Over the past few months, as my schedule has allowed for it, I’ve spent some time poking around inside the MTA’s datasets. I’ve explored turnstile numbers along the L train in Brooklyn, and I’ve looked at glimpses of exit and entry data at various times of the day. If I had the time and coding skills, I would have explored the fare media breakdown across the system. Luckily, The Wall Street Journal has seemingly done it for me (and you and anyone else who gets lost in data about the subway).
The visualization — available right here in its interactive glory — is a near-textbook use for governmental datasets. Two Journal reporters have provided an unprecedented snapshot into the way we pay. They’ve broken down MetroCard use — pay-per-ride, senior fares, 30- and 7-day Unlimited swipes — by station over time periods both before and after the December 2010 fare hike. It’s quite the glimpse into ridership patterns.
In an accompanying article, Andrew Grossman and Albert Sun discuss their methodology and findings. Essentially, they mapped a few different variables. First, they categorized every MetroCard swipe by type of card. Second, they looked at changes in use during the 27 non-holidays before and the 27 non-holiday days after the December 30th fare increase. They explained some highlights of their findings:
Users of 30-day unlimited MetroCards tend to be wealthier than those who pay per ride, MTA surveys show. Their growing use in neighborhoods such as Greenpoint (up 11.8%) and Bushwick (16.7%) in Brooklyn could point to gentrification under way there. The monthly MetroCard use in those areas came despite a Dec. 30 fare hike pushing the cost from $89 to $104.
The fare hike appears to have hit other neighborhoods harder. In Broad Channel, Queens, about an hour from Midtown Manhattan by subway, use of monthly passes dropped 15.5%. Riders said they had stopped buying it because of the cost. “You are paying more per month if you are only using it going back and forth to work,” said Teri Bautz, a Verizon worker who rides the A train to Manhattan from Broad Channel. “Some months, you have an entire week off. In the beginning it was beneficial, now, not so much.”
According to recent MTA data, overall use of the 30-day card is now around 31 percent. Before the fare hikes, around 33 percent of straphangers used a monthly unlimited. But if anything, the decrease represents a market correction. As I explored last October, MTA demographics surveys revealed that 25 percent of 30-day card users did not reach the break-even point. At the time, that point came on the 46th swipe. When the MTA raised fares, the break-even point for the $104 card moved to 50 rides, and in October 2009, 36 percent of 30-day card users did not reach 50 swipes.
Similarly, Grossman and Sun found that seven-day card use has increased. Although few riders used the 14-day card, it’s likely that many of them switched to the seven-day card either because use patterns or personal economics dictated the expense. Furthermore, some 30-day card users who couldn’t afford to pay $104 at once for a MetroCard likely downgraded to a seven-day card as well. They may pay more over the course of four weeks, but the seven-day purchases allow them greater flexibility for start dates. Still, in 2009, nearly 36 percent of seven-day card users never reached the break-even point (as compared with a pay-per-ride discount), and that trend likely continues today.
Anyway, the map is fascinating. It’s broken down into neighborhoods based upon the areas surrounding the closest subway stops, and the data is tremendous. We can see across-the-board increases in the use of pay-per-ride cards after the fare hikes. In fact, the only stations that didn’t enjoy such an increase were closed due to construction work. The use of 30-day cards declined in the city’s less well-off areas, and seven-day cards rose in popularity at nearly every subway stop after the fare hike.
Over the next few weeks, I’d love to spend some more time with the data. It seems, for instance, that MetroCard purchases break down across socio-economic lines as well as neighborhood and borough, and the data could raise some interesting questions concerning the MTA’s pricing schemes. For now, just enjoy the visualization. It’s a great example of the creativity that can emerge from open data.