Still Short: Suppressed Households in 2021

(Joint with Jens von Bergmann and cross-posted at MountainMath)

In May we estimated suppressed household formation across Canada using what we called the Montréal Method, finding strong evidence for suppression across many parts of Canada. As a reminder, we designed the Montréal Method to estimate housing shortfalls related to constraints upon current residents who might wish to form independent households but are forced to share by local housing markets. Now that we’ve got 2021 Census data out, it’s time to update our estimates. Given the data available, currently we can only estimate metro area effects of our previous Model 1 (crude household maintainer rates) and Model 2 (age-adjusted household maintainer rates). But that’s a start, and we’re also now enabled to extend the long timelines for Toronto, Montréal and Vancouver from our previous post to include 2021. Overall, current suppression of households alone suggests a shortfall of over 400,000 dwellings in Metro Toronto, and 130,000-200,000 across Metro Vancouver.

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Where did all the cheap rents go?

(Joint with Jens von Bergmann and cross-posted at MountainMath)

It can be really useful to count things, but sometimes numbers end up causing confusion and misunderstanding rather than helping. Often this has to do with how the number is presented and attached to claims. Other times it has to do with problematic procedures used to obtain the number. Here we want to explore these problems more in detail concerning a claim that “Canada lost 322,000 affordable homes” between 2011 and 2016. This stat is generally made in reference to “private” rentals, and is contrasted to the number of non-market units built between 2011 and 2016, pegged at 60k units.

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Rent Growth in GDP

(Joint with Jens von Bergmann and cross-posted at MountainMath)

Every now and then the topic of the GDP share of the “Real Estate Industry” comes up, often linked to the suggestion that an economy has become too dependent upon real estate. But this usually involves a fundamental misreading of the data. As people who pay attention know, the NAICS sector [53] “Real Estate Industry” of the expenditure based GDP produced by StatCan is mostly just rent and imputed rent.

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25 Years of Structural Change

(Joint with Jens von Bergmann and cross-posted at MountainMath)

How are big Canadian Metros growing? Can we see different patterns? Here we want to provide a brief look back at the last 25 years, exploring change over time from 1996 to our most recent Census in 2021. This is also a test of R skills for one of us, who began this post as a learning exercise drawing upon Jens’ excellent CanCensus package and recent data updates.

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Tumbling Turnover

(Written jointly with Jens von Bergmann and cross-posted at MountainMath)

We’re increasingly gathering lots of different measures of residential mobility in Canada. Which is great! Especially insofar as we want up-to-date information about demographic response through the pandemic. Here we want to add the CMHC Rental Market Survey (RMS) to the mix, comparing to Census and CHS (Housing Survey) results. Adding it in reveals a general decline in tenant mobility only recently (and partially) reversed. But it also raises a mystery worth solving about divergent CHS results and points toward the value of triangulation.

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A Brief History of Canadian Real Estate Investors

(Written jointly with Jens von Bergmann and cross-posted at MountainMath)

The newest trend in the search for reasons for rising home prices is to look toward investors. The Bank of Canada released a report showing that the share of investors has risen over time. For this they took mortgage data from federally regulated financial institutions and matched them with credit history to determine if some of the buyers already owned property before they bought (during roughly the past 10 years) and kept it after they bought.

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On Broadway

(Written jointly with Jens von Bergmann and cross-posted at MountainMath)

We have finally found some time to take a closer look at the Broadway Plan. There are many good things to say about the plan, it adds housing in an amenity and job rich area about to get a new subway line. It promises to not just undo the downzoning the city imposed on parts of the area in the 1970s but enables a bit more housing to make up for lost time.

The plan also tacks heavily against the displacement risk to renters in the established rental apartment areas by both 1) limiting the redevelopment potential in those areas and 2) increasing the strength of tenant relocation and right of return policies, a hard-learned lesson from the redevelopment activity around Metrotown in neighbouring Burnaby. In short, overall there’s a lot to like.

In this post we want to accomplish several somewhat diverse goals

  1. Provide some code to improve the data analysis in the plan that uses census data,
  2. Place the Broadway plan more firmly into context of historical zoning changes in that corridor, and
  3. Interrogate the decision to limit development potential in the existing low-density areas, which we have argued in the past make for ideal sites to concentrate development becaues of their low displacement implications.

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Estimating Suppressed Household Formation

(Written jointly with Jens von Bergmann and cross-posted at MountainMath)

TL;DR

We develop and elaborate a Montréal Method for estimating housing shortfalls related to constraints upon current residents who might wish to form independent households but are forced to share by local housing markets. Applying simple versions of the Montréal Method to Metro Areas across Canada suggests that Toronto has the biggest shortfall, which we estimate at 250,000 to 400,000 dwellings, depending upon assumptions. For Vancouver, the estimated shortfall range is narrower, from roughly 75,000 to 100,000 dwellings. But models suggest housing shortfalls remain widespread, and there is much room for further elaboration. Note: shortfalls estimated in this post only account for those due to suppressed household formation among residents and do not account for e.g. migration pressures, which means that overall housing shortfalls are likely much larger.

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What’s Up With Squamish?

(Written jointly with Jens von Bergmann and cross-posted at MountainMath)

In our previous post we have outlined the broad problems with the recent UBCM report, in this post we return to one particular one, the comparison of dwelling growth to population growth for “BC Major Census Metropolitan Areas” (Figure 2 in the report), paying particular attention to Squamish as the largest outlier. To start out, let’s take a comprehensive look at how dwelling and population growth play out across BC’s CMAs and CAs.

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