Using Replica to Study Housing and Climate Policy at the Terner Center for Housing Innovation

UC Berkeley’s Terner Center published a new report focused on building “equitable pathways to sustainability and affordability.” We spoke with author Zack Subin about how Replica contributed to the underlying research.

Published on
April 4, 2024

On March 6th, the Terner Center published “Housing + Climate Policy: Building Equitable Pathways to Sustainability and Affordability”. The full report can be read here. Author Zack Subin wrote a companion blog that focused on understanding the role of new housing in reducing climate pollution, which is available here. We conducted the following interview with Zack to discuss some of the findings in his report.

Thanks for joining us, Zack. Can we start with you introducing yourself and giving a little bit of background about the report that you just published?

Definitely. My name is Zack Subin. I am an associate research director at the Terner Center, leading our housing and climate research initiative. I'm also a new person at Terner, joining last summer after spending three years at the Rocky Mountain Institute, which is where I first learned about Replica. 

The research we just released is a review of the literature on housing and climate, as it relates to three broad areas. First, is how new housing — the type and where it is located — can reduce greenhouse gas emissions. Second, is how upgrading existing homes needs to be done equitably to increase comfort and resilience while reducing emissions, and making sure we’re protecting renters and housing affordability while we’re doing this. And the third area is how we respond to climate disasters and severe weather.

A couple of our current projects are focused on the first of the three, which is where the Replica data comes in.

Great. And was that the focus of the blog you wrote?

Yes. The article serves two purposes. The first is to introduce what may be some new ideas for a lot of folks related to how it matters where we build housing and what factors should go into those choices. The second is to establish that we need to do more research and lay out an agenda for that path moving forward.

The issue is housing policy needs to be nuanced. We can’t just purely optimize for minimizing vehicle-miles-traveled when we're building housing. We also need to think about historical patterns of segregation and fair housing, and to recognize that we've got this massive housing shortage that we've accumulated over decades. 

Clearly not every new housing project can be perfect, so how can we use data to prioritize among those differing, and sometimes, conflicting priorities? It can’t just be a static ranking of 30 dimensions that are the same everywhere.

Let’s come back to that in a minute because one of the things we hear all the time from our customers is that one of the things that making working in the public sector so hard is that each place is unique and a rigid checklist or a one size fits all approach just doesn’t work in the real world.

But first, I don’t mean to boil your research down to 180 characters, but if you had to tweet out the bottom line of the new report, what is it?

So the bottom line is building new housing in urban areas — particularly in places like SF and Palo Alto — can lead to a pretty large avoidance of climate pollution by helping to meet demand and reducing the need to build in more highly emitting areas. 

Determining the exact magnitude of that is pretty challenging though, and that's why it's been left out of a lot of policy planning. And if we did have a better understanding of that, it could help us prioritize against other climate and housing strategies.

You talk about this a little bit in the article, but obviously when you build housing in denser places, trips are shorter and those trips are less likely to be by car. But does the data show that all trips are created equal? Are commute trips different from discretionary trips? How does the difference start to shake out?

Well this comes back to the checklist we spoke about. A lot of California state policy has started with, “We need to have a jobs-housing balance, and we need to build housing near transit, and that's how we check the box. But that's a little bit too rigid. Even before the pandemic, 70% of vehicle miles traveled were not going to and from work and perhaps that's even lower post-pandemic. 

Unfortunately, as much as I love transit and we need to build more of it, we also need to recognize most of the country has not been built in ways that support transit. And if we completely exclude all of those areas from new housing, we’re just not going to reach the scale we need to address the housing shortage.

That’s also a very bad approach for fair housing because we would be saying, “these exclusionary single family suburbs that have set themselves up to be car oriented, we're going to give you a pass on seeing any more affordable housing types built in your community.”

We're trying to move beyond that and that's a little bit of what I try to do in this piece. Take the examples of Palo Alto versus Oakley. These are both suburbs, in a sense that they are of similar density with mostly single family detached houses. But, as Replica data shows, people in Palo Alto have lower VMT per person.

Very little of that is due to transit. Almost no trips by Palo Alto residents are being taken on transit. What you do see is there's quite a bit of walking and biking in Palo Alto though. And when people are getting in their car, they're going shorter distances because the shopping centers and jobs there are closer. So they're going a half mile, or one mile, or two miles, instead of going five or ten miles.

What was your experience using Replica data to do this analysis?

Well, previously, having access to this type of data was a huge gap in our research. Even just seeing VMT per capita maps was difficult, and reliant on using National Household Travel Survey data that’s six years old at this point, which is pre-pandemic.

With Replica we can do that, and can dig into what’s underlying particular trips.

And I will say, I’m not a transportation planner by training. It’s great to have a tool that’s more accessible. Enabling people, and agencies, and nonprofits, and ideally, advocates, to be able to dig into this type of data is a step forward.

We’re glad to hear that. So to wrap up, I’d love to know what’s on your housing wish list. If Governor Newsom called you up and said you can enact one policy tomorrow, no questions asked. What are you getting across the finish line?

I think we're still working on the answer to that. We’ve seen a lot of new bills passed to make it easier to build housing in infill locations. And now, we’re starting to see laws like SB 743 and last year’s proposed AB 68, which focus on VMT and try to explicitly make the link between building more housing in the places we do want and making it harder to build housing in the places we don’t want, as it relates to environmental factors. But I worry that if we don’t do this right we could make housing affordability worse. There are still a lot of ways for exclusionary communities to block housing, and we have to balance both sides of the equation here, building more infill as well as less sprawl. 


For example, my blog looked at Palo Alto, which hasn’t been building much new housing– even though it’s pretty low VMT and high opportunity– the kind of place our state policy is saying we should be building more in, for both climate and fair housing reasons.

That's a great and nuanced answer. It can be scary to give complex questions simple answers, which is why we try to avoid it here at Replica. 

Totally. Great, thanks.

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