How will a new inclusionary zoning ordinance affect the development of much-needed housing stock? What about changes to density requirements? Or permitting time? There are many factors that influence housing production and with an affordable housing crisis mounting, it is important to understand how these factors impact the development of new housing. In an effort to answer some of these important questions, the Terner Center for Housing Innovation created the Housing Development Dashboard, an interactive set of tools that aims to create a way to easily understand the interaction of land use measures and market conditions on housing production.
Carol Galante, Faculty Director for the Terner Center, announced the Housing Development Dashboard in a blog post on May 31. Her post suggests that “the Dashboard disrupts the status quo of limited, outdated, expensive and often highly politicized information about the potential implications of new policies and replaces it with accessible data that will result in more informed decision-making.”
The Development Calculator predicts the likelihood that a certain development will be built based on the economic and regulatory environment it is in. The calculator works best for properties of 50 units or more, projects in which the developer has not yet entered into an option agreement, and where the land seller is motivated to sell. The website cautions that many of these factors move together, so users should be careful to interpret results significantly different from existing market conditions.
The Policy Gauge is designed for local politicians, city staff, and the general public to understand how policies could impact housing production and city revenues where they live and work. Right now, the calculator focuses on San Francisco, Oakland, Pleasanton, and Menlo Park.
According to the website, the methodology and default assumptions included in each tool were vetted by area development experts, data collection, and analysis from January to May of this year. The tools are currently in βeta testing.