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This study draws on a balanced panel dataset covering 14 ECOWAS countries from 2010 to 2023 in order to examine how political and institutional alignment in the rice sector relates to rice productivity over time. The database was constructed by combining institutional, agricultural, macroeconomic, trade, and climate variables from several complementary sources. Its main purpose is to capture not only changes in rice output performance, but also the broader policy and governance conditions within which rice production evolves across West Africa. The central explanatory variable is the Political and Institutional Alignment Index, designed to measure the degree of coherence between national rice sector governance and regional agricultural commitments. This index is built from four core dimensions: strategic alignment, regulatory alignment, multi-stakeholder coordination, and monitoring and evaluation. Each dimension was coded annually using an ordinal scale ranging from 0 to 2, where 0 reflects absence or very weak institutionalization, 1 reflects partial or emerging institutionalization, and 2 reflects full institutionalization. The coding process relied on information drawn from CAADP Biennial Review reports, ECOWAP-related monitoring frameworks, and National Rice Development Strategies. To improve data quality and consistency, the coding was reviewed and refined through a structured validation process involving national focal points familiar with the rice sector and the implementation status of national strategies. After validation, the four dimensions were aggregated into a synthetic indicator using Principal Component Analysis. The dependent variable is rice yield, used here as a proxy for sectoral productivity. In addition to the institutional index, the dataset includes a broad set of control variables intended to capture the main factors that can influence rice productivity. These include seed use, cultivated rice area, relative price incentives, GDP-related indicators, electricity access, household consumption per capita, and agricultural credit. Climate-related variables, especially temperature anomalies, were also incorporated to account for environmental shocks affecting agricultural performance. In some model specifications, trade variables such as rice import volumes or import values were added to reflect the role of external market exposure and competitive pressure from imported rice. Taken together, these data provide a multidimensional representation of the rice sector in ECOWAS. They make it possible to assess whether countries that are more institutionally aligned, more coordinated, and better equipped in terms of policy follow-up tend to achieve stronger productivity outcomes over time, while controlling for broader structural and climatic constraints.