How Local Market Conditions Shape Housing Policy Outcomes: Terner Housing Policy Simulator

Findings from the Terner Housing Policy Simulator at Terner Labs

Local market conditions—such as land values, construction costs, and regulatory environments—can shape how housing development responds to policy changes. Therefore, reforms that meaningfully expand housing supply in one city may have far more limited effects in another. Understanding these differences is critical for policymakers: without accounting for local market dynamics, even well-intentioned housing policies may fail to produce the intended increases in production.

Terner Labs—an independent nonprofit founded as an innovation lab by Terner Center leaders—has developed a tool to help researchers and policymakers understand the implications of adopting housing policies in specific jurisdictions.

The Terner Housing Policy Simulator (Simulator) uses a complex set of models that forecasts development based on thousands of inputs. The Terner Labs team works closely with research partners to develop and modify the inputs, testing policy details and sensitivities. The Simulator takes into consideration local economic conditions, zoning rules, historical development patterns, and financial metrics of potential projects. Based on these inputs, it estimates the likelihood of a developer building multifamily market-rate housing on a given piece of land and calculates how this might change if a specific policy were applied.

The Simulator Visualization, a public-facing Terner Labs interactive, allows users to explore how various policy scenarios and economic conditions affect housing development across specific cities, starting with Denver, CO; San Diego, CA; and Tucson, AZ. 

“Introducing the Simulator Visualization: Methods, Uses, and Limitations” provides a high-level overview of the models that drive the Simulator Visualization.

 

 

 

The paper, “How Local Market Conditions Shape Housing Policy Outcomes: Comparing Denver, San Diego, and Tucson,” offers a deeper dive into the insights available to users of the Simulator Visualization. It describes the policy scenarios featured in the Simulator Visualization, provides an overview of the cities included and their current development contexts, and highlights key takeaways from using the tool. 

The results underscore a critical reality for urban planners: housing reforms are not “one-size-fits-all” solutions. The profiles of Denver, San Diego, and Tucson show that the effectiveness of a policy depends on whether it addresses the specifics of each local market.

The research also shows that by utilizing data-driven modeling like the Housing Policy Simulator, leaders of cities across the United States can set realistic expectations, target the true constraints of their local markets, and design more effective strategies to address the housing shortage.

Users can also access the full Simulator Methodology.