The Mount Laurel Doctrine
In 1975, plaintiffs brought a lawsuit against the township of Mount Laurel, NJ. They challenged the township’s zoning ordinances under the grounds that they excluded low and moderate-income people from obtaining housing. The plaintiffs won, and the NJ Supreme Court declared that “municipal land use regulations that prevent affordable housing opportunities for the poor are unconstitutional” (NJ Fair Share Housing Center). Despite this ruling, little was done to expand affordable housing as Mount Laurel fought the ruling with zoning changes that made it practically impossible to develop.
Fast-forward to 1983. Faced with non-compliance, the NJ Supreme Court released a new ruling forcing towns to provide their “fair share” of the regional need for low and moderate-income housing by requiring “realistic opportunity” be created. This ruling came to be known as the Mount Laurel Doctrine, a landmark civil rights decision prohibiting economic discrimination through local land rights and zoning. Unfortunately, towns and municipalities continued to fight the ruling, dragging out court battles and interpretations of housing requirements to avoid their fair share. Decades passed, and while many towns drew up plans or began allowing the construction of low-income housing, NJ became a patchwork of compliance and non-compliance.
Fast-forward to 2018. Two wealthy NJ towns, Princeton and West Windsor, lose a court battle challenging the Mount Laurel Doctrine, and the most up-to-date ruling by Judge Jacobson critically specifies that towns must make up for decades of non-compliance. In whole, New Jersey needs approximately 154,000 affordable housing units across the state.
Simplifying Decades of Complexity
The aim of this project was to create a concise, simplified visualization of the affordable housing needs across NJ. The Mount Laurel Doctrine and Judge Jacobson’s updated ruling include a rats nest of unintuitive terminology, hard-to-find updated data, and seemingly arbitrary groupings of housing requirements across various time periods.
At the core of this project is the data provided by David Kinsley, a Princeton University lecturer and Fair Share Housing Center collaborator who extrapolated Judge Jacobson’s 2018 ruling for Princeton and West Winsor to detail the affordable housing needs of every municipality in the state. Thanks to his generosity and willingness to collaborate, the visualizations created are based on the most up-to-date numbers available.
Methods
Using Tableau, Kinsley’s data was imported and linked to NJ geometry data through a common attribute across data sources – each municipalities unique 4 digit code.
A map was chosen for the visualization to provide rich, granular level detail at the municipality level. This visualization method brings immediate spatial understanding for NJ residents (I can find my municipality or a municipality I’m interested in) and allows for quick comparisons of required housing numbers through choropleth theming.
One of the most difficult aspects of the project was how to communicate such complex groupings of data in an intuitive way. Based on clarifications from David and research into the Jacobson ruling, time periods were simplified and grouped to promote understanding.
| Court Terms | Simplified Categories |
| Prior Round Obligations (1987-1999) | Prior Need (1987-1999) |
| Gap Present Need (2015) | Prior Need (2000-2015) |
| Present Need (2015) | Present Need (as of 2015) |
| Prospective Need (2015-2025) | Future Need (2015-2025) |
These ranges were further clarified when I learned a critical detail – that the Present Need category largely consists of the renovation of existing housing, while the other three categories refer to the construction of new housing. This led me to create a 2-tier hierarchy in the visualization so viewers can focus less on understanding the terms and more on the total number of homes needing to be built or renovated.
In addition to the map, a stacked bar chart is provided at the county level to provide a bigger-picture sense of total affordable housing needs in the state.
Footnotes were added to quickly summarize the four categories and provide meaning to otherwise arbitrary year ranges. While the visualization would have been simpler if both Prior Need ranges were collapsed into one, I felt that such simplification would have made this visualization less useful to policymakers and municipalities looking to better understand their housing requirements within the context of official year ranges as defined in various court rulings.
Results
The final results combine the two visualizations described above with a dashboard to provide organization and context.
Reflection
Overall this project proved to be exciting and gratifying given the limited access to the dataset, updated numbers providing current data municipalities can apply now, and a feeling of doing good by making NJs affordable housing history and current requirements easier to access and interpret. With more time, the next steps for this project would be to provide more meaning behind the numbers, moving this visualization beyond an interactive reference sheet and towards a tool that can provide a deeper understanding of how the numbers are derived. One of the primary future expansions would be to overlay municipality low and moderate-income household numbers from the American Community Survey. Comparing the number of households eligible for affordable housing to the planned affordable housing could illuminate how well local communities will meet the need of their low and moderate-income populations. But, such a comparison (or ratio) would need to be considered for accuracy as there may be problems (such as not factoring in low to moderate-income households who already own a house, or not considering the incoming immigration of people from other municipalities or states).
Additionally, Tableau appears to be hitting some software limitations in the display of the map. It is clunky to navigate and zoom, likely due to the municipality-level geometry data. Other mapping software might handle this heavy map a bit better.