## Quarterly National Accounts/High Frequency Indicators of Economic Activity

## Source details

**Canonical URL:** [Quarterly National Accounts/High Frequency Indicators of Economic Activity](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ol/2024/qnaxol24-101)

## Other formats

- [Markdown version](/en/capacity-development/training/icdtc/schedule/ol/2024/qnaxol24-101/index.md)
- [Structured JSON version](/en/capacity-development/training/icdtc/schedule/ol/2024/qnaxol24-101/index.json)
- [Bundle manifest](/en/capacity-development/training/icdtc/schedule/ol/2024/qnaxol24-101/bundle-manifest.json)

## Bibliographic details
- Session: OL 24.101
- Location: Course conducted online
- Dates: March 28, 2024 - May 16, 2024 (10 weeks)
- Delivery method: Online Training
- Primary language: French
- Status: Deadline passed

---

### Training program and delivery
- Session No.: OL 24.101
- Location: Course conducted online
- Date: March 28, 2024 - May 16, 2024 (10 weeks)
- Delivery Method: Online Training
- Primary Language: French
- Status: Deadline passed
- Presented by: Statistics Department

### Target audience and qualifications
- Target audience:
  - Officials worldwide who are responsible for compiling quarterly national accounts (QNA) and/or high frequency indicators of economic activity (HFIEA).
- Qualifications:
  - Expected to have a degree in economics or statistics; or equivalent experience.
  - Access to a computer with a reliable Internet connection and a Google Chrome web browser are essential.

### Course description — scope and techniques
- Purpose:
  - Prepares participants to compile QNA and/or HFIEA by providing a thorough understanding of concepts, source data, and compilation techniques.
- Coverage:
  - Theoretical and practical compilation issues.
  - Benchmarking.
  - Seasonal adjustment techniques.
  - Volume estimates and their application to time series data.
- Data and assessment:
  - Identifying and assessing available data sources for compiling QNA and HFIEAs.
  - Using related real-time series databases to assess the quality of QNA and HFIEAs.
  - Implementing a suitable revisions policy.

### Course objectives and learning outcomes
Upon completion of the course, participants should be able to:
- Recognize the role, scope, and uses of QNA and HFIEAs.
- Describe the compilation framework for the QNA and the different compilation methods for HFIEAs (including composite leading indicators).
- Review available data sources for compiling QNA by the income, expenditure and production approaches, and HFIEAs.
- Explain the use of volume measures and the basic relation between value, quantity, and price—expanding on how to detect and address issues such as the need for updated weights; and recognizing the loss of additivity for chain-linked volume estimates.
- Compile benchmarked series using the recommended techniques.
- Apply basic techniques for filling data gaps.
- Identify good seasonal adjustment practices and apply basic seasonal adjustment techniques to time series.
- Formulate a balanced revisions policy taking account of how related real-time database can be used to assess the reliability of the QNA/HFIEA estimates.

---


## References

- [Online Training](https://www.imf.org/en/capacity-development/training/icdtc/delivery-methods)
- [Core Elements of Banking Supervision (CBS)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2027/cbsat27-10)
- [Advanced Government Finance Statistics (GFS-A)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/gfs-ace26-45)
- [Fiscal Sustainability (FS)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/fsce26-38)
- [Safeguards Assessments of Central Banks (SAC)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/at/2026/sacat26-30)
- [Macroeconomic Management in Resource Rich Countries (MRC)](https://www.imf.org/en/capacity-development/training/icdtc/schedule/ce/2026/mrcce26-44)

_Source: https://www.imf.org/en/capacity-development/training/icdtc/schedule/ol/2024/qnaxol24-101_