This thesis assesses the feasibility of developing a reliable real estate price index using unprecedented transaction-based data on Swiss investment real estate for the period between 1940 and 2017. Multiple different methodological approaches are employed and scrutinised to assess their suitability for the computation of hedonic property price indices. Despite the broad availability and the extensive research on real estate indices, most benchmarks lack transparency as they are deficient in a detailed definition and description of the underlying construction methodology. As such, acclaimed price indices may show significantly diverging price dynamics arising - inter alia - from varying methodical approaches. This thesis establishes an extensive number of property indices and subsequently compares results with the most widely-known indices in the Swiss real estate environment. A secondary objective of this thesis is the integration of macroeconomic data to observe possible co-movements in price dynamics and to assess their contribution to the established property price index. By means of a principal component analysis, I compute an index that correctly captures the relative contribution of twenty-two "stand-alone" indices. Yet demonstrating similar price dynamics, computed indices vary substantially in magnitude. The results confirm the initial notion that differences among property indices may in fact result from inconsistencies in the underlying methodological approaches. The final index is in line with other well recognized Swiss indices, displaying an annual mean growth rate of 2.47% and a standard deviation of 0.07, which is slightly below the average value of its peers over the observed timeframe. Further, I find certain lagged macroeconomic factors to be significantly associated with price trends in the Swiss property asset market.

The importance of house prices to households, real estate developers, banks and policy-makers cannot be overemphasised. House price changes affect consumer spending and business investment patterns, which in turn affect the wider macro economy and the entire business cycle. Measuring and understanding house prices is therefore essential to a functioning economy, but researchers continue to disagree on the best methodological approach for constructing real estate indices. This book argues the need for more accurate house price indices, outlines the various methods used to construct indices and discusses the existing house price indices around the globe. It shows how the raw data of property transactions can be prepared for the purpose of constructing indices, discusses various applications of property price indices and empirically demonstrates how the index numbers can be used to model the supply of new houses and to estimate the price elasticity of supply. Essential reading for economists, real estate professionals and researchers, and policy-makers.

This book contains a special issue of the Journal of Real Estate Finance and Economics, comprising thirteen articles on house price measurement. These articles address the various procedures used to compute cross-sectional or temporal house price indices. Specifically, these articles contain research that: (1) evaluates hedonic, repeat sales, or hybrid approaches to constructing house price indices; (2) evaluates alternative sources of data on house prices and corresponding housing characteristics; (3) identifies the most influential land, structural, neighborhood, and proximity determinants of house prices (and associated changes in house prices); (4) provides a methodology for identifying housing market segments; (5) incorporates spatial autocorrelation in house price indices; and (6) provides more accurate estimates of the variance in house prices.

This booklet discusses some major methodological issues relating to the construction of house price models on a macro level. There is no single method that always produces the optimal results; the choice of a particular approach, method, theory, model and technique is context-dependent. This is especially true in housing markets, where a multitude of different submarkets exist. The methodology chosen should be based on sound theory, from which the basic concepts of analysis can be derived. This booklet discusses the use of potential models, which can be constructed using a general field theory, and which act as a theoretical foundation for further analysis. If we use potential models for house price analysis we can discover additional features from the data set that other approaches would simply miss. This e-book presents a pragmatic overview of key methodological concerns with the emphasis on the use of potential models. Theoretical methodological questions are left unanswered, and are not even presented in this text, since they have little relevancy to real-world modelling questions.

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.

The importance of house prices to households, real estate developers, banks and policy-makers cannot be overemphasised. House price changes affect consumer spending and business investment patterns, which in turn affect the wider macro economy and the entire business cycle. Measuring and understanding house prices is therefore essential to a functioning economy, but researchers continue to disagree on the best methodological approach for constructing real estate indices. This book argues the need for more accurate house price indices, outlines the various methods used to construct indices and discusses the existing house price indices around the globe. It shows how the raw data of property transactions can be prepared for the purpose of constructing indices, discusses various applications of property price indices and empirically demonstrates how the index numbers can be used to model the supply of new houses and to estimate the price elasticity of supply. Essential reading for economists, real estate professionals and researchers, and policy-makers.