Canadian Real Estate Prices To Fall Up To 26%, Bay Street Firm Warns Institutions

Canadian real estate prices may take a big tumble, Bay Street researchers warn. Veritas Investment Research, a prominent Canadian firm, sent institutional clients a real estate forecast. The firm warned real estate price declines are unlikely, except in the event of supply shock. They now believe supply shock may arrive soon, and can send prices up to 26% lower.
About The Numbers
Veritas’ analysis is geared to investment managers, so it’s different from a bank forecast. The firm used regression analysis in its conclusion with various risk scenarios. They concluded months of inventory has the highest correlation with prices. Recently, the market has been tight, sending prices higher during a recession. They believe that’s about to change when mortgage deferrals expire, and things get back to “normal.”
The firm’s model is based on a percent of mortgage payment deferrals turning into inventory. They gave scenarios for 5%, 10%, or 15% of homeowners with deferrals turning into sellers. This isn’t the same as assuming they’ll default. While some people will default, you typically never default if you can sell first. Canada’s tight housing supply means most people can do that, instead of defaulting. This is a point the CMHC has recently made as well, so it’s not an outlandish assumption. It’s actually an ideal scenario.
We should also first add, they warned clients about the uncertainty during the pandemic. Since pretty much nothing has been predictable, they’re advising clients to watch the months of inventory closely. In other words, do your own due diligence, but this is what they’re watching for and expect at this time.
Canadian Real Estate Prices To Drop Up To 11%
Canadian real estate prices are expected to make modest to substantial declines. The firm’s model suggests potential price declines between 4 and 11 percent. As stated before, this is based on the assumption inventory will rise as a result of deferrals turning into listings. This doesn’t include additional supply, which Canada is currently building records amounts of, and is often flipped back into resale markets.
Toronto Real Estate Prices May Drop Up To 26%
Toronto real estate has the largest dive in the forecast. The firm expects a potential price drop between 15 and 26 percent. For the regional models, they assumed a distribution of deferrals was similar to that of all real estate markets. However, CMHC deferral data shows Toronto may be overrepresented in the deferrals.
Vancouver Real Estate Prices To Drop Up To 17%
Vancouver real estate’s prices are forecasted to make a smaller drop than Toronto. The firm sees a potential price drop between 10 and 17 percent. They are once again assuming a proportional distribution of deferrals. Worth mentioning, the CMHC also forecasted smaller price declines for Vancouver as well. However, their numbers didn’t show as quick of a recovery for prices as Toronto.
The firm expects this price movement around six months after the inventory increase. The timeline puts it fairly close to when the CMHC has been forecasting. The forecast is a little more aggressive than those of banks and other vested interests. However, it’s similar to what other institutional risk advisory firms have forecasted. It’s also similar to Canada’s state-backed mortgage insurer.
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CRA: 800,000 Ineligible People Did Not Get CERB, But They’re Checking Applications

Canada’s national tax agency clarified a major news organization’s allegations of CERB “ineligibility” is, well… not entirely accurate. The Canada Revenue Agency (CRA) responded to our request for clarification on tax-filer application data yesterday. CRA spokesperson Pamela Tourigny didn’t just clarify the data, but also generously provided their take on CERB fraud, and how they plan on dealing with it.
No, 800,000 Canadians Didn’t Collect CERB While Ineligible
Despite the rumors started by a major news organization, the data doesn’t show hundreds of thousands of ineligible CERB claims. This mistake was due to people interpreting 800,000 claims without taxes filed in 2019, as ineligible. Like we pointed out when breaking down the impact to income flow, unfiled 2019 taxes didn’t necessarily mean applicants are ineligible. It just meant the data wasn’t ready, and will need verification later.
“For the emergency benefits, there is no requirement for individuals to have filed a tax return. As such, it would be erroneous to conclude that claims from applicants who have not filed a tax return are being paid out to fraudsters or to non-eligible individuals. Income eligibility for Canada Emergency Response Benefit (CERB) is determined based on an individual having earned a minimum of $5,000 (before taxes) in the last 12 months, or in 2019 from one of the following sources: employment, self-employment or provincial benefit payments related to maternity or paternity leave.”
The CRA Will Verify CERB Eligibility Next Tax Season
It would be naive to say some Canadians didn’t cheat the system. It’s a fact some people cheated to get CERB. However, it’s a little more difficult to know if they intentionally did it, or it was accidental. The CRA won’t have the full data to verify these circumstances until the end of this tax year. They mention they’ll be verifying this information during the next tax season.
