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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.本研究采用2010至2023年间覆盖14个西非国家经济共同体（Economic Community of West African States, ECOWAS）成员国的均衡面板数据集，旨在探讨水稻部门的政治与制度契合度如何随时间推移影响水稻生产效率。该数据集通过整合多类互补来源的制度、农业、宏观经济、贸易及气候变量构建而成，其核心目标不仅在于捕捉水稻产出绩效的动态变化，更旨在涵盖西非地区水稻生产所处的更广泛政策与治理语境。 本研究的核心解释变量为政治与制度契合度指数（Political and Institutional Alignment Index），该指数用于衡量一国水稻部门治理与区域农业承诺之间的一致性程度。该指数由四大核心维度构建：战略契合、监管契合、多方利益相关者协调，以及监测与评估。每个维度均采用0至2的序数标尺进行年度编码：0代表制度缺失或制度化程度极弱，1代表部分或初步制度化，2代表完全制度化。编码过程依托非洲全面农业发展计划（Comprehensive Africa Agriculture Development Programme, CAADP）两年期审查报告、ECOWAP相关监测框架，以及国家水稻发展战略中的信息完成。为提升数据质量与一致性，研究通过结构化验证流程对编码结果进行复核与完善，该流程邀请熟悉水稻部门及国家战略实施现状的国家联络点参与。验证完成后，采用主成分分析法（Principal Component Analysis）将四大维度整合为综合指标。 本研究的被解释变量为水稻单产，将其作为部门生产效率的代理变量。除制度契合度指数外，数据集还包含一系列宽泛的控制变量，用于捕捉可能影响水稻生产效率的核心因素，具体包括种子使用量、水稻种植面积、相对价格激励、与GDP相关的指标、电力可及性、人均家庭消费，以及农业信贷。此外，研究还纳入了气候相关变量，尤其是气温异常值，以反映影响农业绩效的环境冲击。在部分模型设定中，还加入了水稻进口量、进口额等贸易变量，以体现外部市场暴露及进口稻米带来的竞争压力的作用。综上，这些数据构建了西非国家经济共同体水稻部门的多维度画像，能够用于评估在控制更广泛的结构性与气候约束的前提下，制度契合度更高、协调更完善、政策跟进能力更强的国家是否能够在长期中取得更优的生产效率表现。