Self-Sufficiency Standard

Exploring new understandings of the cost of living at a basic needs level using the Self-Sufficiency Standard database

The Team

Project Leads: Annie Kucklick and Lisa Manzer (Center for Women’s Welfare at the University of Washington)

Data Science Lead: Bryna Hazelton (University of Washington)

DSSG Fellows: Azizakhon Mirsaidova (Northwestern University), Priyana Patel (University of Washington), Cheng Ren (UC Berkeley), Hector Sosa (University of Massachusetts - Amherst)


The Official Poverty Measure (OPM) sets eligibility for critical benefits (e.g., food assistance, child care subsidies, or housing vouchers). Many families, however, cannot afford their basic needs and are not considered “in need” by the OPM and cannot access these supports. The Self-Sufficiency Standard (SSS) was created by the Center for Women’s Welfare (CWW) at UW to provide an alternative to the OPM by defining the income working families need to meet their basic necessities without public or private assistance. However, the current data is spread across “state” and “year,” which makes it difficult for researchers to conduct deep analyses. The following project seeks to answer how we can store the SSS data to increase efficiency for stakeholders to use the data, extract meaningful information, and conduct further analyses. Our team created a relational database using SQLAlchemy and Python to hold the SSS for the 42 states in which the Standard has been calculated. Our database includes a primary table with the SSS based on the family household type and several secondary tables, such as the cost of broadband and cellphone(s). The research also aims to increase the transparency and accessibility of data for stakeholders with varying technical backgrounds through robust documentation.

For more program-related information, visit the UW Data Science for Social Good (DSSG) program.