Nominal GDP in local currency (units of local currency; seasonally unadjusted) - Malta - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Malta, seasonally-unadjusted nominal GDP was 6,183,497,933 units of local currency in 2026-Q1, compared to 6,299,131,204 in 2025-Q4. This represents a reduction of 1.84 percent.
Sample. There are 125 observations in the quarterly series displayed in the figure above. The time span covered by the series extends from March 1995 to March 2026.
History. Here are some statistics we computed on the full sample: GDP achieved a maximum of 6,380,106,165 units of local currency in September 2025; it recorded a bottom of 706,641,996 in March 1995; it had a mean value of 2,341,557,043.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2025-09-30 | 6380106165.0 |
| 2025-12-31 | 6299131204.0 |
| 2026-03-31 | 6183497933.0 |
Heads-up. For easier exploration, we organize series into data sets and worksheets. By scrolling down, you will find how we structured further information linked to the statistics published here.
Not for investment purposes. Data and any other information distributed on FetchSeries are not meant for investment purposes or as a basis for financial-decision making. Users should seek expert advice and do their own independent due diligence before pledging money to any investment.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Malta |
| 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.