Rental housing in France is both heavily regulated and supported through dedicated public funds. Here's a high-level overview of what that means (via this 2021 Brookings case study by Arthur Acolin):

• Homeownership rates in France went from 35% in 1954 to 56% in 2001

• As of 2018, 58% of French households own, 40% rent, and the remaining 2% supposedly get free housing from either their employer or a family member

• Not surprisingly, younger households are most likely to rent (the figure is > 60% for people aged 18-29)

• Household size seems to play a major factor in how likely people are to live in public housing

• France has some 4.5 million public housing units and 17% of all households live in them (which represents about 43% of all renter households)

• Within the unsubsidized rental market, 93.5% of households live in homes owned by individual investors (this is as of 2013) and only about 3.5% live in homes owned by institutional investors

• This is pretty typical of Europe, where multi-family isn't an established real estate asset class like it is in North America; so for those of you who like to hate on individual condo investors, check out France

• In the decade between 2010 and 2020, 28 metro regions in France adopted some form of rent control and, in a few markets, like Paris and Lille, there are also maximum rents that can be charged for specific housing types

If you're interested in rental housing, Brookings also has articles covering the US, Germany, Spain, Japan, and the UK. They can be found here.

Back in the spring, I wrote about a study that was done by the University of Toronto and the University of California, Berkeley that measured “downtown recoveries” using mobile phone data.

In other words, it looked at where people’s phones were lingering to try and determine if they were back in the office and doing things downtown.

The headline finding was that San Francisco had the lowest recovery quotient (RT) and that Salt Lake City had the highest, alongside cities like San Diego, Baltimore, and Bakersfield.

But why was there such a spread in recoveries?

One possible explanation was commute times. The cities with the lowest average commute times seemed to generally perform better in this study and have higher recovery quotients. But it’s maybe more nuanced than this.

Here is a recent Brookings article by Tracy Hadden Loh that looks at this same study. And to give just one example, she notes that San Diego’s airport happens to fall within the same zip code as its downtown. Meaning, airport traffic would have been picked up as downtown traffic.

The article also includes the above chart, showing the amount of downtown apartments built since 2019. I don’t think I knew that Chicago was so prolific.

We need more "activity centers". That is my takeaway from this report by Brookings.

Activity centers are exactly what they sound like. But to be more specific, the definition used in the report is based on five categories of assets: community, tourism, consumption, institutional, and economic. And what the authors did was look at the relative concentration of each across the 110 metropolitan statistical areas (MSAs) in the US with at least 500,000 residents.

They then came up with 3 different kinds of activity centers. Monocenters (blue in the above map), secondary centers (yellow), and primary centers (orange). Monocenters have, as you'd probably expect, a lot of one kind of asset. Secondary centers, on the other hand, have "some of at least two kinds of assets." And primary centers have "a lot of at least two kinds of assets."

Looking at the above map, it is pretty clear -- and not at all surprising -- that Manhattan is, for the most part, one giant activity center. There is a lot going on. But this is not the typical condition. In the 110 metro areas looked at in the study, activity centers only occupy about 3% of land on average. The remaining 97% of land is, based on the above definition, a non-activity center.

Why this matters is that activity centers punch above their weight. Despite representing a small land area, activity centers are home to 40% of all private sector jobs in the US. Supposedly, they also increase productivity (by an additional ~$1,723 per worker), yield higher property values (+26%), increase inclusivity, and reduce vehicle miles travelled.

So yeah, more activity centers sounds like a good thing for our cities. Though as we have learned in recent years, we need to be careful with monocenters.

Map: Brookings

Rental housing in France is both heavily regulated and supported through dedicated public funds. Here's a high-level overview of what that means (via this 2021 Brookings case study by Arthur Acolin):

• Homeownership rates in France went from 35% in 1954 to 56% in 2001

• As of 2018, 58% of French households own, 40% rent, and the remaining 2% supposedly get free housing from either their employer or a family member

• Not surprisingly, younger households are most likely to rent (the figure is > 60% for people aged 18-29)

• Household size seems to play a major factor in how likely people are to live in public housing

• France has some 4.5 million public housing units and 17% of all households live in them (which represents about 43% of all renter households)

• Within the unsubsidized rental market, 93.5% of households live in homes owned by individual investors (this is as of 2013) and only about 3.5% live in homes owned by institutional investors

• This is pretty typical of Europe, where multi-family isn't an established real estate asset class like it is in North America; so for those of you who like to hate on individual condo investors, check out France

• In the decade between 2010 and 2020, 28 metro regions in France adopted some form of rent control and, in a few markets, like Paris and Lille, there are also maximum rents that can be charged for specific housing types

If you're interested in rental housing, Brookings also has articles covering the US, Germany, Spain, Japan, and the UK. They can be found here.

Back in the spring, I wrote about a study that was done by the University of Toronto and the University of California, Berkeley that measured “downtown recoveries” using mobile phone data.

In other words, it looked at where people’s phones were lingering to try and determine if they were back in the office and doing things downtown.

The headline finding was that San Francisco had the lowest recovery quotient (RT) and that Salt Lake City had the highest, alongside cities like San Diego, Baltimore, and Bakersfield.

But why was there such a spread in recoveries?

One possible explanation was commute times. The cities with the lowest average commute times seemed to generally perform better in this study and have higher recovery quotients. But it’s maybe more nuanced than this.

Here is a recent Brookings article by Tracy Hadden Loh that looks at this same study. And to give just one example, she notes that San Diego’s airport happens to fall within the same zip code as its downtown. Meaning, airport traffic would have been picked up as downtown traffic.

The article also includes the above chart, showing the amount of downtown apartments built since 2019. I don’t think I knew that Chicago was so prolific.

We need more "activity centers". That is my takeaway from this report by Brookings.

Activity centers are exactly what they sound like. But to be more specific, the definition used in the report is based on five categories of assets: community, tourism, consumption, institutional, and economic. And what the authors did was look at the relative concentration of each across the 110 metropolitan statistical areas (MSAs) in the US with at least 500,000 residents.

They then came up with 3 different kinds of activity centers. Monocenters (blue in the above map), secondary centers (yellow), and primary centers (orange). Monocenters have, as you'd probably expect, a lot of one kind of asset. Secondary centers, on the other hand, have "some of at least two kinds of assets." And primary centers have "a lot of at least two kinds of assets."

Looking at the above map, it is pretty clear -- and not at all surprising -- that Manhattan is, for the most part, one giant activity center. There is a lot going on. But this is not the typical condition. In the 110 metro areas looked at in the study, activity centers only occupy about 3% of land on average. The remaining 97% of land is, based on the above definition, a non-activity center.

Why this matters is that activity centers punch above their weight. Despite representing a small land area, activity centers are home to 40% of all private sector jobs in the US. Supposedly, they also increase productivity (by an additional ~$1,723 per worker), yield higher property values (+26%), increase inclusivity, and reduce vehicle miles travelled.

So yeah, more activity centers sounds like a good thing for our cities. Though as we have learned in recent years, we need to be careful with monocenters.

Map: Brookings