Nominal GDP in local currency (units of local currency; seasonally adjusted) - Sweden - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Sweden, seasonally-adjusted nominal GDP was 1,727,068,000,000 units of local currency in 2026-Q2, compared to 1,699,945,000,000 in 2026-Q1. This represents a gain of 1.60 percent.
Sample. There are 134 data points in the quarterly series displayed in the figure above. The series covers the time period extending from March 1993 to June 2026.
History. Take a look at some summary statistics we calculated on the full sample: GDP reached a maximum of 1,727,068,000,000 units of local currency in June 2026; it recorded a minimum of 406,781,000,000 in March 1993; it had a mean value of 921,548,447,761.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2025-12-31 | 1696202000000.0 |
| 2026-03-31 | 1699945000000.0 |
| 2026-06-30 | 1727068000000.0 |
Hint. We group series into data sets and worksheets to simplify research. By moving down the page, you will discover how we structured further information related to the statistics found here.
Not for investment purposes. Content accessible on this web site is not not supposed to be used for investment purposes or any other financial decision. Users should consult professional advice and perform their own independent due diligence before taking any financial risk.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Sweden |
| Economic concept | Flow |
| Data type | Nominal aggregate |
| Seasonally adjusted | Yes |
| 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.