Nominal GDP in local currency (units of local currency; seasonally unadjusted) - Italy - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Italy, seasonally-unadjusted nominal GDP was 562,282,900,000 units of local currency in 2025-Q3, versus 555,893,800,000 in 2025-Q2. This constitutes a rise of 1.15 percent.
Sample. In the quarterly time series presented in the plot, there are 123 data points in total. The time span covered by the series stretches from March 1995 to September 2025.
History. Take a look at some statistics computed on the full sample: GDP had an average value of 394,230,817,886 units of local currency; it recorded a minimum of 228,297,600,000 in March 1995; it achieved a maximum of 584,269,700,000 in December 2024.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2025-03-31 | 533352800000.0 |
| 2025-06-30 | 555893800000.0 |
| 2025-09-30 | 562282900000.0 |
Suggestion. To simplify research, we organize series into data sets and worksheets. If you navigate further down, you will discover how we arranged further information linked to the statistics published here.
Not for investment purposes. Content provided on this web site is not not supposed to be used for investment purposes or as a basis for financial-decision making. Users should consult expert advice and do independent analysis before pledging money to any investment.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Italy |
| 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.