The first empirical evaluation of New York's congestion pricing has just been published.
Spoiler: It worked really, really wellđź§µ
First, what is congestion pricing?
It's an added fee sent to drivers when they drive on certain roads, at certain times, in order to dissuade people from using the road when they don't need to.
The initiative aims to cut down on needless overuse, leading to slow roads.
Congestion pricing, in New York, acts as a sort of redistribution:
Because people pay to get into Manhattan, fewer go in, and the payments that would go to paid parking lot owners are effectively redistributed to the city government.
Congestion pricing can improve land use!
Congestion pricing should also increase the use of public transit, like the subway and buses and such.
This also helps with the redistribution from inefficient land users in Manhattan to the city government, and it's fine because transit has lots of excess capacity.
The way congestion pricing was evaluated was by using a "synthetic control".
The data from NYC was compared to the data from a counterfactual NYC based on data from other, comparable cities.
The estimate is New York (real) vs New York (projected without congestion pricing).
Some of the data underlying this model looks like this.
In this example, we can see average daily speeds within New York's Central Business District (CBD) in red and in comparison cities in gray.
Notice the jump around congestion pricing being introduced?
With that data, we can compare real New York to the ensembled New York and get this result, our treatment effect of interest.
On average, road speeds went up by a whopping 16%!
But here's something interesting:
Speeds on highways went up 13%, arterial road speeds went up by 10%, and local road speeds increased by 8%.
None of that's 16%, and that's important: This means congestion pricing sped roads up, but also sorted people to faster roads.
In response to having to pay a toll, people not only got off the road, they also made wiser choices about the types of roads they used!
Now let's look at the times of day, as a check on the model
It works: Congestion pricing just boosts speed when it's active and shortly after:
As another check, let's look at the effects by location.
In the CBD, trips are faster. Going to the CBD, trips are faster. Leaving it, trips are faster, but not much. And outside of it, where congestion pricing is irrelevant? No effect.
This policy has economic benefits and incentive benefits, but it also helps residents of New York who aren't directly paying the fee.
This is because vehicle emissions are down!
They're down the most in the areas with the highest rate exposure (co-occurrence), too.
The policy is also fair: The impacts do not fall on particularly low- or high-class neighborhoods, and the distributional impacts are thus pretty much neutral, with some regional differences.
The big effect is really just that people are able to get into the city more reliably.
In short, congestion pricing, though only briefly in place, has been a rousing success.
But New Yorkers don't seem to mind if the policy goes. They seem to prefer being able to freely waste time in traffic, even though it's inefficient and boring.
As an added note, subway ridership was increasing and, more interestingly, with congestion pricing, more people were choosing to take the express service buses.
Because of the reduced traffic, those buses were also making their trips much faster.
This research directly militates against modern blood libel.
If people knew, for example, that Black and White men earned the same amounts on average at the same IQs, they would likely be a lot less convinced by basically-false discrimination narratives blaming Whites.
Add in that the intelligence differences cannot be explained by discrimination—because there *is* measurement invariance—and these sorts of findings are incredibly damning for discrimination-based narratives of racial inequality.
So, said findings must be condemned, proscribed.
The above chart is from the NLSY '79, but it replicates in plenty of other datasets, because it is broadly true.
For example, here are three independent replications:
A lot of the major pieces of civil rights legislation were passed by White elites who were upset at the violence generated by the Great Migration and the riots.
Because of his association with this violence, most people at the time came to dislike MLK.
It's only *after* his death, and with his public beatification that he's come to enjoy a good reputation.
This comic from 1967 is a much better summation of how the public viewed him than what people are generally taught today.
And yes, he was viewed better by Blacks than by Whites.
But remember, at the time, Whites were almost nine-tenths of the population.
Near his death, Whites were maybe one-quarter favorable to MLK, and most of that favorability was weak.
The researcher who put together these numbers was investigated and almost charged with a crime for bringing these numbers to light when she hadn't received permission.
Greater Male Variability rarely makes for an adequate explanation of sex differences in performance.
One exception may be the number of papers published by academics.
If you remove the top 7.5% of men, there's no longer a gap!
The disciplines covered here were ones with relatively equal sex ratios: Education, Nursing & Caring Science, Psychology, Public Health, Sociology, and Social Work.
Because these are stats on professors, this means that if there's greater male variability, it's mostly right-tail
Despite this, the very highest-performing women actually outperformed the very highest-performing men on average, albeit slightly.
The percentiles in this image are for the combined group, so these findings coexist for composition reasons.