Nominal GDP in local currency (units of local currency; seasonally unadjusted) - Canada - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Canada, seasonally-unadjusted nominal GDP stood at 780,166,000,000 units of local currency in 2025-Q2, compared to 758,948,000,000 in 2025-Q1. This represents an increase of 2.80 percent.
Sample. There are 258 records in the quarterly series displayed in the chart above. The series covers the span of time stretching from March 1961 to June 2025.
History. Have a look at some summary statistics computed on the whole sample: GDP reached a minimum of 9,514,000,000 units of local currency in March 1961; it reached its maximum of 800,823,000,000 in September 2024; it had a mean of 248,750,193,798.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2024-12-31 | 798836000000.0 |
| 2025-03-31 | 758948000000.0 |
| 2025-06-30 | 780166000000.0 |
Hint. Our metadata often include links to the sources of the data we provide. You can use these links to search for additional information needed in your analyses.
Not for investment purposes. Any data disseminated on FetchSeries are not not supposed to be used for investment purposes or as a basis for financial-decision making. Users should obtain expert advice and perform their own independent due diligence before pledging money to any investment.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | Canada |
| 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.