(Unedited) Podcast Transcript 322: Less Congestion After Ride Hailing Cessation
This week we’re joined by UC Berkeley PhD candidate Matthew Tarduno. Matt talks to us about his paper comparing congestion and economic impacts of ride hailing companies Uber and Lyft before and after the cessation of service in Austin Texas.
For a full unedited transcript check below the fold:
Jeff Wood (1m 27s):
Well, Matt Tarduno, welcome to the talking headways podcast.
Matt Tarduno
Yeah. Pleasure to be here.
Jeff Wood
Thanks for joining us before we get started. Can you tell us a little bit about yourself?
Matt Tarduno (1m 37s):
Yeah. So I’m a fourth year PhD candidate at UC Berkeley. I’m in the department of agricultural and resource economics and my research focuses mainly on transportation policy and climate policy.
Jeff Wood (1m 51s):
That’s interesting. So you’re in the agricultural economics school, but then you’re doing research on ride hailing, right?
Matt Tarduno (1m 58s):
Yeah. People often that’s a bit of a head scratcher when they see kind of my subject line of my email. How did those two things intersect? Yeah. So, so my department is named agriculture and resource economics, but it largely acts as an applied economics program. So students in faculties study environmental economics development, economics and agricultural economics.
Jeff Wood (2m 18s):
So how did you get into economics?
Matt Tarduno (2m 20s):
Yeah, actually I kind of backed in, in a way, so my high school had an economics requirement. Your senior year, you had to take econ or test out of it and that the test was notoriously easy. And so people would kind of study last minute and try to pass the test. And I did that and failed. And so I was required to take an actual econ class, but my high school had a great offering through Syracuse university called Syracuse university project advance. And they kind of put pair with the university with a high school teachers. And I had a really engaging teacher and kind of enjoyed the coursework. And that was around the time like middle of the great recession and Freakonomics was coming out. So it was, yeah, it just kind of swept up in it.
Matt Tarduno (3m 0s):
And I continued to take classes through college, even though that wasn’t kind of initially where I intended to go. It stuck around and as demonic game or more interested in it,
Jeff Wood (3m 10s):
The study that you wrote is about ride hailing, specifically Uber and Lyft, but you know, what kind of brought you to that topic?
Matt Tarduno (3m 16s):
So one of my first real jobs was actually in the transportation and congestion space. So my senior year of college before my senior year of college, I was kind of at a fork in the road and I had the opportunity. I had two summer job offers and one was to go do environmental consulting. And like I was going to go either to Juneau, Alaska and fly in Bush planes and do environmental consulting there, or move to LA and work for a state Senator there on a transportation planning project. So if you know, the seven, 10 freeway and the entire kind of like decades long debate over whether or not that freeway should be finished.
Matt Tarduno (3m 57s):
And I ended up moving to LA and working, just kind of diving into the environmental impact statement about this freeway. And I learned a lot kind of just like on the fly about traffic congestion and induced demand. And so that was something that was just kind of like lodged in my head. And then when I found myself in grad school, a couple of years later, learning about externalities congestion had always kind of been on my mind and this paper actually evolved out of a second year project. So everybody in my department, you write a second year paper and you kind of go through like a mock process of the peer review. And so I wrote mine about this like causal question of do like ride sharing companies, cost traffic congestion, and I got really positive feedback on it.
Matt Tarduno (4m 38s):
So it continued to work on it. And it evolved into this paper.
Jeff Wood (4m 41s):
Did you learn about the seven, 10 freeway? That’s, you know, that’s the vexing question of the day?
Matt Tarduno (4m 46s):
Yeah. So it was interesting that like I was really brought in to kind of write an opinionated review of the environmental impact statement. I guess I can kind of say this now because of like long left that office. So for people who might not be in the know the seven, 10 is this freeway that was kind of slated to be built and it stopped in the sixties. It was in Pasadena, California. And so right now the seven, 10 freeway basically just stops and it doesn’t connect to kind of like the North and South parts of these communities in LA. And so the question is, do they want to finish the freeway or do they want to pour a tunnel like underneath existing houses to finish the freeway? And basically when you look at it any way of finishing that freeway is going to be incredibly expensive and it’s an open question as to whether or not it would relieve congestion at all.
