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We’re all well aware of the trajectory of housing prices since the start
of the pandemic: The Canadian Real Estate Association (CREA) reported a 17.7%
increase in average housing prices nationally between December 2020 and 2021. Reported increases in Atlantic Canada range
from 9.3% in St. John’s NL, to 41.9% in Yarmouth NS. We’ve arranged the following table of
reported Atlantic Canadian areas in descending order by rate of increase, and
included the dollar value that increase translates to.
 Source:
CREA. * MLS® HPI benchmark prices; all
other areas are average prices. We don’t
know why Charlottetown is not reported.
Another thing we’re all aware of is
current rock bottom interest rates, which were lowered from already low levels
at the outset of the pandemic in an effort to keep the economy from coming to a
crashing halt. As someone who first
bought a house when interest rates seemed low to those who held a mortgage in
the 1980s, but high to those who weren’t yet born in the 1980s, I wanted to
take a look at the cost of buying a home with a mortgage over the course of the
past few decades, and how that relates to income.
The following charts show average
income for “economic
families[i]
and persons not in an economic family[ii]”. The available data goes as far forward as 2019
and it was provided in constant 2019 dollars.
I wanted to look also at current dollar income, so I adjusted it using
the relevant consumer price index (CPI).
Over the past four decades, average incomes have approximately quadrupled in Canada (+290%) and the Atlantic provinces (NL +318%; PE +291%; NS +284%; NB +295%; maybe a little more since 2019?)
 Source:
Statistics Canada. Table
11-10-0191-01 Income statistics by
economic family type and income source; and Table 18-10-0005-01 Consumer Price Index, annual average, not
seasonally adjusted.
 Source:
Statistics Canada. Table
11-10-0191-01 Income statistics by
economic family type and income source.
Historic lending rates are provided on
a weekly basis. From the start of 1980
to the start of 2022, lending rates have declined substantially, by 8.46
percentage points (pp) for posted mortgage rates and 13.5 pp for the bank
rate. Mortgage rates peaked at 21.75%
for a 10-week period in 1981 and reached their lowest between 2015 and 2017, at
4.64%.
 Source:
Statistics Canada. Table 10-10-0145-01
Financial market statistics, as at Wednesday, Bank of Canada.
And the final piece of the puzzle is
housing prices. Part of our Compuval™
suite of databases is our residential database, which captures details of
housing sales transactions in Halifax Regional Municipality, dating back to the
mid-1970s. So, with apologies to all the
other areas, for this portion, we are looking only at the housing prices for
HRM. The average price for a house in
1981 was $60,738; in 2021, it was $486,861, an increase of just over 700%, well
above the quadrupling of incomes over the period.
 Source:
Turner Drake & Partners Ltd. Compuval™ Residential Database; Statistics
Canada. Table 10-10-0145-01 Financial
market statistics, as at Wednesday, Bank of Canada.
We also used the CPI to adjust average
housing prices to 2021 levels: the increase over the forty years was 187%, even
accounting for inflation.
 Source:
Turner Drake & Partners Ltd. Compuval™ Residential Database; Statistics
Canada. Table 10-10-0145-01 Financial
market statistics, as at Wednesday, Bank of Canada.
No matter which way you look at,
adjusted or otherwise, housing prices have increased over the past 40 years
(what??!), and quite sharply over the past 2 years. But interest rates have declined, so where
does that put mortgage payments? The
following two tables show mortgage payments on the average priced home annually
since 1981. The mortgage rates are
necessarily approximate because mortgage rates vary throughout the year – these
are the annual averages of the reported weekly rates – and because there are
other factors at play that might mean someone pays a different rate from that
posted (negotiation, general discounts off the posted rate, etc.), but the
purpose here is to show the trend over time.
I’ve also ignored down payments, so these payments are based on the full
average price of houses, purely for simplicity.
The first table shows the five-year fixed rate, while the second shows
the variable rate; payments are shown on average house prices in current
dollars, and also adjusted to 2021 dollars using the CPI.
 Source:
Turner Drake & Partners Ltd. Compuval™ Residential Database; Statistics
Canada. Table 10-10-0145-01 Financial
market statistics, as at Wednesday, Bank of Canada (for fixed mortgage rates);
Super Brokers Mortgage Rate History https://www.superbrokers.ca/tools/mortgage-rate-history
(for variable rates).
