Global Demographics & Ageing

The single biggest structural force on labour supply, growth and public finances - ageing - in one clean Parquet: old-age and young-age dependency ratios, the 65-and-over and under-15 population shares, the total dependency ratio, plus the two drivers of the transition itself - fertility rate and life expectancy - per country per year since 2000, ~200 countries. Ageing sets the ceiling on the workforce, drives pension and health spending, and separates the demographically young emerging world from the greying rich one. The cross-country demographics panel macro, pension, insurance and workforce-strategy analysts need; the demographic backbone of the Labour & Human Capital domain. Joins the labour, health and country-profile products on ISO-3 code. Worldwide - the whole demographic transition.

What's included

• 7 indicators × ~200 countries × 2000-present - old/young/total dependency, 65+ & youth shares, fertility, life expectancy
• Worldwide; ageing is the #1 structural constraint on labour supply and public finances
• Separates the demographically young emerging world from the greying OECD
• country (ISO3) × indicator × year; joins global-labour-market, global-health
• Source: World Bank Open Data (CC-BY-4.0) - fully redistributable

Schema

Sample & preview

Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: World Bank (redistributable open data; attribution passes through - see our Licence).

import pandas as pd
df = pd.read_parquet("global-demographics-ageing_sample.parquet")
df.info()   # typed columns, gap-aware, ready to join