Nominal GDP in local currency (units of local currency; seasonally unadjusted) - Ukraine - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Ukraine, seasonally-unadjusted nominal GDP stood at 2,021,451,000,000 units of local currency in 2025-Q2, compared to 1,923,124,000,000 in the previous quarter. This represents a gain of 5.11 percent.
Sample. There are 102 records in the quarterly series presented in the figure above. The time range covered by the series stretches from March 2000 to June 2025.
History. Here's a snapshot of a few statistics computed on the whole sample: GDP was equal on average to 584,825,539,216 units of local currency; it recorded a maximum of 2,194,371,000,000 in December 2024; it hit a minimum of 32,309,000,000 in March 2000.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2024-12-31 | 2194371000000.0 |
| 2025-03-31 | 1923124000000.0 |
| 2025-06-30 | 2021451000000.0 |
Suggestion. A benefit of using FetchSeries is that we publish rich metadata. Find it below to better understand the attributes of the indicators that you are exploring.
Not for investment purposes. Financial data made available on FetchSeries are not intended for investment purposes or other financial decisions. Users should obtain expert advice and perform independent analysis before making any financial commitments.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Ukraine |
| 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.