Panel Paper: How Do Cities in California Limit Housing Production? Process Vs. Prohibition in Local Land Use Regulations

Friday, November 8, 2019
I.M Pei Tower: Terrace Level, Columbine (Sheraton Denver Downtown)

*Names in bold indicate Presenter

Paavo Monkkonen, Michael Lens and Michael Manville, University of California, Los Angeles


California’s residents are spending historically high sums of money on housing or relocating out of the state altogether. A failure to build new homes is undoubtedly one driver of these trends. There is general agreement that local land use regulations prevent new housing from being built, but there is less agreement about how exactly regulation reduces housing supply. One obvious channel is prohibition: most cities do not allow more than one housing unit on the vast majority of the parcels in their jurisdictions. Planners often cite prohibition (a lack of developable land) when asked about slow housing production. Developers, on the other hand, point to process: even on sites where rules permit multifamily housing, these rules—ranging from impact fees, inclusionary housing set-asides, parking requirements, or just multi-step approvals that require many hearings—often make new building too expensive.

We seek to disentangle the differential impacts of these two aspects of regulation using the Terner Center Residential Land Use Survey, combined with vacant sites inventory data from cities' housing elements. We will do this first, by modeling housing permitted recently (from 2011-2017) across cities as a function of market demand factors and the two dimensions of land use regulations, process and prohibition. We will measure process factors using responses to questions about approvals and public opposition, and prohibitions with questions about single-family zoning and minimum lot sizes. Econometric studies of regulation and housing markets suffer from endogeneity threats, which we avoid somewhat by modelling new supply rather than home prices (which are more prone to both reverse causality and omitted variables). We will also address the issue of endogeneity directly using instrumental variables, and examine the conditions under which endogeneity truly biases estimates of regulation’s impact.