TANF Data Collaborative Pilot: Wage Outcomes by ZIP Code in California

The pilot team aimed to quantify wage outcomes for CalWORKs participants in specific ZIP Code areas. It focuses on developing a model to understand the factors associated with achieving stable wages that can support raising a family in California. This helps assess the effectiveness of the TANF program. 

The project utilized state administrative data to explore the long-term earnings outcomes of TANF participants. By linking TANF and wage data from the Medi-Cal Eligibility Data System (MEDS) and the California Employment Development Department, the project focused on a cohort of individuals who exited the TANF program in 2015. Five targeted ZIP Code Tabulation Areas (ZCTAs) were selected, and individual-level data were aggregated to the case level. Two separate generalized logistic regressions were conducted to identify characteristics associated with achieving stable wages above poverty thresholds. Model one considered case-level variables, while model two incorporated community-level variables. Stable wages were defined using the official poverty measure (OPM) and the California poverty measure (CPM). The analysis encompassed three years prior to TANF exit and four years afterward. The project's design process involved creating an analytic data set, performing regression analyses, and considering future individual-level analyses. The project delivered valuable insights into the factors associated with stable wages among TANF participants in specific ZCTAs.

The findings revealed that only 10% of TANF participants achieved stable earnings after exiting the program with the presence of earnings at the time of exit as the strongest predictor of stable wages. Future plans include tracking earnings for up to four years post-TANF exit and examining regional outcome differences. 

This project serves as a replicable model for staff from other agencies looking for examples of efforts that support the use of administrative data for learning and improvement. Policymakers, researchers, and organizations seeking to expand the use of data in state TANF agencies may find interest in this project.