INTERNATIONAL FISCAL ADAPTATION PANEL (IFAP DATASET)

Public finance systems worldwide are being tested by persistent global disruptions, climate volatility, and digital transformation pressures. Governments must maintain fiscal stability while responding rapidly to uncertainty. These challenges highlight the need for datasets that explain how nations adapt and remain resilient under fiscal strain (OECD, 2023). The dataset developed for this study captures cross-country fiscal adaptability, institutional accountability, and digital transparency, offering a comprehensive empirical foundation for analyzing resilient budgeting (IMF, 2024). It holds significance across global, regional, and national levels as it helps policymakers, researchers, and institutions quantify and compare how fiscal systems adjust under disruption. The dataset extends the Theory of Fiscal Federalism by introducing digital integration and adaptive coordination into its analytical structure. This Dataset contributes to theory by extending the Theory of Fiscal Federalism through the addition of digital transparency and adaptive coordination, thereby broadening its explanatory scope and offering a refined framework for understanding fiscal resilience in global governance settings (Ahir, Bloom, & Furceri, 2022; OECD, 2024). The inclusion of multi-country data from 58 economies allows testing competing perspectives on institutional complementarity and fiscal flexibility across income groups. It responds to a hot global issue the stability of government finance under technological and geopolitical uncertainty and contributes to open science through transparency and reproducibility. The dataset employs harmonized indicators from the IMF Fiscal Monitor, OECD Government at a Glance, World Bank Global Economic Prospects, and the World Uncertainty Index. Each source was selected for its data consistency, cross-regional coverage, and alignment with recognized global fiscal governance standards (IMF, 2024; World Bank, 2024). The multi-level sampling captures 118 economies, ensuring global representativeness across advanced, emerging, and developing regions. The sample size is optimal to identify robust statistical patterns in fiscal adaptability and coordination. Using structural equation modeling and multilevel regression, the analysis found that fiscal coordination (β=0.41), institutional accountability (β=0.39), and digital budgeting (β=0.34) jointly explain 83 percent of fiscal resilience variation (OECD, 2023; IMF, 2024). These results highlight the predictive power of fiscal integration and adaptive systems in maintaining budget credibility under crisis. The dataset’s novelty lies in its integration of fiscal coordination, accountability, and digital capacity into a unified framework, unlike prior repositories that analyze these constructs separately. It bridges policy and academic discourse by connecting fiscal resilience with real-time governance analytics. The cross-sectoral and cross-country design facilitates comparative analysis, enabling annual updates and policy simulations. By capturing fiscal dynamics across jurisdictions and digital governance capacities, the dataset enables evidence-based policymaking aligned with sustainable finance goals. It supports testing of alternative theories such as institutional resilience, adaptive governance, and public accountability under disruption. The dataset is relevant for open-access collaboration, fostering replication, longitudinal tracking, and global policy benchmarking.全球公共财政体系正面临持续的全球动荡、气候波动与数字化转型压力的多重考验。各国政府必须在维持财政稳定的同时，快速应对不确定性。这些挑战凸显了构建可阐释各国在财政压力下如何实现适应性调整与韧性维持的数据集的必要性（经济合作与发展组织[Organisation for Economic Co-operation and Development, OECD]，2023）。本研究开发的数据集涵盖了跨国财政适应性、制度问责性与数字化透明度等维度，为分析韧性预算提供了全面的实证基础（国际货币基金组织[International Monetary Fund, IMF]，2024）。该数据集在全球、区域与国家层面均具有重要价值，可帮助政策制定者、研究人员与各类机构量化并比较财政体系在动荡环境下的调整路径。 本数据集将数字化整合与适应性协调纳入分析框架，拓展了财政联邦主义理论（Theory of Fiscal Federalism）的研究范畴。通过新增数字化透明度与适应性协调维度，本数据集进一步丰富了财政联邦主义理论的内涵，拓宽了其解释边界，并为理解全球治理语境下的财政韧性提供了更为精细化的分析框架（Ahir、Bloom与Furceri，2022；经济合作与发展组织[Organisation for Economic Co-operation and Development, OECD]，2024）。数据集纳入了58个经济体的跨国数据，可用于检验关于不同收入组别间制度互补性与财政灵活性的各类竞争性假说。本数据集回应了“技术与地缘政治不确定性下政府财政稳定性”这一全球热点议题，并通过数据透明性与可复现性助力开放科学发展。 本数据集采用了来自国际货币基金组织《财政监测》、经济合作与发展组织《政府概览》、世界银行[World Bank]《全球经济展望》以及世界不确定性指数（World Uncertainty Index）的标准化指标。各数据源均因其数据一致性、跨区域覆盖范围与契合全球公认财政治理标准的特性而被遴选（国际货币基金组织[International Monetary Fund, IMF]，2024；世界银行[World Bank]，2024）。多层级抽样覆盖了118个经济体，确保了样本在发达、新兴与发展中地区的全球代表性。该样本规模足以精准识别财政适应性与协调机制中的稳健统计规律。通过结构方程模型（structural equation modeling）与多层回归（multilevel regression）分析，研究发现财政协调（β=0.41）、制度问责性（β=0.39）与数字化预算管理（β=0.34）三者共同解释了83%的财政韧性变异（经济合作与发展组织[Organisation for Economic Co-operation and Development, OECD]，2023；国际货币基金组织[International Monetary Fund, IMF]，2024）。上述结果凸显了财政整合与适应性体系在危机时期维持预算公信力的预测效力。 本数据集的创新性在于将财政协调、问责性与数字化能力整合为统一分析框架，而此前的相关数据库多对这些维度进行单独分析。它架起了政策与学术话语间的桥梁，将财政韧性与实时治理分析相结合。其跨部门与跨国的设计便于开展比较分析，支持年度更新与政策模拟。通过捕捉各司法管辖区的财政动态与数字化治理能力，本数据集可助力制定契合可持续金融目标的循证政策。它可用于检验制度韧性、适应性治理与动荡环境下的公共问责等各类替代性理论。本数据集支持开放获取合作，可推动研究复现、纵向追踪与全球政策基准设定。