CANSIM
There are many useful metrics to understand neighbourhood change, change in the income distribution, change in the share of population in low income and change in dwelling units, change in households who rent, or just overall population change and how that relates to zoning. All these tell us something about how neighbourhoods change, the metric we want to focus on in this post is the number of children under 15.
(Joint with Nathan Lauster and cross-posted at HomeFreeSociology)
The Federal, Provincial, and Municipal governance structure in Canada creates a fun pattern whereby all governments are happy to take credit for good things that happen, but when bad things happen, each tends to point the finger at the others. So we get the spider-Man meme.
When it comes to Canada’s housing crisis, pointing Spider-Men are all too common. But sometimes one level of government really is to blame.
Census data serves as the baseline for a lot of downstream data products, we like to think of it as a solid and authoritative data source. And the data from the Canadian census is indeed amazing. But counting people is hard, and the closer one looks the more one realizes little problems.
All it takes to shake your faith in census data is spending 30 minutes browsing dissemination block or dissemination area data in a neighbourhood you know well.
(Joint with Nathan Lauster and cross-posted at HomeFreeSociology)
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.
(Joint with Nathan Lauster and cross-posted at HomeFreeSociology)
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.