Professor Monkkonen’s Letter on Regional Housing Needs Assessment (RHNA) Methodology

As a member of SCAG’s RHNA methodology subcommittee, I write to urge the Regional Council to reject the use of local inputs for the allocation of regional housing need, and instead, ask SCAG staff to propose an allocation formula based on objective measures that align with the stated priorities of Housing Element Law. The draft proposal for RHNA allocation presents three possible methods. Two of the three (Option 1 and 3) are based on local inputs, and Option 2 uses an inadequate set of factors (only population share and access to transit). The CEHD committee and the Regional Council should not vote to clear the SCAG draft  proposal for RHNA allocation for public comment as it currently stands. Public discussion of the RHNA methodology should not be guided by these options. In this letter, I first explain why using local inputs would work in opposition to the goals of the Housing Element Law, as it would allocate disproportionate amounts of housing to areas of low-opportunity, far from job centers, adding to regional congestion, increasing emissions,
negatively impacting air quality and people’s overall quality of life. I then outline a set of factors that could be used in a RHNA methodology to align with the State’s goals of social equity and environmental sustainability.

Local inputs are projections of household growth under current zoning. Using them as a basis for RHNA works directly against environmental and social goals because it pushes more housing to parts of the region with fewer jobs and lower incomes. Cities in Los Angeles County and Orange County closest to abundant job opportunities are mostly “built out” under existing zoning, and therefore have a relatively low projected household growth. These cities could, however, accommodate housing by rezoning land strategically. Figure 1 demonstrates the regional imbalance and the way Option 1 and 3 would distribute RHNA. Using local inputs to allocate RHNA is not consistent with a law requiring the plan “to increase access to areas of high opportunity for lower-income residents”. RHNA should push for more low-income housing in high opportunity cities but using local inputs does the opposite. It pushes housing growth to the cities farthest from job opportunities – which have land to build on, and thus higher projected household growth.

I propose that the CEHD committee and the Regional Council replace Option 1 and 3 with different allocation methods for public consideration, methods that use objective measures consistent with the goals of advancing environmental sustainability and social equity. SCAG’s Option 2 considers population share and access to high-quality transit. This is based on objective measures, but it is not sufficient. I suggest SCAG also consider factors including:

1. Housing costs,
2. The share of multifamily housing stock,
3. The share of subsidized housing,
4. The ratio of jobs to housing in the city, and
5. The share of regional jobs within a short commute.

Using these objective measures would allocate regional housing need in a way that advances environmental sustainability, and affirmatively furthers fair housing at the regional scale. The social equity adjustment is also an important issue. It is used to modify RHNA allocations by income category, to give higher numbers of lower-income need to relatively more affluent jurisdictions. It should be increased from the past practice of 110% to 200%. It is important to note, however, that if high opportunity cities have a low total RHNA number, the social equity adjustment will have a limited impact. The way we decide cities’ total housing need is potentially more consequential for increasing access to areas of high opportunity for lower-income residents.

A RHNA allocation that actually matches state goals is important. RHNA numbers are increasingly consequential (e.g. under laws like SB35) and the state assesses housing production according to RHNA targets as a valid measure of housing need. This means that assigning high RHNA numbers to cities with low housing demand unfairly punishes them, they are less likely to meet these production targets. Additionally, assigning low RHNA numbers to cities with high housing demand unfairly rewards them for meeting goals. Moreover, assigning higher RHNA numbers to cities with higher demand for housing will actually lead to more
housing production overall. Should you have any questions about this matter, I would be happy to discuss further.

Paavo Monkkonen
Associate Professor of Urban Planning and Public Policy
UCLA Luskin School of Public Affairs
paavo.monkkonen@ucla.edu

Paavo Monkkonen is an Associate Professor in the Department of Urban Planning at the UCLA Luskin School of Public Affairs, where he teaches courses on housing markets and policy, economics, research methods, and global urban segregation. His research focuses on five areas: housing policy with an emphasis on low-income housing, the role of finance, policy, and economic development in the changing spatial structures of cities, the impacts of land use regulation on housing markets, the regularization of informally developed neighborhoods, and property taxation. Current research projects include an international comparative analysis of household formation, a study of regulations and urbanization in Asia and Latin America funded by the Global Development Network and the Inter-American Development Bank, and a spatial analysis of the housing market of Chengdu, China. He was recently awarded the David C. Lincoln fellowship to study the urban development impacts of land taxation in Mexicali, Baja California. Dr. Monkkonen has a Master of Public Policy from the School of Public Affairs at the University of California, Los Angeles. He completed his PhD in City and Regional Planning at the University of California, Berkeley. His dissertation research, funded by fellowships from the Fullbright-Hays, North American Regional Science Council and the UC MEXUS research institute, analyzed how the reform of Mexico’s provident fund housing finance system transformed access to housing, the homebuilding industry, urban growth patterns, and the socio-spatial structure of cities. Entitled The Housing Transition in Mexico: Local Impacts of National Policy, it was the winner of the 2010 Aareal Award for Excellence in Real Estate Research from the Real Estate Management Institute of the European Business School. He was previously an Assistant Professor in the Department of Urban Planning and Design at the University of Hong Kong.