“…we will take steps at a later time to verify that claimants were eligible to receive payments for any COVID-related economic measures. The CRA has records of those who received the CERB and for what period. These will be used, along with tax slips received from employers and other relevant information available to the CRA, to validate eligibility next tax filing season. Where eligibility is in question, a review will be conducted to ensure that recipients were only paid amounts they were entitled to.”
No, Repayment Won’t Be An Unfair Burden On Low Income Households
The other concern frequently circulating is low income Canadians found to be ineligible, will be punished. That’s not exactly the case. If the CRA finds people were ineligible, they plan on working with them to create a repayment plan based on their income. In this case, the economy essentially used a pull-forward mechanism on consumer spending. For those that refuse to repay if found ineligible, the agency claims they may take further legal action. Below is the statement from the CRA:
“The CRA is sensitive to the hardship of Canadians still facing the financial impacts of COVID-19. The payment arrangement parameters have been expanded to give Canadians more time and flexibility to repay based on their ability to pay. If an individual is unable to repay ineligible CERB amounts, we will evaluate their situation and follow-up when their financial circumstances change. Canadians who applied for the CERB in good faith, and later determined they were ineligible will be required to pay money back without penalties or interest. For situations when an individual has the capacity to pay and refuses to reach a mutually acceptable payment arrangement, the CRA may take legal action.”
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Canada Saw Tens Of Thousands Of Six-Figure Earners Apply For Emergency Income

Canada’s emergency benefit applications are giving a little more insight into income disruption. Canada Revenue Agency data presented to the House of Commons shows a breakdown of CERB applicant income from last year. The data, first reported by Blacklock’s Reporter, shows hundreds of thousands of applicants didn’t file taxes at the time of application. More interesting though, is the number of high income applicants. Tens of thousands of CERB applicants made six-figures last year. This shows an altered income pattern for many of Canada’s top earners.
Why Is This Important?
Today we’re looking at CERB applicants by income reported in tax filings the previous year. For non-Canadians, the Canada Emergency Response Benefit (CERB) was a $2,000 monthly emergency payment, given to people with pandemic related income losses. This is a similar amount made by many low income Canadians. However, it’s a lot lower than the income made by thousands of people that applied.
Somewhat surprising, is that tens of thousands of relatively high income Canadians applied for CERB. Now, this isn’t a rich bashing piece to say they didn’t need it. This tells us about a disruption in income, or a delay some Canadians made paying themselves. This will alter, delay, or eliminate consumer consumption. If the losses are semi-permanent, then this buying power disappears from the economy. If it was just delayed or paused, it explains why we’re seeing income catapult so quickly again, and should expect a consumption boom. This data point further adds to the excess savings trend we discussed yesterday.
Over 128,000 Applicants Made 6-Figures A Year Before
Tens of thousands of Canadians that applied for the pandemic income, made over six figures. Even more had income just below that mark. CRA data shows 90,720 people applied for CERB that had an income between $93,259 to $147,667 in 2019. Another 23,900 applicants filed taxes that showed they made between $147,667 and $210,371 last year. In the highest disclosed bracket, 14,070 applied for CERB that made over $210,371 last year. If all approved, this would be between $209.58 million to $1.26 billion of benefits consumed by this demographic.
Canadian CERB Applicants By 2019 Tax Bracket
The number of CERB applicants by 2019 tax bracket, including those that have not filed 2019 taxes.The largest pool of applicants was relatively low income. The majority, 3,844,090 applicants, made less than $47,630 the year before applying. This represents about 71.45% of the applicants. In some instances, low income households may have made more on CERB. However, there may be cases where they had their income cut in half as well.
The Second Largest Demographic Is Completely Unknown
Another interesting observation in the data is the second largest segment of applicants didn’t file taxes. There were 823,580 CERB applicants who did not file 2019 taxes at the time of application. The read on that is a little more mixed in my opinion. It doesn’t mean they weren’t automatically ineligible. The income tax filing deadline was pushed to September 30, the day these numbers were tallied. Further, the criteria reads:
“Who had employment and/or self-employment income of at least $5,000 in 2019 or in the 12 months prior to the date of their application”
This makes the takeaway a little less obvious. There’s no doubt a number of people that didn’t technically qualify for CERB, took it anyway. There are also a number of people that may have been late on taxes, or earned the $5,000 minimum in 2020. These people would have still been eligible. Basically, not even the government is sure how this will change spending patterns.
