Nominal GDP in local currency (units of local currency; seasonally unadjusted) - Iceland - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Iceland, seasonally-unadjusted nominal GDP was 1,216,865,442,764 units of local currency in 2025-Q2, versus 1,166,337,474,455 in 2025-Q1. This marks a rise of 4.33 percent.
Sample. In the quarterly time series shown in the chart, there are 122 observations. The time period covered by the series goes from March 1995 to June 2025.
History. Check out some simple statistics we computed on the full sample: GDP reached a maximum of 1,216,865,442,764 units of local currency in June 2025; it registered a minimum of 110,479,329,046 in March 1995; it had an average value of 480,285,665,680.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2024-12-31 | 1169083305322.0 |
| 2025-03-31 | 1166337474455.0 |
| 2025-06-30 | 1216865442764.0 |
Hint. One of the pluses of using our web site is that we publish accurate metadata. Check it below to better understand the properties of the time series that you use in your work.
Not for investment purposes. Financial data accessible on FetchSeries are not suitable for investment purposes or as a basis for making financial decisions. Users should seek expert advice and do their own independent due diligence before making any financial commitments.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Iceland |
| Economic concept | Flow |
| Data type | Nominal aggregate |
| Seasonally adjusted | No |
| Deflation method | Current 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.