## Residential Property Price Index (RPPI) — Training Program

## Source details

**Canonical URL:** [Residential Property Price Index (RPPI) — Training Program](https://www.imf.org/en/capacity-development/training/icdtc/courses/rppi)

## Other formats

- [Markdown version](/en/capacity-development/training/icdtc/courses/rppi/index.md)
- [Structured JSON version](/en/capacity-development/training/icdtc/courses/rppi/index.json)
- [Bundle manifest](/en/capacity-development/training/icdtc/courses/rppi/bundle-manifest.json)

## Bibliographic details
- Published: July 29, 2025

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### Topic and scope
- Topic: Macroeconomic Statistics
- The course identifies the key uses of RPPIs; reviews data sources and methods for compiling RPPIs; and outlines strategic issues for country-specific application.
- Emphasis on evaluating alternative data sources in terms of:
  - coverage
  - timeliness
  - richness in terms of supporting a quality-mix methodology
  - suitability of a price measure
  - weighting
- Trade-offs involved in selecting data sources are considered, as are strategies for longer-run development of data sources.
- The course follows the principles of the 2013 Handbook on RPPIs published by Eurostat, International Labor Organization (ILO), IMF, Organization for Economic Co-operation and Development (OECD), United Nations Economic Commission for Europe (UNECE), and the World Bank.

### Target audience and qualifications
- Target audience:
  - Mid-level to senior officials and compilers responsible for, or planning to introduce or develop, a residential property price index (RPPI).
- Qualifications:
  - Participants are expected to have a degree in economics or statistics; or equivalent experience.

### Methodological focus
- Core methodological problem:
  - The quality-mix problem: a change in the mix of properties transacted each period can bias measures of change in average prices.
- Main mix-adjustment methods emphasized:
  - Stratification
  - Hedonic regression
- Interactivity:
  - Interactive workshops address stratification and hedonic regression topics.
- Integration of issues:
  - The course highlights how data source and methodological issues are intertwined.

### Learning outcomes (course objectives)
- Upon completion of this course, participants should be able to:
  - Explain the nature and uses of RPPIs.
  - Identify the strengths and weaknesses of possible data sources for RPPIs.
  - Select the most appropriate method for RPPI compilation based on the availability of data.
  - Apply different methods for compiling RPPIs.
  - Make recommendations, where necessary, for the further development of data sources.

---


## References

- [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)

_Source: https://www.imf.org/en/capacity-development/training/icdtc/courses/rppi_