Regional House Price Index Construction - The Case Of Sweden

• The academic literature on the construction of regional house price indexes usually uses geographic areas whose boundaries are administratively drawn. However such administrative regions might not be optimal for the construction of regional price indexes. When producing housing price indexes, we often encounter problems with insufficient number of observations. One way to remedy this problem is to estimate a quarterly index instead of a monthly index. Another possible way to mitigate the thin markets problem is to construct indexes for geographically aggregated regions. However, the literature that discusses methods of dealing with the problem of thin markets and especially geographical aggregation is very rare. The goal of this paper is to construct a housing price index for a major part of Sweden, and to construct price index series for a number of regions. The number of regions, and how their boundaries should be created in order to construct reliable regional price indexes, is however an open question. We apply traditional hedonic methodology in order to estimate house price indexes for both predefined regions whose boundaries are based on a division of labor markets in Sweden, as well as a division of regions based on statistical cluster analysis. The results from this study suggest that regions should be clustered together based on regional price levels and/or price development as clustering variables. If only geographical proximity is used as clustering variable, our computations show that there is a high risk that we end up with some clusters having large standard errors, which in turn might result in inaccurate indexes.

Ämnesord

SAMHÄLLSVETENSKAP  -- Ekonomi och näringsliv (hsv//swe)

SOCIAL SCIENCES  -- Economics and Business (hsv//eng)

Nyckelord

Regional house prices

Hedonic price index

Cluster analysis

Aggregation

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