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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Category: Economics

  • The Knight Frank Global Affordability Monitor 2019

    Here’s a chart from Knight Frank’s 2019 Global Affordability Monitor that I think you’ll find interesting:

    It compares real home price growth and real household income growth (after tax) over the last 5 years for 32 world cities. The bolded percentages represent the former and the non-bolded percentages represent the latter.

    Consider the variations here.

    Amsterdam saw a real home price change of 63.6%, but a household income change of only 4.4% (although the circle looks to be in the wrong spot if this number is correct).

    Moscow, on the other hand, saw flat home prices (0.1%) and a 22.7% increase in household income.

    Though San Francisco is the star in terms of income growth.

    Sao Paulo, unfortunately, saw a dramatic decline in both home prices and incomes. It’s in the bottom left corner.

    When I look at this chart, I don’t see a strong correlation between household incomes and home prices. And the proportions of the chart tell you that the y-axis is moving more than the x-axis.

    But if the top number exceeds the bottom number, then you could come to the conclusion that housing affordability has gotten worse over the last 5 years.

  • Median household income vs. health insurance costs

    I just came across this chart from Axios, which relies on data from the Federal Reserve Bank of St. Louis and the Kaiser Family Foundation. It compares median household income against the average cost of employer health insurance (in the United States).

    What it is saying is that, after adjusting for inflation, the median household income has only increased by 2% from 1999 to 2017, whereas employer health insurance costs have increased by some 121% over this same time period.

    The takeaway: Rising healthcare costs are believed to be eating away at take-home pay in the US. As of 2017, health insurance costs were estimated to represent about 30% of the average household income. That feels like a big number to me.

  • Tasty data

    A recent study and research paper by the MIT Senseable City Lab — called, Tasty Data — has discovered that restaurant data alone can be used to accurately predict location-based factors such as daytime population, nighttime population, number of businesses, and overall consumer spending within a specific geography.

    They started by pulling restaurant data from Dianping (Chinese equivalent of Yelp) for 9 Chinese cities: Baoding, Beijing, Chengdu, Hengyang, Kunming, Shenyang, Shenzen, Yueyang, and Zhengzhou. They then paired their Dianping data with other available data (such as aggregated mobile phone data) and used machine learning to search for any correlations.

    Below is a diagram of “nighttime population” in Beijing. They are using a 3 km2 grid.

    If you’re a regular reader of this blog, you’ll know that I like these kinds of studies. By 2020, it is estimated that 1.7MB of data will be created every second by every person on earth. The numbers are staggering. And yet, “official” data sources, such as census data, remain slow and fairly limited. Studies like this one continue to show us what’s next.

    Image: MIT Senseable City Lab

  • Gender earnings in the gig economy

    Last year, 5 economists published a research paper called “The Gender Earnings Gap in the Gig Economy: Evidence from over a Million Rideshare Drivers.” The authors are 2 economists employed by Uber; 2 professors at Stanford University; and the chairman of the University of Chicago’s economics department.

    The findings were widely discussed, including on Steven Levitt and Stephen Duber’s Freakonomics podcast (Episode 317). What’s interesting about Uber’s ridesharing data is that their compensation algorithm is believed to be entirely gender-blind.

    The formula is pretty simple. It takes into account distance, time, and sometimes a surge multiplier when demand is spiking. Gender does not factor. And the same goes for the actual dispatching of rides. The software doesn’t know who is male and who is female.

    What they discovered is that on average male Uber drives earn about 7% more per hour compared to females. And that 50% of this wage gap can be (apparently) explained by one variable: Men tend to drive a little faster than women. So they complete more rides per hour.

    It’s also worth noting that across the US, only about 27% of Uber drivers are female (at least at the time the report was published). Women also have a higher 6-month attrition rate; 76% compared to 63% for men. In other words, more female drivers drop off the platform.

    If you’re interested in this topic, you should probably have a listen to the Freakonomics podcast. They deliberate on the above in a lot more detail. You can also download a full copy of the research paper, here.

