Assessing the Quantification Methodology for the Affordable Housing and Sustainable Communities Program

Daniel G. Chatman, Seva Rodynansky, Marlon Boarnet, Andre Comandon, Breitling Snyder, Kieran Patel and Jon Atkins

Institute of Transportation Studies, Research Reports, Working Papers, Proceedings from Institute of Transportation Studies, UC Berkeley

Abstract: Do affordable housing projects in high-quality transit-oriented development areas reduce auto use? By how much? Under what conditions? These questions are complex but highly relevant for the state of California. Its Affordable Housing and Sustainable Communities (AHSC) program estimates reductions in vehicle miles traveled (VMT) associated with project applications, and scores applications partly on this basis. Building on a large set of existing empirical literature, we carried out a new analysis of how the built environment affects travel in California. We relied on several data sources including movement data from cell phones purchased from a private firm; travel diary data from the 2017 National Household Travel Survey (the most recent household travel survey for the state); data on housing characteristics and commuting from the 2017 American Housing Survey; and neighborhood, community, and regional built environment and public transportation data from Federal and local sources. Consistent with previous literature, we did not find evidence that parcel-level characteristics influenced auto use, but our study reinforced the evidence in existing empirical literature about the importance of larger-scale built environment factors influencing VMT, from the scale of the Census block group up to the radius of a 45-minute drive from home. We recommend that the AHSC calculator be modified to take these factors into account, in addition to including the availability of off-street parking, when calculating VMT reductions. We also recommend that the calculator use a counterfactual assumption about alternative development locations using our quantitative estimates and based on a more appropriate spatial scale.

Keywords: Social; and; Behavioral; Sciences (search for similar items in EconPapers)
Date: 2025-08-15
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