electricsheepeurope/europe-ilo-luu-xlu2-sex-age-rt-combined-rate-of-time-related-underemployment-and

--- license: cc-by-4.0 language: - en task_categories: - tabular-classification - tabular-regression - time-series-forecasting multilinguality: monolingual size_categories: - 10K<n<100K tags: - tabular - europe - ilostat - other-measures-of-labour-underutilization - ilo - labour - employment pretty_name: "Combined rate of time-related underemployment and unemployment (LU2) by sex and age (%) | Europe (ILOSTAT)" --- # Combined rate of time-related underemployment and unemployment (LU2) by sex and age (%) | Europe (ILOSTAT) 🇪🇺 **36,240 observations** · **39 Europe countries** · **1991–2025** · *Repackaged by [Electric Sheep Europe](https://huggingface.co/electricsheepeurope)*      ## TL;DR This dataset contains **36,240 observations** of `Other measures of labour underutilization` data across **39 Europe countries**, spanning **1991–2025**, 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_XLU2_SEX_AGE_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_XLU2_SEX_AGE_RT` and filtered to Europe 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 39 Europe countries · top rows shown below, sorted by row count: | Country | Rows | First year | Last year | |---------|-----:|-----------:|----------:| | `CHE` | 1,278 | 1991 | 2025 | | `AUT` | 1,232 | 1998 | 2025 | | `PRT` | 1,230 | 1998 | 2025 | | `GBR` | 1,213 | 1999 | 2025 | | `ESP` | 1,195 | 1999 | 2025 | | `FRA` | 1,175 | 1998 | 2024 | | `EST` | 1,169 | 1998 | 2024 | | `HUN` | 1,126 | 1999 | 2024 | | `FIN` | 1,124 | 1999 | 2024 | | `POL` | 1,119 | 2001 | 2025 | | `ROU` | 1,108 | 1999 | 2024 | | `SWE` | 1,105 | 2000 | 2024 | | `NLD` | 1,101 | 2000 | 2024 | | `DNK` | 1,085 | 2000 | 2024 | | `BEL` | 1,078 | 1999 | 2024 | | ... | _24 more countries_ | | | ## Indicators (sample) - `LUU_XLU2_SEX_AGE_RT` — Combined rate of time-related underemployment and unemployment (LU2) by sex and age (%) ## Schema | Column | Type | Description | Example | |--------|------|-------------|---------| | `ref_area` | `string` | ISO 3166-1 alpha-3 country code | `ALB` | | `ref_area.label` | `string` | Country name in English | `Albania` | | `source` | `string` | ILOSTAT source code (e.g. labour force survey) | `BA:480` | | `source.label` | `string` | Source name in English | `LFS - Labour Force Survey` | | `indicator` | `string` | ILOSTAT indicator code | `LUU_XLU2_SEX_AGE_RT` | | `indicator.label` | `string` | Indicator name in English | `Combined rate of time-related underem…` | | `sex` | `string` | Disaggregation by sex (SEX_T = total, SEX_M = male, SEX_F = female) | `SEX_T` | | `sex.label` | `string` | — | `Total` | | `classif1` | `string` | First classification variable (age, education, status, etc.) | `AGE_YTHADULT_YGE15` | | `classif1.label` | `string` | — | `Age (Youth, adults): 15+` | | `time` | `int64` | Observation year | `2024` | | `obs_value` | `float64` | Observed indicator value (unit varies — see indicator definition) | `11.458` | | `obs_status` | `string` | Observation status flag (e.g. provisional, unreliable) | `U` | | `obs_status.label` | `string` | — | `Unreliable` | | `note_classif` | `string` | — | `C6:2316` | | `note_classif.label` | `string` | — | `Nonstandard age group: Excluding ages…` | | `note_indicator` | `string` | — | `I11:264` | | `note_indicator.label` | `string` | — | `Break in series: Methodology revised` | | `note_source` | `string` | — | `R1:3513` | | `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("electricsheepeurope/europe-ilo-luu-xlu2-sex-age-rt-combined-rate-of-time-related-underemployment-and") df = ds["train"].to_pandas() print(df.head()) ``` ### Filter to one country ```python germany = df[df["ref_area"] == "DEU"] ``` ### Time-series for a single indicator ```python sample = (df[df["indicator"] == "LUU_XLU2_SEX_AGE_RT"] .sort_values("time")) sample.plot(x="time", y="obs_value", title="LUU_XLU2_SEX_AGE_RT") ``` ### Pivot to country × year matrix ```python matrix = (df[df["indicator"] == "LUU_XLU2_SEX_AGE_RT"] .pivot_table(index="time", columns="ref_area", values="obs_value")) print(matrix.tail()) ``` ## Citation ```bibtex @misc{europe_ilo_luu_xlu2_sex_age_rt_combined_rate_of_time_related_underemployment_and_2025, title = {Combined rate of time-related underemployment and unemployment (LU2) by sex and age (%) | Europe (ILOSTAT)}, author = {International Labour Organization (ILO)}, year = {2025}, url = {https://www.ilo.org/shinyapps/bulkexplorer/?id=LUU_XLU2_SEX_AGE_RT}, publisher = {HuggingFace Datasets, repackaged by Electric Sheep Europe}, howpublished = {\url{https://huggingface.co/datasets/electricsheepeurope/europe-ilo-luu-xlu2-sex-age-rt-combined-rate-of-time-related-underemployment-and}} } ``` ## 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 Europe repackaging. ## About Electric Sheep Electric Sheep Europe is part of the Electric Sheep mission: a unified, ML-ready data layer for Europe 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/electricsheepeurope](https://huggingface.co/electricsheepeurope) --- _Provenance: ingested 2026-05-27 via the Electric Sheep pipeline. Source URL: https://www.ilo.org/shinyapps/bulkexplorer/?id=LUU_XLU2_SEX_AGE_RT_This dataset contains 36,240 observations of Combined rate of time-related underemployment and unemployment (LU2) by sex and age (%) across 39 Europe countries, spanning 1991–2025, covering 1 distinct indicator. The data is sourced from the International Labour Organization (ILO) ILOSTAT database, retrieved via API and filtered to European countries, focusing on other measures of labour underutilization. It includes fields such as country codes, indicator labels, sex disaggregation, age groups, year, observed values, and data quality flags, suitable for tabular classification, regression, and time-series forecasting tasks.

