Geographic Information Systems Can Help Measure Impact of Economic Development Incentives

How can the use of geographic information systems (GIS) help state policymakers evaluate the effectiveness of economic development incentives? The systems, known for their ability to store and represent locational information visually on maps, allow for powerful types of analysis that can help show where incentives are having an impact.

At a webinar in March 2024 presented by The Pew Charitable Trusts, auditors from the Kansas Legislative Division of Post Audit (LPA) demonstrated some of the expanded GIS analytical uses relevant to economic development programs.  

Mohri Exline and Matthew Fahrenbruch, auditors with the nonpartisan team, shared examples of how their office uses GIS to aid in evaluation and how the systems can be used to improve existing datasets. They also highlighted quality data resources. In addition, Exline and Fahrenbach discussed common GIS challenges and offered advice to evaluation offices just getting started with GIS analysis.

The presenters described multiple GIS analysis methods that they have used in economic development incentive evaluation and in other program audits.

Cluster analysis

For its evaluation of the state’s Rural Opportunity Zones program, LPA used a methodology called cluster analysis to investigate whether the initiative was helping to slow or reverse rural depopulation trends. The analysis enabled the auditors to visualize the spatial dispersion of beneficiaries and identify the parts of the state where the program had the largest effect on population changes. LPA concluded that the program had the greatest impact in the northwestern part of the state, a finding that had not been apparent from data tables.

Network analysis 

The auditors said they also have used GIS for network analyses, which are used to examine relationships between data points. In the Rural Opportunity Zones evaluation, they used it to identify and measure migration flows as residents relocated between counties. In addition, LPA used network analysis in an evaluation of the STAR Bonds Financing Program, a state initiative intended in part to encourage construction of attractions that bring visitors—and their spending—from out of state. The analysis helped to identify where visitors were coming from and whether this program goal was being met for each participating attraction.

Buffer analysis

In the same STAR Bonds evaluation, LPA researchers also used what is known as buffer analysis. This method allowed auditors to gauge whether the program was meeting another one of its key goals: drawing tourists and their spending from places more than 100 miles from the attractions that had taken advantage of the incentives. Using the buffer analysis technique and GPS location data, LPA could count the visitors from various origin points to determine which attractions met this goal.

Other techniques and uses

The LPA staffers also discussed their use of other GIS techniques, such as comparative, time and space, optimal area, and cannibalization analyses. In addition, they spoke about how GIS can be used to ensure that data is free of errors before it is analyzed.

As technology advances, evaluators benefit from tools that help them do their work in new and interesting ways. Pew has worked with state and city tax incentive evaluators for more than a decade. A library of resources on evaluation processes and approaches is available in our toolkit.

Logan Timmerhoff is a principal associate with Pew’s state fiscal health project.