GeoState State State in which 

housing inquiry 

occurred

State Postal Codes GeoState Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

AZ 228 3.34 228 3.34

CA 885 12.95 1,113 16.29

CO 228 3.34 1,341 19.63

CT 6 0.09 1,347 19.71

DC 99 1.45 1,446 21.16

FL 356 5.21 1,802 26.37

GA 356 5.21 2,158 31.58

ID 6 0.09 2,164 31.67

IL 334 4.89 2,498 36.56

IN 12 0.18 2,510 36.73

KY 81 1.19 2,591 37.92

MA 83 1.21 2,674 39.13

MD 87 1.27 2,761 40.41

MI 305 4.46 3,066 44.87

MN 223 3.26 3,289 48.13

MO 286 4.19 3,575 52.32

NC 105 1.54 3,680 53.86

NM 103 1.51 3,783 55.36

NY 475 6.95 4,258 62.32

OH 270 3.95 4,528 66.27

OK 20 0.29 4,548 66.56

PA 633 9.26 5,181 75.82

RI 1 0.01 5,182 75.84

SC 36 0.53 5,218 76.36

TN 154 2.25 5,372 78.62

TX 660 9.66 6,032 88.28

UT 105 1.54 6,137 89.81

VA 114 1.67 6,251 91.48

WA 345 5.05 6,596 96.53

WI 237 3.47 6,833 100.00
An Estimate of Housing Discrimination Against Same-Sex Couples 28

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

4 WrongMSAFlag Check for correct MSAs 0 = pass

1 = flag WrongMSAFlag Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 6,829 99.94 6,829 99.94

1 4 0.06 6,833 100

5 Protected Property in State with Same 

Sex Protection

0 = Unprotected

1 = Protected Protected Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 3,727 54.54 3,727 54.54

1 3,106 45.46 6,833 100

6 Protect_Type Type of Same-sex 

Protection

0 = No Protection

1 = States prohibiting housing 

discrimination based on 

sexual orientation and 

gender identity

2 = States prohibiting housing 

discriminatino based on 

sexual orientation

Protect_Type Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 3,727 54.54 3,727 54.54

1 2,224 32.55 5,951 87.09

2 882 12.91 6,833 100

7 metro_aud Metro (MSA) List of MSAs sampled Metro_aud Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

Albuquerque, NM MSA 103 1.51 103 1.51

Asheville, NC MSA 58 0.85 161 2.36

Atlanta, GA MSA 300 4.39 461 6.75

Austin-San Marcos, TX MSA 132 1.93 593 8.68

Binghamton, NY MSA 47 0.69 640 9.37

Buffalo-Niagara Falls, NY MSA 134 1.96 774 11.33

Chicago, IL PMSA 300 4.39 1,074 15.72

Columbia, SC MSA 13 0.19 1,087 15.91

Columbus, OH MSA 180 2.63 1,267 18.54

Dallas, TX PMSA 205 3 1,472 21.54

Dayton-Springfield, OH MSA 89 1.3 1,561 22.85

Denver, CO PMSA 228 3.34 1,789 26.18

Detroit, MI PMSA 228 3.34 2,017 29.52

Fayetteville, NC MSA 18 0.26 2,035 29.78

Fort Myers-Cape Coral, FL MSA 86 1.26 2,121 31.04

Grand Rapids-Muskegon-Holland, 

MI MSA

77 1.13 2,198 32.17

Greenville-Spartenburg-Anderson, 

SC MSA

23 0.34 2,221 32.5

Harrisburg-Lebanon-Carlisle, 

PA MSA

72 1.05 2,293 33.56

Houston, TX PMSA 227 3.32 2,520 36.88

Jacksonville, FL MSA 42 0.61 2,562 37.49

Los Angeles-Long Beach, CA PMSA 300 4.39 2,862 41.88

Louisville, KY-IN MSA 89 1.3 2,951 43.19

McAllen-Edinburg-Mission, 

TX MSA

13 0.19 2,964 43.38

Milwaukee-Waukesha, WI PMSA 228 3.34 3,192 46.71

Minneapolis-St. Paul, MN-WI MSA 225 3.29 3,417 50.01

Modesto, CA MSA 42 0.61 3,459 50.62
An Estimate of Housing Discrimination Against Same-Sex Couples 29

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

7 metro_aud

(continued)

Metro (MSA) List of MSAs sampled Metro_aud Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

Nashville, TN MSA 153 2.24 3,612 52.86

New York, NY PMSA 300 4.39 3,912 57.25

Oklahoma City, OK MSA 20 0.29 3,932 57.54

Orange County, CA PMSA 86 1.26 4,018 58.8

Philadelphia, PA-NJ PMSA 300 4.39 4,318 63.19

Phoenix-Mesa, AZ MSA 228 3.34 4,546 66.53

Pittsburgh, PA MSA 228 3.34 4,774 69.87

Racine, WI PMSA 5 0.07 4,779 69.94

Raleigh-Durham-Chapel Hill, 

NC MSA

30 0.44 4,809 70.38

Rockford, IL MSA 36 0.53 4,845 70.91

Sacramento, CA PMSA 228 3.34 5,073 74.24

Salt Lake City-Ogden, UT MSA 105 1.54 5,178 75.78

San Antonio, TX MSA 85 1.24 5,263 77.02

San Francisco, CA PMSA 228 3.34 5,491 80.36

Savannah, GA MSA 56 0.82 5,547 81.18

Scranton--Wilkes-Barre--Hazleton, 

PA MSA

5 0.07 5,552 81.25

Seattle-Bellevue-Everett, WA PMSA 227 3.32 5,779 84.57

Spokane, WA MSA 124 1.81 5,903 86.39

Springfield, MO MSA 62 0.91 5,965 87.3

St. Louis, MO-IL MSA 228 3.34 6,193 90.63

Tampa-St. Petersburg-Clearwater, 

FL MSA

228 3.34 6,421 93.97

Washington, DC-MD-VA-WV PMSA 300 4.39 6,721 98.36

Worcester, MA-CT PMSA 84 1.23 6,805 99.59

York, PA MSA 28 0.41 6,833 100

8 jurisdiction_aud Jurisdiction List of Jurisdictions sampled 

(TBD)

9 x_city Name of City listing was 

posted in.

List of Cities sampled X_City Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

albuquerque 103 1.51 103 1.51

asheville 58 0.85 161 2.36

atlanta 300 4.39 461 6.75

austin 116 1.7 577 8.44

binghamton 47 0.69 624 9.13

buffalo 134 1.96 758 11.09

chicago 300 4.39 1,058 15.48

columbia 13 0.19 1,071 15.67

columbus 180 2.63 1,251 18.31

dallas 205 3 1,456 21.31

dayton 89 1.3 1,545 22.61

denver 228 3.34 1,773 25.95

detroit 228 3.34 2,001 29.28

fayetteville 18 0.26 2,019 29.55

fortmyers 86 1.26 2,105 30.81
An Estimate of Housing Discrimination Against Same-Sex Couples 30

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

9 x_city 

(continued)

Name of City listing was 

posted in.

List of Cities sampled X_City Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

grandrapids 51 0.75 2,156 31.55

greenville 23 0.34 2,179 31.89

harrisburg 72 1.05 2,251 32.94

holland 6 0.09 2,257 33.03

houston 227 3.32 2,484 36.35

jacksonville 42 0.61 2,526 36.97

losangeles 300 4.39 2,826 41.36

louisville 89 1.3 2,915 42.66

mcallen 13 0.19 2,928 42.85

milwaukee 228 3.34 3,156 46.19

minneapolis 225 3.29 3,381 49.48

modesto 42 0.61 3,423 50.1

muskegon 20 0.29 3,443 50.39

nashville 153 2.24 3,596 52.63

newyork 300 4.39 3,896 57.02

ogden 5 0.07 3,901 57.09

oklahomacity 20 0.29 3,921 57.38

orangecounty 86 1.26 4,007 58.64

philadelphia 300 4.39 4,307 63.03

phoenix 228 3.34 4,535 66.37

pittsburgh 228 3.34 4,763 69.71

racine 5 0.07 4,768 69.78

raleigh 30 0.44 4,798 70.22

rockford 36 0.53 4,834 70.74

sacramento 228 3.34 5,062 74.08

saltlakecity 100 1.46 5,162 75.55

sanantonio 85 1.24 5,247 76.79

sanmarcos 16 0.23 5,263 77.02

savannah 56 0.82 5,319 77.84

scranton 5 0.07 5,324 77.92

seattle 227 3.32 5,551 81.24

sfbay 228 3.34 5,779 84.57

spokane 124 1.81 5,903 86.39

springfield 62 0.91 5,965 87.3

stlouis 228 3.34 6193 90.63

tampa 228 3.34 6,421 93.97

washingtondc 300 4.39 6,721 98.36

worcester 84 1.23 6,805 99.59

york 28 0.41 6,833 100

10 postid Posting ID Identification 

number assigned 

to every ad 
An Estimate of Housing Discrimination Against Same-Sex Couples 31

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

11 monthad Month ad appeared 1 = January

2 = February

3 = March

4 = April

5 = May

6 = June

7 = July

8 = August

9 = September

10 = October

11 = November

12 = December

monthad Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

6 418 6.12 418 6.12 7 3,340 48.88 3,758 55 8 1,664 24.35 5,422 79.35 9 1,411 20.65 6,833 100

12 datead Date ad appeared List actual date 

(e.g., 1 for 1st, 12 

for 12th)

Dates of the Month datead Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 172 2.52 172 2.52 2 32 0.47 204 2.99 4 149 2.18 353 5.17 5 299 4.38 652 9.54 6 311 4.55 963 14.09 7 245 3.59 1,208 17.68 8 381 5.58 1,589 23.25 9 205 3 1,794 26.25

10 334 4.89 2,128 31.14

11 315 4.61 2,443 35.75

12 355 5.2 2,798 40.95

13 285 4.17 3,083 45.12

14 251 3.67 3,334 48.79

15 217 3.18 3,551 51.97

16 104 1.52 3,655 53.49

17 144 2.11 3,799 55.6

18 330 4.83 4,129 60.43

19 179 2.62 4,308 63.05

20 318 4.65 4,626 67.7

21 268 3.92 4,894 71.62

22 230 3.37 5,124 74.99

23 177 2.59 5,301 77.58

24 197 2.88 5,498 80.46

25 238 3.48 5,736 83.95

26 246 3.6 5,982 87.55

27 95 1.39 6,077 88.94

28 73 1.07 6,150 90

29 333 4.87 6,483 94.88

30 291 4.26 6,774 99.14

31 59 0.86 6,833 100
An Estimate of Housing Discrimination Against Same-Sex Couples 32

