Justin Trudeau recently tweeted, “Everyone deserves a safe and affordable place to call home”. But what is affordable? And where is housing not affordable? Most define affordable housing based on how much a family unit spends as a percent of their gross income; if that ratio is more than 30% it would put them into the ‘unaffordable’ area.
RBC has been taking a look at the situation for several years now. They estimate what it takes to purchase a house using income against home prices. Their findings seem to point out the great discrepancy based on location; with Vancouver and the GTA being outliers from the rest of Canada on the size of mortgages against income ratio. The Public Sector Digest also recently published an issue dedicated to Affordable Housing, and here’s rel8ed.to’s take on the subject…
Digging into the middle
Instead of going to the ends of the spectrum, the ultra-rich or super-poor, the staff at rel8ed.to investigated the area in the middle. Our findings, based on Statistics Canada data (2011, 2016) and current market rates, support the findings of discrepancy amongst areas, but find the issue is exacerbated much more for renters. What does this mean?
To deep dive the data we used Tableau to sort and visualize the findings. For a cross section of the largest Canadian cities, home to the majority of the population, we examined data from 20 cities: the ten provincial capitals and the ten largest cities non-capital cities. On the Renters and Homeowners tab, in all the 20 cases, there were more renters in the unaffordable category than home buyers. In most cases, the percent of renters with unaffordable housing was double (or more!) than that of the percent of owners. Quebec City was the city most affordable on both the renting and ownership fronts while Toronto was the least affordable (followed closely by Vancouver).
Just over 25% of Torontonians homeowners lived in ‘unaffordable’ housing while about 50% of their renters did so.
Is income tied to the rent/own question?
On the surface, one could speculate that income alone was the main factor – that is, people who made more were owners of houses while people who made less were renters. This proved to be the case in most cities, but not always. For example in Regina, SK and Halifax, NS the monthly cost to own was 20-30% more than renting. In Vancouver, the monthly cost of owning is 3x renting and in Toronto is well over 2x. In stark contrast we found that in Fredericton, NB rent and mortgage payments were about the same.
From these results, we conclude that renters are usually impacted more, and also that Vancouver and Toronto areas are the ones with the most unaffordable housing.
Next, we looked at the change over time (Income and Housing tab) for these 20 cities. For most, we can see that rental prices increased more than housing prices – note that this is before the most recent run-up on actual house prices. General inflation in that time period was around 8%, yet 80% of our sample had increases greater than 10% for rent and home values. Vancouver and Toronto (and a few larger cities in the GTA – Oshawa and Hamilton) had higher home value increases than rent increases.
The best and worst cities for affordable housing
Finally, we assessed the average rent and compared it to income across the 20 cities. Of no surprise is that the rent-to-income ratio is worst in Toronto and Vancouver. But there are some real deals going on in Quebec City, Montreal, Windsor and St. John’s. Great news for the tech sectors in those University-driven hotspots.
We conclude: Vancouver and Toronto are overall the least affordable cities for renters – and find that Quebec and several mid-sized cities have real potential for up-and-coming enterprises and the workers they need to thrive.
Housing prices are becoming a larger component of people’s budgets, but the big effect seems to be in the larger cities known for their recent economic growth. If these trends continue along their same lines, the idea that “everyone deserves a safe and affordable place to call home” will fall even more out of step with the reality of what large portions of the population can afford.Categorised in: Business Data Analysis, Government Data, Open Data, Uncategorized
This post was written by Drew Fones