Brandon Donnelly — Daily insights for city builders. Published since 2013 by Toronto-based real estate developer Brandon Donnelly. — Page 884

What a weekend.

Almost 4,000 people came through the Junction House sales office for our neon popup gallery . At one point throughout the day on Saturday, there was an over 1 hour wait to get in. The team had to implement a viewing time limit in order to keep the line moving.

The event surpassed all of our expectations in terms of visitors and buzz. Many of the local businesses in the area also experienced a pop in foot traffic as a result.

The Downtown Yonge BIA and Neon Demon Studio (as well as many others) did an incredible job coordinating and curating the exhibit. And we are thrilled to have played a small role in bringing it to life.

What is clear to me after this weekend is that people really love neon (and, of course, Instagramming said neon) and that there's a market here in Toronto for a permanent museum. It's going to happen .

For those of you who missed the exhibit, there's no shortage of photos online. Check out #JunctionHouse and #NeonMuseumTO to get started. A big thank you to the entire team for making this happen.

For more information on our Junction House condominium project, click here .

Uber filed its S-1 last week in anticipation of going public in May. The WSJ reported on it, here . These are always interesting documents because you get access to previously private information. Here we can see that Uber's ride-hailing market share in the US is down to 67% (as of February 2019) from 78% two years earlier. Revenue from this business line -- which is the company's biggest -- also seems to have levelled off (chart from the WSJ):

The ride-hailing business today has become a commodity. A lot of people, myself included, simply check to see which service is the cheapest (usually it's Uber vs. Lyft). So this space feels to me like a giant race to build the biggest network and get to something new, whether that be autonomous vehicles or delivery drones. Uber calls this creating a "liquidity network effect." Here's an excerpt from the S-1:

We have a massive, efficient, and intelligent network consisting of tens of millions of Drivers, consumers, restaurants, shippers, carriers, and dockless e-bikes and e-scooters, as well as underlying data, technology, and shared infrastructure. Our network becomes smarter with every trip. In over 700 cities around the world, our network powers movement at the touch of a button for millions, and we hope eventually billions, of people. We have massive network scale and liquidity, with 1.5 billion Trips and an average wait time of five minutes for a rider to be picked up by a Driver in the quarter ended December 31, 2018. Every node we add to our network increases liquidity, and we intend to continue to add more Drivers, consumers, restaurants, shippers, carriers, and dockless e-bikes and e-scooters. We also hope to add autonomous vehicles, delivery drones, and vertical takeoff and landing vehicles to our network, along with other future innovations. Our strategy is to create the largest network in each market so that we can have the greatest liquidity network effect, which we believe leads to a margin advantage.

If you'd like to download a full copy of their filing, click here .

Jens von Bergmann (data analyst and mathematician); Nathanael Lauster (sociologist); and Douglas Harris (law professor) have been working since 2018 on a study of how condominiums are used and occupied across Canada. The goal is to use the results to better inform public and academic debate.

They recently presented some of their early findings at the National Housing Conference in Ottawa and have since made that information public . It is still a work in progress, but already there are some interesting takeaways. To start, here is a chart showing occupied housing units in Canada and in select CMAs:

Not surprisingly, Canada is broadly speaking a nation of single-detached houses. But in our three largest cities -- Toronto, Montreal, and Vancouver -- apartments/condominiums are doing a lot of the heavy lifting.

Vancouver has the highest proportion of condominiums. It is a geographically constrained metro area and it is one of the first cities in the country to adopt condominiums as a housing tenure. And in Montreal, there are more apartments under 5 storeys than there are single-detached houses. Not surprising. There's no "missing middle" in this city.

But the really interesting question is, how are these condominiums being used and occupied? It's a challenging question to answer, which is why it's so often debated, but here's what the researchers have found so far:

The owner and renter categories are self-explanatory. Temporary, which is the least common type of tenure, is where the owner has declared their principal residence as being somewhere else. In other words, the condominium is a second home.

The vacant category is effectively that city's condominium rental vacancy rate. These are condominium units which are empty, but that are at the same time listed for rent. There are relatively few of these. In Toronto and Vancouver they're virtually non-existent in this dataset (2016).

Finally, we get to unoccupied units. This one is tricky and the researchers aren't exactly clear on what is driving this number. They chalk it up, at least partially, to the flexible nature of condominiums. For example, it could be empty because the unit is switching from owner-occupied to rental, or vice versa.

That said, it is very interesting to note that Toronto and Vancouver actually have the lowest percentage of unoccupied condominium units. This may be surprising to some of you given the public discourse around investor units in these two cities.

Generally, they found that in Canada's three largest metro areas, the following rule of thumb seems to apply: For every 10 condominium units built, 6 will become owner-occupied, 3 will enter the rental stock, and 1 will go unoccupied. Does that seem right to you?

If you'd like to dig into the methodology that the researchers used, you can do that over here at Mountain Doodles . All of the charts and data used in this post were taken from there.