Tag: uc berkeley

• How clustering makes us all more productive and innovative

  

  Earlier this year, Enrico Moretti, who is a professor at UC Berkeley, published this research paper looking at the effect of high-tech clusters on productivity and innovation. (I am unclear if there is any relationship to the Italian brewing company Birra Moretti.)

  One of the things he looks at in the paper is the decline of Kodak. Headquartered in Rochester, New York, Kodak famously missed the transition to digital photography. And so by the late 1990s, they were forced to start letting people go. The result was an almost 50% decline in the size of the entire “high-tech cluster” in Rochester.

  But what Moretti goes on to test in his paper is the impact that this employment decline had on productivity and innovation outside of Kodak and outside of the photography sector (but within Rochester). And what he found was that between 1996 and 2007, the productivity of non-Kodak inventors dropped by about 20%!

  This, of course, is one of the great features of cities. Even if you’re not working at some big company with lots of smart people, just being in the same city, on the same block, or within the same office building, can make you more productive. It turns out that business ecosystems are pretty interconnected. Spillovers are important.

  For more on this topic, check out this recent Wired article by Viviane Callier. In it she makes the case that remote work is going to negatively impact productivity and innovation over the long run.

  Photo by Yassine Khalfalli on Unsplash

  2021.09.03

• How many people showed up to the Raptors’ championship parade? (Hint: We don’t know)

  Today was a historic day for Toronto, for Canada, and for the game of basketball in this country. The Toronto Raptors are world champions for the first time since their founding in 1995. Soak it in. Here is a photo that I took of the parade coming through the Financial District at around 2:30pm:

  

  Some of the estimates going around are that 1 to 2 million people attended today’s championship parade. But 2 million seems like a lot, even though today was frenetic (see above photo, again). I mean, that’s 1/3 of the population of the Greater Toronto Area.

  The fact that some of the “official” estimates also have a 1 million person spread tells me that, as of right now, we actually have no idea how many people were at today’s parade.

  So that got me thinking: How do people count crowds? And are we using drones to do it, yet? Subway and rail ridership for the day — which surely spiked — will give us some indication. But definitely not the full picture.

  It turns out that the typical approach to counting crowds is known as Jacobs’ Method. It was invented in the 1960s by a professor at UC, Berkeley, named Herbert Jacobs. He came up with the method while trying to count the number of students protesting the Vietnam War.

  The concept is simple: It’s area x density. And permutations of his method usually use this same principle. What you do is take the area filled with people, break it up into a smaller grid, and then come up with a population density estimate for each square.

  He had some rules of thumb for that. A light crowd was about 1 person per 10 square feet. And a dense crowd (such as a mosh pit or an NBA championship parade in Toronto) was about 1 person per 2.5 square feet.

  Using this method and aerial photos of today’s parade, I would imagine that we could eventually get to a more precise estimate than 1 to 2 million people. But surely somebody has figured out how to program a drone (or other UAV) and do this even more accurately.

  Crowd data is valuable information, particularly for political rallies and protests (I would imagine). If you know of a company doing this, please leave it in the comment section below. And if it doesn’t yet exist, well then, now you have a new business idea.

  2019.06.17

• Housing supply and displacement in San Francisco

  

  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

  2018.09.15

• Interactive map of carbon footprints across America

  Atlantic Cities recently published an article called, “Beefing Up Population Density Won’t Curb Greenhouse Gas Emissions.” And in it, they link to a really neat interactive map created at UC Berkeley that outlines the carbon emissions of nearly every zip code in America (2013 numbers). 

  Not surprisingly, it shows that urban folk generally have a much smaller carbon footprint as compared to suburbanites. Here’s what New York City looks like (green is lower carbon emissions and red is higher):

  

  But the article also goes on to say that the solution is not to work towards increasing population densities in either urban centers or suburbs. And that, in fact, efforts to increase population densities in the suburbs would only make things worse—emission levels have been shown to only go up and then new suburbs end up getting formed around the intensified ones.

  I understand the last point about endless suburbs, but I don’t fully understand this recommendation. Do carbon emissions go up in the suburbs when population densities are increased because it still remains car dependent and so all you have is more people driving?

  Intuitively, it would seem that if more people stopped driving, shopped locally and lived in more compact spaces, carbon emissions would fall. But perhaps I’m missing something.

  If anyone has any insights on this topic, I would love to hear from you in the comment section below or on twitter.

  2014.01.11