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

13 dayad Weekday ad appeared 1 = Sunday

2 = Monday

3 = Tuesday

4 = Wednesday

5 = Thursday

6 = Friday

7 = Saturday

dayad Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 713 10.43 713 10.43 2 1,284 18.79 1,997 29.23 3 1,278 18.7 3,275 47.93 4 1,288 18.85 4,563 66.78 5 1,150 16.83 5,713 83.61 6 949 13.89 6,662 97.5 7 171 2.5 6,833 100

14 timead Time ad posted am/pm time

15 monthEDT Month ad appeared 

(in EDT time)

1 = January

2 = February

3 = March

4 = April

5 = May

6 = June

7 = July

8 = August

9 = September

10 = October

11 = November

12 = December

monthEDT Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

6 418 6.12 418 6.12 7 3,340 48.88 3,758 55 8 1,664 24.35 5,422 79.35 9 1,411 20.65 6,833 100

16 dateEDT Date ad appeared 

(in EDT time)

List actual date 

(e.g., 1 for 1st, 

12 for 12th)

Dates of the Month dateEDT Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 172 2.52 172 2.52 2 32 0.47 204 2.99 4 149 2.18 353 5.17 5 299 4.38 652 9.54 6 310 4.54 962 14.08 7 245 3.59 1,207 17.66 8 382 5.59 1,589 23.25 9 205 3 1,794 26.25

10 334 4.89 2,128 31.14

11 315 4.61 2,443 35.75

12 355 5.2 2,798 40.95

13 285 4.17 3,083 45.12

14 251 3.67 3,334 48.79

15 217 3.18 3,551 51.97

16 104 1.52 3,655 53.49

17 144 2.11 3,799 55.6

18 330 4.83 4,129 60.43

19 179 2.62 4,308 63.05

20 318 4.65 4,626 67.7

21 268 3.92 4,894 71.62

22 230 3.37 5,124 74.99

23 177 2.59 5,301 77.58

24 197 2.88 5,498 80.46

25 237 3.47 5,735 83.93
An Estimate of Housing Discrimination Against Same-Sex Couples 33

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

16 dateEDT

(continued)

Date ad appeared 

(in EDT time)

List actual date 

(e.g., 1 for 1st, 

12 for 12th)

Dates of the Month dateEDT Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

26 246 3.6 5,981 87.53

27 96 1.4 6,077 88.94

28 72 1.05 6,,149 89.99

29 331 4.84 6480 94.83

30 294 4.3 6,774 99.14

31 59 0.86 6,833 100

17 TimeEDT Time ad posted (in EDT 

time)

am/pm time

18 listcat Apartment listing category 

(for Boston and others 

like Boston – may not be 

applicable if no sites in our 

sample have this)

1 = fee

2 = no fee

3 = by owner

4 = NA

listcat Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 86 1.26 86 1.26

2 20 0.29 106 1.55

3 194 2.84 300 4.39

4 6533 95.61 6833 100

19 company Name of real estate/

management company 

in ad

1 = yes

2 = no Company Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 2962 43.35 2962 43.35

2 3871 56.65 6833 100

20 agent Agent name in ad 1 = yes

2 = no agent Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1904 27.86 1904 27.86

2 4929 72.14 6833 100

21 ownoprov Name of owner or other 

provider in ad

1 = yes

2 = no ownoprov Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1148 16.8 1148 16.8

2 5685 83.2 6833 100

22 company1 Name of real estate/

management company/

apartment complex

List name – 9 = NA

23 company2 Name of real estate/

management company/

apartment complex

List name – 9 = NA

24 company3 Name of real estate/

management company/

apartment complex

List name – 9 = NA

25 agentname1 Name of agent (1) in 

real estate/management 

company

List name – 9 = NA

26 agentname2 Name of agent (2) in 

real estate/management 

company

List name – 9 = NA

27 agentname3 Name of agent (3) in 

real estate/management 

company

List name – 9 = NA

28 ownoprovname1 Name of owner or other 

provider (1)

List name – 9 = NA
An Estimate of Housing Discrimination Against Same-Sex Couples 34

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

29 ownoprovname2 Name of owner or other 

provider (2)

List name – 9 = NA

30 ownoprovname3 Name of owner or other 

provider (3)

List name – 9 = NA

31 refnum Reference number Reference 

number given by 

housing provider 

in ad

– 9 = NA

32 emailc Craigslist given email 

address

Record email 

address

33 email2 Email address in body 

of text

Record email 

address

– 9 = NA

34 email3 Other email address 

given

Record email 

address

– 9 = NA

35 email4 Other email address 

given

Record email 

address

– 9 = NA

36 phoneno1 Phone number (1) List number with 

area code

(999)999–9999 = NA

37 phoneno2 Phone number (2) List number with 

area code

(999)999–9999 = NA

38 phoneno3 Phone number (3) List number with 

area code

(999)999–9999 = NA

39 phoneno4 Phone number (4) List number with 

area code

(999)999–9999 = NA

40 unitst Street address of unit List address of 

unit, including 

house number

41 housing_apt_# Additional address 

information such as 

apartment number

– 9 = NA

42 crosssts Cross streets of unit List cross streets 

at which unit is 

approximately 

located

43 city City/town List name of city/

town in which 

unit is located

– 9 = NA

44 geo_oth Other Geographic 

Information

– 9 = NA

45 state State List name of 

state in which 

unit is located

1 = AL 

2 = AK 

3 = AZ 

4 = AR 

5 = CA 

6 = CO 

7 = CT 

8 = DC

state Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 3,530 51.66 3,530 51.66

3 141 2.06 3,671 53.72

4 2 0.03 3,673 53.75

5 339 4.96 4,012 58.72

6 204 2.99 4,216 61.7

7 1 0.01 4,217 61.72

8 76 1.11 4,293 62.83
An Estimate of Housing Discrimination Against Same-Sex Couples 35

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

45 state

(continued)

State List name of 

state in which 

unit is located

9 = DE 

10 = FL 

11 = GA 

12 = HI 

13 = ID 

14 = IL 

15 = IN 

16 = IA 

17 = KS 

18 = KY 

19 = LA 

20 = ME 

21 = MD 

22 = MA 

23 = MI 

24 = MN 

25 = MS 

26 = MO 

27 = MT

28 = NE

29 = NV

30 = NH

31 = NJ

32 = NM

33 = NY

34 = NC

35 = ND

36 = OH

37 = OK

38 = OR

39 = PA

40 = RI

41 = SC

42 = SD

43 = TN

44 = TX

45 = UT

46 = VT

47 = VA

48 = WA

49 = WV

50 = WI

51 = WY

state Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

9 12 0.18 4,305 63

10 218 3.19 4,523 66.19

11 243 3.56 4,766 69.75

121 0.01 4,767 69.76

14 285 4.17 5,052 73.94

153 0.04 5,055 73.98

18 14 0.2 5,069 74.18

201 0.01 5,070 74.2

21 67 0.98 5,137 75.18

22 61 0.89 5,198 76.07

23 118 1.73 5,316 77.8

24 160 2.34 5,476 80.14

26 86 1.26 5,562 81.4

271 0.01 5,563 81.41

281 0.01 5,564 81.43

32 23 0.34 5,587 81.76

33 289 4.23 5,876 85.99

34 64 0.94 5,940 86.93

36 92 1.35 6,032 88.28

37 10 0.15 6,042 88.42

381 0.01 6,043 88.44

39 158 2.31 6,201 90.75

401 0.01 6,202 90.77

41 21 0.31 6,223 91.07

421 0.01 6,224 91.09

43 61 0.89 6,285 91.98

44 249 3.64 6,534 95.62

45 26 0.38 6,560 96

461 0.01 6,561 96.02

47 95 1.39 6,656 97.41

48 112 1.64 6,768 99.05

50 55 0.8 6,823 99.85

51 10 0.15 6,833 100

46 zipcode_aud Zip code List first 5 digits 

of zip code in 

which unit is 

located

99999 = NA
An Estimate of Housing Discrimination Against Same-Sex Couples 36

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

47 zipcodesuff_aud Zip code optional suffix List last 4 digits 

of zip code 

in which unit 

is located IF 

PROVIDED

9999 = NA

48 jurisdictionsize_

aud

Size of Metropolitan Area

49 legislation_aud Same-Sex discrimination 

protecting unit in listing?

50 unitdes Unit facility 1 = in large apartment building 

(10 + units)

2 = in small apartment building 

(4-9 units)

3 = in triplex (3 units)

4 = in duplex (2 units)

5 = apartment, but size of 

building unknown

6 = single family, detached 

house

7 = recreational vehicle

8 = high rise

9 = don’t know

unitdes Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 161 2.36 161 2.36

2 184 2.69 345 5.05

3 61 0.89 406 5.94

4 181 2.65 587 8.59

5 5,353 78.34 5,940 86.93

6 128 1.87 6,068 88.8

7 15 0.22 6,083 89.02

8 61 0.89 6,144 89.92

9 689 10.08 6,833 100

51 unitdes1 Additional unit info 1 = condominium

2 = townhouse

3 = in-law unit

4 = loft

5 = Basement

6 = Other (specify after ;)

7 = No additional information

8 = Studio/Efficiency

unitdes1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 438 6.41 438 6.41

2 62 0.91 500 7.32

3 11 0.16 511 7.48

4 137 2 648 9.48

5 65 0.95 713 10.43

6 293 4.29 1,006 14.72

7 5,727 83.81 6,733 98.54

8 100 1.46 6,833 100

52 unitdes1_oth Other Response for 

unitdes1

– 9 = NA

53 seniorhsg Unit in senior housing 

community

1 = yes

2 = no seniorhsg Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 104 1.52 104 1.52

2 6,729 98.48 6,833 100

54 cats Whether cats allowed 1 = yes

2 = no

– 9 = NA

cats Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 1,641 24.02 1,641 24.02

1 4,009 58.67 5,650 82.69

2 1,183 17.31 6,833 100

55 dogs Whether dogs allowed 1 = yes

2 = no

– 9 = NA

dogs Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 2,292 33.54 2,292 33.54

1 3,117 45.62 5,409 79.16

2 1,424 20.84 6,833 100
An Estimate of Housing Discrimination Against Same-Sex Couples 37

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

56 rent Monthly rent Dollar amount of 

monthly rent listed 

in ad for given unit

– 9 = NA Mean Std Dev Minimum Maximum

rent 871.1152942 561.3193183 89 6,000

57 rentrangeUL Monthly Rent Upper Limit Upper limit of a 

rent range

– 9 = NA Mean Std Dev Minimum Maximum

rentrangeUL 896.8296915 660.0781003 195 7747

58 bfee Broker fee 1 = broker fee required as 

stated in ad

2 = broker fee NOT required 

as stated in ad”

bfee Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 98 1.43 98 1.43

2 6,735 98.57 6,833 100

59 bfeeamt Broker fee amount record amount of 

broker fee listed

– 9 = NA

60 appfeead Application fee in ad 1 = yes, mentioned

2 = no, NOT mentioned appfeead Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 802 11.74 802 11.74

