171 - Developing and Using Scoring Processes to Assess Policy Priority

Abstract Information: In May 2021, HUD announced the 10 public housing agencies (PHAs) that have been selected for the Stepped and Tiered Rent Cohort of the Moving to Work Expansion. Stepped rent and tiered rent changes policies used to calculate subsidized households’ contributions to the rent to increase by small amounts regardless of income earned. It limits the connection between income and rent to encourage residents to increase their incomes without their rent rising in tandem. While MDRC conducts the 10-site random assignment evaluation, Abt Associates was selected to conduct qualitative research with residents in two sites: Akron Metropolitan Housing Authority and Housing Authority of the County of Kern. This poster will describe a rubric Abt Associates developed to guide purposive sampling of residents based on their apparent opportunity to respond to the incentives and potential of the rent reform changes.

Abt used baseline survey responses from MDRC via secure file transfer of Stepped and Tiered Rent Demonstration (STRD) participants enrolled in Kern County and metropolitan Akron, Ohio to date. Abt developed a “Policy Priority Score” to prioritize outreach to participants from the survey responses to participate in baseline interviews. Abt received survey responses from both sites that include every resident who had consented to participate in the research since recruitment began. This amounted to 1,300 survey responses from the Akron PHA and 735 survey responses from the Kern County PHA. Survey responses included basic contact and demographic information, preferred communication language, and questions regarding tenure on Section 8, work status, limitations to work, and finances.

From these, Abt developed a Policy Priority Score to reflect a resident’s apparent opportunity, based on survey responses, to change their actions to benefit from the new rent policy (i.e., their capacity to work more or improve their financial well-being) in over 2000 participants in Kern County, California and Akron, Ohio. The score can range between 0 to 25, with higher scores denoting more opportunity for a resident to benefit from the potential incentives of the new rent policy. Each resident’s score was developed by applying weights to participants’ current work status and hours worked, childcare accessibility, physical and/or mental health issues, transportation, monthly finances including rent, and utilities expenses. For example, residents already working full-time, or more, were coded to have a low opportunity to respond to the new rent policy since they could not increase their work hours further. Those who experienced barriers to employment such as childcare or transportation were coded as having a high opportunity to benefit from the rent policy change. After creating the Policy Priority Score, the team identified the range of scores in the highest 50% (high policy priority score) and lowest 50% (low policy priority score) in each site. The usage of this scoring was not intended to be representative but helped us to recruit a purposive sample that is diverse across the dimensions of residents’ lives and provides a clear way to describe our interview sample in relation to the policy change under study.