Skills-in-Literacy Adjusted Human Capital Dataset (SLAMYS)

The dataset of global Skills-in-Literacy Adjusted Mean Years of Schooling (SLAMYS) provides the indicator for 185 countries, by gender and three broad age groups (20-64; 20-39; 40-64) presented in five-year steps from 1970 to 2025. This dataset is an extention and update of Lutz et al. (2021) which included estimates until 2020 and for working age population (age 20-64) only. This new dataset allows for more nuanced analyses of gender-specific trends and generational shifts in skill formation, with particular attention to younger adult populations. The dataset is based on more up to date survey data, including the most recent OECD’s Programme for the International Assessment of Adult Competencies Cycle 2 data (PIAAC, 2023), most recent the Demographic and Health Survey (DHS), and Multiple Indicator Cluster Surveys (MICS). It also uses more recent mean years of schooling (MYS) which are sourced from the most recent Wittgenstein Centre Human Capital Data Explorer, version 3 (K. C. et al., 2024; , https://dataexplorer.wittgensteincentre.org/wcde-v3). Estimates for 2020 and 2025 correspond to the medium scenario (SSP2) of the 2023 update (v15) of the Wittgenstein Centre’s Human Capital Projections (K.C. et al 2024). MYS values for the period 1970–2015 are based on a historical reconstruction (KC et al. 2025) that is fully consistent with the SSP2 scenario. Additionally, estimates of educational attainment distributions by sex and age for all 185 countries—used as covariates in the prediction models—are drawn from the same sources and are fully aligned with the MYS values. See the attached technical documentation for more details. The dataset contains output data files including technical variables (MYS, SAFs) and a technical documentation. The documentation describes calculation steps, data structures, and includes illustrative examples to guide the interpretation of the main output variables. This dataset consists of the following files: Dataset: SLAMYS_2025_v1.csv The csv file includes the following variables: country_code (3-numeric ISO code, UN standard) country_name year (year in five year steps, 1970-2025) age_group (20-64, 20-39, 40-64) gender (Female, Male, Both) mys (mean years of schooling) saf (skill adjustment factor) slamys (skills-in-literacy adjusted mean years of schooling) calculation (predicted values == 1, empirical values == 0) source (survey name for empirical values, NA for predicted values) Data sources: SLAMYS_data-source-documentation_v1.csv Documentation and methodology: L4S_deliverable D2.4 Skills adjusted global human capital dataset_2025-08-22_final.pdf R codes: https://github.com/clreiter/Skills-in-Literacy-Adjusted-Human-Capital-Dataset全球识字技能调整平均受教育年限（Skills-in-Literacy Adjusted Mean Years of Schooling, SLAMYS）数据集为185个国家提供了分性别、三大年龄组（20-64岁、20-39岁、40-64岁）的指标，时间跨度为1970年至2025年，以5年为间隔。本数据集是对Lutz等人2021年研究的扩展与更新，后者仅涵盖了2020年及之前的劳动年龄人口（20-64岁）估算结果。这款新数据集支持对技能形成过程中的分性别趋势与代际变迁开展更细致的分析，尤其聚焦于青年成年群体。 本数据集基于最新的调研数据，包括经济合作与发展组织（Organisation for Economic Co-operation and Development, OECD）最新的国际成人能力评估项目第二周期数据（Programme for the International Assessment of Adult Competencies Cycle 2, PIAAC, 2023）、最新的人口与健康调查（Demographic and Health Survey, DHS）以及多指标类集调查（Multiple Indicator Cluster Surveys, MICS）。同时采用了最新的平均受教育年限（mean years of schooling, MYS）数据，该数据来源于2024年发布的维特根斯坦中心人力资本数据探索器第三版（K. C. et al., 2024；https://dataexplorer.wittgensteincentre.org/wcde-v3）。2020年与2025年的估算结果对应维特根斯坦中心2024年发布的人力资本预测2023年更新版（v15）的中等情景（Shared Socioeconomic Pathways 2, SSP2）。1970年至2015年的MYS数值基于一项与SSP2情景完全一致的历史重构研究（KC et al., 2025）。此外，作为预测模型协变量的所有185个国家分性别、分年龄的受教育程度分布估算结果，均来源于相同数据源，且与MYS数值完全对齐。更多细节请参阅随附的技术文档。 本数据集包含输出数据文件，其中涵盖技术变量（Skill Adjustment Factors, SAFs、MYS）以及一份技术文档。该文档详细说明了计算步骤与数据结构，并附带示例以指导用户解读主要输出变量。 本数据集包含以下文件： 数据集文件：SLAMYS_2025_v1.csv 该CSV文件包含以下变量： country_code（3位数字ISO代码，符合联合国标准） country_name（国家名称） year（以5年为间隔的年份，覆盖1970-2025年） age_group（年龄组，包含20-64岁、20-39岁、40-64岁三类） gender（性别，包含女性、男性、合计三类） mys（平均受教育年限，mean years of schooling） saf（技能调整因子，skill adjustment factor） slamys（识字技能调整平均受教育年限，skills-in-literacy adjusted mean years of schooling） calculation（计算类型，预测值记为1，实测值记为0） source（数据来源，实测值对应调研名称，预测值为NA） 数据源文件：SLAMYS_data-source-documentation_v1.csv 文档与方法论文件：L4S_deliverable D2.4 Skills adjusted global human capital dataset_2025-08-22_final.pdf R代码仓库：https://github.com/clreiter/Skills-in-Literacy-Adjusted-Human-Capital-Dataset