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The purpose of this paper is to investigate the accuracy and volatility of different methods for estimating and updating hedonic valuation models.

The authors apply six estimation methods (linear least squares, robust regression, mixed-effects regression, random forests, gradient boosting and neural networks) and two updating methods (moving and extending windows). They use a large and rich data set consisting of over 123,000 single-family houses sold in Switzerland between 2005 and 2017.

The gradient boosting method yields the greatest accuracy, while the robust method provides the least volatile predictions. There is a clear trade-off across methods depending on whether the goal is to improve accuracy or avoid volatility. The choice between moving and extending windows has only a modest effect on the results.

This paper compares a range of linear and machine learning techniques in the context of moving or extending window scenarios that are used in practice but which have not been considered in prior research. The techniques include robust regression, which has not previously been used in this context. The data updating allows for analysis of the volatility in addition to the accuracy of predictions. The results should prove useful in improving hedonic models used by property tax assessors, mortgage underwriters, valuation firms and regulatory authorities.

The purpose of this paper is to demonstrate the application of robust techniques to the estimation of hedonic house price indexes.

The authors use simulation analysis to compare an index estimated using ordinary least squares (OLS) with several indexes estimated using robust techniques. The analysis uses sales transactions data from a US city. The authors then explore how robust methods can correct for omitted variables under some circumstances and how they affect the revision problem that occurs when longitudinal hedonic indexes are updated.

Robust methods can resolve missing variable problems in some circumstances and also can substantially reduce the revision problem in longitudinal hedonic indexes.

Robust techniques may be preferable to OLS when constructing longitudinal hedonic indexes.

This is the first paper to undertake a systematic analysis of the applicability of robust techniques in constructing hedonic house price indexes.

As financial markets move toward increased globalization, it becomes worth considering whether inherent differences in financial markets across different countries will diminish. For two countries more similar than different in terms of geography, location, government and culture, Canada and the USA remain strikingly different in terms of housing finance. Public policy objectives toward housing followed quite different paths over the past 70 years and fundamental differences in banking practices have led to considerably different outcomes in terms of mortgage finance instruments in the two countries. Examines some of the differences in policy and in competitive practices between Canada and the USA in an attempt to illuminate why differences in rates and terms across the two countries still exist. While a part of the difference remains due to legal constraints concerning the finance of the domestic housing sector, focuses on the economics and public policy choices that have led to the observed differences rather than on an analysis of the legal structure.

Urban green spaces are valuable to residents for a variety of reasons and some degree of management is needed to ensure at least their preservation, if not enhancement, in a rapidly urbanising society. Intensification of the urban environment brings pressure upon the undeveloped spaces within a city and an understanding of the needs of residents is needed if green spaces are to be managed in alignment with their wishes, so that changes will be accepted. However, gaining such an understanding of the complex relationships between people and their environment is difficult. Constructs may exist that researcher, respondent, or both have not yet articulated. This paper sets out to address this issue.

The repertory grid method is described as an approach that addresses this problem by researcher and respondent collectively, creating a survey instrument, which the respondent then completes.

The repertory grid technique was applied in Zurich and revealed a surprisingly dominant anthropocentric attitude towards urban green spaces.

The universal anthropocentric perspective allows the interpretation that residents see Zurich essentially as a place for people and furthermore see green spaces as places for themselves to pursue their own interests.

Application of this technique, in the context of an exploratory study, simultaneously provides direction for further research and demonstrates its utility as a tool for planners and managers of urban green spaces.

This study examines the issue of cross‐continental publishing in real estate research to understand the research interaction between the two major English‐speaking countries and to determine if a home bias exists. This study also determines the extent to which authors from other countries publish in US and UK journals, and provide a ranking of non‐US universities and authors. The survey of top US and UK real estate journals from 1993 through 1998 reveals that a home bias exists. The home bias concentration is higher in US journals than in UK journals, while UK journals exhibit more balanced origins, emanating not only from the USA/Canada, but also from Australia, New Zealand and Asia. In addition, the study reveals that the Universities of Reading, Ulster and Glasgow are well placed among European universities, while the National University of Singapore ranks well in Asia. Top US researchers tend to publish exclusively in US journals; likewise the same is observed for UK researchers. However, some notable exceptions are observed. Finally, a possible reason for the home bias could be the different research approaches undertaken by US and UK journals.

Tobler's law of geography states that things that are close to one another tend to be more alike than things that are far apart. In this regard, the spatial pattern of price distribution is defined by the arrangement of individual entities in space and the geographic relationships among them. The purpose of this paper is to provide emerging findings of research analysing the salient factors which impact on the sale price of residential properties using a spatial regression approach.

The research develops and formulates a geographically weighted regression (GWR) model to incorporate residential sales transactions within the Belfast Metropolitan Area over the course of 2010. Transaction data were sourced from the University of Ulster House Price Index survey (2010, Q1‐Q4). The GWR approach was then evaluated relative to a standard hedonic model to determine the spatial heterogeneity of residential property price within the Belfast Metropolitan Area.

This investigation finds that the GWR technique provides increased accuracy in predicting marginal price estimates, in comparison with traditional hedonic modelling, within the Belfast housing market.

This study is one of only a few investigations of spatial house price variation applying the GWR methodology within the confines of a UK housing market. In this respect it enhances applied based knowledge and understanding of geographically weighted regression.

The purpose of this paper is to examine the history of the Conferences on Historical Analysis & Research in Marketing (CHARM) from their inception in 1983 through 2007 focusing on the influence of Stanley C. Hollander, who co‐founded the CHARM conference and whose drive and determination fueled its growth for the first 20 years.

This study uses traditional historical narrative based on personal interviews, archival research, and content analysis of CHARM Proceedings.

The history of CHARM is described and Hollander's role in developing the conference is highlighted.

There is no written history of CHARM. This story is a major part of Hollander's legacy.