Matt Tarduno (5m 32s):
And so that’s kind of where the question of induced demand comes in is if you build more capacity, is that going to relieve congestion or not? And kind of the evidence is mixed on, on that, but it, it suggests not if anything. And so it’s probably not a good use of public funds to finish that freeway is kind of like my personal opinion. And that happened to be also the greater opinion of the office that I was working for. So it was nice that summer to kind of like be in a place where, as I was looking at the data, I didn’t have to like spin it in some way that I didn’t want to, but I think it was also like leaving that it was clear that I didn’t want to work directly in government because it was, it was somewhat uncomfortable.
Matt Tarduno (6m 13s):
Like at certain times, if I would like chafe with bosses or like people and trying to write something in a more objective manner. And they’re like, well, like what about this at some points? I like, yeah, I found that uncomfortable, but overall it was a, it was certainly a trial by fire. And I learned so, so much about moving away from just like the theory of traffic congestion don’t count policies and decisions are made in practice. There’s so much
Jeff Wood (6m 35s):
Interesting things that have come out of that process, especially the purchase of property by Caltrans. And they owned it for a long time and then housing was built on there or, or was, was not removed. And so there’s this whole saga of people being allowed or not allowed to buy houses. They lived in forever. And then there was a Tod where the gold line went through. Just a lot of interesting kind of background. If anybody gets a chance to kind of go and dig into the weeds. I imagine if you Google it, you’ll find a lot of information about kind of the background. I agree with you. I didn’t think it would, the seven tenant connection was very valuable at this time. Yeah. But it’s, it’s totally an interesting project or not project for that matter.
Matt Tarduno (7m 10s):
Yeah. That’s exactly the situation as it were an interesting way to demonstrate that, like what could have been in the sixties does not mean what shouldn’t be now.
Jeff Wood (7m 18s):
Right. So you wrote a paper entitled the congestion costs of Lyft and Uber in the journal of urban economics. I’m curious what the impetus was. I mean, you kind of explained a little bit, but what the impetus was for, you know, going and thinking about Austin for pulling the information about this and thinking about congestion specifically as it pertains to ride hailing.
Matt Tarduno (7m 36s):
Yeah. So the kind of intellectual history of this project would be that I was interested just in the causal question of do ride sharing companies, impact congestion, and kind of just stepping away from maybe some of the valence of this question. You know, the answer could go either way, either they are after all called ride sharing companies. Sometimes you could imagine that either the ride sharing effect could dominate and that people are actually using Uber and Lyft to carpool congestion could go down as these companies expand. Alternatively, there were a lot of people who use Uber and Lyft who don’t have vehicles or who might use them differently than they would their personal car. And so you can imagine that Uber and Lyft could add cars to the road and make congestion worse.
Matt Tarduno (8m 20s):
So when I started thinking about this problem, there were a couple of studies that had looked into this, some using Uber data, some using just city specific data. But the one thing that I noticed is that all of these studies kind of looked at the change in Uber entering cities. And there’s kind of a interesting causal question there and that, like you can say, okay, in between 2010, say in 2016, traffic got worse in a city and also the use of Uber and Lyft increased, but that doesn’t necessarily mean, right. Correlation does not mean causation. So it’s not clear that that increased congestion was caused Uber and Lyft because there were a lot of other changes that are happening in between 2010 and 2016.
Matt Tarduno (9m 0s):
Like we’re coming out of a recession. There’s gentrification, there’s the expansion of companies like Amazon. So what I wanted to do is kind of find an example where you had a really abrupt change in Uber service, where you had say disruption disrupting the disruptor. That kind of went from city to city and looked at cases where Uber and Lyft had exited either they had chosen to exit or they were forced to exit. And then I checked, which cities kind of had reasonable traffic data that I could use to answer that question. And Austin was kind of the intersection of that Venn diagram. They have great traffic data. And then also there’s this great natural experiment where Uber and Lyft left for a year. And so that’s why Austin,
Jeff Wood (9m 38s):
The Austin story is really interesting. What’s the background on why Uber and Lyft left Austin?
Matt Tarduno (9m 43s):
Yeah. So Uber and Lyft left Austin in may of 2016 and that was following a vote to overturn a local ordinance. So that’s all, that’s one big sentence. So I’ll kind of break that down. So in 2015, Austin passed a local ordinance regulating rideshare. So that said among other things that rideshare needed to share data with the city and they need to do background checks on drivers and Uber and Lyft were not a fan of this ordinance. And I think they made kind of like a big stir about the background checks, but also under the radar. I think they were probably very unhappy about sharing their data.
