BUREAU OF CONSUMER FINANCIAL PROTECTION

PAPERWORK REDUCTION ACT SUBMISSION

INFORMATION COLLECTION REQUEST

SUPPORTING STATEMENT PART B

[OWNING A HOME EVALUATION STUDY

(OMB CONTROL NUMBER: 3170-XXXX)

PART B. COLLECTIONS OF INFORMATION EMPLOYING STATISTICAL

METHODS

1. Describe (including a numerical estimate) the potential respondent universe and any 

sampling or other respondent selection method to be used. Data on the number of 

entities (e.g., establishments, State and local government units, households, or persons) 

in the universe covered by the collection and in the corresponding sample are to be 

provided in tabular form for the universe as a whole and for each of the strata in the 

proposed sample. Indicate expected response rates for the collection as a whole. If the 

collection has been conducted previously, include the actual response rate achieved 

during the last collection. 

The target audience for the Owning A Home suite of tools is prospective home-buyers. To 

replicate this target audience as much as possible, the respondent universe is composed of active 

members of a national homebuying website. Active members are defined as those who have 

accessed the website sometime in the past 3 months. A random sample of active members will 

be invited to participate in the study via email and directed to visit the study’s homepage. The 

partner website will send these recruiting emails using their email management system. We are 

targeting an initial pool of 50,000 potential respondents. Potential respondents will be asked to 

complete a short screening questionnaire to determine eligibility for the study. To participate, 

respondents must intend to purchase a home in the next 3 months, be involved in financial 

decisions in their household, and not be professionally involved in the real estate industry.

Table 1. Survey sample and estimates of response rate

Active members of homebuying site 1,000,000 +

Initial pool of potential respondents 50,000

Eligible respondents (60%) 30,000

Eligible participants who opt-in and 

complete baseline survey (30-33%)

9,500-10,000

Participants who complete the entire 

study (23-25%)

2,300-2,350

Participants who complete the entire 1,150-1,175
study and submit final mortgage 

documents (50%)

Approximately 60% of potential respondents are expected to meet initial screening criteria, of 

which we expect approximately 30-33% to agree to participate in the study. There is likely to be 

additional attrition over time. Monetary incentives will be offered to encourage participation in 

the study and to incentivize survey completion. Further efforts to increase response rates are 

detailed below.

2. Describe the procedures for the collection of information:

Data will consist of a combination of participant surveys and administrative data from the 

Owning a Home suite of tools.

Participant surveys: Surveys will be used to obtain additional information on 

respondents’ shopping behavior, perceptions of the market, mortgage knowledge, and 

feelings of empowerment. Surveys will be administered online every two weeks for three 

months or until a home is purchased, whichever occurs first. An initial baseline survey

will additionally contain information on respondents’ background characteristics, 

including information on their existing assets and liabilities. Closing surveys will ask for 

information on terms of the home purchase and mortgage obtained, including a request to 

provide the final mortgage documents. If participants have not purchased a home before 

the end of the three month study window, they will be asked to complete a final closing 

survey, administered upon closing and up to 8 weeks later.

Owning a Home web suite of tools: Website metrics will include measures of 

participants’ activity on the site. For instance, participants may access various tools (e.g. 

background information on the process of searching for a mortgage, a mortgage rate 

benchmarking tool, or a mortgage document comparison tool), and may spend varying 

amounts of time on each. 

Before analysis, data will be de-identified to exclude any direct identifying information protect 

the privacy of sampled consumers.

a. Include statistical methodology for stratification and sample selection,

As described above, the sample will be drawn from a homebuying website’s existing members. 

Respondents will be asked to complete a short screening questionnaire first in order to determine 

if they are eligible. Data obtained in the screening questionnaire does not contain any directly 

identifying information and will be analyzed only in the aggregate to assess which eligibility 
criteria have the most impact on disqualifying individuals. Upon completing the screening 

questionnaire, respondents are presented with informed consent language and asked to opt-in to 

the study.

The research team does not anticipate the need to rely on stratification, although respondents 

may be analyzed according to individual characteristics (e.g. previous homeownership 

experience).

b. Estimation procedure,

The primary analytic technique for estimating the impact of a randomized controlled trial (RCT) 

such as this study is a comparison of outcomes for participants in different study groups. In 

particular, in estimating the impact of the Owning a Home suite of tools, the research team will 

compare outcomes for participants who were given access to these tools (the treatment group) to 

those who were not given access (the control group). The research team intends to use “intent to 

treat” analysis, thereby estimating effects on those who had the opportunity to receive treatment, 

including those who did and did not use the tools. Assuming that the randomization process is 

performed correctly, this analysis identifies the causal impact of access to the Owning a Home 

suite of tools on mortgage outcomes for the study population.

Estimates of the differences between the two groups will be calculated using data from surveys, 

online tracking, and mortgage outcomes. For each difference, statistical confidence intervals 

will be calculated using standard statistical assumptions.

