Brandon Donnelly

Daily insights for city builders, delivered every morning at 6 AM ET. I’m Brandon Donnelly — a Toronto-based real estate developer and founder of Globizen. I’ve been writing here since 2013.

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Tag: research study

  • Rents are lower, but what does that ultimately mean?

    Paris is the first city in France to implement some form of residential rent control. The first came in 2014 (enacted in the market in 2015), but this was later removed in 2017. The second came in 2019, and this current program remains in place until November 2026, at which time it will be reviewed.

    But given that it has already been in place for a number of years, people have started to analyze it’s effectiveness. Here is a study by Atelier Parisien d’Urbanisme (APUR) that was published this month.

    The report is in French, but I can tell you that, what they did, was compare the Paris region to 8 other cities in France — all of which do not have the same rent controls. They were: Aix-en-Provence, Grenoble, Marseille, Nantes, Nice, Strasbourg, Toulon, et Toulouse. These were allegedly chosen because their housing markets are thought to be similar to that of Paris’.

    What they found was that from July 2019 to July 2023, legislated controls in Paris lowered rents by approximately 4.2%, compared to where they would have been without any market intervention.

    At the same time, they noticed that these same controls seemed to become more effective over time. From July 2019 to June 2020, they lowered rents by 2.5%, but from July 2022 to June 2023, they lowered rents by 5.9%.

    Finally, they also found that the controls seemed to impact smaller places the most. For apartments between 8 and 18 m2, rents were 10.2% lower than expected during July 2019 and July 2023.

    This is all interesting stuff, but in many ways, it is expected. Rent controls are intended to depress rental growth. That’s the whole point. And based on this data from APUR, it is working in Paris.

    But the really tough questions pertain to the possible knock-on effects. If rents are 4.2% lower, but operating costs are now growing faster than rents, then this is a problem for the housing market. You’re on an unsustainable path.

    And if lower rents mean that fewer developers are going to build new housing, then this is also a problem, because less supply will eventually translate into more upward pressure on rents. I don’t know for sure that this is happening in Paris, right now, but these are crucial considerations.

    It’s never as simple as just looking at rents and thinking lower is better for long-term affordability.

  • Most of Europe is getting denser

    Here is an interesting set of maps (from this study) showing density trends, population trends, and residential area trends (i.e. sprawl), across Europe between 2006-2012 and 2012-2018:

    The key takeaway is that, broadly speaking, there is — or at least there was five years ago — a new density trend across most European cities. From 2006 to 2012, the prevailing trend was de-densification. That is, fewer people per hectare. However, from 2012 to 2018, that trend largely reversed. With the exception of the Iberian Peninsula and Eastern Europe, the majority of cities flipped to densification.

    The study tells us that there are two main reasons for this switch. The first is that more cities started growing again. During the first period, about 60% of cities in the sample size of 300+ cities, were adding people. In the second period, this figure increased to 75%. It’s also worth noting that this growth is being largely driven by immigration, and increasingly so. The number of cities with positive natural growth diminished from 67% to 51% between the two study periods.

    The second driver is a reduction in sprawl. Though almost every city in the study continued to expand outward, the rate of expansion was much lower between 2012 and 2018. So less land consumption, and more people. That’s how you increase your urban density. Of course, it would be interesting to see if any of this has changed or reversed (again) as a result of the pandemic. 2018 kind of feels like eons ago, doesn’t it?

  • Proximity matters for knowledge spillovers

    I am at my most creative when I’m in the same room with other people and we are bouncing ideas around. There’s a compounding effect that takes place. One person says something and that then triggers a new idea. I find the whole experience very rewarding and, for me, it’s a reminder that creativity can be a process. It is also a reminder that proximity is important for those of us who have jobs that deal in creativity.

    We have spoken a lot about this on the blog, but here is an interesting and recent study that looked at knowledge transfers across different tech startups within one of the largest co-working spaces in the US. For context, the co-working space itself consisted of five floors, about 100,000 square feet, and housed 251 different startups. To measure knowledge transfer, the researchers looked at instances of a startup adopting a component of a peer’s technology stack.

    What they found was the following:

    • Knowledge exchange is greater amongst startups that are dissimilar
    • Close physical proximity greatly influences the chance of knowledge spillovers; however, this effect quickly falls off
    • After 20 meters or so, there’s almost no difference between being down the hall or being on a separate floor within the building
    • One of the ways you can counteract this last finding is to create shared spaces; startups with overlapping common areas, such as a kitchen, saw greater distances of influence

    In short: proximity matters.

    If you’d like to download a full copy of the study, click here.

