Nominal GDP in local currency (units of local currency; seasonally unadjusted) - Greece - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Greece, seasonally-unadjusted nominal GDP was 62,086,164,179 units of local currency in 2025-Q2, versus 55,066,513,752 in the previous quarter. This constitutes an increase of 12.75 percent.
Sample. The quarterly series presented in the graph has 122 observations overall. The span of time covered by the series goes from March 1995 to June 2025.
History. Here's a glimpse of a few statistics computed on the whole sample: GDP hit a peak of 64,953,912,000 units of local currency in September 2024; it registered a minimum of 21,025,888,000 in March 1995; it averaged 44,838,731,688.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2024-12-31 | 61647492000.0 |
| 2025-03-31 | 55066513752.0 |
| 2025-06-30 | 62086164179.0 |
Tip. We organize time series into data sets and worksheets to facilitate exploration. By scrolling down, you will discover how we arranged further information linked to the statistics provided here.
Not for investment purposes. Data and analyses collected and published on this web site are not not supposed to be used for investment purposes or other financial decisions. Users should seek professional advice and do independent analysis before taking any financial risk.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Greece |
| 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.