2 6,031 88.26 6,833 100

61 secdepositad Security deposit in ad 1 = yes, mentioned

2 = no, NOT mentioned secdepositad Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 2,625 38.42 2,625 38.42

2 4,208 61.58 6,833 100

62 secdepamtad Security deposit amount 

in ad

Record security 

deposit amount

– 9 = NA

63 credchk Credit check mentioned 1 = yes, mentioned

2 = no, NOT mentioned credchk Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 651 9.53 651 9.53

2 6,182 90.47 6,833 100

64 credchkfee Credit Check Fee 

Mentioned

1 = yes, mentioned

2 = no, NOT mentioned credchkfee Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 232 35.64 232 35.64

2 419 64.36 651 100

Frequency Missing = 6,182

65 credchkfeeamt Credit Check Fee Amount record amount of 

credit check fee 

listed

– 9 = NA Mean Std Dev Minimum Maximum

credchkfeeamt 69.7095745 207.2339406 0 2,700

66 fee Other fee 1 = yes, mentioned

2 = no, NOT mentioned fee Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 706 10.33 706 10.33

2 6,127 89.67 6,833 100

67 rentdiscount Rent discount offered in ad 1 = yes, offered

2 = no, NOT offered rentdiscount Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1,140 16.68 1,140 16.68

2 5,693 83.32 6,833 100

68 lease Lease in ad 1 = yes, mentioned

2 = no, NOT mentioned lease Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1,703 24.92 1,703 24.92

2 5,130 75.08 6,833 100

69 leaseterm Lease term record actual 

lease term 

(in months)

Accepts range, 

(XX-XX), – 9 = NA
An Estimate of Housing Discrimination Against Same-Sex Couples 38

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

70 eqopp Equal Opportunity 

statement present in ad

1 = yes

2 = no eqopp Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1,118 16.36 1,118 16.36

2 5,715 83.64 6,833 100

71 eqoppsymb Equal Opportunity symbol 

present in ad

1 = yes

2 = no eqoppsymb Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1,184 17.33 1,184 17.33

2 5,649 82.67 6,833 100

72 protectclass1 Protected class restriction 

in advertisement

record 

discriminatory 

ad language

– 9 = NA

73 protectclass2 Protected class restriction 

in advertisement

record 

discriminatory 

ad language

– 9 = NA

74 protectclass3 Protected class restriction 

in advertisement

record 

discriminatory 

ad language

– 9 = NA

75 imagesize Size of largest image (in 

pixels)

size (in pixels) 

of largest image 

in listing

76 TesterOrient Sexual Orientation of 

Sender of Email (i.e. Tester)

S = Straight

G = Gay

L = Lesbian

TesterOrient Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

G 3,424 25.05 3,424 25.05

L 3,409 24.95 6,833 50

S 6,833 50 13,666 100

77 SenderGender Gender of Sender M = Male

F = Female SenderGender Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

F 6,818 49.89 6,818 49.89

M 6,848 50.11 13,666 100

78 Contact

TimeRecode

Recode of Contact Time

79 TesterOrder

Recode

Tester Order Recode 1 = first tester 

2 = second tester TesterOrderRecode Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 6,833 50 6,833 50

2 6,833 50 13,666 100

80 ID Original ID in Tester Table 

Database

Number assigned 

for the audit

81 TesterID testerID Tester ID of tester 

who created the 

entry in the tester 

database

82 metro_test Metro (MSA) List of MSAs sampled metro_test Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

Albuquerque, NM MSA 206 1.51 206 1.51

Asheville, NC MSA 116 0.85 322 2.36

Atlanta, GA MSA 600 4.39 922 6.75

Austin-San Marcos, TX MSA 264 1.93 1,186 8.68

Binghamton, NY MSA 94 0.69 1,280 9.37
An Estimate of Housing Discrimination Against Same-Sex Couples 39

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

82 metro_test

(continued)

Metro (MSA) List of MSAs sampled metro_test Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

Buffalo-Niagara Falls, NY MSA 268 1.96 1,548 11.33

Chicago, IL PMSA 600 4.39 2,148 15.72

Columbia, SC MSA 26 0.19 2,174 15.91

Columbus, OH MSA 360 2.63 2,534 18.54

Dallas, TX PMSA 4103 2,944 21.54

Dayton-Springfield, OH MSA 178 1.3 3,122 22.85

Denver, CO PMSA 456 3.34 3,578 26.18

Detroit, MI PMSA 456 3.34 4,034 29.52

Fayetteville, NC MSA 36 0.26 4,070 29.78

Fort Myers-Cape Coral, FL MSA 172 1.26 4,242 31.04

Grand Rapids-Muskegon-Holland, 

MI MSA

154 1.13 4,396 32.17

Greenville-Spartenburg-Anderson, 

SC MSA

46 0.34 4,442 32.5

Harrisburg-Lebanon-Carlisle, PA 

MSA

144 1.05 4,586 33.56

Houston, TX PMSA 454 3.32 5,040 36.88

Jacksonville, FL MSA 84 0.61 5,124 37.49

Los Angeles-Long Beach, CA 

PMSA

600 4.39 5,724 41.88

Louisville, KY-IN MSA 178 1.3 5,902 43.19

McAllen-Edinburg-Mission, TX MSA 26 0.19 5,928 43.38

Milwaukee-Waukesha, WI PMSA 456 3.34 6,384 46.71

Minneapolis-St. Paul, MN-WI MSA 450 3.29 6,834 50.01

Modesto, CA MSA 84 0.61 6,918 50.62

Nashville, TN MSA 306 2.24 7,224 52.86

New York, NY PMSA 600 4.39 7,824 57.25

Oklahoma City, OK MSA 40 0.29 7,864 57.54

Orange County, CA PMSA 172 1.26 8,036 58.8

Philadelphia, PA-NJ PMSA 600 4.39 8,636 63.19

Phoenix-Mesa, AZ MSA 456 3.34 9,092 66.53

Pittsburgh, PA MSA 456 3.34 9,548 69.87

Racine, WI PMSA 10 0.07 9,558 69.94

Raleigh-Durham-Chapel Hill, NC 

MSA

60 0.44 9,618 70.38

Rockford, IL MSA 72 0.53 9,690 70.91

Sacramento, CA PMSA 456 3.34 10,146 74.24

Salt Lake City-Ogden, UT MSA 210 1.54 10,356 75.78

San Antonio, TX MSA 170 1.24 10,526 77.02

San Francisco, CA PMSA 456 3.34 10,982 80.36

Savannah, GA MSA 112 0.82 11,094 81.18

Scranton--Wilkes-Barre--Hazleton, 

PA MSA

10 0.07 11,104 81.25

Seattle-Bellevue-Everett, WA PMSA 454 3.32 11,558 84.57

Spokane, WA MSA 248 1.81 11,806 86.39

Springfield, MO MSA 124 0.91 11,930 87.3
An Estimate of Housing Discrimination Against Same-Sex Couples 40

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

82 metro_test

(continued)

Metro (MSA) List of MSAs sampled metro_test Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

St. Louis, MO-IL MSA 456 3.34 12,386 90.63

Tampa-St. Petersburg-Clearwater, 

FL MSA

456 3.34 12,842 93.97

Washington, DC-MD-VA-WV PMSA 600 4.39 13,442 98.36

Worcester, MA-CT PMSA 168 1.23 13,610 99.59

York, PA MSA 56 0.41 13,666 100

83 jurisdiction_test Jurisdiction List of jurisdictions sampled 

(TBD)

84 testorder Order of test 1 = first tester

2 = second tester testorder Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 6,833 50 6,833 50

2 6,833 50 13,666 100

85 emailername1 Name of tester 1st contact list name or 

assign numeric 

code to names

86 partnername1 Name of partner in email list name or 

assign numeric 

code to names

87 contactdate1 Date of 1st contact List actual date 

(e.g., 1 for 1st, 12 

for 12th)

Dates of the Month Contactdate1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 749 5.48 749 5.48

2 457 3.34 1,206 8.82

3 272 1.99 1,478 10.82

4 90 0.66 1,568 11.47

5 229 1.68 1,797 13.15

6 449 3.29 2,246 16.43

7 533 3.9 2,779 20.34

8 516 3.78 3,295 24.11

9 473 3.46 3,768 27.57

10 215 1.57 3,983 29.15

11 628 4.6 4,611 33.74

12 769 5.63 5,380 39.37

13 730 5.34 6,110 44.71

14 515 3.77 6,625 48.48

15 708 5.18 7,333 53.66

16 474 3.47 7,807 57.13

17 223 1.63 8,030 58.76

18 410 3 8,440 61.76

19 445 3.26 8,885 65.02

20 453 3.31 9,338 68.33

21 641 4.69 9,979 73.02

22 390 2.85 10,369 75.87

23 541 3.96 10,910 79.83

24 393 2.88 11,303 82.71

25 442 3.23 11,745 85.94

26 496 3.63 12,241 89.57
An Estimate of Housing Discrimination Against Same-Sex Couples 41

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

87 contactdate1

(continued)

Date of 1st contact List actual date 

(e.g., 1 for 1st, 

12 for 12th)

Dates of the Month Contactdate1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

27 314 2.3 12,555 91.87

28 169 1.24 12,724 93.11

29 487 3.56 13,211 96.67

30 383 2.8 13,594 99.47

31 72 0.53 13,666 100

88 contactday1 Weekday of 1st contact 1 = Sunday

2 = Monday

3 = Tuesday

4 = Wednesday

5 = Thursday

6 = Friday

7 = Saturday

Contactday1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1,175 8.6 1,175 8.6

2 1,334 9.76 2,509 18.36

3 1,364 9.98 3,873 28.34

4 1,982 14.5 5,855 42.84

5 2,625 19.21 8,480 62.05

6 2,869 20.99 11,349 83.05

7 2,317 16.95 13,666 100

89 contactmonth1 Month of 1st contact 1 = January

2 = February

3 = March

4 = April

5 = May

6 = June

7 = July

8 = August

9 = September

10 = October

11 = November

12 = December

Contactday1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

6 208 1.52 208 1.52

7 7,111 52.03 7,319 53.56

8 3,257 23.83 10,576 77.39

9 2,961 21.67 13,537 99.06

10 129 0.94 13,666 100

90 contacttime1 Time of 1st contact Put in standard 

time

91 numresp Number of responses 

(in 2-week window)

1–20

numresp Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 5,576 40.8 5,576 40.8

