During the pandemic, there was a lot of erroneous talk about the death of cities. Much like when the consumer internet first came around, the thinking was that technology would make geography irrelevant. I was and am vehemently against this idea, but it's hard to not feel like technology is doing something. But what exactly? According to Richard Florida, Vladislav Boutenko, Antoine Vetrano, and Sara Saloo, it is creating something called the Meta City:

The various communities that make up the Meta City may be in different time zones and noncontiguous locations, but they function together as a coherent network with a distinct structure and logic. The Meta City combines physical and virtual agglomeration, in seeming defiance of the laws of physics, making it possible to occupy more than one space at the same time. As a result, urban areas within the Meta City network can share economic and social functions.

The narrative is compelling. Cities have always responded to and been a product of new mobility technologies. Streetcars, subways, and the car have all reshaped the geography of our cities. Some would argue for the worse. What the Meta City proposes is that technology today is not a disruptor of cities, it is simply another mobility shift. Rather than make cities irrelevant, it actually makes them more important by expanding their reach:

The pandemic-era shift to remote work is yet another technology stretching the boundaries of the city into a new and larger geographic unit. But instead of doing so physically, it does so by enabling virtual expansion. The share of American workers engaged in remote work tripled from roughly 6% in 2019 to almost 18% in 2021. Remote workers can access significant quality of life at far more affordable prices in smaller cities, suburbs, and rural areas.

Some specific examples:

Many of these rising places are critically connected to established cities. As we will see, Austin’s rise is best understood as a satellite of San Francisco’s long-established tech hub. Miami is enmeshed in New York City’s finance and real estate complex. The rise of the Meta City informs a counterintuitive logic: Leading superstar cities are seeing their role as economic hub expand, even as some talent and some industry disperse to satellite centers.

Finally, here's their ranking:

If you believe this to be true, then it should be good news for the real estate located in the cities listed above. But it also means that we are now facing a new kind of hub-and-spoke model of urbanism. London and New York remain at the center, but tech is only strengthening their reach and influence. This is a new way of thinking about the flow of human capital around the world, and I'm sure it will have impacts on how we plan and build our cities.

Image: Harvard Business Review

We know that educational attainment is probably the single biggest determinant of urban economic success. If you're hoping to predict average household incomes, looking at the percentage of the population with a 4-year college degree is a pretty good place to start. But let's take this a step further: to what extent does graduating from an elite university affect both pay and performance?

It turns out, according to this recent study, that the pedigree of one's university isn't all that good at predicting motivation and talent. It does, however, impact pay. Average early career salaries for graduates of the top 10 colleges in the US are almost 50% higher than those with degrees from the ten colleges within the City University New York school system. This is according to data from Payscale and the US Department of Education.

But this pay delta doesn't necessarily match the performance delta that you might expect. The study found that for every 1,000 positions that you move in Webometrics' global university ranking (which is what they used for their research), overall performance only changes by about 1.9%. In other words, a graduate from the alleged number one university is only going to perform, on average, about 1.9% better than someone from the 1,000th best school.

I'm not exactly sure how to practically interpret a 1.9% improvement in performance. But 2% compounding on 2% each year should get you somewhere. Regardless, graduates from top universities do generally score higher on competency examinations. The reasoning behind this is thought to be at least twofold: 1) more selective admissions create a better pool of students and 2) top universities should provide better training.

Whether that's enough to justify the higher pay is a separate discussion. But if you're looking to measure urban economic success, the data does suggest that elite universities should lead to overall higher average incomes.

Ever notice how whenever you’re taking an Uber the driver usually gets another fare just before he (Uber drivers are overwhelmingly male) is about to drop you off? That’s on purpose.

Earlier this month the New York Times published an interactive feature describing how Uber uses behavioral economics (or psychological tricks) to encourage its drivers to work longer, take more fares, and so on.

Here’s a quick sidebar note about behavioral economics from Francesca Gino of Harvard Business School:

According to the traditional view in economics, we are rational agents, well informed with stable preferences, self-controlled, self-interested, and optimizing. The behavioral perspective takes issue with this view and suggests that we are characterized by fallible judgment and malleable preferences and behaviors, can make mistakes calculating risks, can be impulsive or myopic, and are driven by social desires (e.g., looking good in the eyes of others). In other words, we are simply human.

And now back to Uber. One tactic they use is goal setting. People are drawn to goals. This translates into driver messages like this one: “You’re $10 away from making $330 in net earnings. Are you sure you want to go offline?”

But the experiment I found most interesting from the NY Times piece is the one that Lyft completed where it discovered that showing drivers lost/dropped fares was a far more powerful motivator than showing completed rides. In other words: Look at all this money you’re losing out on by not driving!

This finding is in line with something I’ve written about a few times before on this blog: prospect theory. One of the tenets of this theory is that “losses hurt more than gains feel good.” We, humans, tend to focus more on the former.

Of course, Uber is not alone in employing behavioral economics. Every app on your phone is being continuously optimized so that it gets as much of your attention as possible. But where is the line between encouragement and manipulation?

If you’re interested in this topic, check out this HBR article called, Uber Shows How Not to Apply Behavioral Economics.