ESI Introduces New Way to Visualize the PHI

For this month’s update on the ESI Philadelphia Housing Index (PHI) we introduce our new interface, which allows users to more closely interact with our index and analyses. Now when you select discrete geographies and hover over a time series, the tool will show the name of the geography that you’ve selected as well the month and Index value for that month. We haven’t changed any of the analytical components since our last PHI remodel, so just like before, our Index is controlling for a number of variables, predicting the price for a house that has average Philadelphia traits and removing seasonal effects.

One goal of fine-tuning our visualization is to make the Neighborhood-scale Index more clear, especially once you get past the 10 to 15 neighborhoods with the highest PHIs. The changes and trends in neighborhoods like Grays Ferry, Hartranft and others, which cluster along the Y axis of the chart can be difficult to discern without a careful review.

Looking a little closer you can see that Grays Ferry, while about on level with the citywide PHI, has grown by 13.2 percent in the last 6 months. Hartranft’s Index increased by 25.4 percent.

With this new way of visualizing the PHI, we hope this in-depth look at all the geographic boundaries we’ve created for the PHI are more easy to access. We also would like to hear from you about what other layers we could add to the PHI? Construction permits? Median household income? You tell us!

 

Econsult Solutions offers the Philadelphia Housing Index (PHI), free of charge to the public.

Sales are arms-length transactions of single-family homes only. The price indexes are estimated by Econsult Solutions, Inc. using a quality controlled measure of average sale appreciation using hedonic regression analysis.

Gina Lavery is an Associate Director at Econsult Solutions. Gina focuses and leads projects on market research and analysis for the Greater Philadelphia area.

 

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Jing Liu is a Senior Research Analyst at Econsult Solutions. She specializes in spatial analysis, quantitative analysis, and data visualization. Prior to joining ESI in 2016, Jing received her Master’s in City Planning and Urban Spatial Analytics from the University of Pennsylvania.

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