 Source:
Turner Drake & Partners Ltd. Compuval™ Residential Database; Statistics
Canada. Table 10-10-0145-01 Financial
market statistics, as at Wednesday, Bank of Canada (for fixed mortgage rates);
Super Brokers Mortgage Rate History https://www.superbrokers.ca/tools/mortgage-rate-history
(for variable rates).
The analysis shows that interest rates
and mortgage payments followed a similar pattern until approximately the year
2000 for fixed rate mortgages, and 2009 for variable rate mortgages, at which
points the two diverge, with interest rates continuing their downward
trajectory while mortgage payments climbed with relative consistency to the
present day (side note: over the study period, there were just three years
where the annual average for variable rates was higher than that of fixed
rates: 1981, 1989, and 1990).
“Affordability”
for housing is relatively refined in its definition (you can read a bit about
it in our blog from June of last year), and this next table isn’t intended to
comment on affordability in that regard, but rather to show the pattern of
change in average incomes, annual mortgage payments, and consumer prices (CPI),
all indexed to a common starting point (1980).
It is noteworthy how closely together the three moved between 1980 and
1990, at which point annual mortgage payments dropped relative to income and CPI;
the latter two continued apace for about the next eight years, till incomes
started to outpace consumer prices. Even
in 2020, the index for annual mortgage payments fell below that of income, but
in 2021, these two came back together, suggesting that mortgage costs (index
value in 2021 = 411.7) relative to income (index value in 2021 = 414.4) is now
approximately equivalent to where it was in 1980 (both 100), or 1990 (index
values 181.7 and 184.8, respectively).
 Source: Turner Drake & Partners Ltd. Compuval™ Residential Database;
Statistics Canada. Table 10-10-0145-01
Financial market statistics, as at Wednesday, Bank of Canada (for fixed
mortgage rates); Statistics Canada. Table 18-10-0005-01 Consumer Price Index, annual average, not
seasonally adjusted; and Statistics Canada.
Table 11-10-0191-01 Income
statistics by economic family type and income source.
One more exercise in modelling prices,
payments, and interest rates: what would someone pay, including interest, if
they bought an average house in 1981, versus in 2021? In order to estimate this, I used a 25-year
amortization period with 5-year terms.
For the first 5-year term, I used the average house price and fixed
mortgage rate in the year of purchase, and then used an amortization schedule
to determine the balance owing at the end of the term. I repeated the process for each of the 5-year
terms, using the end balance for the previous term as the mortgage amount,
reducing the amortization period by five years, and using the prevailing
interest rate of the first year of each term.
This is reasonable for the 1981 purchase, but the 2021 purchase is trickier
because future interest rates are unknown.
Therefore, I simply modelled it looking backwards at interest rates in
five-year increments, on the assumption that maybe rates will work their way
back up. Is it perfect? No. Is
it reasonable? Probably. Is it interesting to speculate? I think so.
The results: an average house
purchased in 1981 cost $60,738; when fully paid off 25 years later, the total
cost of principal and interest was $196,564 (note that the starting principal
and total principal are off by $91, likely due to rounding). The average house purchased in 2021 cost
$486,681. The full cost including
principal and interest 25 years hence is modelled to be $858,865.
Alex Baird Allen is the Manager of Turner Drake's Economic Intelligence Unit. In her role, Alex frequently undertakes market surveys, site selection studies, trade area analyses, supply & demand analyses, and demographic reports for a wide range of property types throughout Atlantic Canada. If you'd like more information on market research or our semi-annual Market Survey (recently updated and published with December 2021 results), you can reach Alex at 902-429-1811 Ext.323 (HRM), 1-800-567-3033 (toll free), or email ABairdAllen@turnerdrake.com
Affordable housing has been a hot topic in
recent years, and is even more so now as rental vacancy rates are extremely
tight and housing prices have experienced record rates of increase in Atlantic
Canada. A recent news article caught my
attention, with its reference to a price point – “attainable” – I
haven’t heard as much about, and it inspired me to take a look at what the
difference is, and how each lines up with Atlantic Canadian markets. Then, because alliterations sound better in
threes, I needed a third A: the obvious choice in this context is to look at availability.
First, the definitions, a slipperier
thing to pin down than one might imagine.