1 7,349 53.78 12,925 94.58

2 622 4.55 13,547 99.13

3 91 0.67 13,638 99.8

4 18 0.13 13,656 99.93

5 8 0.06 13,664 99.99

7 2 0.01 13,666 100

92 response1 First response 1 = yes, received a response

2 = out of office response

3 = undeliverable message 

response

4 = automated response

5 = scam response

– 9 = NA

response1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 7,355 90.91 7,355 90.91

2 49 0.61 7,404 91.52

3 512 6.33 7,916 97.85

4 172 2.13 8,088 99.98

5 2 0.02 8,090 100

Frequency Missing = 5,576
An Estimate of Housing Discrimination Against Same-Sex Couples 42

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

93 respdate1 Date of first response List actual date 

(e.g., 1 for 1st, 

12 for 12th)

1–31, – 9 = NA respdate1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 345 4.26 345 4.26

2 247 3.05 592 7.32

3 171 2.11 763 9.43

4 59 0.73 822 10.16

5 163 2.01 985 12.18

6 254 3.14 1,239 15.32

7 344 4.25 1,583 19.57

8 306 3.78 1,889 23.35

9 195 2.41 2,084 25.76

10 114 1.41 2,198 27.17

11 358 4.43 2,556 31.59

12 427 5.28 2,983 36.87

13 424 5.24 3,407 42.11

14 292 3.61 3,699 45.72

15 481 5.95 4,180 51.67

16 332 4.1 4,512 55.77

17 134 1.66 4,646 57.43

18 268 3.31 4,914 60.74

19 264 3.26 5,178 64

20 265 3.28 5,443 67.28

21 343 4.24 5,786 71.52

22 283 3.5 6,069 75.02

23 288 3.56 6,357 78.58

24 176 2.18 6,533 80.75

25 293 3.62 6,826 84.38

26 365 4.51 7,191 88.89

27 232 2.87 7,423 91.76

28 117 1.45 7,540 93.2

29 337 4.17 7,877 97.37

30 173 2.14 8,050 99.51

31 40 0.49 8,090 100

Frequency Missing = 5,576

94 respday1 Weekday of first response 1 = Sunday

2 = Monday

3 = Tuesday

4 = Wednesday

5 = Thursday

6 = Friday

7 = Saturday

respday1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 640 7.91 640 7.91

2 1,186 14.66 1,826 22.57

3 939 11.61 2,765 34.18

4 1,186 14.66 3,951 48.84

5 1,489 18.41 5,440 67.24

6 1,608 19.88 7,048 87.12

7 1,042 12.88 8,090 100

Frequency Missing = 5,576
An Estimate of Housing Discrimination Against Same-Sex Couples 43

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

95 respmonth1 Month of first response 1 = January

2 = February

3 = March

4 = April

5 = May

6 = June

7 = July

8 = August

9 = September

10 = October

11 = November

12 = December

– 9 = NA

respmonth1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1 0.01 1 0.01

5 1 0.01 2 0.02

6 57 0.7 59 0.73

7 4,122 50.95 4,181 51.68

8 1,912 23.63 6,093 75.32

9 1,893 23.4 7,986 98.71

10 103 1.27 8,089 99.99

12 1 0.01 8,090 100

Frequency Missing = 5,576

96 resptime1 Time of first response Put in Standard 

Time, XX:XX AM/

PM

– 9 = NA resptime1 Mean Std Dev Minimum Maximum

11:02:24 

PM

18:57 12:00:00 AM 12:00:00 AM

97 respnmeinemail1 Housing provider’s name 

in the “From” line

Record housing 

provider’s name

– 9 = NA

98 respprovothname1Housing provider’s name 

in body of email

Record housing 

provider’s name

– 9 = NA

99 response2 Second response 1 = yes, received a second 

response

2 = automated response

3 = scam response

– 9 = NA

response2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 2 0.27 2 0.27

1 718 96.9 720 97.17

2 20 2.7 740 99.87

3 1 0.13 741 100

Frequency Missing = 12,925

100 respdate2 Date of second response List actual date 

(e.g., 1 for 1st, 12 

for 12th)

1–31, – 9 = NA respdate2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 31 4.18 31 4.18

2 13 1.75 44 5.94

3 18 2.43 62 8.37

4 18 2.43 80 10.8

5 11 1.48 91 12.28

6 21 2.83 112 15.11

7 21 2.83 133 17.95

8 16 2.16 149 20.11

9 20 2.7 169 22.81

10 15 2.02 184 24.83

11 17 2.29 201 27.13

12 25 3.37 226 30.5

13 33 4.45 259 34.95

14 39 5.26 298 40.22

15 37 4.99 335 45.21

16 38 5.13 373 50.34

17 15 2.02 388 52.36

18 21 2.83 409 55.2

19 18 2.43 427 57.62
An Estimate of Housing Discrimination Against Same-Sex Couples 44

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

100 respdate2

(continued)

Date of second response List actual date 

(e.g., 1 for 1st, 

12 for 12th)

1–31, – 9 = NA respdate2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

20 32 4.32 459 61.94

21 33 4.45 492 66.4

22 26 3.51 518 69.91

23 36 4.86 554 74.76

24 25 3.37 579 78.14

25 26 3.51 605 81.65

26 24 3.24 629 84.89

27 30 4.05 659 88.93

28 33 4.45 692 93.39

29 21 2.83 713 96.22

30 22 2.97 735 99.19

31 6 0.81 741 100

Frequency Missing = 12,925

101 respday2 Weekday of second 

response

1 = Sunday

2 = Monday

3 = Tuesday

4 = Wednesday

5 = Thursday

6 = Friday

7 = Saturday

respday2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 86 11.61 86 11.61

2 111 14.98 197 26.59

3 82 11.07 279 37.65

4 121 16.33 400 53.98

5 110 14.84 510 68.83

6 127 17.14 637 85.96

7 104 14.04 741 100

Frequency Missing = 12,925

102 respmonth2 Month of second response 1 = January

2 = February

3 = March

4 = April

5 = May

6 = June

7 = July

8 = August

9 = September

10 = October

11 = November

12 = December

– 9 = NA

respmonth2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

6 1 0.13 1 0.13

7 359 48.45 360 48.58

8 162 21.86 522 70.45

9 187 25.24 709 95.68

10 32 4.32 741 100

Frequency Missing = 12,925

103 resptime2 Time of second response Put in Standard 

Time, XX:XX AM/

PM

– 9 = NA resptime2 Mean Std Dev Minimum Maximum

10:19:12 

AM

9:07 12:00:00 AM 12:00:00 AM

104 respnmeinemail2 Housing provider’s name 

in the “From” line

Record housing 

provider’s name

– 9 = NA

105 respprovothname2Housing provider’s name 

in body of email

Record housing 

provider’s name

– 9 = NA
An Estimate of Housing Discrimination Against Same-Sex Couples 45

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

106 response3 Third response 1 = yes, received a second 

response

2 = automated response

3 = scam response

– 9 = NA

response3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 108 90.76 108 90.76

2 11 9.24 119 100

Frequency Missing = 13,547

107 respdate3 Date of third response List actual date 

(e.g., 1 for 1st, 

12 for 12th)

1-31, – 9=NA respdate3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1 0.84 1 0.84

3 6 5.04 7 5.88

4 2 1.68 9 7.56

5 5 4.2 14 11.76

6 1 0.84 15 12.61

7 2 1.68 17 14.29

8 4 3.36 21 17.65

9 2 1.68 23 19.33

10 1 0.84 24 20.17

11 2 1.68 26 21.85

12 1 0.84 27 22.69

13 4 3.36 31 26.05

14 2 1.68 33 27.73

15 5 4.2 38 31.93

16 6 5.04 44 36.97

17 2 1.68 46 38.66

18 7 5.88 53 44.54

19 4 3.36 57 47.9

20 10 8.4 67 56.3

21 5 4.2 72 60.5

22 2 1.68 74 62.18

23 4 3.36 78 65.55

24 6 5.04 84 70.59

25 5 4.2 89 74.79

26 7 5.88 96 80.67

27 3 2.52 99 83.19

28 7 5.88 106 89.08

29 4 3.36 110 92.44

30 3 2.52 113 94.96

31 6 5.04 119 100

Frequency Missing = 13,547

108 respday3 Weekday of third response 1 = Sunday

2 = Monday

3 = Tuesday

4 = Wednesday

5 = Thursday

6 = Friday

7 = Saturday

respday3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 9 7.56 9 7.56

2 23 19.33 32 26.89

3 15 12.61 47 39.5

4 22 18.49 69 57.98

5 18 15.13 87 73.11

6 15 12.61 102 85.71

7 17 14.29 119 100

Frequency Missing = 13,547
An Estimate of Housing Discrimination Against Same-Sex Couples 46

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

109 respmonth3 Month of third response 1 = January

2 = February

3 = March

4 = April

5 = May

6 = June

7 = July

8 = August

9 = September

10 = October

11 = November

12 = December

– 9 = NA

respmonth3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

7 51 42.86 51 42.86

8 30 25.21 81 68.07

9 28 23.53 109 91.6

10 10 8.4 119 100

Frequency Missing = 13,547

110 resptime3 Time of third response Put in Standard 

Time, XX:XX 

AM/PM

– 9 = NA resptime3 Mean Std Dev Minimum Maximum

4:19:12 PM 4:33 12:00:00 AM 12:00:00 AM

111 respnmeinemail3 Housing provider’s name in 

the “From” line

Record housing 

provider’s name

– 9 = NA

112 respemail3 Housing provider’s email 

address in the “From” line

Record housing 

provider’s email 

address

– 9 = NA

113 respprovothname3Housing provider’s name in 

body of email

Record housing 

provider’s name

– 9 = NA

114 available1 Availability 1 = unit available

2 = unit not available

3 = housing provider not sure 

about availability

– 9 = NA

available1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 1,113 13.76 1,113 13.76

1 6,123 75.69 7,236 89.44

2 706 8.73 7,942 98.17

3 148 1.83 8,090 100

Frequency Missing = 5,576

115 availdate1 Date of availability List actual date 

(e.g., 1 for 1st, 

12 for 12th)

1–31, – 9 = NA availdate1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 5816 94.99 5816 94.99

1 157 2.56 5973 97.55

2 14 0.23 5987 97.78

3 3 0.05 5990 97.83

4 5 0.08 5995 97.91

5 13 0.21 6008 98.12

6 3 0.05 6011 98.17

7 5 0.08 6016 98.25

8 12 0.2 6028 98.45

9 3 0.05 6031 98.5

10 19 0.31 6050 98.81

12 3 0.05 6053 98.86

13 1 0.02 6054 98.87

14 1 0.02 6055 98.89

15 20 0.33 6075 99.22

17 4 0.07 6079 99.28
An Estimate of Housing Discrimination Against Same-Sex Couples 47

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

115 availdate1

(continued)

Date of availability List actual date 

(e.g., 1 for 1st, 

12 for 12th)

1–31, – 9 = NA availdate1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

19 5 0.08 6084 99.36

20 4 0.07 6088 99.43

21 3 0.05 6091 99.48

22 4 0.07 6095 99.54

23 6 0.1 6101 99.64

24 1 0.02 6102 99.66

25 4 0.07 6106 99.72

26 4 0.07 6110 99.79

28 1 0.02 6111 99.8

29 4 0.07 6115 99.87

30 2 0.03 6117 99.9

31 6 0.1 6123 100

Frequency Missing = 7,543

116 availASAP1 avalabile as soon as 

possible?

