Project AWESOME, a multi-year effort, is producing cross-cutting research that is responsive to the needs and interests of the field. Mathematica is supporting the development, implementation, and dissemination of this research program.
- Evaluation design
- Evidence-based labor programs and practices
- Systematic reviews
- Training and Reemployment
- Unemployment Insurance
- Family Support
- TANF and Employment Issues
Annalisa Mastri is an expert at designing and conducting experimental and nonexperimental evaluations. She has worked on projects in labor, family support, and education.
She currently leads the analysis of administrative data and benefit-cost analysis for a random assignment evaluation of the Workforce Investment Act, one of the nation’s largest publicly funded employment and training programs. She is also principal investigator for the U.S. Department of Labor’s (DOL) Clearinghouse for Labor Evaluation and Research (CLEAR) and the Administration for Children and Families’ Employment Strategies for Low-Income Adults Evidence Review (ESER).
Mastri, who joined Mathematica in 2007, is a member of the American Economic Association and the Association for Public Policy Analysis and Management and presents her work at related professional conferences as well as the Society for Research on Educational Effectiveness, the Welfare Research and Evaluation Conference, and others. She holds a Ph.D. in education economics from Stanford University.
Project AWESOME: Advancing Welfare and Family Self-Sufficiency Research
Clearinghouse for Labor Evaluation and Research (CLEAR)
CLEAR’s mission is to make research on labor topics more accessible to practitioners, policymakers, researchers, and the general public so that it can inform their decisions about labor policies and programs.
Employment Strategies for Low-Income Adults Evidence Review (ESER)
Mathematica is conducting a systematic review of the research literature on programs and strategies intended to help low-income adults acquire and maintain employment and achieve self-sufficiency.