Leveraging Labor Market Data in Guatemala, El Salvador & Honduras Evaluation
How to strengthen labor market data programming.
The Bureau of International Labor Affairs’ (ILAB) Office of Trade and Labor Affairs (OTLA) at the U.S. Department of Labor commissions research to generate evidence of effective practices and conditions for sustainable outcome generation to inform future programming and strengthen its theory of sustained change for its global portfolio. For accountability and learning, OTLA requested a final performance evaluation of the “Leveraging Data to Build an Efficient Labor Market in El Salvador, Guatemala, and Honduras” project, implemented by The American Institutes of Research (AIR). The project aimed to help authorities produce and publish reliable, comprehensive, and current labor market information in user‐friendly formats for the general public and professional audiences. It also aimed to build skills among professionals, officials, and scholars to understand and use labor market data.
NORC’s expertise in complex evaluation and sustainable change assessed project success.
We completed a mixed-methods performance evaluation that shed light on the project’s accomplishments and challenges in reaching its intended outcomes in each country. Through administering 66 key-informant interviews in El Salvador, Guatemala, Honduras, and the U.S. and an online survey (n=125), we collected rich information on project implementation, outcomes, sustainability conditions, and partnerships. Respondents included project staff, key project partners, trainees, and representatives of national statistical institutes, labor ministries, academic institutions, and private sector organizations. We also identified positive practices and collected lessons learned by interviewing key informants from AIR and the statistical agencies in each country.
We found uneven achievements within an uncertain context for sustainability.
We found that while the project was able to engage productively with the statistical agencies in all three countries and impact the production of more reliable, comprehensive, and current labor market information in user‐friendly formats, its ability to increase the skills to use and understand such information systems was not as successful. Sampling strategies and data collection methods continue compromising data quality and reliability. Such limitations harm the validity of any inferences made with local labor market data.
Our recommendations offered a clear path to ILAB and other funders to continue supporting stronger systems of labor market data in the region. The evaluation confirmed that volatile political conditions in all three countries offer no certainty for long-term planning and developing labor market information systems. Engaging with and strengthening the capacity of non-political actors is crucial to enhance information systems independently of political upheavals. A key recommendation for future funding of LMI initiatives is to have a two-pronged approach that bolsters the use of LMI among decision makers and increases LMI quality, standardization of data collection practices, and digitization.