Now that the results from Paris' first round of municipal elections are in, I thought I would do a follow-up to my post from a few days ago (which was mostly about bicycles). The second and final round happens this weekend, but here's what we've learned so far:

Emmanuel Grégoire (Union of the Left) is in the lead with 37.98% of the vote:

And Rachida Dati (Union of the Right) is in second with 25.46% of the vote:

What is not unexpected, but super interesting nonetheless, is the clear divide between the west and east within Paris proper. The west voted right, and the east voted left.

Here in Toronto, our voting maps typically exhibit a semi-clear divide between "Old Toronto" and the inner suburbs. For example, these are the results from our 2023 mayoral by-election:

Conveniently, it is a divide that loosely tracks the city's built form. If you live in the oldest parts of the city, where transit usage is higher and there's rail in the middle of the street, there's a higher probability that you voted for Chow. The inner suburbs, on the other hand, tended to vote for Bailão.

In the case of Paris, there isn't the same built form contrast. This is not an urban-suburban divide; it's a socio-economic divide. The western arrondissements have historically been the wealthiest areas of Paris (for a variety of reasons), and that continually appears in the voting patterns.

It also shows up in the modal splits. The western arrondissements tend to have higher car ownership rates compared to the east. These basic facts are interesting because Paris represents more of a controlled urban experiment, in contrast to Toronto's dense downtown and otherwise generally low-rise built form.

But in the end, I'm not sure the political mappings of Paris and Toronto are all that different. If you look closely at Toronto's 2023 by-election map, you'll see that the wealthiest pockets of the city voted exactly as you would expect. Turns out, bank balances may matter more than built form.

Cover photo by Maximilian Zahn on Unsplash

Every time you get into a car, there is a non-zero chance that you might get injured, or worse, die. The probability of this happening depends largely on where you're driving and, of course, how much you drive. However, there are a few different ways to measure this statistical risk. A recent Bloomberg article by David Zipper highlights one ongoing debate.

The three most common methods are:

• Road deaths per capita

• Road deaths per registered vehicle

• Road deaths per distance traveled

In my opinion, options 1 and 3 seem the most relevant. Option 1 is useful because it measures a citizen's overall risk and allows driving risk to be easily compared to other causes of death (which tend to be measured on a per capita basis). The limitation is that it is harder to compare a country where everybody drives to a country where few people drive.

That's where option 3 comes in. In theory, it provides the best indicator of road risk by accounting for distance traveled, which is the primary argument for why it's commonly used in the US where the car is king. But it does "dilute" the fatality count the more people drive, and it hides overall car dependency. In his article, Zipper likens this approach to measuring cancer deaths per cigarette smoked.

In any event, here is how both methods appear in the International Transport Forum's 2025 Annual Road Safety Report (which is cited in the article):

On a per vehicle-kilometre basis, the data appears much more gradual. But on a per capita basis, the countries with the highest road fatalities appear much more as outliers. Here, you can more easily see that, broadly speaking, a person in Colombia is nearly ten times more likely to die in a road-related incident than a person in Norway (pretty much the gold standard when it comes to road safety).

Perhaps the answer is to just look at both figures to make sure you're not lying to yourself.

Cover photo by Tom Barrett on Unsplash

Charts from Road Safety Annual Report 2025

High Art Capital recently announced the launch of a new fund called the Greater Toronto Area (GTA) Rental and Affordable Housing Initiative. It has been anchored by a $300 million mezzanine debt commitment (and a "nominal equity investment") from the Building Ontario Fund (BOF) and is expected to be capitalized in total with a minimum of $1.3 billion.

The objective is to acquire approximately 2,200 rental homes in blocks within newly completed, unsold condominiums across the GTA and convert them into long-term rental housing. Included within this will be approximately 550 affordable rental homes that are expected to be title-protected at rents set at the lower of 25% below local market rent or 30% of median gross household income.

This is interesting, but it's certainly not the first example of investors buying, or wanting to buy, excess condominium inventory. However, it may become the largest in Toronto and, as far as I know, it's the only one to partner with the public sector (BOF is a provincial Crown agency).

The way it is intended to work is as follows:

Condominium developers are sitting on unsold inventory and maybe on inventory they took back after purchasers defaulted (and which may be subject to legal action). What High Art will do is say to developers, "Hey, if you give me a really awesome deal, I'll take 50 of those condominium units off your hands." And if the developer is desperate enough, they will say, "Sure, that sounds good. Let's do a deal and then go for a nice closing dinner."

But at what price?

As we've talked about many times before on the blog, developer pricing is typically based on a cost-plus model. We take our costs, add a margin, and there's the final sticker price. The reason prices haven't fallen as much as one might expect on unsold units is because they're hitting the "cost floor"; developers don't want to lose money, unless they are given no other option.

But for this rental fund model to work at reasonable costs of debt, I suspect that, in many/most cases, deals will need to be struck below a developer's cost basis. So, it'll be very interesting to watch how this fund deploys capital and who the winners and losers are in this market.

Regardless, I think it is good that we are seeing this sort of activity. The faster we deal with the pain, the faster we'll get to the other side.

Cover photo by Patrick Boucher on Unsplash