An analysis of how geographicalfactors affect real estate prices

In the real estate business it is common to assume that the value and potential of a property isfundamentally determined by its location. Certain sites are attractive because they may have abeautiful view, shore and forests in the vicinity, good rail and road connections without noiseand all kind of public and private services. Corporate Property Evaluation has generallyfocused on financial methods that analyse how site-specific variables will influence potentialcosts and revenues from the site; unfortunately these methods sometimes do not take inaccount all the possible considerations for the site. This project studies the importance ofspatial factors in real estate appraisal and evaluates which of them affect the value of theproperties. The result could be useful to evaluate, for example, for geographical expansionstrategies. The study is carried out using Geographical Information Systems, which arecomputer systems capable of storing, displaying and analysing geographical information. Thisstudy is performed for the Stockholm’s municipality located in Sweden.In a Multi Criteria Evaluation the attempt is to combine a set of factors and criteria to comeup with a basis for a decision according to a particular objective. In this project the objectiveis to find out which factors cause a higher price in properties. We know which properties haveelevated price but we don’t know the factors that affect it. For this reason, the thought is toperform a MCE analysis approach a large number of times with different combinations ofdata, criteria and weights in order to search for a combination that gives a result that fits theknown prices. This method can be seen as a Data Mining approach. Data Mining is atechnique for distilling data and to find useful information.The results are based on the output obtained by the Data Mining technique and are displayedboth visually and in an Excel table. By visualising the results in maps it has been possible tocompare them with original data, finding out that factors like the proximity to water and thenumber of foreign people living in an area affect the value of the land. Several factors havebeen included in the analysis, being the most important the quality of the environment, thesocial standing of the population and the public transportation facilities. Although the resultsare quite reasonable, this analysis could be more accurate by testing more combinations ofdata and weights