  • Turns out, pedestrianization actually increases retail sales volumes

    As many of you know, I have been keeping a close eye on the pedestrian-only pilot that is currently underway on Market Street. And judging from all the engagement that my tweets usually get, a lot of you would love to see a lot more of this kind of urbanism both here in Toronto and elsewhere. (When Kensington Market?) The below photo was taken on Friday evening and Cirillo’s Academy, which is a culinary event space at the foot of the pedestrian-only stretch, was running some sort of event. All of the tables were filled with diners and it was basically a full fledged restaurant in the middle of the street. It was great to see.

    But the question that always comes up with these sort of initiatives, particularly here in North America, is: Will it hurt the businesses? To answer that, here’s a study that @economistcarson shared with me on Twitter that looks at the economic impact of street pedestrianization in Spanish cities. What the researchers did was essentially look at card transaction data from a major Spanish bank and then overlay it on top of land-use changes from an Open Street Map dataset. In doing so, they discovered some pretty important takeaways.

    Here’s what they found:

    • Pedestrianization actually increases retail sales volumes
    • Geographic location within a city tends to be insignificant
    • The two key factors for driving revenue are: (1) store density and (2) store category
    • For store category, the largest positive effect was observed for cafes, restaurants, bars, and other non-tradeable, local consumption activities

    What this last point is saying is that people, at least in Spanish cities, tend to prefer pedestrian-friendly environments when it comes to experience-based activities. And that makes complete sense. On the other hand, if you’re just running out for a little toilet paper and hemorrhoid cream, having a nice pedestrian-first experience is less critical. And this also makes sense.

    Some of you, I’m sure, will correctly point out that Spain has, on average, better weather compared to a place like Canada. And that their store densities and overall densities are likely higher, and that they have deep historic urban fabrics to rely on. All of these things are certainly factors. But I don’t think any of this should stop us from working to better optimize our cities for pedestrians. There are lots of successful examples all across Canada. It can work. Just look at Market Street.

  • A mapping of US rental housing rents, scraped from Craigslist

    This is an interesting way of seeing rental housing rents (national scale). And there’s a lot that you can glean from a mapping like this. But it’s also interesting in that what you are seeing here is a visualization of some 11 million Craigslist rental housing listings (taken from this study). The authors refer to it as a “nontraditional source of volunteered geographic information”, and they argue that it’s probably more granular and real-time than what is typically available when it comes to rental housing. That sounds right to me.

  • Slime mold may be better than us at transportation planning

    So slime mold, which is a fungus-like single-celled organism, has a tendency to build highly optimized networks across its food sources. In other words, if you scattered a bunch of food on a surface and then dropped in some slime mold, it would naturally create an interconnected web of linked veins across this surface. And this web would be based on the shortest and most efficient paths of travel between the various food sources.

    I am mentioning this odd factoid because ten years ago researchers in Tokyo used this naturally occurring phenomenon for the purposes of trying to improve transportation planning. What they did was map out greater Tokyo. They then placed oat flakes (i.e. food) in spots that correspond to the various cities and urban centers that surround the city. Alongside this, they blocked off the areas where transportation networks do not typically run, such as through mountains and into the water. They then dropped in some slime mold, wet the surface, and watched it grow.

    What they found was that the resulting network was remarkably similar to Tokyo’s actual rail network. The slime mold had found the most efficient routes, eliminated redundancies, and generally discovered the optimal way in which to connect its food sources. And if you think about it, this is basically what transit networks are supposed to do. They should connect clusters of people in the most efficient way possible.

    It has been a decade since this slime mold transportation discovery was first publicized, and it would seem that it hasn’t really caught on as an invaluable planning tool. So I’m going to go out on a limb and suggest that we should take out a map of every major city in the world, plot its population centers, drop down some oat flakes, and then let slime mold tell us all the ways in which we are screwing up and over-politicizing our transportation planning efforts.

    Thank you to Angus Knowles for making me aware of this study. Angus writes an occasional newsletter about cities and housing, over here.

    Image: LiveScience

  • Longer-term benefits of Airbnb for housing supply

    There is a commonly held view that short-term rentals (such as the ones you might find on platforms like Airbnb) are bad for housing affordability because they take long-term rentals out of the market and they help to drive up property values. And there’s evidence for this. A study published in Harvard Business Review found that home-sharing alone might be responsible for about 20% of the average annual rent increases across the US.

    Findings like these have encouraged municipalities around the world to put restrictions in place for STRs. But like most policy issues, there are nuances. And the thoughtful answers are rarely as obvious as they may initially seem. This has been part of my complaint around inclusionary zoning. It sounds good when politicians say it: let’s just get developers to build us free affordable housing. But again, there are nuances to consider.

    Short-term rentals are similar. A recent follow-up study that was again published in Harvard Business Review has actually uncovered some interesting longer-term benefits to STRs.

    Using residential permit data, Airbnb listings, and STR policies across the US, the team found that when you look over a longer time horizon, Airbnb listings actually tend to increase the supply of residential housing. On average, a 1% increase in Airbnb listings led to a 0.769% increase in permit applications. Supply is of course good for a whole host of reasons, one of which is boosting the local tax base.

