Nominal GDP in local currency (units of local currency; seasonally adjusted) - Morocco - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Morocco, seasonally-adjusted nominal GDP was 443,761,708,229 units of local currency in 2025-Q4, versus 431,007,888,339 in 2025-Q3. This marks an increase of 2.96 percent.
Sample. There are 48 records in the quarterly series shown in the chart above. The series covers the span of time going from March 2014 to December 2025.
History. Have a look at some simple statistics computed on the whole sample: GDP hit a minimum of 245,477,203,600 units of local currency in March 2014; it reached its maximum of 443,761,708,229 in December 2025; it had an average value of 318,795,540,740.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2025-06-30 | 420815526201.142 |
| 2025-09-30 | 431007888338.686 |
| 2025-12-31 | 443761708229.497 |
Nugget of wisdom. A benefit of our data visualization and download service is that we provide rich metadata. Check it below to delve deeper into the characteristics of the indicators that you use in your research.
Not for investment purposes. Financial data published on this web site are not meant for investment purposes or any other financial decision. Users should seek professional advice and do independent analysis before making any financial commitments.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Morocco |
| 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.