Residential Property Price Index

Source details

Training Program: Residential Property Price Index
Session No.: OL 25.232
Deadline: Deadline passed
Location: Course conducted online
Date: July 17, 2025 - December 31, 2025 (42 weeks)
Delivery Method: Online Training
Primary Language: Spanish
Target Audience: Mid-level to senior officials and compilers responsible for, or planning to introduce or develop, a residential property price index (RPPI).

Participants are expected to have a degree in economics or statistics; or equivalent experience.

Presented by the Statistics Department.
Purpose: Identify the key uses of RPPIs; review data sources and methods for compiling RPPIs; and outline strategic issues for country-specific application.
Emphasis on evaluating alternative data sources for compiling RPPIs 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, and strategies for longer-run development of data sources are discussed.
Methodological component emphasizes 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 covered:
- stratification
- hedonic regression
Interactive workshops address stratification and hedonic regression topics.
The course highlights how data source and methodological issues are intertwined and 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.
Practical advice on RPPI compilation draws on the 2020 RPPI Practical Compilation Guide published by the IMF.

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.