Matt Tarduno (10m 23s):
And so what they did, and this is becoming more common is they backed about proposal to overturn kind of this regulation against them. So we saw this again recently in California, but unlike the recent California story in this case, the proposition that Uber and Lyft backed failed. And then, so Uber Lyft kind of made good on their threat and they left two days after it failed. So May 9th, 2016, the companies stopped operate operating.
Jeff Wood (10m 50s):
Yeah, it was interesting. All the stuff that happened at that time, I actually went to school in Austin. And so I pay a little bit of closer attention to what goes on there sometimes. And you know, it was interesting to see kind of all the commentary from all of my Facebook friends and everything. And people were not happy with Uber and Lyft at the time. And especially drivers, people that were driving for Uber and Lyft, they were like, you’re leaving us, you’re abandoning us. There was interesting things about how Houston, for example, had the background checks and they didn’t want it to Austin, but your point about data is really interesting. So there was just so much going on and, and just kind of left. And I think people felt like they were left in the lurch to a certain extent because they’d come to depend on the ride hailing to get to, you know, late night, sixth street and things like that.
Jeff Wood (11m 30s):
So it is an interesting thing that happened. I’m also kind of interested, you know, there was after Lyft and Uber left, you know, there was a non-profit organization, right. Austin that kind of took over, you know, does that play into the discussion much as well, the replacement by another kind of service or other services. Yeah.
Matt Tarduno (11m 47s):
And kind of in a couple of ways that that’s important for, for this paper and kind of the conversation more generally before we get into that, I do want to ask though, did you ever ride with write-offs? I did. Yeah. Yeah. What was that experience like?
Jeff Wood (12m 0s):
It was expensive, but it was great. And I get, you know, that’s the thing is like Uber and Lyft are popular, I think in part, because they are lowering prices below what actually the cost of the rides are, and we’ll get to the economic part in a bit. But, you know, I think that that’s something that probably surprised a bunch of people cause right, Austin, you know, they had to pay for all of their, what they’re doing. They didn’t have a lot of money behind them. So, you know, if you want to ride from the Arboretum all the way down to the airport, it was going to cost you 70, $80, which is something that you’d probably pay for a taxi to get to an airport in any other city, but, you know, that’s the cost, right. So, yeah, I didn’t use it necessarily to get around the city, but I did use it to get to the airport.
Matt Tarduno (12m 38s):
Yeah. And that’s kind of tied into one of the things that I do in the paper is spoiler alert. I’ll share that I found small impacts of these companies on traffic speeds that they cause mild congestion. And so what I do is I compare those costs to kind of what are the benefits of these companies. And one way to do that is to look at consumer surplus. So kind of like how much are people getting from these companies compared to what they would be willing to pay. And I think this kind of illustrates that Uber and Lyft are significant urban amenities. And so when we think about kind of the implications that they have for say congestion or public safety, we also have to weigh that against yeah. These considerable benefits that Uber and Lyft really are like head and shoulders, efficiency-wise above the competition.
Matt Tarduno (13m 23s):
And now yes, there’s an open question of whether or not like that can continue forever and whether or not this is just kind of like burning up a VC runway or not. But for the time being
Jeff Wood (13m 32s):
Also a question about what efficiency actually means, I’m sure. Yes. Especially in cities that have kind of larger bases and, you know, places like San Francisco, maybe New York city in the, in the urban core. But yeah, that’s the finding, I think that a lot of people kind of gravitated to was the finding that there were congestion impacts and after Uber and Lyft left, Austin congestion was reduced. You found by anywhere between one. And I think it was with 3% or something, you had one in 5%, something around those lines.
Matt Tarduno (13m 59s):
Yeah. Yeah. So the daytime speed increased 2.3% on average. And these effects might be heterogeneous by location or by weekend versus weekday, but kind of any way you slice it, you’re not going to have an effect that’s say less than 1% or greater than about 5%.
Jeff Wood (14m 19s):
And also one other thing that was interesting you found was the economic impacts, you know, with Uber and Lyft leave, there’s a benefit from a congestion reduction standpoint, but then there’s also a loss of a service that people use.
