Technical Analysis Using Multiple Time Frame By Br Sachsen Fernsehen, L

[Wesley Dupler]

As all observations are geo-coded, we merge information on spatial amenities using GIS to include price-defining attributes that are not given in the contracts to capture various influences of location. We add information on street and rail noiseFootnote 13 as traffic noise is generally thought of as a crucial price defining factor.Footnote 14 Furthermore, information on public transport accessibility is included by using the distance to light rail stations.Footnote 15 A negative correlation between noise exposure and public transport accessibility is obvious but within this analysis unproblematic. The same is true for the distance to the motorway. Checking for multicollinearity using variance inflation factors (VIF), the variables of interest are unaffected by any multicollinearity. Though the proximity to water is correlated with the feature of interest which is the location within the flood risk hazard zone, we include distance to the main river Elbe. The importance to include the proximity or distance to the river is pointed out in Bin et al (2008).Footnote 16 Further, time invariant location related aspects are controlled for by the inclusion of the ZIP code. Those spatial fixed effects also capture the distance to the city center. Last but not least we include information on the altitude of the lot in relation to the river Elbe.Footnote 17 This information helps us to identify comparable lots with regard to flood risk.

Technical Analysis Using Multiple Time Frame By Br sachsen fernsehen, l

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