Canada Mortgage and Housing Corporation (CMHC) defines affordable
housing as housing that costs less than 30% of a household’s before-tax (gross)
income, absent any requirement for the housing to be provided or made possible
through a government program, and without restriction on tenure or type.
With that definition, affordability
is very much relative: in theory, a $4.3-million home would be “affordable”,
provided your household income is $300,000 – about 1.7% of Atlantic Canadian
households. Relatively affordable: on the market for approximately
$4.4-million. Source: ViewPoint Realty
Seems likely that this is not the
intention of the definition, or any measures put in place to encourage the
supply of affordable housing. And in
fact, CMHC’s Housing Continuum graphic implies that affordable housing is
separate from market housing. Wikipedia
offers a slightly more specific definition:
…housing which is deemed affordable
to those with a median household income or below as rated by the national
government or a local government by a recognized housing affordability index.
 If we combine the two, that would
indicate that affordable housing is housing which costs no more than 30% of the
median household income – and for practical purposes, let’s assume that is in
reference to local median incomes, and not, for example the national figure…more
on that later.
We conducted a very high-level
analysis of the median incomes for the four Atlantic provinces and a selection
of cities. We used average rental rates
for 2-bedroom units because this is by far the dominant unit type for rental
accommodation. The calculation is simple
(very!): divide 30% of the median household income by 12 to get the monthly
income, subtract off the average rental rate and an allocation for utilities of
$150 per month (property tax and water are included in the rental rate;
electricity/heating may or may not be included, so to play it safe, we assumed
that it’s not for most units) and see what’s left over. Great news: positive balances all-round,
averaging $620 per month surplus – hoorah, there’s no affordability issue!
 Data Sources: Environics Analytics via Sitewiseweb;
CMHC; Dalhousie University
Here’s the “but”…and it’s not
inconsequential by any stretch. Median
household income is, by definition, the middle of the income spectrum. So, a household earning the median income
being able to afford average costs for rental housing tells only half the
story. Our next analysis worked the
figures backwards: we took the average rent plus the same allocation for utilities,
on an annual basis and figured out how much a household would need to earn in
order for housing costs to equal 30% of their gross income – then figured out
approximately how many households fell below that income threshold, based on
the number of households in various income brackets. Reports of an issue don’t look overblown at
all.
Data Sources: Environics Analytics via Sitewiseweb;
CMHC; Dalhousie University
Prices for owner-occupied housing
have increased substantially over the course of the pandemic. We ran the same sort of analysis as above,
for average/median sale prices in 2020 and 2021. The geographic availability of data is a bit
inconsistent, but our aim is a general idea, so overall, the data is fit for
purpose. Mortgage rates impact the cost
of housing; we used discounted rates (rather than the posted rates) relevant at
the relative times. To keep things
simple, we assumed a 5% down payment, then based on a very unscientific poll
around the office cross referenced against an online monthly expenses
calculator, we allocated 40% of the mortgage cost to cover property tax,
utilities, and insurance costs: rough idea, fit for purpose.
Data Sources: Environics Analytics via Sitewiseweb;
CREA; ratehub.ca
We also looked at the year-over-year
change in house prices: in 2020, the median income was sufficient to afford a
house in all Atlantic provinces, and the selected cities (2020 house price data
for Moncton is conspicuous by its absence), but in 2021, the income needed to
afford a typical house climbed over the median level for Nova Scotia and PEI,
and their capital cities.
Data Sources: Environics Analytics via Sitewiseweb;
CREA; ratehub.ca
Obviously, averages and medians are
the central figures: there will be houses priced
lower as well as houses priced higher, so the above analysis is not to say that
in HRM, for example, you couldn’t find a house priced within your means if your
household income is less than $100,000 (though it’s getting trickier,
especially with our recent embrace of the “offers over” system of home
buying). But this does provide an
indication of affordability, and leads us to the next A on the list:
attainability.
Again, the definition is slippery,
and in some senses, attainability is defined the same way as affordability,
i.e., at no more than 30% of gross household income. It seems that the key difference is the
removal of reference to median income: each income bracket will have its own
price range of attainable housing – and associated appropriate housing types,
categorized by type, size, and tenure.
Implicit in the idea of attainability is that suitable housing exists in
the local market in a variety of forms and price points, sufficient to meet the
needs of the population.