Matt Tarduno (14m 32s):
Right. Yeah. And yeah. So to kind of like be clear about exactly what I did is I said, okay, like these companies seem to have slowed traffic. There’s kind of like a broad literature on what people are willing to pay for reductions in travel time. And so I kind of take a couple of different sources of data, some just from Austin, some from kind of national surveys and say, let’s price this, let’s say take the congestion impacts and assign a dollar value to them. And so what I find is that the slowdowns caused by these companies cost Austinites roughly 30 to $50 million a year. And then so it was like, okay, that’s a number that we have up on the wall.
Matt Tarduno (15m 12s):
What should we make of this? And kind of, how would we compare it to the benefits of these companies? And one thing that we can do is look at what do consumers get out of it. So for getting the supply side for a second for getting kind of the profits to Uber, or even the benefits to gig workers, we can look at what consumers get. And there’s a great paper by authors at the university of Chicago using Uber data. And what they do is they kind of calculate the consumer surplus in this like very cool and data intensive method. And I kind of take their figures and do acapella envelope calculations for Austin. And when I run those numbers, I find that consumer surplus from ride sharing is about the same, so 40 to $70 million a year.
Matt Tarduno (15m 57s):
And so what that means is that if you were to just like, again, go to Austin and say, no ride sharing, at least comparing congestion and consumer surplus, it’s roughly a transfer. And so when you’re thinking about policy, is it like, well, these companies are bad for congestion, so we should outright ban them. That’s kind of like one end of the extremity spectrum of what you could do in terms of policy. It seems like that’s probably a policy where the costs outweigh the benefits.
Jeff Wood (16m 23s):
It’s interesting to think about benefits and value and what that actually means. I know from here in California and prop 22 passing, and also there was an article, I think in a number of different publications the other day about Uber saying that it wants the EU to adopt prop 22, like mechanisms, which the EU seems like an even harder place to do that than say than California with its ballot initiatives. But, you know, I always, I’m trying to think about like value that’s created and how we calculate it. And so, you know, when you talk about congestion, I often kind of pushed back sometimes on the idea that, you know, congestion in the TTI reports, the Texas transportation Institute, or even INRIX reports, you know, they actually measure congestion accurately.
Jeff Wood (17m 4s):
I mean, I actually, one of the times there was a TTI speaker and they were at a conference and they were talking about their congestion report. And for me as somebody who took Bart to Oakland every day for eight years, I never saw any of that congestion. And so it’s kind of a weird calculation to me. And especially if you’re measuring things based on whether people have free flow freeway speeds, which is, you know, maybe that’s not so good for urban life overall because that means that place is dead. And so, you know, I’m, I’m wondering like if there is kind of an alternative take on the value that some of these companies create, we can see that they benefit a lot of people in terms of getting from one place to another, for an inexpensive ride, but then there’s externalities quote, unquote, externalities that come about there’s pollution, there’s the impact on people’s wages and gig workers and things like that.
Jeff Wood (17m 54s):
There’s also, like you said, you know, there’s traffic generally, and then all those things. So I’m curious about that.
Matt Tarduno (17m 59s):
Yeah. I think a good place to start is, is asking kind of value and costs. So Austin generally speaking, right? Like not all Austinites are going to use ride sharing. And I think just like a good place to start is looking at, say Pew data and finding out like, okay, who are rideshare users? And then if there are costs to using that platform, like who bears the cost. And so the first question is are those two separate groups at all, right? Because if it’s the same people who drive, who also use ride sharing, and they’re just kind of like congesting, like each other back and forth, then in some sense it’s a wash. But I think where people might be a little bit more uncomfortable is if one kind of group is using a platform and that’s imposing costs on others that don’t reap the benefits of that platform.
Matt Tarduno (18m 47s):
Right? And so like, if you look at the data on who’s using ride sharing companies, it skews young and it’s use high income. And then it also skews like people who do not own a car. And then if you ask, say, let’s just for a second, think about congestion externalities who bears the brunt of those it’s people who drive a lot and people who don’t have access to other modes of transportation. And so if you kind of like do a Venn diagram of who’s in these different groups, there is kind of a slice of the population that is probably lower income car users who might not have access to other modes of transit of who also aren’t using ride sharing apps. And they’re kind of bearing a lot of the brunt of the congestion, but they’re not in a group that’s kind of reaping the benefits.
