Over the last year, our Community Data Analytics (CDA) team has been busy presenting this groundbreaking methodology to assess development-related impacts to a larger audience and demonstrating how our data products can help make better planning decisions. As part of this effort, the team recently presented at the American Planning Association NJ Chapter Annual Conference. They were joined by our esteemed senior advisor and peer fiscal impact expert Steven Nelson, who authored this post.
New Tools and New Ways to Use Them
Fiscal impact analysis (FIA) is an essential tool for estimating and communicating how development affects local government budgets. By using FIA, municipalities and school districts can better understand how land development and future land use is likely to impact both revenues and costs, and therefore allowing for a more informed decision making process. Fiscal impact analysis has been a mainstay for planners, real estate developers and decision-makers for over 40 years. However, changing demographics and new ways of using FIA are requiring a fresh look at this tool.
The Community Data Analytics team of Econsult Solutions was invited to present on these topics at the American Planning Association New Jersey Chapter’s Annual Conference in late January. ESI Senior Advisor, Sidney Wong Ph.D, Charles Heydt, Senior Planner at Dresdner Robin, and I participated in a panel that was moderated by ESI Senior Vice President Peter Angelides with roughly 30 planners in attendance.
Sidney focused on how FIA practioners need to use the most current Census and geographically relevant data, both found by using Public Use Microdata Sample (PUMS) data sets. In a thoughtful and data-filled presentation that specifically focused on New Jersey, he demonstrated how the most current PUMS data and PUMS geographic areas (PUMAs) more accurately reflect likely population and school-aged children generated from new development. Both estimates are crucial in correctly estimating the fiscal impacts likely to occur. Sidney showed how older Census data tends to overstate the number of school-aged children in several types of housing units.
Turning it Upside Down
In my presentation, I took the traditional FIA methodology and “turned it upside down” to show how it could also be used to estimate fiscal impacts of the loss of development due to property buy-outs. Property buy-out strategies are, unfortunately, becoming more and more prevalent as hazard mitigation planning and resiliency planning becomes more sophisticated and cost driven. In my presentation, a “reverse fiscal impact” methodology was given, where revenue loss resulting from the acquisition of taxable properties was quantified and compared to potential cost savings from reduced government services demand. In three case studies in New Jersey, reverse fiscal impact was used as part of the decision making process for future hazard mitigation efforts. I concluded by noting that this new use of FIA was still in its infancy, but has great potential as a tool that can help foster informed decision making about how property buy-outs might affect local budgets.
The Community Data Analytics team will be making presentations at the American Planning Association’s National Conference in May and are available to groups interested in these topics.
For more information on Community Data Analytics, please visit: www.cda-esi.com
Steven L. Nelson is a certified planner and policy maker; and understands the interplay between public policy, innovation and constituency building.