Real GDP in local currency (units of local currency; seasonally unadjusted) - Qatar - IMF - Quarterly
This series is part of the dataset: Real GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In Qatar, seasonally-unadjusted real GDP was 200,749,000,000 units of local currency in 2016-Q4, compared to 205,047,000,000 in 2016-Q3. This constitutes a reduction of 2.10 percent.
Sample. In this quarterly series, there are a total of 16 data points. The period covered by the series extends from March 2013 to December 2016.
History. Have a look at some simple statistics calculated on the full sample: GDP reached a maximum of 205,047,000,000 units of local currency in September 2016; it hit a minimum of 179,474,744,947 in December 2013; it averaged 190,663,094,046.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2016-06-30 | 197468000000.0 |
| 2016-09-30 | 205047000000.0 |
| 2016-12-31 | 200749000000.0 |
Heads-up. We categorize time series into data sets and worksheets to simplify complex analyses. By moving down the page, you will find how we structured further material linked to the statistics provided here.
Not for investment purposes. Information distributed on FetchSeries is not meant for investment purposes or other financial decisions. Users should ask for expert advice and do independent analysis before making any financial commitments.
Series Metadata
| Field | Value |
|---|---|
| Description | Real Gross Domestic Product (GDP) in domestic currency |
| Country | Qatar |
| Economic concept | Flow |
| Data type | Real aggregate |
| Seasonally adjusted | No |
| Deflation method | Constant 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.