For some outcomes, the research team is additionally interested in how outcomes changed during 

the home shopping process. For example, it may be expected that respondents who have 

completed their home purchase and have closed on a mortgage will have higher knowledge of 

the mortgage process than those who are in the initial stages of their home search. As such, 

changes in mortgage knowledge between baseline and the final survey will be compared for 

those in treatment and control groups.

c. Degree of accuracy needed for the purpose described in the justification,

There is limited existing data on the methods that prospective homebuyers use to search for 

home and mortgage options. Additionally, there is limited evidence regarding how much money 

homebuyers will save from obtaining an additional mortgage estimate. As such, it is difficult to 

estimate the expected effects of the described intervention, and in turn, the degree of accuracy 

required.

Based on power analyses using existing information on estimated savings from mortgage search, 
the research team has estimated that approximately 2,200 participants are needed to complete the 

study in order to detect a difference between those exposed to the Owning a Home tools and 

those who are not. Given expected attrition, the recruitment plan is sufficient to produce 2,200 

complete participants with a small additional cushion. 

d. Unusual problems requiring specialized sampling procedures, and

The research team does not anticipate using any specialized sampling procedures.

e. Any use of periodic (less frequent than annual) data collection cycles to reduce 

burden. 

The proposed research does not include any use of less-frequent-than-annual periodic data 

collection cycles.

3. Describe methods to maximize response rates and to deal with issues of non-response.

The accuracy and reliability of information collected must be shown to be adequate for 

intended uses. For collections based on sampling a special justification must be 

provided for any collection that will not yield “reliable” data that can be generalized to 

the universe studied. 

Non-response may be a challenge for this study, particularly because respondents are being 

asked to participate multiple times throughout their shopping process. While we will strive to 

minimize attrition over the course of the study, we will also include partial participants’ data in 

our analysis where appropriate. The survey modules have been carefully designed to collect the 

data needed for analysis while minimizing burden to participants. Additionally, a combination of 

strategies is being employed to address non-response, as outlined below.

Strategies to maximize participation

a. Participants will be offered a cash incentive, which has been shown to increase 

response rates.1

b. Reminder emails will be sent to those who have not taken a survey or who dropped 

out in the middle. These emails will request that participants complete the survey. 

Such reminders have been shown to increase response rates.2

Strategies to minimize incomplete responses

 1 Phil Edwards, Ian Roberts, Mike Clarke, Carolyn DiGuiseppi, Sarah Pratap, Reinhard Wentz, and Irene Kwan, 

“Increasing Response Rates to Postal Questionnaires: Systematic Review,” British Medical Journal 324 

(2002):1183-1189 2 Crawford, Scott D., Mick P. Couper, and Mark J. Lamias. (2001). “Web Surveys: Perceptions of Burden,” Social 

Science Computer Review, 19(2): 146-62; Cook, Colleen, Fred Heath, and Russel L. Thompson. (2000). “A MetaAnalysis of Response Rates in Web- or Internet-Based Surveys,” Educational and Psychological Measurement, 

60(6): 821-36.
a. To reduce respondent burden, the survey has been constructed so that participants 

will answer only a subset of questions for each survey. Specifically, the survey 

modules that are administered will change depending on initial screening questions 

that allow us to quickly assess the respondent’s current situation. By reducing the 

number of questions that are asked (and the associated time required to respond) more 

respondents are expected to complete the surveys.

b. Additionally, participants will be allowed to “suspend” their survey session so that 

they can “resume” it at a later date. Such a design accommodates technical problems 

that may prohibit participants from completing the survey, such as an Internet 

connection issue, as well as scheduling constraints.3

4. Describe any tests of procedures or methods to be undertaken.

The CFPB plans test the survey instrument and data collection procedures prior to running the 

full-scale study. These techniques are meant to reduce the total public burden of the study by 

ensuring that information collection is optimized. There are two planned tests: cognitive 

interviews and a pilot study.

Cognitive interviews will be conducted in order to refine the survey instrument.4

 During these 

interviews, participants will be able to think aloud regarding their interest in the questions and 

their understanding of the questions, revealing potential problems with question 

comprehensibility and response options. 

Second, the CFPB plans to conduct a pilot study. This study will be conducted online and will 

reveal potential problems with question sequencing and skip patterns, completion time, 

randomization of the order of response options, and checks for invalid responses. During these 

tests, we will allow participants to report problems that they are experiencing and track 

participant behavior through drop-out or non-response. That feedback, combined with other data 

gathered from the pretest, will be used to revise the survey questions and software as appropriate.

5. Provide the name and telephone number of individuals consulted on statistical aspects 

of the design and the name of the agency unit, contractor(s), grantee(s), or other 

person(s) who will actually collect and/or analyze the information for the agency.

Dustin Beckett

Economist

Division of Research, Markets and Regulations

 3 This practice is recommended by survey methodologists; see pages 336-339 of Couper, Mick P. (2008).

“Designing Effective Web Surveys,” New York, NY: Cambridge University Press. 4 For additional information on cognitive interviewing, see Willis, Gordon B. (2005). “Cognitive Interviewing: A 

Tool for Improving Questionnaire Design,” Thousand Oaks, CA: Sage.
Consumer Financial Protection Bureau

202-435-9399