Jeff Wood (19m 34s):
You also mentioned in your Twitter explainer about the paper that you didn’t think taxation could be expected to deliver those congestion reduction outcomes. I’m curious about that as well,
Matt Tarduno (19m 43s):
Right? Yeah. And so if we take a step back just to kind of the overall impact of these companies, right, we’re talking about 1%, 5%. And if we just look at the past decade of kind of like how traffic speeds have decreased kind of the median American city has seen like a much greater decrease in traffic speeds than can be explained safe if Austin were representative. And so I don’t think we should expect say policies, reducing the number of Uber and Lyft vehicles or policies aimed to tax Uber and Lyft to generate large congestion effects. Because if you think about entirely eliminating ride sharing and Austin that delivered maybe a 5% increase in traffic speeds and taxation is going to reduce TNC activity less than would entirely removing the companies from a city.
Matt Tarduno (20m 35s):
So you might be talking about a fraction of a percent of increase in traffic speeds. And that’s kind of backed up by just like looking at the number of TNC vehicles on the road versus total vehicles.
Jeff Wood (20m 49s):
I think, you know, one of the interesting parts too, is that for midsize cities, I feel like that makes a lot of sense, but when you get to space constraint, places that might be a little bit harder in the Manhattans in the downtown San Francisco’s in the downtown Seattle is the places that kind of are space constrained. There’s a lot of people trying to get a lot of places. There’s a good transit network already. It seems like there are places where it might not have as much impact. You know, I personally have thought that Austin should do a coordinate on the downtown for a long time just for traffic generally, because they only have those two North, South freeways and people kind of come in at certain points or even a couple of North South streets that get blocked off by the state Capitol and university of Texas through the center of the city.
Jeff Wood (21m 30s):
But for places like, you know, for Indianapolis or other mid-sized cities, it seems like, yeah, there’s really no reason to do a congestion charge to try to limit the 5% may be that an Uber and Lyft might cause.
Matt Tarduno (21m 43s):
Right. Yeah. And I think I’m going to take two points from that. And so the first is that, right, this is a study in Austin and I find relatively modest impacts. And so the question is, why is Austin representative of San Francisco or New York? And there are plenty of reasons to think that it might not be right. So then the question is, well, maybe you’d want to tax these companies in New York or in San Francisco. And I think the response to that is then right. Like why not tax all vehicles? Why focus on Uber and Lyft specifically, and kind of, sort of, that might be well, if you think that Uber and Lyft are specifically congesting, right? If you think that these companies, you can either target congestion better or that they are saved because of the way that they idle or the way that they pull in and out of traffic, they might be specifically worse for traffic then is your, your average vehicle.
Matt Tarduno (22m 35s):
Those are the situations where you’d want to say, okay, a congestion tax is a well-targeted instrument. And so what I find from the awesome paper is like, that doesn’t seem to hold up, but it would be great if we had kind of another natural experiment in San Francisco or, or in New York where if somebody could answer those questions that like, is it the specific way that these vehicles drive that kind of would rationalize attacks targeted just at them? And you had one other point, which was, are there kind of places or times, right where you might really want to impose regulation on Uber and Lyft. And I do like the idea of say at airports or specific areas say you had a specific example that you incited in, in Austin of like where, you know, transit might be specifically bad, but I live in Berkeley and there’s kind of in downtown Berkeley, there’s just like one segment of storefronts, which are incredibly popular for takeout.
Matt Tarduno (23m 32s):
So Uber eats and people jumping in and out, there’s an acute congestion problem. And it seems to be specifically Uber and Lyft. And so I’m not saying to the Berkeley city commissioners that they should look into this, but if you were to imagine scenario where if we were to want to taxi Uber or Lyft, it would be because of a situation like that, because those cars more than other cars are kind of contributing to the problem. But I think overall, right, cities in terms of congestion, just have a total VMT problem. They don’t seem to have a ride sharing problem right now.
Jeff Wood (24m 4s):
I’d probably agree with that. I think that it’s an overall kind of travel problem. And as we finding out through the pandemic, you know, the delivery increases that are happening in cities are getting bigger as well. And so it’s not just ride hailing. That necessarily is the problem. But overall transportation impacts that, you know, when, when you can’t get your bus through an intersection, because there are too many vehicles, whether it’s Uber or Lyft or somebody’s personal vehicle, that tends to be a problem. And I do like your idea about, and you mentioned it kind of when one in your recommendations about zonal charging, where basically if you have a space, like you were just mentioning in Berkeley that has this really kind of a crush of people trying to get there. And I’m thinking about curb kind of management type stuff, there might be a benefit to figuring out how to tax, you know, curb access.
