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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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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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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Unoccupied Canada

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

TLDR

Canadian Census data on “Dwellings Unoccupied by Usual Residents” are frequently misunderstood. Now that data from 2021 are out, we provide a timely explainer and draw upon a variety of resources, including comparisons with US data, Empty Homes Tax data, and zooming in on census geographies, to help people interpret what we can see.

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No Shortage in Housing BS

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

Say you built a bunch of housing in a cornfield in the middle of rural Iowa. Would people come to live in it? Maybe. But probably not. Let’s imagine the same scenario scooted over to Vancouver. The conditions for our little field of dreams have changed. Here we’re pretty comfortable predicting: if you build it, they will come. Housing limits population growth here in a way it does not in rural Iowa.

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A Brief Data-Based Primer on Mobility and Housing

As a housing demographer, I’m on the lookout for various ways to explain basic aspects of how people and housing fit together. A recurring theme is that this stuff is not obvious to most people. For example, people tend to associate new housing in a metro area with new people coming to a metro area. In fact, most new housing houses people already living within a metro area. But their moves free up other housing, which often incorporates newcomers.

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First Peek at Population and Household Data During COVID & Caveats

co-authored with Jens von Bergmann and cross-posted at MountainMath

In this post we look at the most recent population (and household) estimates to see if we can detect any signals concerning how the COVID-19 pandemic may have impacted how (and where) we live. This is inherently tricky; lots of things changed during COVID times, including how well our normal methods of estimation work. That makes time series less reliable, even as we’re especially concerned with how conditions have changed. So in this post we attempt to pay special attention to what we can and can’t glean from the signals we’re receiving so far.

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