We used data on household income
brackets to model the proportion of households in each province/city by maximum
monthly housing budget. We then used the
same $150 allocation for utilities for rental units to determine affordable
rental ranges, and the same ratios for expenses-to-mortgage (i.e., 60% of
budget is available to service the mortgage, with 40% allocated to property
tax, utilities, and insurance) to determine affordable house prices, as were
used in the earlier analyses. All
figures are approximate at best and should not be relied upon for life
decisions, but they give a sense of what is attainable to each income bracket
from a price perspective.
 Data Sources: Environics Analytics via Sitewiseweb
 Data Sources: Environics Analytics via Sitewiseweb. Note that the annual income from a minimum
wage job, at 40 hours per week and 52 weeks per year varies by province but all
four Atlantic Canadian provinces would fall towards the low end of the
$20,000-$39,999 income bracket, averaging $26,000 overall.
And so we come to the final A: availability. It's an important one, because it's effectively the supply side of the supply and demand equation, which is the driving force behind prices. For this portion of the discussion, we're abandoning price points in the interest of balancing level of effort that can be allocated to a blog post.
One of the components of the attainable definition was that a variety of housing formats would be available locally to serve the various budgets - the CMHC housing continuum graphic gives a rough sense of what this might look like, as does this Housing Life Cycle graphic borrowed from the City of Belleville, Ontario.
From an availability perspective, we
start with rental tenure. With the
exception of Cape Breton and St. John’s, vacancy rates are low across the
selected cities.
Source: CMHC (annually in October)
At a provincial level, in October
2020, there were just over 3,000 vacant rental units in Atlantic Canada, of a
total rental universe just shy of 114,000 units. Once those 3,000 units are sliced and diced
by price, style, and location, availability is probably problematic.
Source: CMHC (October 2020)
For residential sales listings, we
have to rely on data for Nova Scotia only, due to availability, but we suspect
that a similar pattern will be in evidence in the Maritime provinces at least. Prices continue to climb in 2021, but it
appears that the supply-side driving force behind that trajectory may no longer
be in play: the number of listings for the period 1st January to 16th
June in 2021 was greater than any other year in the past five years,
versus 2020, which had the fewest listings of the five years.
 But what about affordability of
these available houses? That’s a
question that could have many answers – in that it can be answered in a myriad
of ways. We’ve opted for a very simple
one, using price points of affordability for the median household income under
two interest rate scenarios: the current posted rate and a current available
discounted rate, and ignoring down payments because we’re more concerned with
monthly costs in this analysis. We’ve also ignored time – and changes to
mortgage rates and income levels over its course, for illustrative purposes
(horseshoes, hand grenades, and this blog post).
|
Median Household
Income
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$67,115
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30%
|
$20,135
|
|
Monthly
|
$1,678
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Mortgage amount @ 1.68% (discount rate)
|
$410,793
|
|
Mortgage amount @ 4.79% (posted rate)
|
$293,120
|
Mortgage rates from ratehub.ca
Let’s just pause on the one-hundred-and-seventeen-thousand-dollar
difference in what is “affordable” under those two rates. In some areas, you could buy a house for
that. Maybe not for much longer, if
interest rates stay low, but there are rumblings from economists that as
interest rates rise, the “affordability” of houses will contract and what some
fear is a housing bubble, may burst.
The second half of 2021 is yet to
be, so here are the Nova Scotia listing counts annually to 16th
June. A few things jump out: (1) there were more listings in the first
half of 2021 than in the same period of any other year in the past five (we
already knew that from earlier); (2) other than at the outset of the pandemic,
when home was so distinctively the safest place to be and few wanted to let
strangers walk through theirs, 2021 had the fewest listings below the posted
interest rate affordability threshold; and (3) 2021 had the fewest listings
below the discounted interest rate affordability threshold, full stop.
 Source: NSAR MLS®, with affordability
thresholds calculated using data from Environics Analytics via Sitewiseweb;
and ratehub.ca.
Back to that mention of localized
median household incomes. In the absence
of sufficient NOAH (Naturally Occurring Affordable Housing: see TDP VP Neil
Lovitt’s excellent blog from earlier this year) in the region,
programs that encourage affordable units in new developments are an important
part of the solution moving forward.
