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electricsheepasia/asia-ilo-ear-emta-sex-ind-nb-average-monthly-earnings-of-employees-by-ilo-secto

Average monthly earnings of employees by ILO sector and sex (local currency) | Asia (ILOSTAT) 🌏 12,386 observations · 23 Asia countries · 2005–2025 · Repackaged by Electric Sheep Asia TL;DR This dataset contains 12,386 observations of Earnings data across 23 Asia countries, spanning 2005–2025, covering 1 distinct indicators. About the source ILOSTAT is the ILO's central statistics database, the leading global source for labour statistics. It… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-ilo-ear-emta-sex-ind-nb-average-monthly-earnings-of-employees-by-ilo-secto.

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Average monthly earnings of employees by ILO sector and sex (local currency) | Asia (ILOSTAT)

🌏 12,386 observations · 23 Asia countries · 2005–2025 · Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)

rows countries years indicators license

TL;DR

This dataset contains 12,386 observations of Earnings data across 23 Asia countries, spanning 2005–2025, 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: Earnings

Methodology

Data pulled directly from the ILOSTAT REST API at https://rplumber.ilo.org/data/indicator?id=EAR_EMTA_SEX_IND_NB 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

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

CountryRowsFirst yearLast year
TUR1,42120052024
VNM1,22220072024
MNG1,04220092024
THA86320132024
KHM85320072023
PHL83820122023
LKA79220132024
PAK64220122025
IND63520122025
PSE60120152025
ARM48820112023
GEO44720172023
BTN42820182024
JOR39920172023
IDN36020122023
...8 more countries

Indicators (sample)

  • —EAR_EMTA_SEX_IND_NB — Average monthly earnings of employees by ILO sector and sex (local currency)

Schema

ColumnTypeDescriptionExample
ref_areastringISO 3166-1 alpha-3 country codeARM
ref_area.labelstringCountry name in EnglishArmenia
sourcestringILOSTAT source code (e.g. labour force survey)BB:173
source.labelstringSource name in EnglishHIES - Households Living Conditions S…
indicatorstringILOSTAT indicator codeEAR_EMTA_SEX_IND_NB
indicator.labelstringIndicator name in EnglishAverage monthly earnings of employees…
sexstringDisaggregation by sex (SEXT = total, SEXM = male, SEX_F = female)SEX_T
sex.labelstring—Total
classif1stringFirst classification variable (age, education, status, etc.)IND_SECTOR_TOTAL
classif1.labelstring—ILO sector: Total
timeint64Observation year2023
obs_valuefloat64Observed indicator value (unit varies — see indicator definition)159067.084
obs_statusstringObservation status flag (e.g. provisional, unreliable)U
obs_status.labelstring—Unreliable
note_indicatorstring—T30:111
note_indicator.labelstring—Currency: ARM - Dram (AMD)
note_sourcestring—R1:3513_T3:240
note_source.labelstring—Repository: ILO-STATISTICS - Micro da…

Disaggregation dimensions

The following columns provide disaggregation dimensions:

  • —`sex` (4 unique values): SEX_T, SEX_M, SEX_F, SEX_O

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-ear-emta-sex-ind-nb-average-monthly-earnings-of-employees-by-ilo-secto")
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"] == "EAR_EMTA_SEX_IND_NB"]
          .sort_values("time"))
sample.plot(x="time", y="obs_value", title="EAR_EMTA_SEX_IND_NB")

Pivot to country × year matrix

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

Citation

bibtex
@misc{asia_ilo_ear_emta_sex_ind_nb_average_monthly_earnings_of_employees_by_ilo_secto_2025,
  title        = {Average monthly earnings of employees by ILO sector and sex (local currency) | Asia (ILOSTAT)},
  author       = {International Labour Organization (ILO)},
  year         = {2025},
  url          = {https://www.ilo.org/shinyapps/bulkexplorer/?id=EAR_EMTA_SEX_IND_NB},
  publisher    = {HuggingFace Datasets, repackaged by Electric Sheep Asia},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-ear-emta-sex-ind-nb-average-monthly-earnings-of-employees-by-ilo-secto}}
}

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 2026-05-29 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=EAREMTASEXINDNB