Real GDP in local currency (units of local currency; seasonally unadjusted) - Iceland - IMF - Quarterly
This series is part of the dataset: Real GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Iceland, seasonally-unadjusted real GDP was 611,575,415,950 units of local currency in 2026-Q2, versus 627,384,825,472 in 2026-Q1. This constitutes a decrease of 2.52 percent.
Sample. There are 126 observations in the quarterly series presented in the figure above. The series covers the span of time going from March 1995 to June 2026.
History. Check out some summary statistics calculated on the full sample: GDP hit a minimum of 238,981,457,551 units of local currency in March 1995; it attained a maximum of 659,493,442,861 in September 2025; it was equal on average to 446,369,532,431.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2025-12-31 | 624043338304.99 |
| 2026-03-31 | 627384825472.29 |
| 2026-06-30 | 611575415950.42 |
Tip. Our metadata often include references to the sources of the data series we publish. You can use these references to search for additional information needed in your analyses.
Not for investment purposes. Content made available on FetchSeries is not suitable for investment purposes or as a basis for making financial decisions. Users should ask for professional advice and perform their own independent due diligence before pledging money to any investment.
Series Metadata
| Field | Value |
|---|---|
| Description | Real Gross Domestic Product (GDP) in domestic currency |
| Country | Iceland |
| Economic concept | Flow |
| Data type | Real aggregate |
| Seasonally adjusted | No |
| Deflation method | Constant prices |
| Rescaling | None |
| Measure type | Level |
| Frequency | Quarterly |
| Unit | Units of local currency |
| Source | International Monetary Fund |
| Source type | International organization |
| Data licence | Free reuse subject to conditions |
| Other information | Not available |
| FSR temporal aggregation code | SM03 |
Series in the same data set
Discover the other time series included in this data set.