Jeff Wood (24m 48s):
And that might not just affect, you know, delivery drivers. It would affect the deliveries that are not food, et cetera, or people. It would also affect packages and those types of things from FedEx ups, et cetera. And so that might be an interesting way to look at things is if you’re thinking, if you’re worried about congestion, or if you’re worried about, you know, people getting to where they want to go in, in a reasonable amount of time, it might be to target those specific places where people are going. Another thing I found interesting from your research was that a lot of the congestion that you’re finding was not coming during rush hour, it was coming during kind of mid day trips. And so that was something that I think kind of targets that specific thing that we’re talking about before with the zonal charging is that those are the trips that are happening, that wouldn’t have happened before that maybe you’re causing problems.
Matt Tarduno (25m 32s):
Yeah. Precisely. And right, if we think about what’s actually happening with these platforms, kind of, there, there is like a rationing going on within them. You could imagine that people aren’t using Uber and Lyft during the middle of the day, the same way that they are in the evening hours, right. There’s surge pricing and people might be more willing to carpool in the evenings. And then overall, if you look at kind of the profile of Uber and Lyft trips, so I use ride Austin’s data actually to kind of get a sense of when people are using more or less ride sharing during the day. And it of course peaks during evening rush hour, but relative to other traffic is highest during the middle of the day. And that might be right. I don’t have specific data on this, but one reason for that could be exactly what you propose is that that’s when you have additional trips and those additional trips might be the trips that are just a single occupant.
Matt Tarduno (26m 21s):
And so you, don’t kind of also benefit from that ride sharing effect.
Jeff Wood (26m 26s):
It would be interesting to know kind of where those trips all went after Lyft, Uber, Lyft, Austin. Because another thing that I’ve been thinking about when I was reading through the paper was, you know, Portland and Joe Cortright, and some others have calculated the, what they are calling a green dividend. And so if you can reduce VMT and get more people, riding, biking, active transportation modes versus driving, you actually take money away from interests that are exporting money outside of the region. Right. So if you’re driving your car, you’re paying a gas company, who’s going to take a lot of those profits out of the region and put it somewhere else. But if you’re spending that money locally, you know, you’re actually driving the local economy. And I’m curious if there’s like some sort of effect like that, that might happen if that might’ve happened.
Jeff Wood (27m 7s):
Even in Austin, after Uber and Lyft left since the money that wasn’t necessarily leaving the city.
Matt Tarduno (27m 13s):
Yeah. So I’m not so sure about money, but I can speak to the first question of kind of where are these trips going? And so this isn’t from, from my research, but some great research by Hampshire at all out of university of Michigan, did a survey after Uber and Lyft exited Austin. And they just asked people kind of, okay, think of, first of all, do you use these companies, second of all, think of a reference trick, a reference Uber or Lyft trip. And now that these companies are no longer available to you, what do you use instead? And I think this was in November of 2016. And so a fair share of people had transferred over to an alternative ride sharing service that was about half, about 40%.
Matt Tarduno (27m 55s):
Didn’t take the trip at all. And then there was kind of a small share for, for biking and walking, but it wasn’t a huge amount of trips that were replaced by kind of like an alternative method of transportation or a kind of walking or biking or something that you might imagine is kind of has these positive local impacts. I think it’s an interesting question about where the money is going when you’re using like transportation services and specifically, right. Uber and Lyft have been kind of criticized for eroding revenues of city governments, and people are using parking less or registering vehicles, less registering for parking permits less.
Matt Tarduno (28m 35s):
And I think right, one of the upshots of the paper is maybe you don’t want to tax Uber and Lyft for congestion purposes, but I want to be careful to say that that doesn’t mean you shouldn’t text them generally. You just might want to do it for another reason. And I think it’s a perfectly fine idea to target those companies. If you think that there are eroding a revenue base and they’re using your public good, right. They’re using the streets and the roads. And so it shouldn’t be the case, right. That they can kind of like go to whatever city in the U S use that public infrastructure and then siphon the revenues to San Francisco or wherever their headquarters.