1 = yes, mentioned

2 = no, NOT mentioned availASAP1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 162 2.65 162 2.65

2 5,961 97.35 6,123 100

Frequency Missing = 7,543

117 availmonth1 Month of availability 1 = January

2 = February

3 = March

4 = April

5 = May

6 = June

7 = July

8 = August

9 = September

10 = October

11 = November

12 = December

– 9 = NA

availmonth1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 5,688 92.9 5,688 92.9

1 4 0.07 5,692 92.96

2 13 0.21 5,705 93.17

7 40 0.65 5,745 93.83

8 120 1.96 5,865 95.79

9 146 2.38 6,011 98.17

10 95 1.55 6,106 99.72

11 16 0.26 6,122 99.98

12 1 0.02 6,123 100

Frequency Missing = 7,543

118 availsoon1 Another unit available soon 1 = provider indicated another 

unit will become available 

soon

2 = provider did NOT indicate 

another unit will become 

available soon

availsoon1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 284 3.52 284 3.52

2 7,794 96.48 8,078 100

Frequency Missing = 5,588

119 inspection1 Inspection 1 = invited to inspect

2 = NOT invited to inspect Inspection1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 5,811 71.83 5,811 71.83

2 2,279 28.17 8,090 100

Frequency Missing = 5,576
An Estimate of Housing Discrimination Against Same-Sex Couples 48

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

120 inspecttime1 Timeframe given to inspect 

unit

1 = anytime 

2 = specify time provided 

(after ;)

3 = no timeframe given

Inspecttime1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 165 2.84 165 2.84

2 3,397 58.46 3,562 61.3

3 2,249 38.7 5,811 100

Frequency Missing = 7,855

121 contprov1 Contact provider 1 = advised to contact 

housing provider

2 = NOT advised to contact 

housing provider

contprov1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 4,333 53.56 4,333 53.56

2 3,757 46.44 8,090 100

Frequency Missing = 5,576

122 rphone1 Phone number given 

in response

1 = yes

2 = no rphone1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 5,517 68.2 5,517 68.2

2 2,573 31.8 8,090 100

Frequency Missing = 5,576

123 rphonenum1 record phone number (999)999–9999 = NA

124 resprent1 Monthly rent in response 1 = yes, mentioned

2 = no, NOT mentioned resprent1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 575 7.11 575 7.11

2 7,515 92.89 8,090 100

Frequency Missing = 5,576

125 rentamt1r1 Rent amount in response – 9 = NA rentamt1r1 Mean Std Dev Minimum Maximum

863.22471 499.9101911 358 3,800

126 rentamt2r1 2nd Rent amount in 

response

– 9 = NA rentamt2r1 Mean Std Dev Minimum Maximum

959.1266376 551.8941837 400 4,000

127 rentamt3r1 3rd Rent amount in 

response

– 9 = NA rentamt3r1 Mean Std Dev Minimum Maximum

817.3478261 362.6475385 450 1,547

128 respbfee1 Broker fee in e-mail 1 = broker fee mentioned by 

provider

2 = broker fee NOT mentioned 

by provider

respbfee1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 12 0.15 12 0.15

2 807,8 99.85 8,090 100

Frequency Missing = 5,576

129 respbfeeamt1 Amount of broker fee – 9 = NA respbfeeamt1 Mean Std Dev Minimum Maximum

. . . .

130 appfee1 Application fee in response 1 = yes, mentioned

2 = no, NOT mentioned appfee1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 197 2.44 197 2.44

2 7,893 97.56 8,090 100

Frequency Missing = 5,576

131 appfeeamt1 Application fee amount – 9 = NA appfeeamt1 Mean Std Dev Minimum Maximum

37.7289017 52.4416151 0 545

132 secdeposit1 Security deposit 

in response

1 = yes, mentioned

2 = no, NOT mentioned secdeposit1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 164 2.03 164 2.03

2 7,926 97.97 8,090 100

Frequency Missing = 5,576

133 secdepamt1 Security deposit amount – 9 = NA secdepamt1 Mean Std Dev Minimum Maximum

310.4032258 381.8625177 0 2,800
An Estimate of Housing Discrimination Against Same-Sex Couples 49

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

134 credchk1 Credit check mentioned 

in response

1 = yes, mentioned

2 = no, NOT mentioned credchk1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 125 1.55 125 1.55

2 7,965 98.45 8,090 100

Frequency Missing = 5,576

135 credchkfee1 Credit check fee mentioned 

in response

1 = yes, mentioned

2 = no, NOT mentioned credchkfee1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 10 8 10 8

2 115 92 125 100

Frequency Missing = 13,541

136 credchkfeeamt1 credit check fee amount 

in response

– 9 = NA credchkfeeamt1 Mean Std Dev Minimum Maximum

33.5 15.6436 10 65

137 respfee1 Other fee in e-mail 1 = yes, mentioned

2 = no, NOT mentioned respfee1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 112 1.38 112 1.38

2 7,978 98.62 8,090 100

Frequency Missing = 5,576

138 respfeeamt1 Amount of other fee – 9 = NA respfeeamt1 Mean Std Dev Minimum Maximum

154.2989691 120.7887416 0 500

139 rentdiscount1 Rent discount offered 

in response

1 = yes, offered

2 = no, NOT offered rentdiscount1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 179 2.21 179 2.21

2 7,911 97.79 8,090 100

Frequency Missing = 5,576

140 lease1 Lease in response 1 = yes, a lease

2 = no, NO lease lease1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 139 1.72 139 1.72

2 7,951 98.28 8,090 100

Frequency Missing = 5,576

141 leaseterm1 Lease term Accepts range, (XX–XX), 

– 9 = NA

142 areaamen1 Area amenities mentioned 

in response

1 = yes, mentioned

2 = no, NOT mentioned areaamen1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 209 2.58 209 2.58

2 7,881 97.42 8,090 100

Frequency Missing = 5,576

143 areaamentyp1a Amenities – schools 1 = yes, schools/good schools 

mentioned

2 = no, schools/good schools 

NOT mentioned

areaamentyp1a Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 31 14.83 31 14.83

2 178 85.17 209 100

Frequency Missing = 13457

144 areaamentyp1b Amenities – transportation 1 = yes, transportation 

mentioned

2 = no, transportation NOT 

mentioned

areaamentyp1b Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 97 46.41 97 46.41

2 112 53.59 209 100

Frequency Missing = 13,457
An Estimate of Housing Discrimination Against Same-Sex Couples 50

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

145 areaamentyp1c Amenities – shopping 1 = yes, shopping mentioned

2 = no, shopping NOT 

mentioned

areaamentyp1c Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 162 77.51 162 77.51

2 47 22.49 209 100

Frequency Missing = 13,457

146 areaamentyp1d Amenities – recreation

(e.g. restaurants, parks, 

museums, etc.)

1 = yes, recreation mentioned

2 = no, recreation NOT 

mentioned

areaamentyp1d Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 149 71.29 149 71.29

2 60 28.71 209 100

Frequency Missing = 13,457

147 areaamentyp1e Amenities – jobs 1 = yes, jobs mentioned

2 = no, jobs NOT mentioned areaamentyp1e Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 15 7.18 15 7.18

2 194 92.82 209 100

Frequency Missing = 13,457

148 areaamentyp1f Amenities – other 1 = yes, other mentioned

2 = no, other NOT mentioned areaamentyp1f Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 117 55.98 117 55.98

2 92 44.02 209 100

Frequency Missing = 13,457

149 buildamen1 Building amenities 

mentioned in response

(e.g., laundry facilities, 

WIFI, garage)

1=yes, mentioned

2=no, NOT mentioned buildamen1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 432 5.34 432 5.34

2 7,658 94.66 8,090 100

Frequency Missing = 5,576

150 raddress1 Address of unit given in 

response

1 = yes

2 = no raddress1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 735 9.09 735 9.09

2 7,355 90.91 8,090 100

Frequency Missing = 5,576

151 attachment1 E-mail attachment present 1 = yes

2 = no attachment1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 254 3.14 254 3.14

2 7,836 96.86 8,090 100

Frequency Missing = 5,576

152 forward1 Offer to forward email or 

email forwarded to others 

besides contact person

1 = yes

2 = no forward1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 71 0.88 71 0.88

2 8,019 99.12 8,090 100

Frequency Missing = 5,576

153 resp1quest1 Employment status 1 = yes, asked

2 = no, NOT asked resp1quest1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 68 0.84 68 0.84

2 8,022 99.16 8,090 100

Frequency Missing = 5,576

154 resp1quest2 Relationship status 

(e.g., married, divorced, 

partnered)

1 = yes, asked

2 = no, NOT asked resp1quest2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 2 0.02 2 0.02

2 8,088 99.98 8,090 100

Frequency Missing = 5,576
An Estimate of Housing Discrimination Against Same-Sex Couples 51

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

155 resp1quest3 Presence of children 1 = yes, asked

2 = no, NOT asked resp1quest3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

11 0.011 0.01

2 8,089 99.99 8,090 100

Frequency Missing = 5,576

156 resp1quest4 Reason for moving 1 = yes, asked

2 = no, NOT asked resp1quest4 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

16 0.076 0.07

2 8,084 99.93 8,090 100

Frequency Missing = 5,576

157 resp1quest5 Current residence 1 = yes, asked

2 = no, NOT asked resp1quest5 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 23 0.28 23 0.28 2 8,067 99.72 8,090 100

Frequency Missing = 5,576

158 resp1quest6 Credit check 1 = yes, asked

2 = no, NOT asked resp1quest6 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 79 0.98 79 0.98 2 8,011 99.02 8,090 100

Frequency Missing = 5,576

159 resp1quest7 Background check 1 = yes, asked

2 = no, NOT asked resp1quest7 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 54 0.67 54 0.67 2 8,036 99.33 8,090 100

Frequency Missing = 5,576

160 resp1quest8 Whether application 

required before inspection

1 = yes, asked

2 = no, NOT asked resp1quest8 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 60 0.74 60 0.74 2 8,030 99.26 8,090 100

Frequency Missing = 5,576

161 resp1quest9 Social Security number 1 = yes, asked

2 = no, NOT asked resp1quest9 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