    Conversely, they found that restricting STRs tended to reduce the supply of new housing and renovations. After new regulations were put in place affecting STRs, Airbnb listings fell on average by about 21% and residential permits fell by 10%.

    Restrictions also seem to have a direct impact on the construction of things like accessory dwelling units (laneway and garden suites for us here in Toronto). When analyzing data in and around the borders between jurisdictions in Los Angeles County, the researchers found that areas without STR regulations saw 17% more ADU permit applications compared to the areas that had restrictions.

    For the 15 US cities that the team studied, they conservatively estimated that STR restrictions reduced property values by about $2.8 billion and impacted tax revenues by about $40 million per year. Some cities, like Chicago, have also found success using STRs as an economic development strategy in distressed neighborhoods, which would further bolster the tax base.

    All of these findings suggest that a more nuanced approach to STR policies is probably merited.

    Photo by Andrea Davis on Unsplash

  • Pigovian transport pricing in Switzerland

    A Pigovian tax is a tax on market activities that produce some kind of negative externality for society. The basic idea behind the tax is to try and use it to correct something that is happening, but that isn’t all that desirable. Examples of negative externalities might include things like pollution and traffic congestion.

    Traffic congestion is a bad thing, which is why I have long been a supporter of road pricing. We know how to do this. It has been proven to work in countless cities, including Singapore, London, Stockholm, as well as many others. But in most cases, there isn’t the political will. That has certainly been the case here in Toronto.

    Maybe this post will help.

    A recent study by ETH Zurich, the University of Basel, and ZHAW has looked at the effects of Pigovian pricing on mobility within Switzerland. The study included 3,700 participants and spanned both French and German-speaking parts of the country.

    The way the study works is pretty simple. They took thousands of people, gave them a transportation allowance (in Swiss francs), and then assigned costs to the various mobility options. These costs were intended to be commensurate with their amount of negative societal impact.

    Driving, for example, came at a cost of 0.1 Swiss francs per kilometer. Whereas participants actually earned money for walking, since you could fairly easily argue that walking produces a net benefit to society. At the end of the four-week experiment, participants were allowed to pocket whatever money was left in their transportation wallet. So in theory there was an incentive to spend less.

    What the researchers were trying to do was simulate Pigovian transport pricing and give people a more direct understanding of the societal costs associated with how they move around. And based on their results, it looks to have worked.

    What the results show is that when you start pricing transport in this way, all mobility declines slightly (the “all modes” line). But that the biggest hit is, not surprisingly, driving. Car use declined by almost 5%, whereas walking, biking, and using public transit all increased. (The price elasticity of demand for car travel was found to be similar to when the cost of gas increases — people drive a bit less.)

    The authors go on to argue that longer-term Pigovian pricing is likely to produce an even greater impact on mobility, as people would likely adjust and start making bigger decisions about where and how they live. That seems plausible to me.

    For a full copy of the study, click here.

  • How new technologies spread (and what that means for superstar cities)

    We know that innovation and economic growth tends to be unevenly distributed. This is the bull case for living in cities and, more particularly, for living in certain cities. But of course, the big question these days is whether or not our little work from home experiment has proven that, for the first time ever, work can now decentralize.

    Well here is a unique study that looked at 29 disruptive technologies over the last two decades in the United States. Using three main sources — patents, job postings, and hundreds of thousands of earnings calls — the team traced where new innovations/technologies have tended to emerge and then how they spread (or didn’t spread) across the rest of the US.

    Their initial findings won’t surprise regular readers of this blog. There are indeed a certain number of pioneering superstar cities. Within their list of new disruptive innovations, the team found that about 40.2% of them came from California. The next “super-cluster” was along the Boston-Washington corridor in the northeast with ~21.2%. By narrowing down their list to “disruptive patents”, as opposed to all patents, innovation looks even spikier.

    Next the team looked at how these disruptive technologies tend to diffuse across the country. This is where job postings and earnings calls come into play. New technology gets created in California garage. Cool. But at what point do CEOs across the country start talking about it and hiring people who are capable of doing things with it? This next figure shows that diffusion at various time intervals.

    Now here are the important takeaways. New disruptive technologies clearly take time to spread. However, high-skilled hiring tends to spread much more slowly than low-skilled hiring. This kind of makes sense as you’ve got a built up and entrenched knowledge base in these pioneering locations.

    But what this also means is that pioneering locations tend to maintain their hegemony for quite some time — decades. The high-paying jobs stick closer to home for much longer, presumably because geography makes it harder to transfer knowledge. This is, of course, based on historical data. But I remain highly suspect that Zoom calls can really disrupt the importance of our superstar cities.

    Maps: Vox

  • Pay and performance for graduates of elite universities

    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.