Households that didn’t need CERB, but qualified and took it anyway, helps explain the savings glut. Without an income cap on benefits, the cash just helped pad savings accounts. The bad news is, high income households just received a subsidized cheque. The good news is they’ll probably spend that money in the economy when it reopens.
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CIBC: Canadians Have $90 Billion In Excess Cash, As Government Doubles Income Lost

Canadian households are sitting on a record amount of cash, waiting to be spent. CIBC Economics’ latest report shows tens of billions in cash just sitting in accounts in Q2 2020. The increase is due to a combination of government supports, lack of places to spend, and payment deferrals.
Canadian Households Saved $90 Billion More Than Expected
Canadians are holding onto an astronomical amount of cash in their bank accounts. CIBC estimates households have saved $90 billion more than typical in Q2 2020. They estimate the amount to be equivalent to 4% of consumer spending. So suddenly everyone’s a great saver, in a country with notoriously high household debt? Not exactly.
Government Transfers Equal $2.25 For Each Dollar Of Income Lost
The bank believes this is largely due to government transfers. The lost income fell $100 billion seasonally adjusted at the annual rate (SAAR) for Q2 2020. This was matched with government transfers from programs like CERB, that add up to $225 billion SAAR. To put it bluntly, the government replaced every $1 of income lost, with $2.25 in the quarter. An unprecedented event for a recession.
Canada’s Household Savings Rate Hits 28%
Combine the higher income delivery with restricted spending, and mortgage deferrals – and you get a lot of cash. Prior to the pandemic, the saving’s rate had reached 3.6% – already a worrying climb. During the pandemic, it escalated to as high as 28.2% in June. In periods of recession, savings rates tend to jump as people worry. When most places are shut down, it becomes pretty hard to spend, even if you try.
Canadian Household Savings Rate
The seasoanlly adjusted rate of household savings.
Quarter | Percent |
---|---|
Q1 1961 | 1.3 |
Q2 1961 | 0.4 |
Q3 1961 | 1.1 |
Q4 1961 | 2.1 |
Q1 1962 | 3.7 |
Q2 1962 | 3 |
Q3 1962 | 4.6 |
Q4 1962 | 3.6 |
Q1 1963 | 4.7 |
Q2 1963 | 3.7 |
Q3 1963 | 3.4 |
Q4 1963 | 4.1 |
Q1 1964 | 3.9 |
Q2 1964 | 3.3 |
Q3 1964 | 3 |
Q4 1964 | 3.1 |
Q1 1965 | 5.7 |
Q2 1965 | 3.3 |
Q3 1965 | 4.7 |
Q4 1965 | 4.8 |
Q1 1966 | 6.2 |
Q2 1966 | 6.8 |
Q3 1966 | 5.8 |
Q4 1966 | 6.6 |
Q1 1967 | 5.9 |
Q2 1967 | 6.1 |
Q3 1967 | 6 |
Q4 1967 | 4.7 |
Q1 1968 | 3.2 |
Q2 1968 | 5.7 |
Q3 1968 | 4.3 |
Q4 1968 | 4 |
Q1 1969 | 4.5 |
Q2 1969 | 3.6 |
Q3 1969 | 4.7 |
Q4 1969 | 4.3 |
Q1 1970 | 6.6 |
Q2 1970 | 4.2 |
Q3 1970 | 5 |
Q4 1970 | 5.5 |
Q1 1971 | 7.9 |
Q2 1971 | 5.6 |
Q3 1971 | 5.5 |
Q4 1971 | 5.2 |
Q1 1972 | 7.9 |
Q2 1972 | 7.2 |
