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Creating Moves to Opportunity in Seattle and King County
Last registered on May 21, 2018


Trial Information
General Information
Creating Moves to Opportunity in Seattle and King County
Initial registration date
March 28, 2018
Last updated
May 21, 2018 4:44 PM EDT

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Primary Investigator
Harvard University
Other Primary Investigator(s)
PI Affiliation
Johns Hopkins University
PI Affiliation
Columbia Teacher's College
PI Affiliation
MIT Sloan
PI Affiliation
Stanford University
PI Affiliation
Harvard University
Additional Trial Information
On going
Start date
End date
Secondary IDs
The Seattle-King County Creating Moves to Opportunity (CMTO) Demonstration aims to help families with children who receive Housing Choice Vouchers (also known as Section 8 Vouchers) have the opportunity to move to and persist in higher opportunity neighborhoods. Families with children under 15 who receive a Housing Choice Voucher from the Seattle Housing Authority (SHA) and King County Housing Authority (KCHA) who elect to participate in the study will be randomly assigned to either the treatment group (expected to be 642 families), who receives access to CMTO services, or the control group (expected to be 642 families), who have access to the normal support services provided by the housing authorities to new voucher-holders. CMTO services include housing locator services (housing search assistance, neighborhood education, and support in preparing rental applications) and access to flexible financial assistance to help cover costs associated with opportunity moves (e.g. security deposits, moving expenses). Additional outreach will be conducted to landlords in opportunity neighborhoods, and landlords will receive financial incentives for leasing to CMTO families in order to help increase the supply of units available to families. Future phases of research may involve randomizing the types of services families receive. The primary outcomes of interest are to determine (1) if CMTO services increase the number of families moving to high opportunity neighborhoods, and (2) how long they persist in those neighborhoods.
Registration Citation
Bergman, Peter et al. 2018. "Creating Moves to Opportunity in Seattle and King County." AEA RCT Registry. May 21. https://doi.org/10.1257/rct.2807-6.0.
Former Citation
Bergman, Peter et al. 2018. "Creating Moves to Opportunity in Seattle and King County." AEA RCT Registry. May 21. http://www.socialscienceregistry.org/trials/2807/history/29856.
Sponsors & Partners

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Experimental Details
Families will receive access to housing locator services to assist in their housing search. The services provided will include marketability counseling to help the families prepare for their housing search, opportunity area education to introduce families to the opportunity neighborhoods, and assistance in finding available apartments. These services will be provided by a third-party provider. Participating families will have access to financial assistance to help cover costs that may be higher in opportunity neighborhoods, such as security deposits, moving expenses, and application fees, in the event families do not have the funds to cover those expenses themselves. Landlords in opportunity areas will also have incentives to lease to voucher-holders, including access to a risk mitigation fund to cover damages above and beyond a security deposit. There will be more intensive recruitment efforts to increase the number of landlords willing to lease to voucher-holders in opportunity areas during the program as well.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Our core short-run outcomes are housing mobility and neighborhood environment characteristics. These include

• Initial lease up rate in an opportunity area (Defined at the family-level as 1 = lease up in opportunity neighborhood; 0 = does not lease up in opportunity neighborhood)

• Exposure to higher opportunity neighborhood quality. Our primary measure of this will be exposure-weighted mean neighborhood quality for the two years after random assignment using the Chetty and Hendren (2018 QJE) mean upward mobility rate of each neighborhood (Census tract). We will consider alternative ways to measure the exposure to neighborhood quality, including

i. Share of post-random assignment period spent residing in a high opportunity neighborhood (using a discrete measure of high opportunity)

ii. Point-in-time measures include measuring opportunity neighborhood residency status (binary or continuous measure using tract-level upward mobility rate) at a given amount of time after random assignment. For example, initial outcomes may be measured as the likelihood each family is living in an opportunity neighborhood one year after being randomly assigned to treatment or control groups.
Primary Outcomes (explanation)
The RCT’s goal is to test which interventions alleviate constraints that decrease the likelihood of low-income families moving to higher-opportunity neighborhoods for their children. Thus, the primary short-run outcome of interest indicating intervention effectiveness will be the likelihood of moving to an opportunity neighborhood, coupled with a measure of treatment persistence and intensity given by exposure-weighted neighborhood quality metrics. A key short-run mediating outcome is the overall housing voucher lease-up rate. CMTO interventions could increase overall housing voucher lease-up rates by providing assistance in housing search, but the CMTO could reduce overall lease-up rates by focusing housing search on higher-opportunity neighborhoods where it is more difficult to lease-up.
Secondary Outcomes
Secondary Outcomes (end points)
A secondary short-run outcome is the housing choice voucher lease up rate (1 = lease up with the housing choice voucher; 0 = does not lease up).