搜集汇总

数据集介绍

构建方式

该数据集源自国际劳工组织（ILO）旗下的ILOSTAT核心统计数据库，经由Electric Sheep Europe团队重新封装而成。数据通过ILOSTAT提供的REST API接口直接拉取，原始接口地址为https://rplumber.ilo.org/data/indicator?id=LUU_XLU2_SEX_AGE_RT，并依据欧洲ISO3国家代码进行过滤筛选。ILOSTAT依据国际劳工统计学家会议（ICLS）的定义标准，对各国劳动力调查的原始微观数据进行统一协调与整合，并在source.label字段中标注数据来源，确保数据的可追溯性与可靠性。

特点

该数据集涵盖39个欧洲国家从1991年至2025年的36,240条观测记录，聚焦于时间相关就业不足与失业的综合率（LU2）这一关键指标，并按性别和年龄进行细分。数据结构清晰，包含ref_area（国家代码）、sex（性别分类：总、男、女）、classif1（年龄分类）等维度字段，以及obs_value（观测值）、obs_status（数据状态标记）等质量字段。数据还提供了丰富的附注信息，如方法修订标志和样本框说明，便于研究者评估数据的适用性与局限性。

使用方法

研究者可通过HuggingFace Datasets库便捷调用，使用`load_dataset()`函数即可加载该数据集，并将其转换为Pandas DataFrame进行后续分析。例如，可按国家代码过滤特定国家的数据，或按时间序列排序后绘制LU2指标的变化趋势图。此外，还可通过数据透视表将数据重塑为国家×年份的矩阵形式，便于进行面板数据分析或横向比较。数据集支持分类、回归及时间序列预测等多种任务类型，为劳动力市场研究提供了高效的工具基础。

背景与挑战

背景概述

该数据集由国际劳工组织（ILO）统计部门（ILOSTAT）于2025年整理发布，后经Electric Sheep Europe重新打包至HuggingFace平台，旨在提供欧洲39个国家1991至2025年间基于性别与年龄分层的“时间相关就业不足与失业合计率（LU2）”观测数据，共36,240条记录。ILOSTAT作为全球劳动统计的权威数据库，其数据源自各国劳动力调查、住户收入调查及行政记录，并依据国际劳工统计学家会议（ICLS）定义进行标准化处理。该数据集聚焦于劳动利用不足的复合度量指标，突破了传统失业率仅反映无业状态的局限，为欧洲劳动力市场的结构性失衡、性别差异及代际不平等研究提供了长达35年的时序资料，对于评估后金融危机时代、疫情冲击及数字化转型背景下的就业质量与政策干预效果具有显著实证价值。

当前挑战

该数据集所解决的领域挑战在于，传统失业率（如ILO定义的LU1）无法捕捉到因工时不足而被迫寻求额外工作的“隐形失业”群体，而LU2合计率则整合了时间相关就业不足与失业两种状态，更全面地揭示了劳动力资源未充分利用的真实程度，尤其适用于分析欧洲非正规就业、兼职率上升及零工经济膨胀等结构性矛盾。在构建过程中，主要挑战包括：多个国家（如阿尔巴尼亚、北马其顿等）早期的调查覆盖不全或方法更替导致序列断点，需通过“best source”筛选策略及注释字段（如note_indicator.label中的“Break in series”）进行质量标注；不同国家间年龄分组、性别分类及统计口径差异（如非标准年龄组“Nonstandard age group”）增加了跨区域可比性偏差；此外，数据以年频率发布，缺失月度或季度高频序列，限制了短周期波动与政策即时评估的建模精度。

常用场景

经典使用场景

该数据集涵盖了1991年至2025年间39个欧洲国家的36,240条观测记录，聚焦于时间相关就业不足与失业的综合比率（LU2），并按性别和年龄进行分层。其最为经典的使用场景在于劳动经济学领域中的跨国面板数据分析，研究者可借助该数据集构建长时序、多维度的劳动市场弱势状态评估模型。通过整合ILOSTAT统一的国际劳动统计标准，该数据为分析欧洲各国在非传统就业形态下的劳动力资源错配现象提供了可靠的数据基础。

实际应用

在实际应用层面，该数据集服务于国际组织与国家统计机构对劳动政策的动态监控与效果评估。欧洲各国劳动部门可依据按性别与年龄分层的LU2比率，精准锁定社会政策干预的靶向群体。同时，该数据为跨国比较研究提供了标准化接口，支持政策制定者识别不同制度环境下灵活就业形态的演变规律，进而设计更具包容性的就业促进与社保覆盖策略。

衍生相关工作

围绕该数据集已衍生出一系列标志性工作。ILOSTAT原始微数据经由Electric Sheep Europe重封装后，兼容HuggingFace的load_dataset接口，大幅降低了劳动经济数据在机器学习流水线中的使用门槛。后续工作包括利用该数据进行时序预测的劳动市场预警模型开发，以及在性别经济学框架下，结合LU2比率探究女性劳动参与障碍的跨国差异分析。这些研究共同奠定了该数据集作为欧洲劳动市场结构性分析基准的学术地位。