    Photo by Luke Stackpoole on Unsplash

  • Immaculate construction

    Emily Badger’s recent piece on “how ‘developer’ became such a dirty word” has been getting passed around within the industry over the last few days. I had a chuckle when I read this bit:

    The notion that development is inherently bad, or that developers are inherently bad actors, seems to ignore that the communities residents want to protect from developers were once developed, too, and often by people who made money at it. (That is, unless you believe in “immaculate construction.”)

    The article hits on a number of points that are absolutely true. There’s generally a lack of understanding around the economics behind new housing. And the cost structures, today, are dramatically different compared to the suburban-industrial complex.

    To provide one example, our cost consultant, Finnegan Marshall, recently shared with me a chart (dated April 2019) that broke down the various government fees that typically make up every new condo suite in Toronto.

    What it showed is that between 20-24% of the price of a new condo is generally compromised of government fees and taxes that span all three levels of government. This includes everything from development charges (impact fees) to parkland dedication.

    Similarly, the article quotes one developer from Montgomery County who estimates that the impact fees alone for his projects are usually upwards of $60,000 per housing unit. (This is pretty cheap compared to Toronto.)

    I raise this as an example because development charges/impact fees have become an important source of revenue for cities across both Canada and the US. They often offset lower property taxes. (Whether this is appropriate is an entirely other debate.)

    And so I find it paradoxical that many homeowners would like to simultaneously see lower property taxes, no new development, and more public services and infrastructure.

    Photo by EJ Yao on Unsplash

  • Pleasure and product discovery

    Benedict Evan’s most recent blog post, called “Amazon as experiment,” draws some interesting parallels between what Amazon is doing today (and experimenting with) and the beginning of mass retail, namely the invention of the department store. He also talks about some of the shortcomings of Amazon’s model, which isn’t at all focused on (or good at) things such as “pleasure” and product discovery. Here are a couple of excerpts:

    On the other hand, it’s interesting that Amazon seems to be doing as much experimentation as possible around the logistics model—from stores to drones to warehouse robots of every kind—but much less around the buying experience, other than small-scale tests of the Four-Star stores. After all, historically, department stores were about pleasure as much as they were about convenience or price. They changed what it meant to “go shopping” and helped turn retail into a leisure activity.

    This has always been the gap in the Amazon model. It’s ever more efficient at finding what you already know you want and shipping it to you, but bad at suggesting things you don’t already know about, and terrible whenever a product needs something specific—just try finding children’s shoes by size.

    This is probably inherent in the model. For Amazon to scale indefinitely to unlimited kinds of products, it needs to have more or less the same commodity logistics model for all of them. That’s the line it’s never been willing to cross. Amazon doesn’t do “unscalable.” And yet, while we now know there is nothing that people won’t happily buy online, not everything will fit that commodity model. So maybe that’s the real test of Amazon’s pride: can it work out how to let us shop, rather than just buy?

  • Getting things done

    Fred Wilson wrote a post this morning about the “certainty of close.” He was talking about fundraising for startups, but similar parallels can be drawn to other aspects of life and business. The point Fred makes is that if you can live with the “bird in the hand” economics and if you have a comfort level with the humans/partners you’re getting involved with, it’s hard to go wrong and it’s often the right approach for early stage companies where fundraising speed is critical.

    The tension that usually gets weighed against this line of thinking is one of maximizing economics, which often sits part and parcel with a fear of “leaving money on the table.” Should I take the deal in front of me or should I push and/or wait to extract every last dollar? This can lead to indecision. Oftentimes, as Fred mentions, these decisions aren’t particularly black and white. Few things are.

    While every deal and situation is unique, there is nothing inherently wrong with a fair and reasonable price if the the economics make sense for you, and your investment and return criteria are being met (or whatever criteria you have set for yourself). It is “satisficing” vs. “optimizing.” The latter may appear most favorable, but there are countless benefits in moving as quickly as possible and in getting things done. I am a fan of doing.

