A New Tool for Infill Policy

Infill development is getting a boost from some states seeking to lower housing costs by increasing the housing supply. While local governments largely manage zoning and land use regulations, state agencies can play an important role by enforcing laws, incentivizing density, and providing valuable information on future housing needs.

In "Overseeing Infill: How State Agencies Can More Effectively Monitor Local Land Use Administration" (Journal of the American Planning Association, Vol. 90, No. 3) Nicholas J. Marantz, Christopher S. Elmendorf, and Youjin B. Kim offers techniques for state agencies to set priorities for enforcement actions under state law and assess which local jurisdictions would benefit most from technical assistance.

The Problem Vs Solution

Several states, including California, Oregon, Washington, and Massachusetts, have tasked state-level agencies with overseeing local efforts to promote infill development. However, this oversight is challenging due to the various regulatory channels municipalities use, such as parking mandates, height restrictions, and development fees.

State agencies often have limited staffing and competing responsibilities, making it difficult to conduct an exhaustive review of every local ordinance.

The authors present two statistical models to assist state agencies in prioritizing local ordinances. The first model evaluates the raw potential for new housing within a jurisdiction, focusing on market conditions and parcel characteristics while excluding factors that might influence housing development politics.

The second model includes these political factors and allows regulators to assess the availability of additional sites for various types of development. The researchers illustrate the models' application by using them to evaluate laws authorizing accessory dwelling units (ADUs) on single-family parcels in California.

Access the code for both models.

Targeting Regulatory Scrutiny

The authors' first model examines how a parcel's location in a municipality affects ADU permitting, controlling for other variables. They use this comparison across jurisdictions to identify areas needing regulatory scrutiny. Jurisdictions with measures significantly below the sample median permit fewer ADUs than expected based on parcel and neighborhood attributes.

The second model identifies attributes of underperforming jurisdictions and uses simulation methods to predict future ADU permits based on parcel, tract, and city-level characteristics. This is crucial for states like California, where officials rely on local housing plans to gauge expected development.

Including city-level characteristics is important because if a city has a feature strongly linked to ADU production, incorporating this information should enhance the model's accuracy in forecasting future ADU permits for that city.

Facilitating Enforcement and Technical Assistance

Efforts to promote infill development through state oversight of local planning and zoning are promising, as long as relevant laws require data collection and enforcement. However, these requirements alone may not be enough if agencies do not effectively use the data to set priorities.

Publicly available models, like those provided by the authors, can assist state agencies in reviewing local plans and ordinances. They also help target enforcement and technical assistance more effectively.

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