Q3 1972 | 7.5 |
Q4 1972 | 8.5 |
Q1 1973 | 7.7 |
Q2 1973 | 9.3 |
Q3 1973 | 10.2 |
Q4 1973 | 11.7 |
Q1 1974 | 11.2 |
Q2 1974 | 8.9 |
Q3 1974 | 11.9 |
Q4 1974 | 13.8 |
Q1 1975 | 12.1 |
Q2 1975 | 12.8 |
Q3 1975 | 13.2 |
Q4 1975 | 12 |
Q1 1976 | 12.8 |
Q2 1976 | 13.6 |
Q3 1976 | 10.7 |
Q4 1976 | 11.8 |
Q1 1977 | 11.2 |
Q2 1977 | 13.4 |
Q3 1977 | 10.9 |
Q4 1977 | 11.4 |
Q1 1978 | 13.7 |
Q2 1978 | 12.8 |
Q3 1978 | 12.1 |
Q4 1978 | 12.6 |
Q1 1979 | 11.6 |
Q2 1979 | 14.1 |
Q3 1979 | 13.2 |
Q4 1979 | 14.4 |
Q1 1980 | 14.1 |
Q2 1980 | 14.9 |
Q3 1980 | 13.9 |
Q4 1980 | 14.9 |
Q1 1981 | 16.4 |
Q2 1981 | 17.3 |
Q3 1981 | 17.8 |
Q4 1981 | 18.2 |
Q1 1982 | 21.6 |
Q2 1982 | 21.3 |
Q3 1982 | 20.2 |
Q4 1982 | 18.6 |
Q1 1983 | 16.6 |
Q2 1983 | 14.7 |
Q3 1983 | 18.7 |
Q4 1983 | 15.7 |
Q1 1984 | 14.6 |
Q2 1984 | 17 |
Q3 1984 | 17.7 |
Q4 1984 | 17.1 |
Q1 1985 | 15.8 |
Q2 1985 | 17.6 |
Q3 1985 | 14.6 |
Q4 1985 | 14.3 |
Q1 1986 | 14 |
Q2 1986 | 14 |
Q3 1986 | 12 |
Q4 1986 | 12.3 |
Q1 1987 | 12.5 |
Q2 1987 | 11 |
Q3 1987 | 11.3 |
Q4 1987 | 11 |
Q1 1988 | 10 |
Q2 1988 | 11.5 |
Q3 1988 | 13 |
Q4 1988 | 13.2 |
Q1 1989 | 13.5 |
Q2 1989 | 12.8 |
Q3 1989 | 12.1 |
Q4 1989 | 12.2 |
Q1 1990 | 13.1 |
Q2 1990 | 11.4 |
Q3 1990 | 13.1 |
Q4 1990 | 13.9 |
Q1 1991 | 14.8 |
Q2 1991 | 11.6 |
Q3 1991 | 12.7 |
Q4 1991 | 13.1 |
Q1 1992 | 12 |
Q2 1992 | 13 |
Q3 1992 | 14.6 |
Q4 1992 | 12.2 |
Q1 1993 | 12.3 |
Q2 1993 | 15.4 |
Q3 1993 | 11.7 |
Q4 1993 | 10.4 |
Q1 1994 | 10.3 |
Q2 1994 | 11 |
Q3 1994 | 10 |
Q4 1994 | 9.6 |
Q1 1995 | 10 |
Q2 1995 | 9.8 |
Q3 1995 | 8.7 |
Q4 1995 | 8.9 |
Q1 1996 | 7.6 |
Q2 1996 | 7.2 |
Q3 1996 | 6.9 |
Q4 1996 | 5.6 |
Q1 1997 | 4.5 |
Q2 1997 | 4.3 |
Q3 1997 | 4.9 |
Q4 1997 | 3.7 |
Q1 1998 | 4.9 |
Q2 1998 | 3.6 |
Q3 1998 | 4.6 |
Q4 1998 | 5.5 |
Q1 1999 | 4.5 |
Q2 1999 | 5 |
Q3 1999 | 4.6 |
Q4 1999 | 4.2 |
Q1 2000 | 4.6 |
Q2 2000 | 4.6 |
Q3 2000 | 4.7 |
Q4 2000 | 5.8 |
Q1 2001 | 6.5 |
Q2 2001 | 2.9 |
Q3 2001 | 4.8 |
Q4 2001 | 5.1 |
Q1 2002 | 5.2 |
Q2 2002 | 2.5 |
Q3 2002 | 2.7 |
Q4 2002 | 2.4 |
Q1 2003 | 2.5 |
Q2 2003 | 3 |
Q3 2003 | 1.2 |
Q4 2003 | 2 |
Q1 2004 | 1.8 |
Q2 2004 | 2.9 |
Q3 2004 | 2.6 |
Q4 2004 | 2.7 |
Q1 2005 | 0.4 |
Q2 2005 | 1.3 |
Q3 2005 | 2.1 |
Q4 2005 | 2.1 |
Q1 2006 | 3.1 |
Q2 2006 | 1.3 |
Q3 2006 | 2.8 |
Q4 2006 | 3.5 |
Q1 2007 | 4.5 |
Q2 2007 | 1.7 |
Q3 2007 | 1.3 |
Q4 2007 | 1.1 |
Q1 2008 | 2.5 |
Q2 2008 | 3 |
Q3 2008 | 3.1 |
Q4 2008 | 5 |
Q1 2009 | 4.6 |
Q2 2009 | 4.8 |
Q3 2009 | 4.8 |
Q4 2009 | 4.3 |
Q1 2010 | 5.4 |
Q2 2010 | 3.7 |
Q3 2010 | 3.8 |
Q4 2010 | 4.2 |
Q1 2011 | 4.5 |
Q2 2011 | 4.3 |
Q3 2011 | 4.3 |
Q4 2011 | 4.3 |
Q1 2012 | 4.7 |
Q2 2012 | 4.9 |
Q3 2012 | 5.4 |
Q4 2012 | 5.2 |
Q1 2013 | 5.8 |
Q2 2013 | 5 |
Q3 2013 | 4.8 |
Q4 2013 | 4.9 |
Q1 2014 | 4.3 |
Q2 2014 | 3.9 |
Q3 2014 | 3.8 |
Q4 2014 | 3.5 |
Q1 2015 | 5.6 |
Q2 2015 | 5.3 |
Q3 2015 | 4.1 |
Q4 2015 | 3.1 |
Q1 2016 | 0.9 |
Q2 2016 | 2.2 |
Q3 2016 | 2.3 |
Q4 2016 | 2.4 |
Q1 2017 | 0.7 |
