The power of geospatial analysis lies in the new ways it provides to look at datasets and the relations among them. It allows you to explore more nuanced questions and discover correlations previously hidden. Used properly, geographic information system (GIS) tools can increase the saliency of a policy issue by expressing your argument visually and often much more effectively. Below is my recent experience in using GIS tools to broaden the audience for my research.
Property Assessment Disparities
Municipalities across the country are under fiscal duress due to cuts in state/federal aid, property tax levy limits, and rising employee fringe benefit costs. Often limited in their ability to generate new revenue streams, municipalities have become overly dependent on property taxes to “keep the lights on”.
Taxes are always a contentious issue and nobody wants to pay more than their fair share. To get a sense of how equitable the property tax burden was in Milwaukee, a city wrestling with all of the challenges noted above, I analyzed 33,000 property sales transactions over a 10-year period and compared them with their corresponding assessment values. By regressing the assessment value/sales price ratio on a host of predictors including building condition, lot size, geographic location, etc., I was able to get a sense of how equitable the city’s property taxation system is. While the findings presented an interesting disparity in who was paying their fair share, the results were neither accessible to the average citizen nor actionable for the policy maker. They required an understanding of my model specification and an ability to interpret coefficients expressed in terms of log odds.
Before I discuss how geospatial analysis broadened the audience for my research let us briefly digress into what property assessments are and why we should care about them.
What Are Property Assessments and Why Should We Care?
Property assessments are a key determinant in your property taxes; the higher the assessment, the higher the tax bill. While your assessment is a function of many factors, including lot size and property condition, the single largest determinant is market value. Your property assessment should reflect the price you could sell it for in an arm’s length market transaction.
The Insights of Geospatial Analysis
Utilizing GIS tools changed the nature of the questions I could explore within my dataset. I was now able to investigate additional questions related to geographic patterns in the results. To the right is a heat map analysis of property assessment disparities aggregated at the census block group level.
The geographic clustering is remarkable. It is clear that segments of the city are paying more in taxes than the value of their property suggests while others are paying less.
Curious about how this distribution compared with other salient attributes, I created additional heat maps of median income and % of black residents below.
Given the complexity and cost of fighting property tax assessments, the correlation with income is not surprising. The findings suggest that providing technical help for low-income homeowners interested in contesting their assessments may be one approach to combat the observed disparities.
As I have reached out to interested parties across the country regarding my findings, I cannot overstate the effectiveness of presenting the results in a geospatial context in generating interest and facilitating conversations.
As governments across the country release more datasets as part of the open data movement and IoT technologies provide a litany of new metrics, it will become increasingly important that we analyze and present data in ways that are actionable and understandable to policy makers and citizens.
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