Jeff Wood (29m 9s):
Yeah. And I think that’s kind of the argument as well for even a congestion charge generally, is that you can take that money and put it into transit, or you can put it into other transportation modes that help the people that aren’t driving or they’re not taking ride hail, et cetera. So it’s an interesting thought about that kind of transfer that cities are thinking about,
Matt Tarduno (29m 24s):
Right? Yeah. So my advisor here at Berkeley, Jim Sully, he’s working on a paper right now. That’s kind of trying to answer this difficult question about who bears the cost of congestion and what you could do with the revenue in terms of trying to make whole Or reduce the regressivity Oh, these policies. Right. So it’s one thing to kind of like sit here and talk about efficiency and congestion pricing, but it’s, it’s well established, right? If you’re not careful about what you do with the money, that’s going to have a regressive impact. So the question is, how do you want to spend those funds? Is it best to just give people rebates? Can you kind of identify the losers from this policy and try to make them whole, or is it better to kind of target other areas where you think there could be a beneficial public good provided public transportation, for example, and one, is that going to benefit the right people?
Matt Tarduno (30m 18s):
And two, is that going to kind of bolster the popularity of these policies in general? Because that’s one big hang up is kind of in the March to make better use of our existing transit infrastructure through congestion pricing, you have to make these policies politically palatable. And I think one way to do that, that I know San Francisco and New York are thinking really hard about right now is exactly the right, like who needs to pay, who gets reimbursed and what projects the money gets spent on.
Jeff Wood (30m 46s):
Yeah. Tough questions for sure. Especially if you think about politics and the way it operates at the moment, even in San Francisco, which is a weird duck for some, you know, we had Haley Rubinson from revel on recently in the last couple of weeks and, you know, they left Austin because, you know, there wasn’t much happening. Part of it was I think the, the way that the city’s laid out the density of the city, you know, the short trips are, are harder to make. I think if you’re a less density and less places to go. And then also, you know, because of the pandemic, there has been a lack of festivals and, you know, things that would attract people to a place like Austin typically. And it makes me think about, you know, what happened after ride hailing left.
Jeff Wood (31m 27s):
And it makes me also think about, and we talked about this a little bit, but like the density of cities and what that means for these services. And is it the same to, you know, be worried about congestion inside the core versus kind of on the periphery where, you know, even the ride hailing companies have a hard time making any money or drivers hard time making any money because of the deadhead trips and things like that. I’m curious if you have any thoughts about density and what that means for these services as a whole.
Matt Tarduno (31m 54s):
Sure. Yeah. I think one thing just kind of a blanket statement is that we have to be very careful for any findings, according from one city to another city, right? Cities have idiosyncratic geography and transit systems, and it’s, it’s really hard to make general statements that being said, I guess, one kind of like way to help thinking about congestion. Congestion is an externality that you may want to price because it has extra costs on other users. And so there’s kind of a distinction to be made between this like gross BMT and the implications that, that might now is having to say, like moving a city away from a Rhone base transit network to a system that’s based on bikes or trains or buses, that could be one policy goal, but that’s not directly related to congestion.
Matt Tarduno (32m 53s):
Right? Congestion is a problem of people not bearing the full consequences of their actions. Right. And so I think it’s useful to when thinking about policy and whether or not you want to price road say to, to disentangle those, those two goals. And so there might be kind of a synergy in between them specifically, if the projects that you need to bring us away from kind of a 1960s view of a car-based city, conduction pricing might be one policy to help you gain the revenue to do that, but it’s not necessarily the right policy for every city. If every city doesn’t kind of have these well, like easy to target problems with really acute congestion where people are not kind of exposed to the bulk cost of their actions, then it might not be the right policy tool.
Matt Tarduno (33m 35s):
Right. If you have a really sprawling city and it’s not easy to price the right roads, or if you just end up say pricing segments or roads where people substitute to another road, and that’s not really a policy that is kind of achieving the congestive pricing ideal, I would say,
Jeff Wood (33m 51s):
So what’s next in terms of the direction of your research, where it’s going, and is there anything else that you want to know moving forward after writing this paper? I’m sure there’s many things, but
Matt Tarduno (34m 0s):
Sure. Yeah. So I’ll say two, yeah. Two research projects that are kind of related. So the first is a project in the Bay area and I’m looking at transit. So traffic congestion, traffic composition, and local air pollution. And so this is a similar project where I’m just like looking at potential policies that would impact the way that people use roads and what vehicles use them. And don’t, but this time, instead of looking at the impact on other drivers and travel speeds, I’m looking at the impacts on local air pollution, right? Another kind of significant urban amenity. And so to do that, I’m kind of taking data from Google self-driving cars, which for the past couple of years have been retrofitted with air pollution, sensing devices.
