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