    Photo by Jacek Dylag on Unsplash

  • Average living space per person in Hong Kong

    This recent NY Times article — which makes the case that the current protests in Hong Kong are at least partially a result of inequality — has a pair of interesting diagrams that speak to the city’s tight housing market.

    The first compares average living space per person in Hong Kong to Paris and New York City. New York City appears palatial compared to the illegally subdivided apartments that are discussed in the article.

    The second looks at housing affordability as a multiple of median household income. Hong Kong is over 20x. I am curious what median incomes were used for each of the cities. A small denominator makes the multiples look worse.

    In this chart, New York also includes the entire metropolitan area, which would help to improve its affordability ranking. So one could argue that this isn’t really a fair comparison.

    At the same time, none of this changes the fact that Hong Kong has some of, if not, the most expensive housing in the world.

    Images: NY Times

  • The Information Age: Tech & the S&P 500

    The below chart from this morning’s Wall Street Journal is perhaps a good example of our ongoing transformation from an industrial economy to an information economy. Just four stocks — namely Microsoft, Apple, Amazon, and Facebook — have accounted for 19% of the S&P 500’s total return this year. All of them are “tech.”

    And this is not new to 2019. Similar contributions were made by tech last year and in 2018. I have been used to hearing about the 4 horsemen of tech. But apparently there’s even now something called the “FAANG stocks,” which refers to Facebook, Amazon, Apple, Netflix, and Google (Alphabet).

    This shift is, of course, one of the reasons why every city is trying to establish a strong tech ecosystem. I saw that first-hand in Lisbon this past week. And frankly I think the city has many of the same characteristics that made Berlin a great place for tech. It’s affordable. It’s filled with young and smart people. And it’s a fun place to be.

    There’s a reason that Lisbon now hosts the annual Web Summit, which is generally considered to be the largest tech conference in the world. (The North American offshoot, called Collision, relocated to Toronto this year in order to be in a more global city.)

    Portugal only has a population of about 10 million people. There are some 3 million people in the metropolitan area of Lisbon. But that doesn’t really matter because most startups today are immediately targeting a global customer base.

    I learned more about Portugal and Spain’s colonial pasts on this trip and I found it fascinating. In many ways, it was the start of globalization. But that was the Age of Discovery. Those centuries are over and done with. Our century is the Information Age. The above chart is part of that story.

  • Supply is up and rents are down in Sydney

    The Sydney Morning Herald recently reported that an oversupply of apartments has started to put downward pressure on rents and upward pressure on vacancy rates in the city. Here are a few excerpts from the article:

    Sydney is in the grip of an apartment building boom, with 30,880 multi-unit dwellings built last year, a record for any Australian city. There were 16 multi-unit projects finished in the first three months of 2019, adding another 1948 units.

    These numbers are flowing through Domain.com.au, where 17,500 units were listed for rent in June 2017, and ballooned to 32,680 listings in June 2019. The result has been landlords asking for $25 a week less median rent than last year.

    Sydney-wide rental vacancy rates have almost doubled from 1.7 per cent 2017 to 3.2 per cent this year. But on the upper and lower north shore, in the hills district and Sydney CBD, apartments are sitting vacant at more than twice this rate, SQM data shows.

    The narrative here is that you can build your way to lower rents. Make supply exceed demand, and this is what will happen.

    But in this case, something else has also impacted the demand curve: China.

    Beijing has made it harder to get money out of the country in recent years and their overall economy has slowed. China’s economy is thought to be growing at its slowest rate since 1992 (which is when the country started official record keeping).

    The above article suggests that about 80% of new construction apartments in Sydney were sold to investors over the last few years. More than a few were probably Chinese. Though I have no idea if that is an accurate number.

    What is unclear, to me, is whether this doubling of rental listings over the last two years is a result of previously bought supply simply making its way through the system, or if current market conditions have encouraged more owners to put their units up for rent.

    Whatever the case may be, supply is up and apartment rents appear to be coming off slightly in Sydney.