Data · dataset · 2026
Life tables and Lee–Carter mortality forecasts, 2000–2050: a reproducible national dataset with prediction intervals
Listed in Teesside University Research Data Repository
This dataset provides abridged life tables and mortality indicators for Uzbekistan at the national level, covering historical reference years (2000, 2005, 2010, 2015, 2019) and annual forecasts to 2050 (recommended Lee–Carter 2024–2050; experimental hybrid 2020–2050).
Description
Seven life-table functions are reported — central death rate (nMx), probability of dying (nqx), survivors of a radix of 100,000 (lx), deaths (ndx), person-years lived (nLx), total person-years remaining (Tx) and life expectancy (ex) — across 19 abridged age groups (<1, 1–4, 5–9, …, 80–84, 85+).
Historical indicators are given for both sexes, males and females; forecasts are given for males and females. Historical rates are drawn from the WHO Global Health Observatory. The 2008 all-population empirical life table (single year of age) is from the State Committee of the Republic of Uzbekistan on Statistics (www.stat.uz).
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The recommended forecast product is an independent, out-of-sample-validated Lee–Carter model fitted to annual UN WPP 2024 abridged life tables for Uzbekistan (2000–2023), with the mortality index k_t extrapolated by a random walk with drift (the standard Lee–Carter time-series choice). The recommended file, forecast_lee_carter_2024_2050_long.csv, provides central estimates with 95% prediction intervals (columns value_central, value_lo95, value_hi95) for all seven life-table functions by sex.
It closely matches the UN WPP 2024 medium variant for both sexes. An experimental hybrid Lee–Carter–Gompertz forecast, in which the log central death rate is expressed as ln m_x(t) = (ln A + B·x) + a_x + b_x·k_t + ε, is retained separately under data/experimental/ for methodological comparison. It does not outperform Lee–Carter out of sample (e0 mean absolute error 2.58/2.92 years vs 0.68/0.31 years for males/females); it is close to the benchmarks for females but optimistic for males, and should be treated as an optimistic scenario.
Data are provided in tidy (long) CSV format keyed by year × sex × age group × indicator, together with a multi-sheet Excel workbook, two single-year 2008 reference life tables (empirical and Gompertz), model-comparison tables (R²/RMSE and AIC/BIC by model and sex), an out-of-sample validation table, a data dictionary, and reproducible Python scripts. Values in the historical and experimental-hybrid files carry a provenance flag: historical rows are historical_estimate (WHO GHO estimates); hybrid-forecast rows are forecast_model (nMx, nqx, lx, ex) or forecast_derived (ndx, nLx, Tx reconstructed from the model's lx by the standard abridged life-table algorithm).
The recommended Lee–Carter file instead reports central values with 95% prediction intervals. All life-table identities were validated programmatically (0 ≤ nqx ≤ 1; monotone lx; ndx = lx(x) − lx(x+n); ex = Tx/lx); a validation report is included.
Links
Where it is published
- DOI doi.org/10.17632/y77grssd62.3 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Biostatistics · Demography · Earth & Environmental Science · Mortality · Social Science · Time-series analysis
- Inferred from text
- Tabular 65%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/y77grssd62.3 | 16 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:380205 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Time Series Analysis'] |
| concepts[field].anzsrc:field:440304 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Mortality'] |
| concepts[field].anzsrc:field:490502 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Biostatistics'] |
| concepts[field].anzsrc:group:4403 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Demography'] |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:tabular | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |