Talking Headways Podcast: Congestion Pricing Data Collection

This week on Talking Headways, we’re joined by Stephen Crim, director of policy and analytical reporting for the New York MTA’s Central Business District Tolling Program.

We chat about the MTA’s one year data report on congestion pricing — including some of the results and how the data was collected. Stephen also discusses the numerous government data partnerships and enhancements including air quality monitoring and what other cities can look to in order to consider future pricing schemes.

Scroll past the audio player below for a partial edited transcript of the episode — or click here for a full, AI-generated (and typo-ridden) readout.

Jeff Wood: When did you all first start collecting data for this report?

Stephen Crim: It depends on when you wanna look at it. I think the important thing to realize is that this report is a real partnership, right? And it’s a partnership between our data science team at the MTA, the New York City Department of Transportation [and the] New York State Department of Transportation. Some of the data that you see in there has been collected for many years as part of data collection programs that predate this program.

New York City DOT, for example, has done work with data coming from the taxi and for-hire vehicle industry for a long while. But I think the analysis and compilation started to come together in 2022, even before I got here, because pulling something like this together is a major achievement, a major undertaking. Even though it took a while from 2019 to program start, there was work going on in those years to lay out: How are we gonna deliver this? What data and what measures, what things, are we going to report on to fulfill our requirements?

Because this is all the requirement of legislation, but, the legislature didn’t tell us, oh, “Measure this metric, or go out and get data on this specific thing.” It just said, “Report on these topics.” It’s been a long time coming. The system that tolls vehicles coming in to the toll zone got constructed or installed in 2023 through 2024, and so that was one of the last data pieces to come online. But a lot of this is us aggregating the work of many others who have been gathering data, preparing data, for many years.

Jeff Wood: So I’m curious then, how do you decide on what data points to collect and which ones are important? I’m sure it’s a consortium of people that come together and it wasn’t like a one person. I’m curious like how that comes together.

Stephen Crim: Yeah, again, I’ll say that some of this was shaped by the enabling legislation. When this program was enabled in 2019, there was a section of a law that called for a report to be delivered one year after the program began on a range of topics.

And I have that listed here to make sure I remember all of them: Traffic congestion in and around the zone, volumes and types of vehicles coming into the zone, transit use and bus speeds, taxi and for-hire vehicle use, air quality and emission trends and the money coming in and expenses from the program.

But those are broad, right? So some of our process was just saying, “Okay, what is readily available? What can we use?” Because we knew that we were gonna have this system tolling people, or tolling vehicles, coming in, so we would have data on those entries, but we don’t have ready-made air quality measures. And then with the Federal environmental review, we made some additional commitments to the federal government as part of our process. One of the most complicated ones was setting up a partnership with New York City’s Department of Health to pay for enhancements and leverage their existing, really sophisticated, air quality monitoring system around the city, because that was something where there wasn’t just some ready-made source.

So we tried to find as many places as possible, “Okay, what is somebody else already reporting?” And that’s why I say, the data on this has been in process for years. We knew we were gonna be building this system and in a few cases it was just a case of, okay, I guess we have to go out and do this data collection.

Jeff Wood: Yeah, it’s difficult. I did an equity atlas, back in the early 2010s, for the city of Los Angeles. And one of the things that was frustrating was the lack of data that was available for time series, evaluation. You could look at county health data, but it was even at the county level versus like a parcel or even, a block or anything along those lines.

So this is very fine-grained data and so I imagine that’s difficult in its own right, is trying to find something of a before and an after when you know, now you have more after data, but the before data was very, sparse, I imagine.

Stephen Crim: I want compliment our colleagues in the region. I think New York is blessed with a lot of resources, but it’s still not as much as we may want. It’s also certainly not as much as I think members of the public think exists. So that’s a challenge.

There’s this concept — maybe because of our devices now and our connectivity thinking — that, “Oh, you must have counts of like just everything out there.” And no, we don’t. And you have to be very careful about before/after comparisons. And that was really a lot of the time that went into the creation of this report. It was saying like, okay, we see before [and] after, but do we see a change because something really related to the program changed or is it like, oh wait, no, there was a change in that data source.

That’s the kind of difficult work that really took the involvement of these other agencies in concert with us who knew these data sources to produce the report.