18 0.18 0.1

2 8,082 99.9 8,090 100

Frequency Missing = 5,576

162 resp1quest10 Income level 1 = yes, asked

2 = no, NOT asked resp1quest10 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 72 0.89 72 0.89 2 8,018 99.11 8,090 100

Frequency Missing = 5,576

163 resp1quest11 Who is the unit for 1 = yes, asked

2 = no, NOT asked resp1quest11 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 54 0.67 54 0.67 2 8,036 99.33 8,090 100

Frequency Missing = 5,576

164 resp1quest12 When are you looking 

to move

1 = yes, asked

2 = no, NOT asked resp1quest12 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 477 5.9 477 5.9 2 7,613 94.1 8,090 100

Frequency Missing = 5,576
An Estimate of Housing Discrimination Against Same-Sex Couples 52

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

165 resp1quest13 Do you have any pets 1 = yes, asked

2 = no, NOT asked resp1quest13 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 162 2 162 2

2 7,928 98 8,090 100

Frequency Missing = 5,576

166 resp1quest14 Are you still interested 1 = yes, asked

2 = no, NOT asked resp1quest14 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 53 0.66 53 0.66

2 8,037 99.34 8,090 100

Frequency Missing = 5,576

167 legalstatus1 Whether legal or illegal 

immigrant

1 = yes, asked

2 = no, NOT asked legalstatus1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 3 0.04 3 0.04

2 8,087 99.96 8,090 100

Frequency Missing = 5,576

168 cphone1 Tester’s phone number 1 = yes, asked

2 = no, NOT asked cphone1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 291 3.6 291 3.6

2 7,799 96.4 8,090 100

Frequency Missing = 5,576

169 sexorient1 Tester’s sexual orientation 1 = yes, asked

2 = no, NOT asked sexorient1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 4 0.05 4 0.05

2 8,086 99.95 8,090 100

Frequency Missing = 5,576

170 addunits1 Additional units 1 = informed of additional 

units

2 = NOT informed of 

additional units

– 9 = NA

addunits1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 895 11.06 895 11.06

1 999 12.35 1,894 23.41

2 6,196 76.59 8,090 100

Frequency Missing = 5576

171 addunitaddress1 Additional unit address list address 

information 

including house 

number and 

street address

– 9 = NA

172 addunitcity1 Additional unit city/town list city/town – 9 = NA

173 addunitst1 Additional unit state list state 1 = AL 

2 = AK 

3 = AZ 

4 = AR 

5 = CA 

6 = CO 

7 = CT 

8 = DC

9 = DE

10 = FL

11 = GA

addunits1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 885 88.59 885 88.59

2 1 0.1 886 88.69

3 13 1.3 899 89.99

5 12 1.2 911 91.19

6 12 1.2 923 92.39

9 1 0.1 924 92.49

10 9 0.9 933 93.39

11 9 0.9 942 94.29

21 1 0.1 943 94.39
An Estimate of Housing Discrimination Against Same-Sex Couples 53

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

173 addunitst1

(continued)

Additional unit state list state 12 = HI 

13 = ID addunits1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

14 = IL 23 5 0.5 948 94.89

15 = IN 24 2 0.2 950 95.1

16 = IA 26 3 0.3 953 95.4

17 = KS 32 2 0.2 955 95.6

18 = KY 33 11 1.1 966 96.7

19 = LA 34 3 0.3 969 97

20 = ME 35 1 0.1 970 97.1

21 = MD 37 2 0.2 972 97.3

22 = MA 41 3 0.3 975 97.6

23 = MI 44 15 1.5 990 99.1

24 = MN 45 2 0.2 992 99.3

25 = MS 48 7 0.7 999 100

26 = MO 

27 = MT

28 = NE

29 = NV

30 = NH

31 = NJ

32 = NM

33 = NY

34 = NC

35 = ND

36 = OH

37 = OK

38 = OR

39 = PA

40 = RI

41 = SC

42 = SD

43 = TN

44 = TX

45 = UT

46 = VT

47 = VA

48 = WA

49 = WV

50 = WI

51 = WY

– 9 = NA Frequency Missing = 12,667

174 addunitzip1 Additional unit Zip code List first 5 digits 

of zip code in 

which unit is 

located
An Estimate of Housing Discrimination Against Same-Sex Couples 54

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

175 addunitzipsuff1 Additional unit Zip code 

optional suffix

List last 4 digits 

of zip code 

in which unit 

is located IF 

PROVIDED

176 available2 Availability available2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 189 25.51 189 25.51

1 513 69.23 702 94.74

2 36 4.86 738 99.6

3 3 0.4 741 100

Frequency Missing = 12,925

177 availdate2 Date of availability List actual date 

(e.g., 1 for 1st, 

12 for 12th)

avaidate2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 492 95.91 492 95.91

1 9 1.75 501 97.66

2 2 0.39 503 98.05

7 2 0.39 505 98.44

19 1 0.19 506 98.64

20 3 0.58 509 99.22

21 3 0.58 512 99.81

23 1 0.19 513 100

Frequency Missing = 13,153

178 availASAP2 avalabile as soon as 

possible? avaiASAP2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 12 2.34 12 2.34

2 501 97.66 513 100

Frequency Missing = 13,153

179 availmonth2 Month of availability 1 = January

2 = February avaimonth2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

3 = March – 9 483 94.15 483 94.15

4 = April 2 2 0.39 485 94.54

5 = May 7 8 1.56 493 96.1

6 = June 8 5 0.97 498 97.08

7 = July 9 10 1.95 508 99.03

8 = August 10 4 0.78 512 99.81

9 = September 11 1 0.19 513 100

10 = October

11 = November

12 = December

– 9 = NA Frequency Missing = 13,153

180 availsoon2 Another unit available soon 1 = provider indicated another 

unit will become available 

soon

2 = provider did NOT indicate 

another unit will become 

available soon

avaisoon2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 17 2.29 17 2.29

2 724 97.71 741 100

Frequency Missing = 12,925
An Estimate of Housing Discrimination Against Same-Sex Couples 55

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

181 inspection2 Inspection 1 = invited to inspect

2 = NOT invited to inspect inspection2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 508 68.56 508 68.56

2 233 31.44 741 100

Frequency Missing = 12,925

182 inspecttime2 Timeframe given to 

inspect unit

1 = anytime

2 = specify time provided 

(after ;)

3 = no timeframe given

inspecttime2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 16 3.15 16 3.15

2 281 55.31 297 58.46

3 211 41.54 508 100

Frequency Missing = 13,158

183 contprov2 Contact provider 1 = advised to contact 

housing provider

2 = NOT advised to contact 

housing provider

contprov2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 363 48.99 363 48.99

2 378 51.01 741 100

Frequency Missing = 12,925

184 rphone2 Phone number given in 

response

1 = yes

2 = no rphone2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 487 65.72 487 65.72

2 254 34.28 741 100

Frequency Missing = 12,925

185 rphonenum2 record phone number (999)999–9999 = NA

186 resprent2 Monthly rent in response 1 = yes, mentioned

2 = no, NOT mentioned resprent2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 46 6.21 46 6.21

2 695 93.79 741 100

Frequency Missing = 12,925

187 rentamt1r2 Rent amount in response – 9 = NA rentamt1r2 Mean Std Dev Minimum Maximum

1088.83 916.5512001 389 5,353

188 rentamt2r2 2nd Rent amount in 

response

– 9 = NA rentamt2r2 Mean Std Dev Minimum Maximum

858.2727273 467.6620769 434 2,135

189 rentamt3r2 3rd Rent amount in 

response

– 9 = NA rentamt3r2 Mean Std Dev Minimum Maximum

837 265.8721497 649 1,025

190 respbfee2 Broker fee in e-mail 1 = broker fee mentioned by 

provider

2 = broker fee NOT mentioned 

by provider

resprent2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 2 0.27 2 0.27

2 739 99.73 741 100

Frequency Missing = 12,925

191 respbfeeamt2 Amount of broker fee – 9 = NA respbfeeamt2 Mean Std Dev Minimum Maximum

. . . .

192 appfee2 Application fee in response 1 = yes, mentioned

2 = no, NOT mentioned resprent2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 13 1.75 13 1.75

2 728 98.25 741 100

Frequency Missing = 12,925

193 appfeeamt2 Application fee amount – 9 = NA appfeeamt2 Mean Std Dev Minimum Maximum

23.8888889 25.5902542 0 75
An Estimate of Housing Discrimination Against Same-Sex Couples 56

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

194 secdeposit2 Security deposit in 

response

1 = yes, mentioned

2 = no, NOT mentioned secdeposit2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 8 1.08 8 1.08

2 733 98.92 741 100

Frequency Missing = 12925

195 secdepamt2 Security deposit amount – 9 = NA secdepamt2 Mean Std Dev Minimum Maximum

248.8333333 233.5664074 87.5 550

196 credchk2 Credit check mentioned in 

response

1 = yes, mentioned

2 = no, NOT mentioned credchk2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 3 0.4 3 0.4

2 738 99.6 741 100

Frequency Missing = 12,925

197 credchkfee2 Credit check fee mentioned 

in response

1 = yes, mentioned

2 = no, NOT mentioned credchkfee2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 3 100 3 100

Frequency Missing = 13,663

198 credchkfeeamt2 credit check fee amount in 

response

– 9 = NA credchkfeeamt2 Mean Std Dev Minimum Maximum

. . . .

199 respfee2 Other fee in e-mail 1 = yes, mentioned

2 = no, NOT mentioned respfee2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 5 0.67 5 0.67

2 736 99.33 741 100

Frequency Missing = 12,925

200 respfeeamt2 Amount of other fee – 9 = NA respfeeamt2 Mean Std Dev Minimum Maximum

190 149.3318452 20 300

201 rentdiscount2 Rent discount offered in 

response

1 = yes, offered

2 = no, NOT offered rentdiscount2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 22 2.97 22 2.97

2 719 97.03 741 100

Frequency Missing = 12,925

202 rentdisdesc2 Description of rent discount – 9 = NA

203 lease2 Lease in response 1 = yes, a lease

2 = no, NO lease lease2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 11 1.48 11 1.48

2 730 98.52 741 100

Frequency Missing = 12,925

204 leaseterm2 Lease term Accepts range, (XX–XX), 

– 9 = NA

205 areaamen2 Area amenities mentioned 

in response

1 = yes, mentioned

2 = no, NOT mentioned areaamen2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 22 2.97 22 2.97

2 719 97.03 741 100

Frequency Missing = 12,925

206 areaamentyp2a Amenities – schools 1 = yes, schools/good schools 

mentioned

2 = no, schools/good schools 

NOT mentioned

areaamentyp2a Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 4 18.18 4 18.18

2 18 81.82 22 100

Frequency Missing = 13,644
An Estimate of Housing Discrimination Against Same-Sex Couples 57

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

207 areaamentyp2b Amenities – transportation 1 = yes, transportation 

mentioned

2 = no, transportation NOT 

mentioned

areaamentyp2b Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 13 59.09 13 59.09

2 9 40.91 22 100

Frequency Missing = 13,644

208 areaamentyp2c Amenities – shopping 1 = yes, shopping mentioned

2 = no, shopping NOT 

mentioned

areaamentyp2c Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 12 54.55 12 54.55

2 10 45.45 22 100

Frequency Missing = 13,644

209 areaamentyp2d “Amenities – recreation

(e.g. restaurants, parks, 

museums, etc.)”