Interim secondary outcomes on families include

• Children’s standardized test scores (state percentile rank)
• Household adults’ employment and earnings

Longer-run child outcomes include

• Post-random assignment childhood exposure-weighted neighborhood quality from random assignment to age 18 (or early 20s) based on the Chetty and Hendren (2018 QJE) measure of neighborhood (Census tract) upward mobility. This is the primary measure of neighborhood environment that the intervention is designed to support.
• Core outcomes from IRS administrative tax data as defined in Chetty, Hendren, and Katz (2016 AER, Table 11) include
i. Individual earnings
ii. Household income
iii. College attendance from age 18-20 (%)
iv. College quality from age 18-20
v. Marital status
vi. Poverty share in zip code of residence (%) (or in Census tract of residence if possible with future versions of administrative tax data)


Chetty, Raj and Nathaniel Hendren. 2018. “The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects.” Quarterly Journal of Economics 133(3), forthcoming.

Chetty, Raj and Nathaniel Hendren. 2018. “The Impacts of Neighborhoods on Intergenerational Mobility II: County-Level Estimates.” Quarterly Journal of Economics 133(3), forthcoming.

Chetty, Raj, Nathaniel Hendren, and Lawrence F. Katz. 2016. "The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment." American Economic Review, 106(4): 855-902.
Secondary Outcomes (explanation)
We will also attempt to measure other short-run outcomes that we do not expect to change substantially in response to the CMTO interventions based on prior research including children’s educational outcomes and household income. In the longer-run, based on prior research on opportunity neighborhood exposure during childhood, we hypothesize that there will be an effect on longer-run child outcomes such as college attendance, individual and household income, marital status and out-of-wedlock childbearing, and adult neighborhood quality.
Experimental Design
Experimental Design
All families with at least one child under age 15, applying for federal housing choice vouchers (HCVs) through SHA or KCHA and eligible for that program (e.g. meeting income requirements) will be offered enrollment in CMTO. If they consent to participate in the study, they will be randomly assigned to a treatment group or a control group. In the first phase of the evaluation, families in the treatment group will have access to all the CMTO services in addition to the regular services provided by the housing authorities for new HCV participants. The control group will only have access to the normal housing authority services. A second phase of research is planned to further test the more promising components of CMTO services and understand their relative cost effectiveness. The services to be tested in this phase will be selected based upon qualitative research during the first phase around which services families are finding most helpful in making opportunity moves.
Experimental Design Details
Not available
Randomization Method
randomization done in office by computer
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
Sample size: planned number of observations
1284 households
Sample size (or number of clusters) by treatment arms
642 treatment, 642 control across Phases 1 and 2 of the RCT
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Assuming conventional 80% power and 95% confidence intervals, preliminary power calculations suggest that the minimum detectable effect size in the first year of the intervention is a 5 percentage-point change (46%) in the likelihood of moving to an opportunity neighborhood when comparing treatment and control groups. Using statistics provided by the Seattle and King County Housing Authorities, we based our calculations on assumptions on the projected number of new families with at least one child under age 15 issued a voucher each year (N = 1284), equally sized treatment and control group sizes, and the usual fraction of families issued vouchers who move to an opportunity neighborhood absent any intervention (11%, standard deviation = 0.31). Although we are interested in outcomes conditional on voucher take up, randomization will occur at the level of issued voucher, and we assume that historical 68% lease-up rates (weighted average across SHA and KCHA) will prevail for both treatment and control. We further assume that gamma = 5% of families assigned to the treatment group will opt-out of services. To calculate the minimum detectable effect size with an expected sample size of 1284 households, we followed equation (4.3) in Orr (1999) Minimum Detectable Effect = 2k*sigma/sqrt((1-gamma)*N) = 0.0502 where k = 2.8 is a constant determined by desired statistical size (5%) and power (80%); sigma = 0.31 is the standard deviation of the unconditional outcome of interest (the fraction of households issued a voucher that lease up in an opportunity neighborhood); gamma = 0.05 is the fraction of sample that decline program participation; and N = 1284 is the total number of vouchers to eligible families expected to be issued during the study across the two housing authorities. Although this is a large effect in relative terms, it is small in absolute terms (less than an extra 100 families a year moving to opportunity neighborhoods), and it is smaller than effects seen in the original Moving to Opportunity experiment evaluation and those estimated non-experimentally for the Baltimore Housing Mobility Program. In phase two, we anticipate two or three treatment arms with more focused interventions based on qualitative lessons learned from phase one, each consisting of smaller sample sizes and resulting in larger minimum detectable effects. For example, to separately examine phase one and phase two with N/2 households in each phase, our minimum detectable effect increases by a factor of sqrt(2) to 0.0710 meaning that we anticipate having sufficient power to detect a 7.1 percentage point treatment effect in phase one or across all treatment arms of phase two.
Supporting Documents and Materials

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IRB Name
MDRC Institutional Review Board
IRB Approval Date
IRB Approval Number
Analysis Plan
Analysis Plan Documents
CMTO Seattle/King County Pre-Analysis Plan

MD5: c8cabc1c4d963348f6cfbe7ada0250fb

SHA1: 54f4dfec1ead61e66b3469d2d3807b44b713bc1d

Uploaded At: May 21, 2018