There’s a knife edge on which
balances the costs of development with what is affordable to those who need
non-market housing. It is highlighted by
reaction to a recent announcement of a sizable federal loan on a new apartment
building that will be approximately one-quarter designated affordable units. They’ll be priced in relation to the median
income for the area, which has generated a fair bit of blow back (to be fair: the
perception of how widespread negative reviews of policy are is almost certain
to be skewed, since those who really disagree are far more likely to speak out
against it, while those who agree or are neutral have less incentive to chime
in on the discussion). The issue they
raise is that the local (Halifax) median income referenced is close to $90,000
(as in, one large Costco order close to), so the affordable units could be
priced as high as $2,238, though most are actually going to be less than that
since the agreement includes provision for a further discount to the 30%‑of‑median‑income
standard. The underlying questions in
the flak are really: is median income a reasonable metric on which to base
affordability measures? And what median
should be used? And is there any
relationship between the maximum “affordable unit” price tag and unit size? One-bedroom versus four at $2,200 is a
pretty substantial difference.
There’s a geographic driver of
housing prices, and it costs more to commute less, generally. Maclean’s magazine published an analysis in 2014 that showed a minute of driving time
could save you thousands in housing costs.
Inspired, we devoted a TDP Trends to the topic; with some variation, in general,
the farther you get from the downtown core, the less expensive houses are.
Source: Turner Drake & Partners Ltd. (2015)
This is relevant to a discussion of
housing that is affordable, attainable, and available because cars are
expensive to own and operate. Pushing
affordable housing to the far reaches of the city, where transit options are
limited/nil (and don’t forget that commute times via bus are going to be
longer), is short-sighted at best, and counter-productive at worst. But median incomes are likely higher where
housing prices are higher, whether that’s localized within a city, or the city
median is used in lieu of the provincial one.
Is there a conclusion? Not in terms of a solution. But an acknowledgement of the complexity of
the issue, and the fact that a broad stroke approach to the metrics may provide
little in the way of assisting those who need support to find and keep suitable
housing that fits both the budget and the family structure. That, and the fact that “affordable housing” as defined, is only of
use if it is also attainable and available.
Turner Drake refines high-level,
surface-scratching analyses like the foregoing, into fine-grained, location
specific consulting assignments, including market and non-market housing supply
and demand analyses throughout Atlantic Canada, and Housing Needs Assessments
from coast to coast. To see how we can
provide solutions to your real estate problems, you can reach Alexandra Baird
Allen at (902) 429-1811 or abairdallen@turnerdrake.com.
Among the fun things to look forward to at this
time of year is PNC’s annual (37 years now!) Christmas Price Index, in which
they calculate the prices of the twelve gifts from the classic song, “The Twelve
Days of Christmas”. The highest increase
year-over-year was for the two turtledoves, up 50% to $450, which contrast to a
few of the other avian gifts: swans, calling birds, and a partridge will cost
you the same this year as last…as will minimum wage milk maids. This year’s index accounts for cancellations
of many live performances: the unavailability of dancing ladies, leaping lords,
pipers, and drummers means that the total cost of these gifts is down over last
year. How far down, though, is a matter
of measurement. If you were to buy just
one of each of the gifts – one goose, one ring, one French hen, etc. – you’d
pay 58.5% less than last year, for a grand total of $16,168.14 (USD). But you can also measure by the full cost of
all the gifts – both the turtle doves,
all the geese, none of the performers – to arrive at grand total for 2020 of
$105,561.80, down just 38% since 2019.
Or, and I’m assuming this is based on the one-of-each option, PNC also
provides a “core” index, which excludes the Swans-a-Swimming, the price of
which is apparently the most volatile.
The core index for 2020 costs $3,043.14, down 88.2% from 2019.
So, the same index has three different
year-over-year price changes. That
provides a perfect segue into a discussion of the critical thought, and careful
consideration required before relying on Price Indices for decision making,
planning, and policy purposes…there are many available from which to choose, including
the overall, oft quoted, Consumer Price Index (CPI). This is not to say that price indices are not
a valuable tool – just that care needs to be exercised in choosing and using
them.
Twice a year, we undertake a comprehensive market survey of rental office
and warehouse space;
the summary results include average net rental rates, realty taxes and
operating expenses, and gross rental rates.
