Congestion Pricing: Who Really Pays?
I’ve been reading a lot about the MTA’s “summer from hell”, lack of funds, and the potential of congestion pricing in New York City to help reduce traffic and subsidize transit. Most recently, the New York Times published an opinion piece about it which included the following quote:
“Bill de Blasio, the city’s Brooklyn-philic mayor, has his own objections. He describes congestion pricing as a “regressive tax” on lower-income drivers, unfairly making them pay the same toll as the wealthy. The mayor prefers what he describes as a “millionaires tax” to raise money for the subways.
The reality, however, is that New York car owners tend to be better off. For starters, more than half the households in the city are carless, according to a census analysis by the Tri-State Transportation Campaign. The median household income of those with wheels is more than double that of those without — $85,000 compared with $40,630. Writing in The Daily News on Sunday, Veronica Vanterpool, executive director of the tri-state campaign, said, “A regressive transportation policy is what we have now: a system that favors free travel by drivers and ignores the environmental, social and economic costs of car-clogged city streets.”
We agree. Besides, there’s nothing regressive about plowing toll revenue into improvements for mass transit, which is how most low- and middle-income New Yorkers get around. Some might even call it progressive.”
So, I’d like to pose the (five word) question “congestion pricing: who really pays?”
I think this could be cleverly answered through some data simulations which show what neighborhood own the most cars in NYC, general median income data based on neighborhoods, and who claimed they commute by SOV or carpool within census or ACS data. Perhaps by also doing a visualization of those who commute by other modes (transit, bike, ped) and comparing the cost of driving with the cost of transit, as well as the subsidizes that affect driving with the subsidizes that affect transit, it could show who really carries the transportation burden in the City.
Some examples of interesting transportation related data visualization that found can be seen below:
