South Korea’s Demographic Transformation and Macroeconomic Sustainability: A Stochastic OLG-DSGE Assessment

Abstract

The fertility rate in South Korea reached its lowest point at 0.72 during 2023 according to OECD statistics while the country faces an accelerating population aging trend that will exceed 40% elderly population by 2050. The research uses a stochastic overlapping-generations (OLG) model within a dynamic stochastic general equilibrium (DSGE) framework to generate new projections which replace previous three-variable models. The model uses KOSIS and OECD and IMF and NHIS data from 2023 to establish its baseline parameters. The model includes four key variables which are per-capita GDP and debt-to-GDP ratio and old-age dependency ratio and collapse probability that represents the first year when GDP per capita drops more than 15% below its previous ten-year average. The model uses Monte Carlo simulations to produce fan charts and sensitivity tests which examine the effects of productivity changes and health cost increases and migration patterns and fiscal rule modifications. The model incorporates specific policy measures for retirement age changes and childcare support and migration control and research and development growth which modify both the central forecast paths and extreme risk outcomes. The model uses three elderly population thresholds to determine fiscal implications: the 24% threshold indicates super-aged strain while 30% shows tax-base deterioration and 40% signals a care burden crisis with labor shortages. The simulations based on household survey data and case studies demonstrate that unaddressed population aging will cause collapse risks to increase dramatically after 2040 but integrated policy solutions will create positive GDP trends while maintaining debt stability and reducing uncertainty ranges.