Nominal GDP in local currency (units of local currency; seasonally adjusted) - United Kingdom - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In the United Kingdom, seasonally-adjusted nominal GDP stood at 764,348,000,000 units of local currency in 2025-Q3, compared to 756,985,000,000 in 2025-Q2. This constitutes a gain of 0.97 percent.
Sample. The quarterly time series shown in the figure has 283 observations overall. The series covers the period extending from March 1955 to September 2025.
History. Check out a few simple statistics computed on the full sample: GDP hit a minimum of 4,666,000,000 units of local currency in March 1955; it recorded its maximum of 764,348,000,000 in September 2025; it had an average value of 218,971,855,124.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2025-03-31 | 748599000000.0 |
| 2025-06-30 | 756985000000.0 |
| 2025-09-30 | 764348000000.0 |
Suggestion. A plus of using FetchSeries is that we give you well-crafted metadata. Find it below to gain insights on the properties of the indicators that you analyze.
Not for investment purposes. Data disseminated on FetchSeries are not not supposed to be used for investment purposes or any other financial decision. Users should ask for expert advice and do their own independent due diligence before taking any financial risk.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | United Kingdom |
| 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.