electricsheepasia/asia-ilo-luu-xlu3-sex-rt-combined-rate-of-unemployment-and-potential-labour

--- license: cc-by-4.0 language: - en task_categories: - tabular-classification - tabular-regression - time-series-forecasting multilinguality: monolingual size_categories: - n<1K tags: - tabular - asia - ilostat - other-measures-of-labour-underutilization - ilo - labour - employment pretty_name: "Combined rate of unemployment and potential labour force (LU3) by sex (%) | Asia (ILOSTAT)" --- # Combined rate of unemployment and potential labour force (LU3) by sex (%) | Asia (ILOSTAT) 🌏 **780 observations** · **34 Asia countries** · **1999–2025** · *Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia)*      ## TL;DR This dataset contains **780 observations** of `Other measures of labour underutilization` data across **34 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](https://www.ilo.org/shinyapps/bulkexplorer/?id=LUU_XLU3_SEX_RT) - **Publisher:** International Labour Organization (ILO) - **License:** [cc-by-4.0](https://creativecommons.org/licenses/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_XLU3_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 34 Asia countries · top rows shown below, sorted by row count: | Country | Rows | First year | Last year | |---------|-----:|-----------:|----------:| | `CYP` | 78 | 1999 | 2024 | | `PHL` | 57 | 2003 | 2023 | | `VNM` | 51 | 2007 | 2024 | | `KOR` | 45 | 2000 | 2019 | | `LKA` | 42 | 2010 | 2024 | | `TUR` | 42 | 2000 | 2013 | | `THA` | 39 | 2010 | 2024 | | `KGZ` | 39 | 2011 | 2023 | | `PSE` | 39 | 2012 | 2025 | | `ARM` | 36 | 2007 | 2018 | | `BRN` | 27 | 2014 | 2024 | | `ARE` | 24 | 2017 | 2024 | | `IDN` | 24 | 2015 | 2023 | | `JOR` | 24 | 2017 | 2024 | | `SAU` | 21 | 2017 | 2024 | | ... | _19 more countries_ | | | ## Indicators (sample) - `LUU_XLU3_SEX_RT` — Combined rate of unemployment and potential labour force (LU3) by sex (%) ## Schema | Column | Type | Description | Example | |--------|------|-------------|---------| | `ref_area` | `string` | ISO 3166-1 alpha-3 country code | `AFG` | | `ref_area.label` | `string` | Country name in English | `Afghanistan` | | `source` | `string` | ILOSTAT source code (e.g. labour force survey) | `BA:15715` | | `source.label` | `string` | Source name in English | `LFS - Labour Force Survey` | | `indicator` | `string` | ILOSTAT indicator code | `LUU_XLU3_SEX_RT` | | `indicator.label` | `string` | Indicator name in English | `Combined rate of unemployment and pot…` | | `sex` | `string` | Disaggregation by sex (SEX_T = total, SEX_M = male, SEX_F = female) | `SEX_T` | | `sex.label` | `string` | — | `Total` | | `time` | `int64` | Observation year | `2021` | | `obs_value` | `float64` | Observed indicator value (unit varies — see indicator definition) | `12.524` | | `obs_status` | `string` | Observation status flag (e.g. provisional, unreliable) | `B` | | `obs_status.label` | `string` | — | `Break in series` | | `note_indicator` | `string` | — | `I11:264` | | `note_indicator.label` | `string` | — | `Break in series: Methodology revised` | | `note_source` | `string` | — | `R1:3513_S3:8` | | `note_source.label` | `string` | — | `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-xlu3-sex-rt-combined-rate-of-unemployment-and-potential-labour") 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_XLU3_SEX_RT"] .sort_values("time")) sample.plot(x="time", y="obs_value", title="LUU_XLU3_SEX_RT") ``` ### Pivot to country × year matrix ```python matrix = (df[df["indicator"] == "LUU_XLU3_SEX_RT"] .pivot_table(index="time", columns="ref_area", values="obs_value")) print(matrix.tail()) ``` ## Citation ```bibtex @misc{asia_ilo_luu_xlu3_sex_rt_combined_rate_of_unemployment_and_potential_labour_2025, title = {Combined rate of unemployment and potential labour force (LU3) by sex (%) | Asia (ILOSTAT)}, author = {International Labour Organization (ILO)}, year = {2025}, url = {https://www.ilo.org/shinyapps/bulkexplorer/?id=LUU_XLU3_SEX_RT}, publisher = {HuggingFace Datasets, repackaged by Electric Sheep Asia}, howpublished = {\url{https://huggingface.co/datasets/electricsheepasia/asia-ilo-luu-xlu3-sex-rt-combined-rate-of-unemployment-and-potential-labour}} } ``` ## License Released under [cc-by-4.0](https://creativecommons.org/licenses/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](https://huggingface.co/electricsheepasia) --- _Provenance: ingested 2026-05-26 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=LUU_XLU3_SEX_RT_This dataset contains 780 observations of the Combined rate of unemployment and potential labour force (LU3) by sex (%) indicator across 34 Asia countries, spanning 1999–2025. It is sourced from the ILOSTAT database of the International Labour Organization (ILO), retrieved via API and filtered to Asian countries, covering other measures of labour underutilization. The dataset includes columns such as country code, country name, data source, indicator code, indicator label, sex disaggregation, year, observed value, and observation status, with breakdowns by sex (total, male, female). Data is published at annual frequency and harmonized by ILO statistical standards, suitable for tabular classification, regression, and time-series forecasting tasks. Repackaged by Electric Sheep Asia to provide a unified, ML-ready data layer for Asia.