1 = yes, recreation mentioned

2 = no, recreation NOT 

mentioned

areaamentyp2d Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 14 63.64 14 63.64

2 8 36.36 22 100

Frequency Missing = 13,644

210 areaamentyp2e Amenities – jobs 1 = yes, jobs mentioned

2 = no, jobs NOT mentioned areaamentyp2e Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 2 9.09 2 9.09

2 20 90.91 22 100

Frequency Missing = 13,644

211 areaamentyp2f Amenities – other 1 = yes, other mentioned

2 = no, other NOT mentioned areaamentyp2f Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 10 45.45 10 45.45

2 12 54.55 22 100

Frequency Missing = 13,644

212 buildamen2 Building amenities 

mentioned in response

(e.g., laundry facilities, 

WIFI, garage)

1 = yes, mentioned

2 = no, NOT mentioned buildamen2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 34 4.59 34 4.59

2 707 95.41 741 100

Frequency Missing = 12,925

213 raddress2 Address of unit given 

in response

1 = yes

2 = no raddress2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 86 11.61 86 11.61

2 655 88.39 741 100

Frequency Missing = 12,925

214 attachment2 E-mail attachment present 1 = yes

2 = no attachment2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 33 4.45 33 4.45

2 708 95.55 741 100

Frequency Missing = 12,925

215 forward2 Offer to forward email or 

email forwarded to others 

besides contact person

1 = yes

2 = no forward2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 10 1.35 10 1.35

2 731 98.65 741 100

Frequency Missing = 12,925

216 resp2quest1 Employment status 1 = yes, asked

2 = no, NOT asked resp2quest1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925
An Estimate of Housing Discrimination Against Same-Sex Couples 58

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

217 resp2quest2 Relationship status 

(e.g., married, divorced, 

partnered)

1 = yes, asked

2 = no, NOT asked resp2quest2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925

218 resp2quest3 Presence of children 1 = yes, asked

2 = no, NOT asked resp2quest3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925

219 resp2quest4 Reason for moving 1 = yes, asked

2 = no, NOT asked resp2quest4 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925

220 resp2quest5 Current residence 1 = yes, asked

2 = no, NOT asked resp2quest5 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12925

221 resp2quest6 Credit check 1 = yes, asked

2 = no, NOT asked resp2quest6 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925

222 resp2quest7 Background check 1 = yes, asked

2 = no, NOT asked resp2quest7 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925

223 resp2quest8 Whether application 

required before inspection

1 = yes, asked

2 = no, NOT asked resp2quest8 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

13 0.43 0.4

2 738 99.6 741 100

Frequency Missing = 12,925

224 resp2quest9 Social Security number 1 = yes, asked

2 = no, NOT asked resp2quest9 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925

225 resp2quest10 Income level 1 = yes, asked

2 = no, NOT asked resp2quest10 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925

226 resp2quest11 Who is the unit for 1 = yes, asked

2 = no, NOT asked resp2quest11 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

12 0.272 0.27

2 739 99.73 741 100

Frequency Missing = 12,925

227 resp2quest12 When are you looking to 

move

1 = yes, asked

2 = no, NOT asked resp2quest12 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 16 2.16 16 2.16 2 725 97.84 741 100

Frequency Missing = 12,925
An Estimate of Housing Discrimination Against Same-Sex Couples 59

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

228 resp2quest13 Do you have any pets 1 = yes, asked

2 = no, NOT asked resp2quest13 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 10 1.35 10 1.35

2 731 98.65 741 100

Frequency Missing = 12,925

229 resp2quest14 Are you still interested 1 = yes, asked

2 = no, NOT asked resp2quest14 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 137 18.49 137 18.49

2 604 81.51 741 100

Frequency Missing = 12,925

230 legalstatus2 Whether legal or illegal 

immigrant

1 = yes, asked

2 = no, NOT asked legalstatus2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 741 100 741 100

Frequency Missing = 12,925

231 cphone2 Tester’s phone number 1 = yes, asked

2 = no, NOT asked cphone2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 25 3.37 25 3.37

2 716 96.63 741 100

Frequency Missing = 12,925

232 sexorient2 Tester’s sexual orientation 1 = yes, asked

2 = no, NOT asked sexorient2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1 0.13 1 0.13

2 740 99.87 741 100

Frequency Missing = 12,925

233 addunits2 Additional units 1 = informed of additional 

units

2 = NOT informed of 

additional units

– 9 = NA

addunits2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 91 12.28 91 12.28

1 58 7.83 149 20.11

2 592 79.89 741 100

Frequency Missing = 12,925

234 addunitaddress2 Additional unit address list address 

information 

including house 

number and 

street address

– 9 = NA

235 addunitcity2 Additional unit city/town list city/town – 9 = NA

236 addunitst2 Additional unit state list state 1 = AL 

2 = AK addunitst2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

3 = AZ – 9 48 82.76 48 82.76

4 = AR 3 2 3.45 50 86.21

5 = CA 33 4 6.9 54 93.1

6 = CO 44 4 6.9 58 100

7 = CT 

8 = DC

9 = DE 

10 = FL 

11 = GA 

12 = HI 
An Estimate of Housing Discrimination Against Same-Sex Couples 60

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

236 addunitst2

(continued)

Additional unit state list state 13 = ID 

14 = IL addunitst2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

15 = IN 

16 = IA 

17 = KS 

18 = KY 

19 = LA 

20 = ME 

21 = MD 

22 = MA 

23 = MI 

24 = MN 

25 = MS 

26 = MO 

27 = MT

28 = NE

29 = NV

30 = NH

31 = NJ

32 = NM

33 = NY

34 = NC

35 = ND

36 = OH

37 = OK

38 = OR

39 = PA

40 = RI

41 = SC

42 = SD

43 = TN

44 = TX

45 = UT

46 = VT

47 = VA

48 = WA

49 = WV

50 = WI

51 = WY

– 9 = NA Frequency Missing = 13,608

237 addunitzip2 Additional unit Zip code List first 5 digits 

of zip code in 

which unit is 

located

99999 = NA

238 addunitzipsuff2 Additional unit Zip code 

optional suffix

List last 4 digits 

of zip code 

in which unit 

is located IF 

PROVIDED

9999 = NA
An Estimate of Housing Discrimination Against Same-Sex Couples 61

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

239 available3 Availability 1 = unit available

2 = unit not available

3 = housing provider not sure 

about availability

– 9 = NA

available3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 46 38.66 46 38.66

1 66 55.46 112 94.12

2 7 5.88 119 100

Frequency Missing = 13547

240 availdate3 Date of availability List actual date 

(e.g., 1 for 1st, 

12 for 12th)

1–31, – 9 = NA availdate3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 65 98.48 65 98.48

21 1 1.52 66 100

Frequency Missing = 13,600

241 availASAP3 avalabile as soon as 

possible?

1 = yes, mentioned

2 = no, NOT mentioned availASAP3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 5 7.58 5 7.58

2 61 92.42 66 100

Frequency Missing = 13,600

242 availmonth3 Month of availability 1 = January

2 = February availmonth3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

3 = March – 9 65 98.48 65 98.48

4 = April 10 1 1.52 66 100

5 = May

6 = June

7 = July

8 = August

9 = September

10 = October

11 = November

12 = December

– 9 = NA Frequency Missing = 13,600

243 availsoon3 Another unit available soon 1 = provider indicated another 

unit will become available 

soon

2 = provider did NOT indicate 

another unit will become 

available soon

availsoon3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 3 2.52 3 2.52

2 116 97.48 119 100

Frequency Missing = 13,547

244 inspection3 Inspection 1 = invited to inspect

2 = NOT invited to inspect inspection3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 59 49.58 59 49.58

2 60 50.42 119 100

Frequency Missing = 13,547

245 inspecttime3 Timeframe given to 

inspect unit

1 = anytime

2 = specify time provided 

(after ;)

3 = no timeframe given

inspecttime3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 34 57.63 34 57.63

3 25 42.37 59 100

Frequency Missing = 13,607
An Estimate of Housing Discrimination Against Same-Sex Couples 62

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

246 contprov3 Contact provider 1 = advised to contact 

housing provider

2 = NOT advised to contact 

housing provider

contprov3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 57 47.9 57 47.9

2 62 52.1 119 100

Frequency Missing = 13,547

247 rphone3 Phone number given in 

response

1 = yes

2 = no rphone3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 75 63.03 75 63.03

2 44 36.97 119 100

Frequency Missing = 13547

248 rphonenum3 record phone number (999)999–9999 = NA

249 resprent3 Monthly rent in response 1 = yes, mentioned

2 = no, NOT mentioned resprent3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 9 7.56 9 7.56

2 110 92.44 119 100

Frequency Missing = 13,547

250 rentamt1r3 Rent amount in response – 9 = NA rentamt1r3 Mean Std Dev Minimum Maximum

1076.78 424.3079005 720 1895

251 rentamt2r3 2nd Rent amount in 

response

– 9 = NA rentamt2r3 Mean Std Dev Minimum Maximum

2344 0 2344 2344

252 rentamt3r3 3rd Rent amount in 

response

– 9 = NA rentamt3r3 Mean Std Dev Minimum Maximum

. . . .

253 respbfee3 Broker fee in e-mail 1 = broker fee mentioned by 

provider

2 = broker fee NOT mentioned 

by provider

respbfee3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

254 respbfeeamt3 Amount of broker fee – 9 = NA respbfeeamt3 Mean Std Dev Minimum Maximum

. . . .

