Real GDP in local currency (units of local currency; seasonally adjusted) - Norway - IMF - Quarterly
This series is part of the dataset: Real GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Norway, seasonally-adjusted real GDP was 811,900,827,305 units of local currency in 2025-Q2, compared to 805,177,548,428 in 2025-Q1. This represents a rise of 0.84 percent.
Sample. The quarterly time series presented in the plot has a total of 190 observations. The series covers the time range stretching from March 1978 to June 2025.
History. Here's a glimpse of some statistics computed on the whole sample: GDP hit a trough of 272,245,642,799 units of local currency in March 1978; it achieved a maximum of 822,920,458,896 in June 2024; it was equal on average to 548,565,394,648.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2024-12-31 | 804739314903.937 |
| 2025-03-31 | 805177548428.08 |
| 2025-06-30 | 811900827304.81 |
Hint. For easier exploration, we categorize indicators into worksheets and datasets. When you navigate further down, you will find how we structured further material linked to the statistics provided here.
Not for investment purposes. Financial data published on this web site are not suitable for investment purposes or as a basis for making financial decisions. Users should seek expert advice and do independent analysis before pledging money to any investment.
Series Metadata
| Field | Value |
|---|---|
| Description | Real Gross Domestic Product (GDP) in domestic currency |
| Country | Norway |
| Economic concept | Flow |
| Data type | Real aggregate |
| Seasonally adjusted | Yes |
| 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.