As part of our analysis, we look at the relationship between the
All-Items CPI and the total for realty taxes and operating costs (RTCAM), over
a five-year period. The CPI is a measure
of the cost of a certain “basket of goods”, and as such generally measures the
rate of inflation – which is expected to be reflected in the costs to operate a
building. The fact that the cost to
operate a building includes a different basket of goods than that required to
run a household – more cleaning and heating, fewer sneakers, school supplies,
and food items – makes it unsurprising that, while these two measures usually move
generally in concert, there can be significant variation. This year, where costs have shifted up and
down across various sectors, particularly highlights the challenge of relying
on the CPI as a surrogate for other baskets of good: the five-year ratio
between CPI and RTCAM, describing how the RTCAM moved for each 1 percentage
point change in the CPI, varied from a 1.14 percentage point decrease in office
RTCAM in Saint John NB, to a 1.01 percentage point increase in Fredericton,
with Moncton, St. John’s NL, and Halifax falling at varying points along that
range. December’s survey includes both
office and warehouse space in Halifax, and there is a differential between the
ratio of CPI to RTCAM for the two sectors, with office RTCAM coming in at 0.59
to 1 percentage point change in CPI, and warehouses coming in at a ratio of 1.2
to 1.
PNC says
about their index:
The PNC Christmas Price Index® is an annual tradition which shows
the current cost for one set of each of the gifts given in the song "The
Twelve Days of Christmas."
It is similar to the U.S. Consumer Price Index, which measures the
changing prices of goods and services like housing, food, clothing,
transportation and more that reflect the spending habits of the average
American.
The goods and services in the PNC Christmas Price Index® are far more
whimsical, of course. And most years, the price changes closely mirror those in
the U.S. Consumer Price Index. This year, the approach to PNC’s CPI takes into
account the sociopolitical environment brought on by the pandemic by using the
Index to provide an analysis of current market conditions, while including the
impacts of COVID-19 as highlighted by the data.
It’s a fun way to measure consumer spending and trends in the economy.
So, even if Pipers Piping or Geese-a-Laying didn’t make your gift list this
year, you can still learn a lot by checking out why their prices have increased
or decreased over the years.
It’s definitely worth checking out. And if you’re interested, we publish the
summary results of our market surveys on our website and through email
distribution. Watch for them in the New
Year – or contact us to subscribe. Wishing
you and yours all the best for the holidays, from all of us at Turner Drake
& Partners Ltd.
Alex Baird Allen is the Manager of Turner Drake's Economic Intelligence Unit. If you'd like more information on market research or our semi-annual Market Survey, you can reach Alex at 902-429-1811 Ext.323 (HRM), 1-800-567-3033 (toll free), or email ABairdAllen@turnerdrake.com
COVID-19, despite months of rumblings that it might be on
its way, arrived rather abruptly on our doorstep. Collectively, we shifted from theoretical
preparations “in case” and “if” the virus impacted us directly, to many people
working from home, a transition that happened within days in some cases. Ready or not, here it came.
Now, just (“just”!) a couple of months later, the next
transition is upon us, as the economy reopens and we figure out, industry by
industry and company by company, what the new normal will look like. It’s a question on the minds of many, and one
my department has spent a fair bit of energy contemplating from our makeshift
at-home workstations (check out this
CBC article
for a peek at mine…kids and various home schooling accoutrements banished for
the deception of professional appearances).
The short answer is that it is too soon to tell, though there are
rumours and rumblings that work-from-home will continue for some people and/or
companies (demand for that may come from either end of the equation).
The longer answer is that major recessions usually result
in a sea change in how office space is utilised. After the 1990
recession, which coincided to a certain degree with the advent of cell phones
and the internet, there was a rise in “telecommuting”, some people working from
home, and “hot desking” where different people used the same desk at different
times of the day. Cubicles rose in
prominence over individual offices (as evidenced by every 90s movie that takes
place in an office). Post-2008 recession, the movement was to open
concept offices, with bullpen style areas where everyone has a laptop and a
cell phone and shares common space and/or works from home part of the
time. Each of these shifts, from individual offices to cubicles to
bullpens, equates to fewer square feet of office space per employee…which in
turn equates to lower costs for companies, for whom office space is often the
single largest expense after HR.
The logical next step in the continuum is an increase in
employees working from home, with an overall reduction in the amount of office
space leased. This could be driven by
employees who find they like shedding their commute and are productive at home
(and expect to be more so when schools and daycares reopen). It could also be mandated by employers who
find that cutting workplace expenses - from rents to coffee supplies - can come
without significant detriment to their business model.