255 appfee3 Application fee in response 1 = yes, mentioned

2 = no, NOT mentioned appfee3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 5 4.2 5 4.2

2 114 95.8 119 100

Frequency Missing = 13,547

256 appfeeamt3 Application fee amount – 9 = NA appfeeamt3 Mean Std Dev Minimum Maximum

28.3333333 40.7226391 0 75

257 secdeposit3 Security deposit in 

response

1 = yes, mentioned

2 = no, NOT mentioned appfee3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 4 3.36 4 3.36

2 115 96.64 119 100

Frequency Missing = 13,547

258 secdepamt3 Security deposit amount – 9 = NA secdepamt3 Mean Std Dev Minimum Maximum

237.25 411.1572084 0 850

259 credchk3 Credit check mentioned in 

response

1 = yes, mentioned

2 = no, NOT mentioned credchk3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 2 1.68 2 1.68

2 117 98.32 119 100

Frequency Missing = 13,547
An Estimate of Housing Discrimination Against Same-Sex Couples 63

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

260 credchkfee3 Credit check fee mentioned 

in response

1 = yes, mentioned

2 = no, NOT mentioned credchk3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 2 100 2 100

Frequency Missing = 13,664

261 credchkfeeamt3 credit check fee amount in 

response

– 9 = NA credchkfeeamt3 Mean Std Dev Minimum Maximum

. . . .

262 respfee3 Other fee in e-mail 1 = yes, mentioned

2 = no, NOT mentioned respfee3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 2 1.68 2 1.68

2 117 98.32 119 100

Frequency Missing = 13,547

263 respfeeamt3 Amount of other fee – 9 = NA respfeeamt3 Mean Std Dev Minimum Maximum

99 0 99 99

264 rentdiscount3 Rent discount offered in 

response

1 = yes, mentioned

2 = no, NOT mentioned rentdiscount3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1 0.84 1 0.84

2 118 99.16 119 100

Frequency Missing = 13,547

265 rentdisdesc3 Description of rent discount – 9 = NA

266 lease3 Lease in response 1 = yes, a lease

2 = no, NO lease lease3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 3 2.52 3 2.52

2 116 97.48 119 100

Frequency Missing = 13,547

267 leaseterm3 Lease term Accepts range, (XX–XX), 

– 9 = NA

268 areaamen3 Area amenities mentioned 

in response

1 = yes, mentioned

2 = no, NOT mentioned areaamen3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 5 4.2 5 4.2

2 114 95.8 119 100

Frequency Missing = 13,547

269 areaamentyp3a Amenities – schools 1 = yes, schools/good schools 

mentioned

2 = no, schools/good schools 

NOT mentioned

areaamentyp3a Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1 20 1 20

2 4 80 5 100

Frequency Missing = 13,661

270 areaamentyp3b Amenities – transportation 1 = yes, transportation 

mentioned

2 = no, transportation NOT 

mentioned

areaamentyp3b Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 4 80 4 80

2 1 20 5 100

Frequency Missing = 13,661

271 areaamentyp3c Amenities – shopping 1 = yes, shopping mentioned

2 = no, shopping 

NOT mentioned

areaamentyp3c Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 4 80 4 80

2 1 20 5 100

Frequency Missing = 13,661
An Estimate of Housing Discrimination Against Same-Sex Couples 64

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

272 areaamentyp3d Amenities – recreation 

(e.g. restaurants, parks, 

museums, etc.)

1 = yes, recreation mentioned

2 = no, recreation NOT 

mentioned

areaamentyp3d Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 4 80 4 80

2 1 20 5 100

Frequency Missing = 13,661

273 areaamentyp3e Amenities – jobs 1 = yes, jobs mentioned

2 = no, jobs NOT mentioned areaamentyp3e Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 5 100 5 100

Frequency Missing = 13,661

274 areaamentyp3f Amenities – other 1 = yes, other mentioned

2 = no, other NOT mentioned areaamentyp3f Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 5 100 5 100

Frequency Missing = 13,661

275 buildamen3 Building amenities 

mentioned in response

(e.g., laundry facilities, 

WIFI, garage)

1 = yes, mentioned

2 = no, NOT mentioned buildamen3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 13 10.92 13 10.92

2 106 89.08 119 100

Frequency Missing = 13,547

276 raddress3 Address of unit given in 

response

1 = yes

2 = no raddress3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 18 15.13 18 15.13

2 101 84.87 119 100

Frequency Missing = 13,547

277 attachment3 E-mail attachment present 1 = yes

2 = no attachment3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 10 8.4 10 8.4

2 109 91.6 119 100

Frequency Missing = 13,547

278 forward3 Offer to forward email or 

email forwarded to others 

besides contact person

1 = yes

2 = no forward3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1 0.84 1 0.84

2 118 99.16 119 100

Frequency Missing = 13,547

279 resp3quest1 Employment status 1 = yes, asked

2 = no, NOT asked resp3quest1 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

280 resp3quest2 Relationship status 

(e.g., married, divorced, 

partnered)

1 = yes, asked

2 = no, NOT asked resp3quest2 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

281 resp3quest3 Presence of children 1 = yes, asked

2 = no, NOT asked resp3quest3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

282 resp3quest4 Reason for moving 1 = yes, asked

2 = no, NOT asked resp3quest4 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547
An Estimate of Housing Discrimination Against Same-Sex Couples 65

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

283 resp3quest5 Current residence 1 = yes, asked

2 = no, NOT asked resp3quest5 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

284 resp3quest6 Credit check 1 = yes, asked

2 = no, NOT asked resp3quest6 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

285 resp3quest7 Background check 1 = yes, asked

2 = no, NOT asked resp3quest7 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

286 resp3quest8 Whether application re-

quired before inspection

1 = yes, asked

2 = no, NOT asked resp3quest8 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

11 0.841 0.84

2 118 99.16 119 100

Frequency Missing = 13,547

287 resp3quest9 Social Security number 1 = yes, asked

2 = no, NOT asked resp3quest9 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

288 resp3quest10 Income level 1 = yes, asked

2 = no, NOT asked resp3quest10 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

289 resp3quest11 Who is the unit for 1 = yes, asked

2 = no, NOT asked resp3quest11 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

11 0.841 0.84

2 118 99.16 119 100

Frequency Missing = 13,547

290 resp3quest12 When are you looking 

to move

1 = yes, asked

2 = no, NOT asked resp3quest112 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

11 0.841 0.84

2 118 99.16 119 100

Frequency Missing = 13,547

291 resp3quest13 Do you have any pets 1 = yes, asked

2 = no, NOT asked resp3quest113 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

11 0.841 0.84

2 118 99.16 119 100

Frequency Missing = 13,547

292 resp3quest14 Are you still interested 1 = yes, asked

2 = no, NOT asked resp3quest114 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 35 29.41 35 29.41 2 84 70.59 119 100

Frequency Missing = 13,547

293 legalstatus3 Whether legal or illegal 

immigrant

1 = yes, asked

2 = no, NOT asked legalstatus3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547
An Estimate of Housing Discrimination Against Same-Sex Couples 66

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

294 cphone3 Tester’s phone number 1 = yes, asked

2 = no, NOT asked cphone3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 1 0.84 1 0.84

2 118 99.16 119 100

Frequency Missing = 13,547

295 sexorient3 Tester’s sexual orientation 1 = yes, asked

2 = no, NOT asked sexorient3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

2 119 100 119 100

Frequency Missing = 13,547

296 addunits3 Additional units 1 = informed of additional 

units

2 = NOT informed of 

additional units

– 9 = NA

addunits3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

– 9 19 15.97 19 15.97

1 12 10.08 31 26.05

2 88 73.95 119 100

Frequency Missing = 13547

297 addunitaddress3 Additional unit address list address 

information 

including house 

number and 

street address

– 9 = NA

298 addunitcity3 Additional unit city/town list city/town – 9 = NA

299 addunitst3 Additional unit state list state 1 = AL 

2 = AK addunitst3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

3 = AZ – 9 9 75 9 75

4 = AR 44 3 25 12 100

5 = CA 

6 = CO 

7 = CT 

8 = DC

9 = DE 

10 = FL 

11 = GA 

12 = HI 

13 = ID 

14 = IL 

15 = IN 

16 = IA 

17 = KS 

18 = KY 

19 = LA 

20 = ME 

21 = MD 

22 = MA 

23 = MI 

24 = MN 

25 = MS 

26 = MO 

27 = MT

28 = NE
An Estimate of Housing Discrimination Against Same-Sex Couples 67

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

299 addunitst3

(continued)

Additional unit state list state 29 = NV

30 = NH addunitst3 Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

31 = NJ

32 = NM

33 = NY

34 = NC

35 = ND

36 = OH

37 = OK

38 = OR

39 = PA

40 = RI

41 = SC

42 = SD

43 = TN

44 = TX

45 = UT

46 = VT

47 = VA

48 = WA

49 = WV

50 = WI

51 = WY

– 9 = NA Frequency Missing = 13,654

300 addunitzip3 Additional unit Zip code List first 5 digits 

of zip code in 

which unit is 

located

99999 = NA

301 addunitzipsuff3 Additional unit Zip code 

optional suffix

List last 4 digits 

of zip code 

in which unit 

is located IF 

PROVIDED

9999 = NA

302 respdum Recode of respnum 

(binary)

if respnum > 0 

then respdum = 1, 

otherwise 0.

0 = No Response

1 = One or more Responses respdum Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 5576 40.8 5576 40.8

1 8090 59.2 13666 100

303 mt1resp Recode of respnum, 

(2+ responses)

if respnum > = 2 

then respdum = 1, 

otherwise 0.

0 = Less than 2 Responses

1 = 2 or More Responses mt1resp Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 12925 94.58 12925 94.58

1 741 5.42 13666 100

304 inspectdum Recode of inspection1 if inspection1 = 1 

then inspectdum 

= 1, otherwise 0.

0 = Inspection mentioned in 

first response

1 = Inspection mentioned in 

1st response

inspectdum Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 7855 57.48 7855 57.48

1 5811 42.52 13666 100

305 contprdum Recode of contprov1 if contprov1 = 1 

then contprdum 

= 1, otherwise 0.

0 = Not asked to Contact the 

provider in first reseponse

1 = Asked to Contact the 

provider in first response

contprdum Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 9333 68.29 9333 68.29

1 4333 31.71 13666 100
An Estimate of Housing Discrimination Against Same-Sex Couples 68

Var# Variable

Name

Variable

Description

Variable

Details Value Labels Frequencies

306 avail1dum Recode of available1 if available1 = 1 

then avail1dum 

= 1, otherwise 0.

0 = Unit NOT available in first 

response

1 = Unit available in first 

response

avail1dum Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

0 7543 55.2 7543 55.2

1 6123 44.8 13666 100

307 stratanew Recode of Strata 1 = small/medium (100,000 to 

to 3999,999)

2 = medium-to-large (400,000 

to 749,999)

3 = large (750,000 to 1,499,999)

4 = very large (1,500,000 to 

4,999,999)

5 = largets (5,000,000 or more)

stratanew Frequency Percent Cumulative 

Frequency

Cumulative 

Percent

1 492 3.6 492 3.6

2 1006 7.36 1498 10.96

3 1520 11.12 3018 22.08

4 7048 51.57 10066 73.66

5 3600 26.34 13666 100
An Estimate of Housing Discrimination Against Same-Sex Couples 69

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