Calibrated Simulation of Individual Level Data for the Basic National Pension Scheme (Tier 1) in Ghana for the Periods 2015 to 2024

This depository is the result of a calibrated microsimulation that generated the first individual-level dataset for Ghana’s Basic National Pension Scheme (Tier 1) for the period 2015 to 2024. The dataset combines publicly available annual aggregates from the Social Security and National Insurance Trust (SSNIT), National Pensions Regulatory Authority (NPRA) and the Ministry of Labour, Jobs and Employment (MLJE) with demographic, labour and mortality inputs from the Ghana Statistical Service (GSS) and the United Nations World Population Prospects. Using stratified sampling, membership transition modeling and poststratification calibration, the dataset recreates contributors, retirees and non-members at fine age-sex resolution while exactly reproducing official totals on contributions and benefits/pensions. The resulting microdata support distributional analysis of earnings, contributions, pensions and replacement rates, as well as actuarial projections, policy simulations and research on pension adequacy, coverage expansion and long-term social protection financing in Ghana.本数据集存储库基于经校准的微观模拟方法构建，生成了加纳2015年至2024年第一层级基本国家养老金计划（Basic National Pension Scheme, Tier 1）的首份个体层面数据集。该数据集整合了来自社会保障与国家保险信托基金（Social Security and National Insurance Trust, SSNIT）、国家养老金监管局（National Pensions Regulatory Authority, NPRA）、劳工、就业与职业部（Ministry of Labour, Jobs and Employment, MLJE）的公开年度汇总数据，并结合了加纳统计服务局（Ghana Statistical Service, GSS）与联合国世界人口展望（United Nations World Population Prospects）提供的人口统计、劳动力及死亡率相关输入数据。 研究团队采用分层抽样、参保状态转移建模及事后分层校准技术，通过该数据集还原生成参保缴费人员、退休领取人员与非参保人员的精细年龄-性别维度分布，同时严格复现了缴费与养老金待遇/给付的官方统计总额。最终生成的微观数据可支撑收入、缴费、养老金及替代率的分布特征分析，同时可用于精算预测、政策模拟以及加纳地区养老金充足性、参保覆盖面拓展与长期社会保护融资等相关研究。