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# Spatial Analysis Methods for Changes in Home Values?

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11-18-2011 11:06 AM
New Contributor
I want to conduct a spatial analysis of home values over a period of five years. The research area for this analysis is a county with mostly suburban and some urban development. I have two data sets, a point data set with assessed values for all parcels in the county for every year from 1997-2002, and a polygon data set with median and mean sale prices for each neighborhood in the county from 1997-2002. My goal is to see how proximity to transit stations effects home values i.e., do home values increase at a greater rate in areas near transit stations than in other area. For the purposes of this analysis I am defining transit stations as heavy or light rail stations.

My question is what spatial analysis method(s) or tools within ArcGIS should I use to conduct this analysis? Any advice or insights would be greatly appreciated.

Thanks
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2 Replies
Esri Regular Contributor
Explore the tools in the Spatial Statistics tools.
Regular Contributor
There are a lot of things you can do and it depends on your expertise with statistics. You could start with moran I (simple in arcgis, GEODA is a free software that is a better way of calculating moran) to see if there is an overall trend of autocorrelation in house prices, ie high priced houses are near one another or not, or house prices are random.

What I think is better and getting closer to what you asked would be a regression type question. To do this I would calculate the distance of each house to a train station and test for a relationship. House Price ~ Distance to train. If there is a slope in the relationship you are golden. However, in doing this analysis you will need to consider the fact that the driving factor behind the price of a house is not the distance it lies from the train but other things such as age, size, condition, yard, view etc. These factors will act as confounds to your analysis, and I expect any relationship to be somewhat weak if you can not control for these factors. Again I would suggest you do regression type analysis is a stats package.

David