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Launching the Housing Development Dashboard

Update December 2022: please see the Terner Center & Labs’ updated approach to policy simulation modeling using the new Terner Housing Policy Dashboard on our website here.


In the short time since we launched the Terner Center for Housing Innovation, I have been inundated with requests to weigh-in on the issue of how to best address the housing affordability crisis- not just at its epicenter in the San Francisco Bay Area- but in similarly situated high job growth regions from Boston to San Diego.

While there are multiple contributing factors to the crisis, I keep coming back to one simple premise: supply matters, and we need to expand housing supply in equitable and environmentally sustainable ways.

This statement rarely makes anyone happy.  Most want to hear answers that fit neatly into their preconceived narrative of the problem. This usually either entails claiming that we need “a total moratorium on development because that is what is causing gentrification and displacement” on the one hand, or the rallying cry of “build, build, build- anywhere at any cost” on the other.

Neither of these perspectives is going to get us to a solution.  We need a tool that can help us to more objectively assess and weigh our multiple policy objectives, from ensuring we have housing for families with a wide range of income levels, to reducing the time people have to spend in their car to get to work.

So we built it.

Today, I am excited to be sharing a new tool–the Housing Development Dashboard–that has the potential to significantly reshape how we engage in the housing development debate in cities across the country.

The Housing Development Dashboard [1] is an interactive platform that allows policymakers, developers, and members of the public to quickly and easily understand the interaction of land use measures and market conditions on housing production. Want to know whether a higher level of inclusionary housing will stall production?  It can tell you that. Curious to see how much more housing would get built if we streamline the approval process? It can estimate those impacts too. The Dashboard disrupts the status quo of limited, outdated, expensive and often highly politicized information about the potential implications of new policies and replaces it with accessible data that will result in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.

So how does it work?  First, we merged multiple data sets and created a set of default assumptions about the economic factors that influence housing production (for example, the cost of construction, land value, and investor return requirements) [2]. Second, we assess how various policies change the cost calculus of development.  The Dashboard currently focuses on policies with an especially high impact on housing production, such as impact fees, density, parking requirements, permitting time, ground floor retail, inclusionary zoning, specific plan areas and discretionary approvals (such as conditional use and planned unit development permits). Within the Dashboard, we’ve launched two separate calculators that allows users to assess the impact of these policies at different scales: one at the project level and the other at the city level.

The Development Calculator allows users to estimate the probability that a given development project will be built, given a particular set of policies and economic conditions. For example, if a proposed policy increases the density requirements in a jurisdiction, holding all other factors constant, how will this change affect the likelihood that a planned multifamily project will be developed?

Second, the Policy Gauge assesses the cumulative impact that a policy change might have on housing production across an entire jurisdiction. The Policy Gauge includes parcel level data on zoning, densities, and site conditions onto which market data such as rents and costs are overlaid with other local policies.  For example, if a city wants to pass legislation allowing for a reduced parking ratio for developments near transit, how might this increase or decrease the overall supply of housing?  Right now, the Policy Gauge has been developed for four (very different) Bay Area cities: San Francisco, Oakland, Pleasanton, and Menlo Park, but we hope to expand to other cities soon!

Though still in beta format, the Dashboard reveals the potential for a fully built out tool like this to inform local housing and land use policies in communities across the country.  Kearstin Dischinger, a Housing Policy Planner in the San Francisco Planning Department said of the tool: “This is the first urban planning model that has advanced our abilities to test various policies with more sophisticated consideration of economic factors. San Francisco Planning is looking forward to testing affordable housing scenarios with this tool.”

How do we hope that these tools will be used?  The Dashboard provides a new mechanism for public engagement around urban development. Both the Development Calculator and Policy Gauge are intuitive resources that present trade-offs in an intentionally simple format, to allow for clarity and ease of use. They have the potential to demystify some of the components of policy development and implementation for the concerned or curious citizen, and do so in a way that can keep up with both market changes and policy proposals as they emerge.

Stay tuned- I’ll soon share some of my own big takeaways about what the Housing Development Dashboard is telling us and the implications this has for housing production and policy.

[1] Tool developed by Graham Macdonald, a recent graduate of the Goldman School of Public Policy, in close consultation with Terner Center leadership and several UC Berkeley faculty members.  Graham’s full paper, which won the prestigious Smolensky Award, can be found here along with technical notes on the model.

[2] All of which went through an extensive ground truthing process in interviews with policymakers, developers, and others.

Update December 2022: please see the Terner Center & Labs’ updated approach to policy simulation modeling using the new Terner Housing Policy Dashboard on our website here.

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