Following the signing of a Memorandum of Understanding (MoU) between the Central Bank of Kenya (CBK) and the International Food Policy Research Institute (IFPRI) on July 8, 2024, the partnership has continued to record significant progress in co-creating evidence to support CBK’s decision-making. Anchored on the foundational work of the CGIAR Initiative on National Policies and Strategies (NPS) and Foresight initiatives, the collaboration has so far delivered three capacity-sharing sessions on Social Accounting Matrix (SAM) analysis, an important tool for evaluating the real sector side of the economy.
The first session, held on July 14, 2025, provided an in-depth introduction to SAMs and SAM-based modeling, highlighting their relevance to policy analysis within CBK. Participants explored the rationale for economywide analysis, reviewed foundational concepts such as the circular flow of income, examined the sources and structure of SAMs, and discussed how to build a Macro SAM and align it with national accounts.
The second session, held on July 17, 2025, advanced these discussions by exploring the relationship between Supply and Use Tables (SUTs), Input-Output Tables (IOTs), and SAMs in disaggregating a Macro SAM into a Micro SAM. Participants also reviewed accounts for activities, commodities, factors, and households, before engaging in sessions on SAM-based models, multiplier analysis, and interpretation of results.
The third session, held on August 14, 2025, emphasized hands-on training. Participants worked with data from national accounts, government accounts, and the current account to construct SAMs and apply them in practice. These intensive exercises laid the groundwork for the next phase of the collaboration, which will focus on co-creating a study using SAM-based models to generate insights into evidence-based policy formulation.
This ongoing capacity-sharing initiative reflects CBK’s and IFPRI’s shared commitment to strengthening analytical tools for macroeconomic policy and ensuring that decisions are informed by robust, data-driven evidence.
