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electricsheepasia/asia-ilo-luu-xlu4-sex-rt-composite-rate-of-labour-underutilization-lu4-by-s

Composite rate of labour underutilization (LU4) by sex (%) | Asia (ILOSTAT) 🌏 582 observations · 31 Asia countries · 1999–2025 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 582 observations of Other measures of labour underutilization data across 31 Asia countries, spanning 1999–2025, covering 1 distinct indicators. About the source ILOSTAT is the ILO's central statistics database, the leading global source for labour… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-ilo-luu-xlu4-sex-rt-composite-rate-of-labour-underutilization-lu4-by-s.

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Composite rate of labour underutilization (LU4) by sex (%) | Asia (ILOSTAT)

🌏 582 observations · 31 Asia countries · 1999–2025 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 582 observations of Other measures of labour underutilization data across 31 Asia countries, spanning 1999–2025, covering 1 distinct indicators.

About the source

ILOSTAT is the ILO's central statistics database, the leading global source for labour statistics. It compiles indicators across employment, unemployment, wages, working time, child labour, informal economy, social protection, occupational injuries, and SDG decent work targets — drawing on national labour force surveys, household income surveys, establishment surveys, and administrative records. Coverage spans 200+ economies, with the ILO's Department of Statistics responsible for harmonisation.

  • —Source: ILOSTAT
  • —Publisher: International Labour Organization (ILO)
  • —License: cc-by-4.0
  • —Topic: Other measures of labour underutilization

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=LUU_XLU4_SEX_RT and filtered to Asia ISO3 country codes. ILOSTAT harmonises raw survey microdata using ICLS (International Conference of Labour Statisticians) definitions; sources are flagged in the source.label column for traceability.

Geographic coverage

31 Asia countries · top rows shown below, sorted by row count:

CountryRowsFirst yearLast year
CYP7819992024
VNM5120072024
LKA4220102024
KGZ3920112023
THA3920102024
TUR3020042013
PSE3020152025
BRN2720142024
JOR2420172024
PHL2120172023
IDN2120162023
GEO1820192024
MNG1820192024
KHM1520032019
AFG1520122021
...16 more countries

Indicators (sample)

  • —LUU_XLU4_SEX_RT — Composite rate of labour underutilization (LU4) by sex (%)

Schema

ColumnTypeDescriptionExample
ref_areastringISO 3166-1 alpha-3 country codeAFG
ref_area.labelstringCountry name in EnglishAfghanistan
sourcestringILOSTAT source code (e.g. labour force survey)BA:15715
source.labelstringSource name in EnglishLFS - Labour Force Survey
indicatorstringILOSTAT indicator codeLUU_XLU4_SEX_RT
indicator.labelstringIndicator name in EnglishComposite rate of labour underutiliza…
sexstringDisaggregation by sex (SEXT = total, SEXM = male, SEX_F = female)SEX_T
sex.labelstring—Total
timeint64Observation year2021
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)19.229
obs_statusstringObservation status flag (e.g. provisional, unreliable)B
obs_status.labelstring—Break in series
note_indicatorstring—I11:264
note_indicator.labelstring—Break in series: Methodology revised
note_sourcestring—R1:3513_S3:8
note_source.labelstring—Repository: ILO-STATISTICS - Micro da…

Disaggregation dimensions

The following columns provide disaggregation dimensions:

  • —`sex` (3 unique values): SEX_T, SEX_M, SEX_F

Data quality & caveats

  • —Data is annual frequency. Some indicators also publish monthly or quarterly series — those are not included here.
  • —When an indicator has multiple sources for the same country×year, the ILO-selected 'best source' is used.
  • —Disaggregation columns (sex, classif1, classif2) are non-null only when the indicator publishes that breakdown.

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepasia/asia-ilo-luu-xlu4-sex-rt-composite-rate-of-labour-underutilization-lu4-by-s")
df = ds["train"].to_pandas()
print(df.head())

Filter to one country

python
indonesia = df[df["ref_area"] == "IDN"]

Time-series for a single indicator

python
sample = (df[df["indicator"] == "LUU_XLU4_SEX_RT"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="LUU_XLU4_SEX_RT")

Pivot to country × year matrix

python
matrix = (df[df["indicator"] == "LUU_XLU4_SEX_RT"]
          .pivot_table(index="time", columns="ref_area", values="obs_value"))
print(matrix.tail())

Citation

bibtex
@misc{asia_ilo_luu_xlu4_sex_rt_composite_rate_of_labour_underutilization_lu4_by_s_2025,
  title        = {Composite rate of labour underutilization (LU4) by sex (%) | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2025},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=LUU_XLU4_SEX_RT},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-luu-xlu4-sex-rt-composite-rate-of-labour-underutilization-lu4-by-s}}
}

License

Released under cc-by-4.0.

Original data © International Labour Organization (ILO). When using this dataset, please cite both the original source above and the Electric Sheep Asia repackaging.

About Electric Sheep

Electric Sheep Asia is part of the Electric Sheep mission: a unified, ML-ready data layer for Asia on HuggingFace. We pull data from authoritative open sources, normalize the schemas, package as Parquet, and publish with consistent dataset cards so researchers and developers can use load_dataset() to start working in seconds.

Browse the full collection: huggingface.co/electricsheepasia


Provenance: ingested 2026-05-27 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=LUUXLU4SEXRT_