Statistical and Analytical Support for the DOL Chief Evaluation Office
The U.S. Department of Labor (DOL) Chief Evaluation Office (CEO) contracted with the Program Evaluation (PE) team to provide support for CEO’s new statistical and analytics services initiative. In an effort to help DOL agencies better understand their administrative data and leverage this data to improve their policies, programs, and regulatory initiatives, CEO offered to work with the agencies to design and conduct short-term statistical and evaluation analyses. Summit’s PE directorate provided a team of researchers and analysts, as well as the team management to enable CEO to do this work.
Over the course of this contract, the PE team worked with nearly every regulatory agency within DOL, as well as the Office of the Assistant Secretary for Policy (OASP) generally. Every analysis project in this initiative was designed to provide quick, actionable information that DOL agencies could use to assess and improve their programs. The PE team’s support of CEO’s statistical and analytics services required the team to quickly learn and effectively use a large variety of administrative data and to employ many different types of statistical, analytical, and evaluation techniques. In addition, the PE team worked with CEO to begin developing a set of guidelines for creating and reviewing public use files (PUFs) from research data commissioned by DOL agencies. This work will help CEO begin to build a repository of high-quality, public use data available to the community of labor and employment researchers. Some of the analytic projects completed under this contract include:
- Examining the inspection, violation, and firm characteristics that are associated with a firm contesting the finding of a regulatory violation,
- Developing an analytic tool to allow an agency to better anticipate staff turnover,
- Providing a demographic analysis of an agency’s potential labor force in the regions, states, and counties where the agency operates,
- Developing, implementing, and providing initial analysis of a satisfaction survey of an agency’s clients,
- Reviewing and transforming survey data to create public use files that meet standards for disclosure limitation, data quality, and ease of use, and
- Developing an alternative method to identify firms that may have discriminatory pay practices using agency collected data paired with public use survey data.