Nominal GDP in local currency (units of local currency; seasonally unadjusted) - India - IMF - Quarterly
This series is part of the dataset: Nominal GDP by country (IMF)
Download Full Dataset (.xlsx)Latest updates. In India, seasonally-unadjusted nominal GDP was 88,268,710,000,000 units of local currency in 2026-Q2, compared to 94,670,470,000,000 in the previous quarter. This constitutes a reduction of 6.76 percent.
Sample. In this quarterly time series, there are 89 observations in total. The span of time covered by the series is from June 2004 to June 2026.
History. Check out some summary statistics computed on the full sample: GDP hit a minimum of 6,953,205,100,000 units of local currency in June 2004; it reached a maximum of 94,670,470,000,000 in March 2026; it was equal on average to 36,989,037,161,798.
Latest values
| Date | Value - Units of local currency |
|---|---|
| 2025-12-31 | 90833930000000.0 |
| 2026-03-31 | 94670470000000.0 |
| 2026-06-30 | 88268710000000.0 |
Tip. One of the pluses of our web site is that we publish complete metadata. Find it below to learn more about the characteristics of the series that you use in your work.
Not for investment purposes. Time series and other data accessible on this web site are not intended for investment purposes or as a basis for financial-decision making. Users should seek professional advice and do their own independent due diligence before taking any financial risk.
Series Metadata
| Field | Value |
|---|---|
| Description | Gross Domestic Product (GDP) in domestic currency |
| Country | India |
| 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.