## Quarterly Gross Domestic Product and Seasonal Adjustment

## Source details

**Canonical URL:** [Quarterly Gross Domestic Product and Seasonal Adjustment](https://www.imf.org/en/capacity-development/training/icdtc/schedule/sa/2023/gdpsa23-43)

## Other formats

- [Markdown version](/en/capacity-development/training/icdtc/schedule/sa/2023/gdpsa23-43/index.md)
- [Structured JSON version](/en/capacity-development/training/icdtc/schedule/sa/2023/gdpsa23-43/index.json)
- [Bundle manifest](/en/capacity-development/training/icdtc/schedule/sa/2023/gdpsa23-43/bundle-manifest.json)

## Bibliographic details
- Session: SA 23.43
- Location: New Delhi, India
- Dates: December 11-15, 2023 (1 week)
- Delivery method: In-person Training
- Primary language: English
- Status: Deadline passed

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### Training program and target audience
- Training Program presented by the IMF's Statistics Department.
- Target Audience: Officials responsible for compiling and using intensely national accounts statistics (NAS).
- Qualifications: Participants should have a degree in economics, statistics, or the equivalent.
- Deadline passed.

### Course description
- The course aims at providing a thorough understanding of concepts, sources of data, and compilation techniques for producing quarterly national accounts (QNA) statistics.
- Introduces benchmarking, seasonal adjustment techniques, as well as volume estimates; and explains the application of these techniques to time series data.
- Discusses how to identify and assess available data sources, use real-time series databases to assess the quality, and implement a suitable revisions policy for compiling QNA.

### Course objectives
Upon completion of the course, participants should be able to:
- Recognize the role, scope, uses, and compilation frameworks for QNA
- Review available data sources for compiling QNA.
- Explain the use of volume measures and the basic relation between value, quantity, and prices.
- Apply basic techniques for compiling benchmarked series and filling data gaps.
- Apply basic seasonal adjustment techniques to time series, based on good seasonal adjustment practices.
- Describe a balanced revisions policy taking into consideration how a related real-time database can be used to assess the reliability of the QNA and HFIEA estimates.

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## References

- [In-person Training](https://www.imf.org/en/capacity-development/training/icdtc/delivery-methods)
- [Sovereign Risk and Debt Sustainability Framework for Market Access Countries (SRDSF-MAC)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/st/2026/srdsf-macst26-22)
- [IMF Data Standards Initiatives](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ol/2026/dsixol26-241)
- [Cash and Debt Management](https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2026/dcmat26-31)
- [Taxation and Domestic Revenue Mobilization](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/tdrmce26-34)
- [Central Bank Balance Sheet and Policy Solvency (CBBST)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/sa/2026/cbbstsa26-35)

_Source: https://www.imf.org/en/capacity-development/training/icdtc/schedule/sa/2023/gdpsa23-43_