Measuring Pro-housing Reforms at Scale: A Comprehensive Guide for Planners, Policymakers, and Researchers

State and local governments across the United States have recognized the need to increase housing supply and housing affordability. As a result, they have started to experiment with a menu of pro-housing reforms. In “Measuring Pro-housing Reforms at Scale: A Comprehensive Guide for Planners, Policymakers, and Researchers,” Tianfang Cui shows how politicians and planners can monitor the effectiveness of their efforts. He provides a standardized evaluation plan that can demonstrate which reforms work in different market conditions.

Getting Incentives Right for Developers 

The appetite for housing reform is greater now than it has been for half a century. A growing body of research has confirmed how local development regulations have decreased housing affordability. With home prices and rents reaching new highs in the 2020s, pro-housing reforms are being passed across North America to reduce regulatory barriers to new housing. 

Pro-housing reforms that increase supply, and therefore relieve pressure on housing affordability, are based on the premise that developers are entrepreneurs. That is, policymakers who pass pro-housing reforms treat developers as individuals who assess the risk of starting a new building project to meet today's market demand. Policymakers should therefore always seek to answer the following question:

What reforms will change developers' calculations enough for them to undertake building more units?

Cui groups reforms into the six categories below:

1. Simplify zoning to allow many uses: Eliminate land-use measures that reserve large sections of land exclusively for single-family detached homes. In 2016, for example, California legalized accessory dwelling units below a certain size, and in 2021 it legalized the conversion of single-family lots into four-unit multiplexes.
2. Address density restrictions: Reform regulations that limit density growth close to the urban core. Such regulations include minimum lot sizes, minimum building sizes, and even height limits for downtowns. For instance, Houston, Texas, has effectively legalized the construction of townhomes that use up the entire lot.
3. Remove parking minimums: No longer mandate a parking space for each apartment unit or for so many square feet of built area. Minneapolis, Minnesota, and other cities have eliminated parking minimums citywide.
4. Bypass discretionary review: Remove officials' power to exercise multiple steps of discretionary review before the approval of permits. To streamline the approval process, for example, Montana and Washington now allow the bypass of state environmental review if there is compliance with other planning laws.
5. Reconsider past multifamily standards: Roll back local regulations that ban the renting of homes to more than a specified number of unrelated people. For instance, to increase renter choice, Boulder, Colorado, reversed a 1962 ordinance and authorized occupancy by up to five unrelated persons per unit.
6. Review building code standards: Modify codes that seek to reduce fire and disaster risks to real estate. A tradeoff exists between minimization of risk and necessary design flexibility, such as constructing new apartment buildings on a small parcel of urban land or constructing small homes with the least expensive materials.

States and cities are passing combinations of the above-listed reforms; taking all these policy experiments together, we can measure the “mother of all comparative outcomes” to understand which pro-housing reforms can affect the market. As real data from these efforts trickle in, Cui offers a roadmap for evaluating the reforms to assess their local impact and to contribute to a better understanding of them.

How to Evaluate the Reforms

The largest gap in knowledge is whether policy reforms alone increase the supply of more affordable housing.

According to the author, an evaluation that uses local permit and administrative data to fill that gap can be produced without high costs. A successful evaluation will require cooperation between researchers and planners—professionals who bring different skills to the table. The plan offered by the author can serve as a reference that keeps involved parties on the same page. He does so by reviewing each step of the evaluation planning process.

• Keep track of the many dimensions of pro-housing reforms, as well as the eligibility requirements that serve as “strings attached,” using reform intensity tables.
• Employ case studies to show how frontier research uses data already provided by local agencies.
• Understand the trade-off between collecting more outcomes in an evaluation plan and the costs involved in processing more data that matter little for measuring policy effectiveness.
• Consider the value of a research design that can provide causal estimates of the reforms’ effect on supply, i.e., impacts that can’t be explained by how the local market looked when the reforms passed, or the peculiarities of where reforms were in effect.
• Review three different research designs used by academic researchers, each of which compares outcomes after the policy takes effect with different “control group” areas or properties.
• Break down how reforms affect different neighborhoods or built forms by estimating impacts separately in areas with different reform intensities.
• Consider a template for a pre-analysis plan, which an evaluation team can adapt for grant application purposes and to communicate their evaluation plan in a standard way.
• Contrast causal research designs with descriptive analysis. The author recommends combining local permit data with free datasets on neighborhood characteristics, which can also be helpful to plan out areas where broad reforms can be piloted and still deliver results.

What the Evaluation Plan Will Deliver

One goal of the plan is to use data to show how local pro-housing officials delivered on their promises with passed reforms—increasing the supply of new housing affordable to a broader population.

Another goal: Through causal research designs, use data from a few cities to find reforms that can scale over many types of housing markets.

Ultimately, practitioners should be in a position to ask and get answers to key causal questions:

Did our recently passed reforms cause more housing construction?

For reforms that included efforts to unlock a certain housing type, did they cause developers to propose more units of that type?