Q2 2017 | 1.9 |
Q3 2017 | 3.1 |
Q4 2017 | 2.5 |
Q1 2018 | 2 |
Q2 2018 | 1.9 |
Q3 2018 | 1.3 |
Q4 2018 | 1.9 |
Q1 2019 | 2.3 |
Q2 2019 | 3.1 |
Q3 2019 | 3 |
Q4 2019 | 3.6 |
Q1 2020 | 7.6 |
Q2 2020 | 28.2 |
A second lockdown is approaching, but another surge of excess capital is unlikely. Programs are now much more targeted, and payment deferrals aren’t raining from the sky. However, this is still a very large capital pool that’s going to need to be deployed in a more efficient manner soon. However, a more important takeaway is there’s households with massive piles of cash waiting to spend, in an economy that has fewer and fewer players by the day.
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Canadian Real Estate Sales Slow For The First Time Since The Beginning Of Pandemic

Canadian real estate is still booming, but slowing faster than seasonally expected. Canadian Real Estate Association (CREA) data shows sales made a small decline in October. The decline only shows in the board’s seasonally adjusted numbers. Unadjusted sales still show large growth, but the rate decelerated for the first time since the pandemic.
Canadian Real Estate Sales “Edged Back” 0.7%
Canadian real estate sales are showing some signs pent-up demand is catching up. CREA data shows 56,186 seasonally adjusted sales in October, down 0.7% from the month before. Unadjusted, there were 59,159 sales in the month, up 32.1% from the same month last year. CREA notes sales “edged back” on the seasonally adjusted count, falling from all-time highs. On the unadjusted numbers, we can see sales are strong. They do seem much stronger due to the shifted comparison period though.
Canadian Real Estate Sales
The unadjusted sales for all home types, as reported through the Canadian MLS.Month | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|
Jan | 23,289 | 25,292 | 25,534 | 24,977 | 24,380 | 27,195 |
Feb | 32,898 | 38,856 | 37,754 | 31,356 | 30,074 | 38,161 |
Mar | 45,527 | 50,773 | 54,290 | 41,983 | 40,167 | 43,317 |
Apr | 52,982 | 58,106 | 53,796 | 46,344 | 48,599 | 20,630 |
May | 56,545 | 61,412 | 60,594 | 51,181 | 54,599 | 33,051 |
Jun | 57,380 | 60,132 | 53,344 | 47,613 | 47,755 | 54,928 |
Jul | 50,036 | 48,577 | 42,599 | 41,872 | 47,793 | 62,533 |
Aug | 43,103 | 47,419 | 42,769 | 41,151 | 43,478 | 58,645 |
Sep | 42,615 | 44,332 | 39,585 | 36,201 | 41,819 | 61,308 |
Oct | 41,981 | 42,537 | 40,691 | 39,313 | 44,499 | 59,159 |
Nov | 36,846 | 37,178 | 38,095 | 33,437 | 37,213 | |
Dec | 27,488 | 26,158 | 27,206 | 21,983 | 26,976 |
Sales Growth Slows For The First Time Since The Pandemic
Unadjusted growth was large, but also showed some signs of reality returning. The growth rate of 32.1% is massive when looked at by itself. In context, this shows the first deceleration since April. This decline is more than likely a temporary detour, as comparison months to the shutdown in April and May approach.
