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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Housing supply and the level of house prices : An outlook on the greater Stockholm region real estate market

Teklay, Filmon January 2012 (has links)
The Swedish housing market has experienced an almost constant increase of housing prices since the economic crisis in the early 90‟s. Many studies have been conducted on the field which have tried to find an explanation to the constant trend and if there is an end in sight. However, this study aims at focusing on the supply/demand relationship in determining the housing prices in the County of Stockholm. The method that was used was both a time series regression and a cross sectional regression, by applying data on the amount of housing that has been constructed per thousand inhabitants in each municipality, the development of housing prices in each municipality and the average annual development of wages. Since there are 26 municipalities in Stockholm County, it would be too time consuming to go through each and every single one of the municipalities, instead the focus was on the 5 municipalities with the highest and lowest construction rate per thousand inhabitants. Thus, we can observe if there is any general difference depending on the construction rate in determining the house price development. The results on the time series regression implies that most of the municipalities housing prices are primarily dependent on the housing construction rate, when construction goes down the prices goes up and vice versa. However, the municipality of Vallentuna had suspicious signs which imply that other factors (then the variables used) are driving the prices up. In the cross sectional regression where both the 5 highest and lowest municipalities with construction rate were regressed together, we can see similar signs as in Vallentuna. It would therefore be interesting to find out what the underlying factors that are driving the prices up in the case of Vallentuna and in the cross sectional analysis.

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