Youth school-to-work transition panel by country (UNICEF)

Commercial use OKFreshLicense: CC-BY-3.0-IGO

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Latest-estimate panel of six youth school-to-work indicators for 186 countries, 2010-2024: adolescent NEET and unemployment rates (15-19), child-labour prevalence thresholds (10-17, economic activity and household chores), and mean weekly hours in economic activities / household chores (10-17). Keyless UNICEF Data Warehouse SDMX, Transition to Work dataflow; joins on country_code with the catalog's other global panels. Fills the catalog's youth-labor gap (existing labor coverage is US/EU-centric).

Source: UNICEF Transition-to-Work intelligence
Rows: 515
Columns: 12
Source cadence: Yearly
Last refreshed: Oct 5, 2026
Theme: labor

Column	Type	Description
country_code	string	ISO 3166-1 alpha-3 country code (UNICEF Data Warehouse field REF_AREA; the ~117 regional aggregates are dropped).
country	string	Country name from the catalog's canonical ISO3 mapper.
indicator	string	Canonical indicator slug: neet_15_19, youth_unemployment_15_19, child_labour_econ, child_labour_chores, time_econ_activity, time_household_chores.
indicator_label	string	Human-readable indicator definition from the UNICEF codelist CL_UNICEF_INDICATOR.
age_band	string	Age band of the indicator: '15-19' or '10-17'.
value	float	Latest published estimate in the indicator's unit (percent for the four rate indicators, hours per week for the two time-use indicators).
unit	string	Unit of value: 'percent' or 'hours_per_week'.
estimate_year	integer	Reference year of the estimate (TIME_PERIOD). The dataflow publishes one estimate year per country-indicator pair.
data_source	string	Underlying survey (DATA_SOURCE, e.g. LFS - Labour Force Survey, MICS 2018).
source_label	string	Source URL (SOURCE_LINK; empty in the feed).
obs_status	string	UNICEF observation status (E = estimated, RA = reported/analyzed).
row_hash	string	Deterministic 12-hex row identity hash (country_code\|indicator\|estimate_year).

First 10 sample rows — a preview, not the complete dataset.

country_code	country	indicator	indicator_label	age_band	value	unit	estimate_year	data_source	source_label	obs_status	row_hash
ABW	Aruba	youth_unemployment_15_19	Percentage of adolescents (aged 15-19 years) in the labour force who are unemployed	15-19	23.6	percent	2,011	LFS - Labour Force Survey	—	RA	187967880ebc
AFG	Afghanistan	neet_15_19	Percentage of adolescents (aged 15-19 years) not in education, employment or training	15-19	39.3	percent	2,021	LFS - Labour Force Survey	—	RA	8e96eb8b8930
AFG	Afghanistan	youth_unemployment_15_19	Percentage of adolescents (aged 15-19 years) in the labour force who are unemployed	15-19	8.8	percent	2,021	LFS - Labour Force Survey	—	RA	51ff3edd65fa
AGO	Angola	child_labour_chores	Child labour thresholds (household chores)	10-17	13.2	percent	2,016	DHS 2015-16	—	E	d6264a0d95e5
AGO	Angola	child_labour_econ	Child labour thresholds (economic activity)	10-17	9	percent	2,016	DHS 2015-16	—	E	36aa0b4946a9
AGO	Angola	neet_15_19	Percentage of adolescents (aged 15-19 years) not in education, employment or training	15-19	21	percent	2,022	LFS - Employment Survey	—	RA	2ec6264115a1
AGO	Angola	time_household_chores	Time spent in household chores	10-17	12.6	hours_per_week	2,016	DHS 2015-16	—	E	bc78c9e4698a
AGO	Angola	youth_unemployment_15_19	Percentage of adolescents (aged 15-19 years) in the labour force who are unemployed	15-19	21.8	percent	2,022	LFS - Employment Survey	—	RA	d346f4f16ae0
ALB	Albania	neet_15_19	Percentage of adolescents (aged 15-19 years) not in education, employment or training	15-19	15.7	percent	2,023	LFS - Labour Force Survey	—	RA	22e6b2026b5a
ALB	Albania	youth_unemployment_15_19	Percentage of adolescents (aged 15-19 years) in the labour force who are unemployed	15-19	19.6	percent	2,023	LFS - Labour Force Survey	—	RA	cd50406b0ce1

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/unicef_wt_intel/unicef_wt_youth_work_transition_panel" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/unicef_wt_intel/unicef_wt_youth_work_transition_panel").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

API endpoint: https://datazimuts.com/v1/datasets/unicef_wt_intel/unicef_wt_youth_work_transition_panel

Tip: fetch /llms.txt for the full machine-readable catalog.

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Pinned to snapshot 20261005T223114Z-01d239d76f95 and its content hash, so readers get exactly the data you used.

APA

UNICEF Transition-to-Work intelligence. (2026). Youth school-to-work transition panel by country (UNICEF) [Data set, snapshot 20261005T223114Z-01d239d76f95, sha256 01d239d76f95]. Datazimuts. Retrieved 2026-10-06, from https://datazimuts.com/en/datasets/unicef_wt_intel/unicef_wt_youth_work_transition_panel?snapshot=20261005T223114Z-01d239d76f95

BibTeX

@misc{dz_unicef_wt_intel_unicef_wt_youth_work_tra_01d239d7,
  title        = {{Youth school-to-work transition panel by country (UNICEF)}},
  author       = {{UNICEF Transition-to-Work intelligence}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/unicef_wt_intel/unicef_wt_youth_work_transition_panel?snapshot=20261005T223114Z-01d239d76f95}},
  note         = {Snapshot 20261005T223114Z-01d239d76f95, sha256 01d239d76f95f29bf1db7cd7b596f2f5a42396d7333aa382435bc36f276f873b; accessed 2026-10-06}
}

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Youth school-to-work transition panel by country (UNICEF)

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