Visualizing House Prices

How does your market stack up?

Price data for housing can be hard to find in Canada, and even when you find it, it’s probably in a less-than-machine-friendly format. This post takes CREA data buried in Excel sheets and turns it into nice and tidy dataframes, with some data viz to go along with it.
Author

Andrew Lis

Published

September 19, 2021

There’s a few sources where one can pull data on housing prices in Canada, but a source that I personally like are data from the Canadian Real Estate Association (CREA). Some of the benefits of the CREA data include:

Some drawbacks of these data are:

Pandemic Pandemonium

It seems like there’s still a debate going on (to some extent) as to whether the COVID-19 pandemic brought about a ‘flight to the burbs’. The crux of the issue seems to lie with the data (or lack thereof) that would be needed to track the movement of households from one region to another.

I’m not going to get into a bun-fight about this in this post, but I was doing some work with housing price data the other day, and I made a chart that struck me as being pretty compelling / interesting.

To preface this chart, if it were true that there was indeed a ‘flight to the burbs’ due to the pandemic, then we’d expect prices for housing in the burbs to have risen quite substantially in a short period of time.

We’d also expect the effect to be fairly immediate – that is to say, there shouldn’t be an enormous lag between the onset of the pandemic and the moment when prices started rising.

With that said, here’s a plot of Single-Detached home prices for every region tracked by CREA across Canada, with the dashed red line denoting March 2020 (the onset of the Pandemic):

Looking at this chart, it does seem like the two criteria I outlined above are met, but I’ll be the first to admit this is still not an open-and-shut case.

There’s a lot of moving parts to this question, but I do think this plot provides some compelling evidence that – even if people didn’t move from cities to the burbs – their money probably did.

But, here’s an interesting conundrum.

If there really was a ‘flight to the burbs’, then shouldn’t we have observed weak (if not downward) price pressure on the attached homes segments (i.e. apartments & townhouses)?

Since the CREA data is actually broken out along these dimensions, we can actually take a look:

So. I don’t know. ¯\_(ツ)_/¯

Sure, it looks like there might have been more of a lag in price movement for (certain) markets in the attached segments, but a lot of these markets have (now) seen upward price pressure as well.

The extra-weird part is that borders were basically shut for the first while of the pandemic here in Canada, so it’s hard to pin these price movements on immigration (although, money could have certainly still crossed borders even when people couldn’t).

Either way, one thing is certain: somehow, against all odds, Canadian housing prices have completely defied expectations and made complete fools out of just about everyone who makes a living forecasting housing markets.

Price Differentials

With prices being where they are today for housing in Canada, and particularly single-detached housing in certain markets (i.e. Vancouver, Toronto), you’d think some lucky owners of this product type might be incentivized to sell out of an expensive market and move to a cheaper one.

Key among the various factors that enter into this (mental) calculus would be the relative price differential of single-detached housing prices between markets.

As it turns out, we can visualize this idea with these data.

Here’s a plot showing the relative price differentials of single-detached homes between markets:

(Note: This plot might take a moment to render and won’t display well on smartphones, unless in widescreen mode).

Interesting stuff.

Among the various markets, Vancouverite single-detached owners appear to be among the ‘luckiest’ (in terms of prices), in that they could likely cash-out of their Vancouver house and move to another house in a cheaper market while pocketing over $1m in many cases. Torontonians also fare pretty well (as expected).

This exercise could be repeated with Apartment and Townhouse prices as well, which are also contained in the CREA data.

For anyone interested in looking at other price spreads or toying around with the data themselves, the data and code needed to build these charts is available on Github here.

Footnotes

  1. Note: It’s debatable whether one really needs to seasonally adjust housing price data. There are pros and cons to doing so, but that’s a lengthy topic and probably good subject matter for a future post.↩︎

  2. Myself included!↩︎