Here is a news story on the outlook for Toronto real estate in 2017: Toronto real estate heading for another hot year: TREB .
I had a look at real estate market conditions for the Greater Toronto Area for the month of November 2016. It’s interesting looking through the data to see what is actually going on in the market. The data may be found in the TREB Market Watch.
Sales for the month of November were a total of 8,547 units throughout the GTA. When you think about the number of units for one month for the entire GTA, it seems to be a pretty small market. What’s also interesting is the breakdown of the sales prices. Now bear in mind that these are averages and not the median prices. Given the data, it’s hard to know what is really selling the most, but I can figure that out later.
Housing prices and units
In November the average house price was just under $770,000. The average prices are: Detached-$1,058,273; Semi-detached-$720,815; Townhouse-$598,432; Condo-$443,586.
The breakdown of unit sales is 3,890 detached houses, 798 semis, 1,318 townhouses and 2,409 condos. Condos and townhouses make up the bulk of the sales, which should not be surprised, they are cheaper.
In won’t go through the spread between 905 properties and 416 properties but will add that 416 real estate sells at around a 20-30% premium over 905 area code real estate. For those of you who don’t know, the 905 versus 416 location is based on area codes. 416 is primarily those areas that used to constitute the old city of Toronto before amalgamation.
In looking at the figures, you can see a definite split in terms of prices. There is a considerable difference between the detached houses and the other forms of residential real estate. Nothing new here. Detached housing is generally more expensive than the others all things being equal.
Units sold tells another story. I am going to look at the year ending November 30, 2016. 107,840 houses were sold during the period, 48% detached and 52 other forms of construction. About 25% of the homes had a purchase price exceeding $900,000. The balance of 75% was with a median purchase price of around $600,000.
Now why have I broken down the sales data this way? I believe that there are really two markets here. The market for detached houses and the market for the others. Why is the distinction important? It relates to affordability. I would think (without data to support it) that the homes being bought over $1,000,000 are being acquired by people who have greater financial resources than those who are buying at around the $600,000 level. Those in the $1,000,000 plus bracket will likely be able to weather an increase in interest rates better those buying around the $600,000 level. I’ll see if there is some data out there to support this.
An increase in interest rates will bite. Some of the analysis out there concludes that we can weather the storm. Unfortunately, like most countries, we have those who are financially insulated from interest rate increases and those who are not. Those who are not will bear the brunt of it and will struggle.
The problem with monitoring housing prices is that the market is very illiquid. In each neighborhood, there are only a few houses to sell. With demand, increasing prices is pretty simple. One house that attracts interest will lift the average house price and impacts subsequent sales.
Real estate agents look at the recent sales as the basis for determining what their clients should bid. To the extent that the market is hot, a bidding war will impact all the house sales subsequent to it. Illiquid markets are particularly prone to this. Add irrational exuberance and you have recipe for a hot real estate market. No one wants to miss the boat.
I just spent some hours reading this book about behavioral finance. It’s quite a good read if you have not been exposed to the topic before. It discusses how we get into these “bubble” scenarios in financial and other markets such as real estate. For me, it was really a summary of the rather obvious things that we can see by just looking at what goes on in the world around us. If you have not been exposed to this material before, it’s a must read.
One of the areas discussed is crowd psychology. In particular, that we are followers and that we’ll do that without very much thought. For example, you’re looking for a restaurant. You’ll see one packed with people and the other empty. Now the empty one might just be empty for a number of reasons unrelated to the quality or price of the food served. The restaurant that is packed may just be the star restaurant of the moment. But people will avoid the empty one and continue to fill the full one. The author doesn’t discuss how this situation gets remedied but just mentions how people behave.
The chapters discuss other examples of crowd psychology from a finance perspective. Where I find the book falls short is taking the next step. How do we use this information to modify our behavior when we invest, say, in real estate or the stock market? I often find that many of these authors are really good at describing the “what” but fall short is dealing with the “how”.
Notwithstanding these comments, if you want to start looking at the topic of behavioral finance, this book is a good place to begin your education.
Here is an article from the Financial Post quoting a recent study prepared by DBRS, the Canadian bond rating agency: Massive drop in housing prices would still leave Canadian households with more equity than debt. I find this one of the hardest articles to read that I have come across in a very long time. Here is a presentation by DBRS on the Canadian housing market. It summarizes their view on where things are. The numbers in the presentation are not supported by any calculations, so it’s not easy to see where they come from.
It’s hard to understand where the average household net worth comes from. Likely a Statistics Canada number. Once again, the average is used rather than the median so the number is heavily impacted by high net worth individuals.
Data from Statistics Canada
Here is a recent report prepared by Statistics Canada on the subject: Annual Household Distribution Tables, estimates of assets, liabilities, and net worth, 2012 to 2015 (provisional estimates). Here is a quote from this report which is relevant to the DBRS comments on the state of affairs in Canada:
Households in the middle of the income distribution have a higher debt burden
Household wealth, or net worth, is not distributed equally by income quintile. Looking at shares for both 2012 and 2015, households in the top income quintile (quintile 5) held more than 45% of total household networth, compared with about 9% for the bottom income quintile. From 2012 to 2015, the share of household net worth remained relatively stable by income quintile.
Households in the middle of the income distribution had a higher debt burden, or debt-to-asset ratio, than those in the top and bottom income quintiles. From 2012 to 2015, households in each income quintile reduced their debt-to-asset ratios by about 1 percentage point.
Households in the bottom income quintile held a higher share of their assets in life insurance and pensions than other quintiles, while all other income quintiles held a higher share of their assets in real estate and a higher share of their liabilities in mortgages.
You can see here how misleading the DBRS report is. It’s really disturbing to see such sloppy analysis. What Statistics Canada is telling us is that household wealth is not distributed evenly and that 45% of it is controlled by the top income earners. Think about that – 45%!!!
So when DBRS says that a significant drop in real estate prices would have a minimal effect on household equity, the statement is at best misleading. 80% of Canadians would be significantly impacted. This is the group that policy makers need to worry about, not the top 20%. In addition, note the comment on the assets classes. The bottom quintile held most of their assets in pensions and life insurance. Financial assets. While the higher quintiles held more real estate.
What the heck
It’s hard for me to understand why DBRS would choose to present the information on such a macro basis without any further analysis. It makes no sense other than it just sloppy. The fact of the matter is that Canadians who cannot afford a real estate price shock will be adversely affected if the market drops 30-40%. It will not impact individuals with exceedingly high net worth. So what’s new about that?