Background
The National Social Security Fund (NSSF) convened a technical consultation in Phnom Penh to incorporate long‑range demographic data into its financial and benefit planning functions. The 2024–2100 population projection covers a 75‑year horizon for Cambodia and is intended to support long‑term planning for the national social security system.
Participants included representatives from the Ministry of Labour and Vocational Training, the National Institute of Statistics, the Secretariat of the Minimum Wage Council, the National Social Protection Council Secretariat, and technical staff from the International Labour Organization; approximately 70 participants attended the workshop. The consultation used the ILO Pop projection tool to generate age‑ and sex‑specific scenarios that NSSF stated will inform analysis of benefit package design and financial risk management.
Policy Context
Demographic projections provide inputs for actuarial valuations that estimate future contribution revenues, benefit liabilities, and required reserve levels under contribution‑based social security systems. Projection scenarios influence the modelling of dependency ratios, expected pensioner counts, and long‑run contribution rates that are central to assessing the fiscal sustainability of social insurance programs.
Institutional Role
The workshop was opened on 30 June 2026 by Government Delegate Meng Hong on behalf of NSSF, and it was organized with ILO technical support using the ILO Pop tool. NSSF coordinated the exercise with national statistical authorities and social protection and labour policy secretariats to produce a common demographic baseline for subsequent actuarial and policy work.
Operational Implications
NSSF indicated that outputs from the projection exercise will be used as primary inputs for internal analyses of benefit packages, contribution scenarios, and financial risk management. These projection datasets are intended to improve the evidentiary basis for multi‑decade planning and to harmonize underlying demographic assumptions across agencies involved in social protection policy.
