Average yearly pay, adjusted for local prices in South Korea: our forecast to 2035
Satoria projects average yearly pay, adjusted for local prices in South Korea at about 67,894 USD in 2035, from 61,259 USD recorded in 2025.
How far the evidence reaches
Beyond tested horizon. Tests cover up to 5 years ahead (through 2030 from this reference), across 27 country series. Longer horizons extend beyond those tests. Colours show evidence, not certainty.
The full name of this series is Average yearly pay, adjusted for local prices (average annual wages, constant prices, USD at purchasing power parity).
The path
- 2026: Satoria forecast 62,527 USD (80% range 60,775 to 63,494)
- 2027: Satoria forecast 63,363 USD (80% range 60,871 to 64,951)
- 2031: Satoria forecast 66,172 USD (80% range 60,882 to 70,715)
- 2035: Satoria forecast 67,894 USD (80% range 59,568 to 74,538)
Where it starts
The latest source value is 61,259 USD recorded in 2025, published by OECD Data Explorer. Everything after that year is Satoria's forecast, with the range printed next to it.
The same measure elsewhere
- Average yearly pay, adjusted for local prices in United States
- Average yearly pay, adjusted for local prices in Germany
- Average yearly pay, adjusted for local prices in India
Every forecast we have for South Korea · Average yearly pay, adjusted for local prices in every country
This forecast as data: https://satoria-pipeline-production.up.railway.app/api/forecast/oecd.avg_annual_wages?country=KOR
Conditions and limits
What this number can establish
The published record supports a statistical projection and a model range. It does not establish why a future event will happen. Connections between measurements are predictive associations, not proof of causation. Source measurements, estimates and Satoria forecasts must be read separately.
The model range is not a guarantee. Historical test coverage is not the probability of the central forecast happening.
All stories · Countries · The map of the future · Why trust Satoria · Engine · About · Satoria vs the IMF · How accurate we are · Method · Indicators · For AI agents