Canadian Real Estate Sales Change
The annual percent chage of unadjusted sales for all home types, as reported through the Canadian MLS.Month | Unadjusted |
---|---|
Jan 2008 | -8.57 |
Feb 2008 | -8.78 |
Mar 2008 | -18.94 |
Apr 2008 | -7.04 |
May 2008 | -17.41 |
Jun 2008 | -15.35 |
Jul 2008 | -12.25 |
Aug 2008 | -20.83 |
Sep 2008 | -3.49 |
Oct 2008 | -27.27 |
Nov 2008 | -42.32 |
Dec 2008 | -32.86 |
Jan 2009 | -40.51 |
Feb 2009 | -31.47 |
Mar 2009 | -13.97 |
Apr 2009 | -11.58 |
May 2009 | -0.86 |
Jun 2009 | 17.67 |
Jul 2009 | 18.69 |
Aug 2009 | 18.69 |
Sep 2009 | 17.31 |
Oct 2009 | 41.73 |
Nov 2009 | 72.75 |
Dec 2009 | 72.65 |
Jan 2010 | 56.26 |
Feb 2010 | 44.22 |
Mar 2010 | 40.3 |
Apr 2010 | 20.4 |
May 2010 | -4.63 |
Jun 2010 | -19.88 |
Jul 2010 | -29.98 |
Aug 2010 | -19.85 |
Sep 2010 | -19.97 |
Oct 2010 | -21.62 |
Nov 2010 | -9.66 |
Dec 2010 | -14.63 |
Jan 2011 | -6.21 |
Feb 2011 | -5.53 |
Mar 2011 | -6.41 |
Apr 2011 | -14.69 |
May 2011 | 2.72 |
Jun 2011 | 11.2 |
Jul 2011 | 12.66 |
Aug 2011 | 16.12 |
Sep 2011 | 11.73 |
Oct 2011 | 9.03 |
Nov 2011 | 5.52 |
Dec 2011 | 4.76 |
Jan 2012 | 4 |
Feb 2012 | 8.66 |
Mar 2012 | 1.34 |
Apr 2012 | 10.99 |
May 2012 | 8.72 |
Jun 2012 | -4.71 |
Jul 2012 | 2.43 |
Aug 2012 | -8.87 |
Sep 2012 | -15.13 |
Oct 2012 | -0.86 |
Nov 2012 | -12.08 |
Dec 2012 | -17.59 |
Jan 2013 | -6.09 |
Feb 2013 | -16.81 |
Mar 2013 | -15.11 |
Apr 2013 | -3.36 |
May 2013 | -2.61 |
Jun 2013 | -0.55 |
Jul 2013 | 9.59 |
Aug 2013 | 11.35 |
Sep 2013 | 17.74 |
Oct 2013 | 8.09 |
Nov 2013 | 5.83 |
Dec 2013 | 12.27 |
Jan 2014 | 0.64 |
Feb 2014 | 3.2 |
Mar 2014 | 4.88 |
Apr 2014 | 0.35 |
May 2014 | 5.46 |
Jun 2014 | 11.53 |
Jul 2014 | 8.1 |
Aug 2014 | 2.32 |
Sep 2014 | 11.13 |
Oct 2014 | 7.57 |
Nov 2014 | 3.12 |
Dec 2014 | 8.61 |
Jan 2015 | -1.97 |
Feb 2015 | 2.67 |
Mar 2015 | 9.14 |
Apr 2015 | 9.9 |
May 2015 | 3.36 |
Jun 2015 | 10.96 |
Jul 2015 | 3.56 |
Aug 2015 | 3.93 |
Sep 2015 | 0.31 |
Oct 2015 | 0.33 |
Nov 2015 | 10.38 |
Dec 2015 | 10.26 |
Jan 2016 | 8.6 |
Feb 2016 | 18.11 |
Mar 2016 | 11.52 |
Apr 2016 | 9.67 |
May 2016 | 8.61 |
Jun 2016 | 4.8 |
Jul 2016 | -2.92 |
Aug 2016 | 10.01 |
Sep 2016 | 4.03 |
Oct 2016 | 1.32 |
Nov 2016 | 0.9 |
Dec 2016 | -4.84 |
Jan 2017 | 0.96 |
Feb 2017 | -2.84 |
Mar 2017 | 6.93 |
Apr 2017 | -7.42 |
May 2017 | -1.33 |
Jun 2017 | -11.29 |
Jul 2017 | -12.31 |
Aug 2017 | -9.81 |
Sep 2017 | -10.71 |
Oct 2017 | -4.34 |
Nov 2017 | 2.47 |
Dec 2017 | 4.01 |
Jan 2018 | -2.18 |
Feb 2018 | -16.95 |
Mar 2018 | -22.67 |
Apr 2018 | -13.85 |
May 2018 | -15.53 |
Jun 2018 | -10.74 |
Jul 2018 | -1.71 |
Aug 2018 | -3.78 |