搜集汇总

数据集介绍

构建方式

该数据集以国际劳工组织ILOSTAT中央统计数据库为源头，通过REST API接口直接抽取指标LUU_XLU3_SEX_RT的原始记录，并按照亚洲ISO3国家代码进行筛选。原始调查微观数据经ILO统计部门依据国际劳工统计学家会议定义进行调和处理，确保跨国可比性。数据由Electric Sheep Asia重新打包，保留来源标签以实现可追溯性，最终形成涵盖34个亚洲国家、1999至2025年间780条观测的结构化表格数据。

特点

数据集聚焦于失业与潜在劳动力合计比率（LU3）这一劳动力未充分利用指标，按性别维度细分为总计、男性和女性三类。覆盖范围横跨34个亚洲国家，时间跨度逾四分之一世纪，包含指标代码、来源信息、观测值及状态标志等丰富字段。数据以年度频率发布，部分指标附带方法修订或序列中断的标注，便于使用者识别数据质量与可比性边界。

使用方法

使用者可借助Hugging Face datasets库以load_dataset函数直接加载该数据集，并通过to_pandas方法转换为数据框进行后续分析。典型操作包括按国家代码筛选特定经济体的时序数据，或按指标代码提取单指标序列并绘制时间趋势图。亦可利用透视表功能将数据重塑为国家与年份的矩阵形式，便于开展跨国比较或面板回归等计量研究。

背景与挑战

背景概述

劳动力未充分利用的测度长期构成就业统计的核心议题，国际劳工组织（ILO）为此构建了涵盖失业率与潜在劳动力之和的LU3指标框架，以更全面刻画劳动力市场的闲置程度。该数据集由Electric Sheep Asia于2025年从ILOSTAT REST API抽取并重新封装，覆盖亚洲34个国家、1999至2025年间780条年度观测，按性别分列，指标代码为LUU_XLU3_SEX_RT。其核心研究问题在于揭示亚洲各国劳动力未充分利用的性别差异与时空演变规律，并为跨国比较提供标准化数据基础。该数据集对亚太地区就业政策评估、SDG体面工作目标监测具有重要参考价值。

当前挑战

该数据集所回应的领域难题在于：传统失业率仅捕捉完全失业人口，无法涵盖那些虽未就业但具备工作意愿与可获取性的潜在劳动力，导致劳动力闲置程度被系统性低估。构建过程中面临多重挑战：一是各国劳动力调查在调查时点、问卷设计与覆盖范围上存在异质性，ILO虽以ICLS定义进行协调，仍难免序列断裂；二是部分国家观测年份稀疏，面板数据不平衡，影响时序建模的稳健性；三是性别分列维度下某些国家仅报告总量，细分数据缺失；四是观测状态标记与来源注释繁杂，对数据清洗与可信度评估构成额外负担。

常用场景

经典使用场景

在劳动经济学与就业政策研究领域，该数据集最经典的使用场景在于以性别为分组维度，对亚洲各国1999至2025年间劳动力未充分利用程度进行跨国比较与趋势追踪。研究者常借助其构建面板数据模型，考察失业率与潜在劳动力之和（LU3）在时间维度上的演变规律，进而揭示不同国家间劳动力市场结构性差异的长期动态。

衍生相关工作

围绕该数据集，已衍生出一系列聚焦亚洲劳动力市场韧性与性别平等的比较研究，涵盖劳动力未充分利用的决定因素分析、青年与女性就业脆弱性评估，以及后疫情时代就业复苏路径的跨国比较。这些工作进一步拓展了ILOSTAT数据在计量分析与政策模拟中的应用边界。

数据集最近研究

最新研究方向

在全球劳动力市场深度转型与亚洲区域经济波动加剧的背景下，该数据集所承载的LU3指标——失业与潜在劳动力的复合比率——已成为研判劳动力未充分利用程度的关键标尺。近期研究聚焦于运用该数据集进行多国面板分析，借助机器学习与时间序列模型识别性别差异下的就业脆弱性，尤其关注后疫情时代青年与女性劳动参与率的非线性演变。同时，国际劳工组织推动的ICLS决议修订促使学者重新审视潜在劳动力界定，该数据集提供的性别分类与来源标注为方法论比较提供了实证基础，相关成果对亚洲各国优化就业政策、实现包容性增长具有显著的决策参考价值。