Real estate pundits point to the average sale price to conclude whether the market is crashing or hyper-inflating. Some go as far as to use the average sale price as an indicator of a recession or a healthy economy. The problem is that averages don’t tell much of a story.

For example, Canada has experienced five recessions of varying degrees between 1972 and 2018, yet the average sale price never dipped below the previous year, except between 1995 to 1996.

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The odd thing is that there was no recession in 1995 to 1996, but there were recessions in the mid 1970s, early ’80s, early ’90s and 2008; yet, the average sale price didn’t dramatically crash during these times. Rather, it increased. To put it another way, if you relied upon “the average”, you’d be led to believe that: (a) we never had a recession until 1995; (b) recessions last only a year and (c) you’ll always make a profit house flipping if you simply just wait a year.

If you bought a home right before the 1974 crash, the early 80s or 90s crash, you know this is not the case. You also know that house flipping isn’t always a guaranteed success – costs in maintaining the property, construction, changing zoning bylaws and even changes in demographic tastes can certainly make a flip a financial disaster.

When you peel back the layers of the “average” provided, you discover a more complex story. Averages mislead when a distribution is heavily stacked at one end, with a small number of unusual outliers weighing the average in their favour. It also misleads if you don’t know the story behind how that number came to be.

Consider the example provided by New York Times guest columnist Stephanie Coontz, When numbers mislead: “In 2011…the average income of the 7,878 households in Steubenville, Ohio, was $46,341. But if just two people, Warren Buffett and Oprah Winfrey, relocated to that city, the average household income in Steubenville would rise 62 per cent overnight, to $75,263 per household.”

The same logic can be applied to our housing market. Take, for example, the GTA’s average sale price to date in 2018 ($805,230) versus 2017 ($862,149). Some people conclude that the average price has decreased because we are in the throes of a housing crash. Nobody wants to buy. And, if they buy, they’re buying it for less than what they would’ve paid for the same property last year because there’s no demand and because last year’s prices were completely unsubstantiated.

Any millennial trying to buy a condo in South Riverdale, Mount Pleasant or Little Italy, however, would beg to differ. Condos in these areas saw an increase in sale price and most condos have sold above asking. Dig deeper and you find an even more complex story.

Those who want to buy larger homes in Toronto – young families or couples – cannot afford the millions that such homes command. And those who can afford it already live in those homes and aren’t interested in buying another multi-million-dollar home.

This more affluent (and older) demographic doesn’t want to sell because they know that demand for their properties isn’t as great as it was in our anomalous record setting-market of 2017 (the multi-million-dollar homes are still selling, it’s just taking slightly longer than it did during the hype of the market; nonetheless, our market turnover is still much faster than in other high-demand markets such as London and Paris). And for those who are looking to downsize, they’re not necessarily selling their primary home. Rather, they’re holding onto their primary homes and buying a cheaper and smaller second home, putting more pressure on the same market in which the millennials are competing for some territory (literally). This has the obvious outcome of creating more competition in the cheaper market than in the multi-million-dollar market. The average is skewed because it is heavily stacked with lots of smaller rather than larger price points.

Purchasing power has further eroded not because of an economic crash or lack of demand, but because of changes in the law. Young families or young couples – the backbone of house purchases – were most affected by the changes in mortgage rules. This means that, due to bad luck, today’s buyers can afford less than they could’ve afforded last year. In turn, people are buying cheaper and smaller homes even if it isn’t the best fit for their lifestyle (large bedrooms for each child, play room). Again, it’s not that demand is down or that prices are plummeting, it’s that the type of demand has shifted because who is buying has changed and how much they can spend has changed.

Digging beyond the average shows that this is a supply problem, not a demand problem. Perhaps our government is focused too much on the average and should re-shift its focus from curtailing demand to increasing supply.


  1. Natalka, do you suppose your last paragraph has anything to do with the law of diminishing returns?

    There’s some additional interesting information in the subset and linked bits here for those who are technically involved in trying to formulate conclusions that fly in the face of supply and demand. We minions are not likely to figure out the government why’s and how come’s anytime soon.

    Carolyne L ?

  2. Speaking of averages… …the average cost to trade up for a middle income family from a moderate condo to a family home is no less than $50,000.00 to $75,000.00. This is average not high end. Double land transfer tax continues to have a huge impact on the supply chain (thank you David Miller former Mayor). It is just too expensive to trade up causing a shortage on entry level homes. Of course we will keep electing this people and nothing will change.

  3. Your articles are always on point, Natalka. And certainly your comment on averaging is absolute.

    REM prior contributor Ross Kay had plenty to say about averaging and he, too, spoke the truth. The word averaging, itself, should perhaps be eliminated from the real estate lexicon. The use of the term no matter how well thought to be substantiated borders on (innocent) misrepresentation.

    The only purpose I can see is that over long periods of time, bell curves can be created using averaging that perhaps merely show overviews, in stacked Mylar sheets. Using averaging stats in agency fiduciary representation could get an agent in plenty of hot water, and not worth taking such a chance either in marketing promo or one on one oral or written discussion with the public.

    Even in farming a tight geographical area, new agents need to be warned about using such methods of communicating (values).

    I had posted a comment regarding averaging at the REM link below.

    Carolyne L ?


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