Sep 2018 | -8.55 |
Oct 2018 | -3.39 |
Nov 2018 | -12.23 |
Dec 2018 | -19.2 |
Jan 2019 | -2.39 |
Feb 2019 | -4.09 |
Mar 2019 | -4.63 |
Apr 2019 | 4.57 |
May 2019 | 6.68 |
Jun 2019 | 0.3 |
Jul 2019 | 14.14 |
Aug 2019 | 5.65 |
Sep 2019 | 15.52 |
Oct 2019 | 13.19 |
Nov 2019 | 11.29 |
Dec 2019 | 22.71 |
Jan 2020 | 11.55 |
Feb 2020 | 26.89 |
Mar 2020 | 7.85 |
Apr 2020 | -57.55 |
May 2020 | -39.8 |
Jun 2020 | 15.2 |
Jul 2020 | 30.84 |
Aug 2020 | 33.5 |
Sep 2020 | 45.6 |
Oct 2020 | 32.1 |
Looking at sales on a rolling 12-month basis helps to smooth out some of the distortion. The 12-month rolling average of sales reached 43,593 sales for October, up 9.30% from the same month last year. This is the highest seen since July 2017, when sales were cooling after a multi-year build up to that level. The pandemic’s shutdown of sales still skews the numbers, but it gives the growth a little perspective.
Canadian Real Estate Sales: Rolling Average
The 12-month rolling average of Canadian real estate sales.Month | 12-Months Rolling |
---|---|
Jan 2008 | 43,457 |
Feb 2008 | 43,162 |
Mar 2008 | 42,366 |
Apr 2008 | 42,054 |
May 2008 | 41,168 |
Jun 2008 | 40,463 |
Jul 2008 | 39,968 |
Aug 2008 | 39,175 |
Sep 2008 | 39,065 |
Oct 2008 | 38,129 |
Nov 2008 | 36,837 |
Dec 2008 | 36,182 |
Jan 2009 | 35,246 |
Feb 2009 | 34,281 |
Mar 2009 | 33,805 |
Apr 2009 | 33,329 |
May 2009 | 33,293 |
Jun 2009 | 33,980 |
Jul 2009 | 34,643 |
Aug 2009 | 35,206 |
Sep 2009 | 35,732 |
Oct 2009 | 36,774 |
Nov 2009 | 38,055 |
Dec 2009 | 39,028 |
Jan 2010 | 39,801 |
Feb 2010 | 40,730 |
Mar 2010 | 41,912 |
Apr 2010 | 42,654 |
May 2010 | 42,461 |
Jun 2010 | 41,551 |
Jul 2010 | 40,290 |
Aug 2010 | 39,580 |
Sep 2010 | 38,868 |
Oct 2010 | 38,103 |
Nov 2010 | 37,809 |
Dec 2010 | 37,471 |
Jan 2011 | 37,337 |
Feb 2011 | 37,169 |
Mar 2011 | 36,906 |
Apr 2011 | 36,263 |
May 2011 | 36,371 |
Jun 2011 | 36,782 |
Jul 2011 | 37,155 |
Aug 2011 | 37,617 |
Sep 2011 | 37,951 |
Oct 2011 | 38,202 |
Nov 2011 | 38,353 |
Dec 2011 | 38,447 |
Jan 2012 | 38,528 |
Feb 2012 | 38,776 |
Mar 2012 | 38,827 |
Apr 2012 | 39,238 |
May 2012 | 39,594 |
Jun 2012 | 39,401 |
Jul 2012 | 39,482 |
Aug 2012 | 39,187 |
Sep 2012 | 38,704 |
Oct 2012 | 38,678 |
Nov 2012 | 38,328 |
Dec 2012 | 37,965 |
Jan 2013 | 37,837 |
Feb 2013 | 37,314 |
Mar 2013 | 36,724 |
Apr 2013 | 36,585 |
May 2013 | 36,469 |
Jun 2013 | 36,447 |
Jul 2013 | 36,773 |
Aug 2013 | 37,118 |
Sep 2013 | 37,598 |
Oct 2013 | 37,840 |
Nov 2013 | 37,989 |
Dec 2013 | 38,198 |
Jan 2014 | 38,210 |
Feb 2014 | 38,293 |
Mar 2014 | 38,455 |
Apr 2014 | 38,469 |
May 2014 | 38,705 |
