Statistical Office of the European Communities, International Labour Office, International Monetary Fund, Organization for Economic Co-operation and Development, United Nations, and World Bank
2.1 There are many areas of society where individuals or organisations use residential propertypriceindices (RPPIs) directly or indirectly either to influence practical decision making or to inform the formulation and conduct of economic policy. Different uses can have a significant impact on the preferred coverage of the index and also on the appropriate methodology applied for its construction.
2.2 From an individual household’s perspective, real estate often represents the single largest investment in their portfolio. It also accounts
This Technical Assistance (TA) report on Georgia is on Residential Property Price Indices (RPPI) Mission. The contents of this report constitute technical advice provided by the IMF staff to the authorities of Georgia in response to their request for TA. The Second Phase of the G-20 Data Gaps Initiative and guidance on Financial Soundness Indicators identify RPPI as a critical ingredient of financial stability policy analysis and macroprudential measures. National Statistics Office of Georgia (Geostat) is aiming at compiling a quarterly RPPI covering new flats and new detached houses for the capital city, Tbilisi. The mission implemented successfully the programs developed in R based on the IMF’s draft for the RPPI Practical Compilation Guide with the available data. The mission provided some guidance on the use of scanner data (SD) on the consumer price index (CPI) compilation. As per request of the Geostat Director, the mission also addressed the use of SD. The introduction of SD should be made on a stepwise approach to avoid huge impacts on the CPI and to make it more manageable, reliable, and safe.
The contents of this report constitute technical advice provided by the staff of the IMF to the authorities of Bangladesh in response to their request for technical assistance. The purpose of the mission was to assist the Bangladesh Bank (BB) in progressing on the compilation of a residential property price index. BB has plans to set up a new data collection system to improve the current existing data starting from July 2020. The new data collection will expand the geographic coverage and the type of dwellings and mostly will increase the current sample resulting in more accurate results. The mission recommended the use of R instead of other software since it allows to perform all the necessary calculations in one script and single software. The mission provided training particularly on the hedonic methods, chain linking and rebasing. The hedonic methods are the most recommended to address the quality changes on the mix of dwellings transacted when following the price of real estate.