Matt Tarduno (34m 47s):
And so they have, you know, millions of data points throughout the Bay area, me this really fine scale resolution image of air pollution for the region. And then what I want to do is ask, okay, what are the, what are the main drivers of that local air pollution from the transit system? And what would an optimal policy look like if we were to target those local air pollutants? Right? So we have evidence already that road pricing or congestion pricing can have local air pollution benefits. So there’s a study from Milan showing that their congestion price had benefits for local air pollution. But the question is right, is that because cars are driving faster and they’re more efficient when they drive faster, is it just that we’re taking cars off the road and you can just as efficiently do this by say, having a tax, or is it a story about composition?
Matt Tarduno (35m 40s):
Right? Most of the pollution comes from a very small facet far as being disliked, diesel trucks and light duty trucks rather than your Prius’s et cetera. So that’s kind of broadly construed the, the, the research question there. And then, you know, the, the second question, and this is something that I think would be a smaller research project, but it’s directly related to by Uber paper is we actually have cities, right. That have taxed in Grinnell. And so that’s San Francisco, New York and Chicago, some of those went into place during the pandemic. So that’s kind of hard to figure out exactly what’s going on. And then what that would look like in a world where people are making decisions like they would, if they were all vaccinated, for example.
Matt Tarduno (36m 23s):
But given that data, you kind of no longer have to speculate about how these companies would respond to taxation. You can, you can say, Hey, look what we found these results from Austin. It doesn’t look like there would be big confession impacts. If you were to tax these companies, then you can take it to another city and try to answer that question as is. And hopefully that would give us some insight as well. And to kind of your questions. Well, Austin is Austin and San Francisco, San Francisco. They’re very different places. So you kind of have like real policies in different cities. That’s another thing that I would love to dive into. I wonder how,
Jeff Wood (36m 55s):
How much the pandemic just changes all the calculus in terms of travel, right? I mean, all these companies that want some of their workers to stay home twice a week, or they allow them to stay home twice a week. I wonder if there’s a negative impact on, you know, the things that I love transit and active transportation, or there’s maybe a positive maybe because you’re only coming into the office three times a week. You think you can afford not to take that auto trip because you feel like you have a little bit more time who knows. So it’s interesting to see kind of how all this stuff will either evolve, change, or kind of get thrown out the window when it comes to the after effects. Yeah. There are a lot of counters
Matt Tarduno (37m 32s):
Bailing forces going on here and remains to be seen how much coronavirus will be a problem in 2022, kind of what happens with bird immunity and vaccination. But yeah, you can imagine right now, seeing people are really staying away from public transit and sticking to passenger vehicles. But at the same time, you have this kind of counteracting force where people are staying home more. So at least in the Bay area, traffic and congestion are down, but you can imagine how that would be a different story as workplaces, if workplaces open up and we don’t see the return to public transit to levels for demand. Yeah.
Jeff Wood (38m 6s):
We’ll find out Matt, where can folks find you on
Matt Tarduno (38m 11s):
Mine? You can find me on Twitter. That’s at Matt Parvino that’s T a R D U N O. And you can also check out my website. That’s Matt dash, Parvino at get home dial. And so in addition to, you can find the ungated version of my paper. So unfortunately, the actual paper, you have to get past a paywall, but I have drafted my paper up on my website, as well as some other fun things, political economy projects about voting and renewable portfolio standards, as well as a little bit about me. Cool.
Jeff Wood (38m 46s):
And also in the show notes, I’ll post the link to the paper that you have ungated and we’ll get that out there as well. So people can take a read if they want to dive deeper. Well, Matt, thanks for joining us. We really appreciate it.
Matt Tarduno (38m 56s):
Yeah. Thanks for having me.
Jeff Wood (39m 2s):
And thanks for joining us. The talking head waste podcast is your project of the overhead wire on the [email protected]. Sign up for a free trial, the overhead wire daily, our 14 year old daily cities news list by clicking the link at the top, right of the overhead wire.com. And please, please, please put the pod going to pitch on.com/the overhead wire many thanks to our current patrons for their ongoing support. And as always, you can subscribe to this podcast on iTunes, Stitcher, SoundCloud, overclass Spotify, and wherever you get your podcasts. And you can always find a traditional home at USA dot Street’s blog.org. See you next time at Talking Headways