Jun 2014 | 39,151 |
Jul 2014 | 39,453 |
Aug 2014 | 39,531 |
Sep 2014 | 39,886 |
Oct 2014 | 40,131 |
Nov 2014 | 40,215 |
Dec 2014 | 40,380 |
Jan 2015 | 40,341 |
Feb 2015 | 40,413 |
Mar 2015 | 40,730 |
Apr 2015 | 41,128 |
May 2015 | 41,281 |
Jun 2015 | 41,754 |
Jul 2015 | 41,897 |
Aug 2015 | 42,033 |
Sep 2015 | 42,044 |
Oct 2015 | 42,056 |
Nov 2015 | 42,344 |
Dec 2015 | 42,558 |
Jan 2016 | 42,724 |
Feb 2016 | 43,221 |
Mar 2016 | 43,658 |
Apr 2016 | 44,085 |
May 2016 | 44,491 |
Jun 2016 | 44,720 |
Jul 2016 | 44,598 |
Aug 2016 | 44,958 |
Sep 2016 | 45,101 |
Oct 2016 | 45,148 |
Nov 2016 | 45,175 |
Dec 2016 | 45,064 |
Jan 2017 | 45,085 |
Feb 2017 | 44,993 |
Mar 2017 | 45,286 |
Apr 2017 | 44,927 |
May 2017 | 44,858 |
Jun 2017 | 44,293 |
Jul 2017 | 43,795 |
Aug 2017 | 43,407 |
Sep 2017 | 43,012 |
Oct 2017 | 42,858 |
Nov 2017 | 42,934 |
Dec 2017 | 43,021 |
Jan 2018 | 42,975 |
Feb 2018 | 42,442 |
Mar 2018 | 41,416 |
Apr 2018 | 40,795 |
May 2018 | 40,011 |
Jun 2018 | 39,533 |
Jul 2018 | 39,473 |
Aug 2018 | 39,338 |
Sep 2018 | 39,056 |
Oct 2018 | 38,941 |
Nov 2018 | 38,553 |
Dec 2018 | 38,118 |
Jan 2019 | 38,068 |
Feb 2019 | 37,961 |
Mar 2019 | 37,810 |
Apr 2019 | 37,998 |
May 2019 | 38,282 |
Jun 2019 | 38,294 |
Jul 2019 | 38,788 |
Aug 2019 | 38,982 |
Sep 2019 | 39,450 |
Oct 2019 | 39,882 |
Nov 2019 | 40,197 |
Dec 2019 | 40,613 |
Jan 2020 | 40,847 |
Feb 2020 | 41,521 |
Mar 2020 | 41,784 |
Apr 2020 | 39,453 |
May 2020 | 37,657 |
Jun 2020 | 38,255 |
Jul 2020 | 39,483 |
Aug 2020 | 40,747 |
Sep 2020 | 42,371 |
Oct 2020 | 43,593 |
October was another unusual month, in an unusual year, with a lot of unhelpful and volatile data. In the same year, the all-time low for sales was printed just months before the all-time high. Neither data point is really helpful in the general picture. Real estate sales are doing very well, but not as well as the record smashing numbers would indicate. There’s also the pull-forward effect of lower mortgage rates, which is difficult to gauge in size.
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Or, you know... wait for your bank's economist to repeat the insights next week. Whateves.
LONDON — The coronavirus crisis pushed global debt levels to a new high of over $272 trillion in the third quarter, the Institute for International Finance said, as it warned of the “attack of the debt tsunami.”
Among advanced nations, debt surged above 432% of GDP in the third quarter — a 50 percentage points increase from 2019.
https://www.cnbc.com/2020/11/19/coronavirus-drives-global-debt-to-a-new-record-high.html
Yay!!!!