A New Approach to Labor Market Assessments

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The majority of the world’s poor still depend on agriculture for their livelihoods. The USAID Bureau for Humanitarian Assistance (BHA) is a key actor in development initiatives that boost employment globally, enhancing the productivity and incomes of smallholder family producers.

To assist rural households in taking advantage of the on- and off-farm opportunities most likely to sustainably increase their productivity, food security and economic well-being, it is necessary to shift from traditional Labor Market Assessments (LMAs) to Systems Labor Market Assessments (SLMAs).

While traditional LMAs generally focus on the target population — their capacities, skills gaps and challenges in entering desired occupations — SLMAs dig deeper. They assess the performance of economic sectors that workers seek to enter. This report presents two assessments that use Market Systems Development (MSD) tools to evaluate job seeker capacities and needs, and the performance of the surrounding economic sectors.

The USAID/BHA-funded Implementer-Led Design, Evidence, Analysis and Learning (IDEAL) activity contracted DevLearn to pilot the SLMA methodology in Haiti and Zimbabwe. The assessments took place between October 2021 and March 2022. These two contexts were chosen following a competitive ranking of applicants across the following criteria:

• Research questions focused on employment and MSD; 
• Clear connection to food security; and 
• Relevance to USAID/BHA and logistical feasibility, including adherence to COVID-19 safety protocols. 

SLMA Process

Learning from these pilots resulted in a standard, six-step SLMA process:

1. Profile the target group: Develop an understanding of the capacities, needs and employment preferences of the target group and relevant subpopulations within that group.
2. Scan the labor market: Conduct a literature review and a limited number of key informant interviews (KIIs) to identify the sectors and systems with the highest potential employment outcomes for the target population. This produces a “long list” of sectors that hold high employment potential.
3. Develop sector short list: Using relevance, feasibility and impact as a guide, develop context-specific evaluation criteria to support selection of three to four sectors that the SLMA will focus on. These may be economic sectors (e.g., household solar or tourism) or crosscutting systems that influence employment outcomes (e.g., transportation or credit for micro-entrepreneurs).
4. Conduct preliminary analysis of shortlisted sectors: Develop preliminary market maps, market actor lists and hypotheses on what types of jobs will be created for the target population in this sector.
5. Conduct a deep analysis of selected sectors: This usually involves primary qualitative research and may require additional secondary research to identify sector underperformances.
6. Produce intervention proposals: The implementation team pinpoints root causes of sector underperformance and develops implementation proposals that include clearly identified partners and estimates for job creation.

Key Lessons Learned

Four key lessons learned about conducting an SLMA include:

1. Following the shortlisting process, preliminary research — supported by a deeper literature review and limited number of KIIs with market stakeholders — should be conducted before designing field research tools. Developing a fuller picture of the market system prior to engaging in primary research helps define and focus the deep dive into the prioritized market systems.
2. Whenever possible, the team responsible for writing up SLMA results and findings should be on the ground, working hand-in-hand with the implementation team. While COVID-19 and the multicountry nature of this assignment necessitated remote support, this is not an ideal setup for future SLMAs.
3. Intervention design is a heavily iterative process and requires full knowledge of the market system as well as the implementation organization. The intervention team, not external consultants, should lead intervention design.
4. Projecting potential job creation estimates requires an understanding of the size of potential partners. While it is possible to generate rough estimates based on qualitative consultations with market actors, more refined estimates around job creation will only be possible once intervention partners are identified.

While resilience and food security programs are actively seeking to adapt to the impacts of COVID-19, capacity to assess and effectively facilitate off-farm and nonfarm employment opportunities remains a key challenge.

This study generated a tremendous amount of learning not only around job opportunities for vulnerable communities in Haiti and Zimbabwe, but also around how humanitarian and development implementers approach employment programing through a new, more systemic lens. The learning and insights captured in this report will also support USAID/BHA-funded Resilience Food Security Activities (RFSAs) in adopting more effective approaches to facilitating off-farm and nonfarm income-generating activities.