Joe Cortright recently wrote about a study by Kate Pennington (UC Berkeley), which looked at the impact of housing production on legal eviction in San Francisco. The goal was to figure out if new housing supply actually causes displacement.
To do this, Pennington went block-by-block and looked at new housing projects, as well as over a decades’ worth of eviction notices.
The relationship between the two was found to be “statistically indistinguishable from zero.” In other words, the “monthly probability of an eviction notice” does not change when new housing supply is completed nearby.
Some have been critical of her findings and some have questioned whether legal eviction notices are, in fact, the right proxy for displacement.
But I agree with Joe Cortright in that this still feels like a meaningful relationship to understand, especially when we’re talking about a tight housing market like San Francisco’s.
Photo by Matthew Cabret on Unsplash
Joe Cortright of City Observatory recently published a post about the types of policies that cities should be looking to adopt in response to autonomous vehicles. It’s called:
Joe Cortright recently wrote about a study by Kate Pennington (UC Berkeley), which looked at the impact of housing production on legal eviction in San Francisco. The goal was to figure out if new housing supply actually causes displacement.
To do this, Pennington went block-by-block and looked at new housing projects, as well as over a decades’ worth of eviction notices.
The relationship between the two was found to be “statistically indistinguishable from zero.” In other words, the “monthly probability of an eviction notice” does not change when new housing supply is completed nearby.
Some have been critical of her findings and some have questioned whether legal eviction notices are, in fact, the right proxy for displacement.
But I agree with Joe Cortright in that this still feels like a meaningful relationship to understand, especially when we’re talking about a tight housing market like San Francisco’s.
Photo by Matthew Cabret on Unsplash
Joe Cortright of City Observatory recently published a post about the types of policies that cities should be looking to adopt in response to autonomous vehicles. It’s called:
Many have argued, including urban economist Edward Glaeser, that autonomous vehicles are going to be positively disastrous for cities. Once you remove the labor costs associated with the driver and the overall price per kilometer plummets because of pooling/technological advances, we are going to see an huge surge in demand – well beyond the capacities of our roads.
Of course, there are solutions. We can accurately price the roads, which is something that more cities should be doing today even before autonomous vehicles arrive. Here is an excerpt from Cortright’s article:
“With modern electronics, and especially with autonomous vehicles, position and speed is monitored with great precision. There is no reason why they [drivers] should not pay for exactly the amount of roadway that they use. And we know that the cost of the city’s roadway varies substantially across space and over time. Use of road capacity in less dense neighborhoods at off-peak hours imposes nominal costs on the city’s road budget. In contrast, peak hour use of city streets and arterials, particularly in and near the city center, imposes huge costs on the city and its residents. Those who use the system at peak hours in congested locations should pay the costs associated with creating, maintaining, and where necessary expanding that infrastructure.”
This isn’t a novel concept, which is why when Toronto was looking at a flat road toll I argued here on the blog that it was a step in the right direction but that it was too blunt a tool.
It’s a moot point now because sadly the province ended up pandering and rejecting the plan, but we should have been considering something that could achieve the above objectives. It needed more finesse.
But in all likelihood our cities will have to face that reality sooner rather than later.
Joe Cortright of City Observatory recently published an interesting post on HOT lanes (high-occupancy toll lanes) and cited a research paper by Austin Gross (University of Washington) and Daniel Brent (Louisiana State University). The paper looked at the behavioral response of drivers to dynamic HOT lane pricing.
They way HOT lanes work is simple: when traffic is light, the price dynamically decreases; when traffic is heavy, the price dynamically increases to ensure a minimum level of service. That is, the price increases until enough cars leave the lane and driving speeds increase to some minimum threshold. In this case, it’s 45 mph.
The key takeaway from the report is that “value of reliability” appears significantly more important to drivers than “value of time”. Put differently: it’s less about the time I’m wasting in traffic and more about the uncertainty of not knowing when I’m going to arrive at my destination.
It’s for this reason that HOT lanes are used more frequently in the morning (when you’re running late for that meeting) than in evening (when you’re just on your way home from work).
Gross and Brent estimate that the spread is about 7.5x. The typical driver values saving time at about $3 per hour and reliability improvements at about $23 per hour! This is fascinating because we tend to focus a lot on time. But arguably what people really want to buy is greater certainty.
I can tell you that it’s definitely one of the things that I love about walking to work, or for that matter cycling somewhere. I always know how long it’s going to take.
Many have argued, including urban economist Edward Glaeser, that autonomous vehicles are going to be positively disastrous for cities. Once you remove the labor costs associated with the driver and the overall price per kilometer plummets because of pooling/technological advances, we are going to see an huge surge in demand – well beyond the capacities of our roads.
Of course, there are solutions. We can accurately price the roads, which is something that more cities should be doing today even before autonomous vehicles arrive. Here is an excerpt from Cortright’s article:
“With modern electronics, and especially with autonomous vehicles, position and speed is monitored with great precision. There is no reason why they [drivers] should not pay for exactly the amount of roadway that they use. And we know that the cost of the city’s roadway varies substantially across space and over time. Use of road capacity in less dense neighborhoods at off-peak hours imposes nominal costs on the city’s road budget. In contrast, peak hour use of city streets and arterials, particularly in and near the city center, imposes huge costs on the city and its residents. Those who use the system at peak hours in congested locations should pay the costs associated with creating, maintaining, and where necessary expanding that infrastructure.”
This isn’t a novel concept, which is why when Toronto was looking at a flat road toll I argued here on the blog that it was a step in the right direction but that it was too blunt a tool.
It’s a moot point now because sadly the province ended up pandering and rejecting the plan, but we should have been considering something that could achieve the above objectives. It needed more finesse.
But in all likelihood our cities will have to face that reality sooner rather than later.
Joe Cortright of City Observatory recently published an interesting post on HOT lanes (high-occupancy toll lanes) and cited a research paper by Austin Gross (University of Washington) and Daniel Brent (Louisiana State University). The paper looked at the behavioral response of drivers to dynamic HOT lane pricing.
They way HOT lanes work is simple: when traffic is light, the price dynamically decreases; when traffic is heavy, the price dynamically increases to ensure a minimum level of service. That is, the price increases until enough cars leave the lane and driving speeds increase to some minimum threshold. In this case, it’s 45 mph.
The key takeaway from the report is that “value of reliability” appears significantly more important to drivers than “value of time”. Put differently: it’s less about the time I’m wasting in traffic and more about the uncertainty of not knowing when I’m going to arrive at my destination.
It’s for this reason that HOT lanes are used more frequently in the morning (when you’re running late for that meeting) than in evening (when you’re just on your way home from work).
Gross and Brent estimate that the spread is about 7.5x. The typical driver values saving time at about $3 per hour and reliability improvements at about $23 per hour! This is fascinating because we tend to focus a lot on time. But arguably what people really want to buy is greater certainty.
I can tell you that it’s definitely one of the things that I love about walking to work, or for that matter cycling somewhere. I always know how long it’s going to take.
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