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Handbook on Residential Property Price Indices

image of Handbook on Residential Property Price Indices

For most citizens, buying a residential property (dwelling) is the most important transaction during their lifetime. Residential properties represent the most significant component of households’ expenses and, at the same time, their most valuable assets. The Residential Property Prices Indices (RPPIs) are index numbers measuring the rate at which the prices of residential properties are changing over time. RPPIs are key statistics not only for citizens and households across the world, but also for economic and monetary policy makers. Among their professional uses, they serve, for example, to monitor macroeconomic imbalances and risk exposure of the financial sector.

This Handbook provides, for the first time, comprehensive guidelines for the compilation of Residential Property Price Indexes and explains in depth the methods and best practices used to calculate an RPPI. It also examines the underlying economic and statistical concepts and defines the principles guiding the methodological and practical choices for the compilation of the indices. The Handbook primarily addresses official statisticians in charge of producing residential property price indices; at the same time, it addresses the overall requirement on RPPIs by providing a harmonised methodological and practical framework to all parties interested in the compilation of such indices.

The RPPIs Handbook has been written by leading academics in index number theory and by recognised experts in RPPIs compilation. Its development has been co-ordinated by Eurostat, the statistical office of the European Union, with the collaboration of the International Labour Organization (ILO), International Monetary Fund (IMF), Organisation for Economic Co-operation and Development (OECD), United Nations Economic Commission for Europe (UNECE) and the World Bank.

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Hedonic Regression Methods

The hedonic regression method recognizes that heterogeneous goods can be described by their attributes or characteristics. That is, a good is essentially a bundle of (performance) characteristics. (1) In the housing context, this bundle may contain attributes of both the structure and the location of the properties. There is no market for characteristics, since they cannot be sold separately, so the prices of the characteristics are not independently observed. The demand and supply for the properties implicitly determine the characteristics’ marginal contributions to the prices of the properties. Regression techniques can be used to estimate those marginal contributions or shadow prices. One purpose of the hedonic method might be to obtain estimates of the willingness to pay for, or marginal cost of producing, the different characteristics. Here we focus on the second main purpose, the construction of quality-adjusted price indices.

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