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Policy Analysis

It is essential to understand the policies that shape current programs and their impacts.

Understanding and evaluating policies to inform service delivery.

Economic and well-being supports in the United States are a patchwork of programs and policies that operate at the federal, state, and local levels. Policymakers and practitioners need evidence to understand what works, including how different policies produce outcomes for program participants or promote economic security.

Policy analysis is also imperative for understanding how some policy decisions may make it more difficult for residents to access benefits or create unanticipated costs. Here, you will find materials that evaluate programmatic efficacy and reach, and offer recommendations for improving and reimagining policies.

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TANF Data Collaborative Pilot: Analyzing Application Denial Rates in Michigan

The project aimed to analyze reasons behind Michigan's higher TANF application denial rate compared to other states, seeking to refine the application process, enhance program accessibility for eligible individuals, and alleviate staff workload by minimizing redundant applications. Research focused on identifying factors relating to eligibility rules and application processing steps. 

MDRC
Case Study

TANF Data Collaborative Pilot: Housing Transitions in New Jersey

New Jersey's pilot project investigated housing transitions for TANF participants experiencing homelessness, specifically those moving from emergency placements to Temporary Rental Assistance (TRA). The analysis aimed to understand the characteristics of families and their movement within the program, informing strategies for effective housing assistance and support. 

MDRC
Case Study

TANF Data Collaborative Pilot: Family Characteristics in Utah

The project explores characteristics of families who exit and return to Utah's TANF cash assistance program. It seeks to understand the reasons for their return and identify services that could reduce their future reliance on assistance. Data quality is also examined for its impact on understanding factors influencing benefit return.

MDRC
Case Study

TANF Data Collaborative Pilot: Longitudinal Data for Understanding Participant Actions in New York

The project aims to understand factors influencing participants in New York's Temporary Assistance (TA) program, including their departure or return, subgroup tendencies, and long-term benefit receipt. The goal is to develop a predictive tool to assist staff in identifying potential long-term participants and improving decision-making on service provision and interventions. 

MDRC
Case Study

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. 

MDRC
Case Study

TANF Data Collaborative Pilot: Analytical Tools for Education and Employment Services in Virginia

The project seeks to create unbiased analytical tools for Virginia Department of Social Services (VDSS) to customize education and employment services for TANF participants, improving their labor market success upon program exit. Demographic characteristics, household compositions, public benefit receipt, and past education/employment activities are analyzed for predictive purposes. 

MDRC
Case Study
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