There are some companies for whom this is a viable option,
but for others, it is not practical. Will
confidential meetings between lawyers and clients take place in lawyers’ basement
playrooms, or out in public at coffee shops? Unlikely. Further, many industries rely on the sharing
of ideas to innovate and problem solve.
The benefit of casual conversations and impromptu collaborative meetings
is worth the expense of working together in one location. So there will
remain demand for professional office space from certain sectors for a variety
of sound reasons. Worth noting, too, is the consideration that the pre-COVID
bullpen office set up has significant drawbacks until (unless) a vaccine
becomes available: shared space is not practical from a public health
perspective, and may redirect those who can’t realistically work from home long
term, to shift back to individual offices that ameliorate physical distancing. That is: more square feet of space per
employee.
And then the final elephant in the room is the total elimination
of demand for office space from companies which do not survive the economic
fallout of the pandemic. It is too soon
to measure how extensive this will be, but there certainly will be casualties
of a recession that may well be deep and prolonged.
So, coming full circle to the short answer: even with lots
of companies opting to return to offices, a decline in overall demand for
office space is certainly expected, probably over the next couple of
years. Because leases are typically signed on 3-5 year terms (or longer),
a “shadow” vacancy of leased-but-vacant space could surface first (i.e. space
for sublease), though if the original lessees can’t pay, the space is
effectively just vacant regardless of any contractual debt on it (distinguished
from, for example, a healthy company who chooses to move to a new office
building when they still have a year left on their lease). With increasing vacancy, landlords will opt
first for rental incentives to entice tenants to their space, and there will be
downward pressure on net rental rates.
Our June Market Survey is underway now…stay tuned in the coming months
for the early indicators of impacts on the market. 
Alex Baird Allen is the Manager of Turner Drake's Economic Intelligence Unit. If you'd like more information on market research or our semi-annual Market Survey, you can reach Alex at 902-429-1811 Ext.323 (HRM), 1-800-567-3033 (toll free), or email ABairdAllen@turnerdrake.com
Who’s Going
to Live In All Those Houses? – A common refrain when there’s a lot of
residential development, whether houses, apartments, or condos. Demographic trends can help to answer the
question after the fact, but more importantly, attention to demographic
patterns ahead of developing can ensure that housing supply meets demand. After all, once it’s built, housing supply is
here for the long haul. At the recent
NSPDA and LPPANS conference, Turner Drake led a workshop examining how
individual decisions feed into patterns in housing supply and demand. Here’s a brief recap (granted, a Nova Scotia‑oriented
recap, but many of the principles apply across Atlantic Canada).
The Life
Cycle of Housing
A typical person will move around a bit in their
lives, starting out in their parents’ house (or houses: if we can infer Canadian behaviours from American stats,
the average person owns 4.5 to 5.5 houses in their lifetime), moving to a
rental apartment before buying their own home(s). Later in life, they may downsize back to an
apartment (possibly a more luxurious one this time) or condo, and finally make
their way to a seniors’ residence.
In-demand housing stock is heavily dependent on the
dominant age groups in any given area.
The primary drivers of rental apartment demand are 20-29 year-olds, and the
65-and-older cohort, though the latter is increasingly shifting to a
75-year-plus bracket, and the former arguably extends to above age 35.
Source: Statistics Canada 2016
Census
The inverse is demand for owned housing, and the primary buyers are
ages 25 through 45. The 25-29/34
year-old age bracket falls into each of the renter and buyer categories: this
is the first-time homebuyer age range, where we see the steepest increase in
home-ownership rates. The inference is
that by age 45, buyers have bought their first home, possibly sold it and
upsized to a larger family home, and here they stay for a prolonged period of
time.
 Age distribution in Nova Scotia
(Source: Statistics Canada Population Estimates)
The graph above shows shrinkage in the brackets
that include ages 20 through 45, but growth in the 65+ brackets. Growth in the 55-64 year old bracket means
that the latter will continue to expand as Baby Boomers age. A 2018 Royal LePage survey of home buying
intentions found that 42% of Atlantic Canadian Baby Boomers plan to downsize in
retirement, with 23% intending to sell their homes and move to their secondary
properties, i.e. to the cottage.
Thirty-two percent would consider buying a cottage in which to live in
retirement. The answer is probably no,
but all this moving to the cottage raises the question of whether the province
will see population ruralisation over
the next few censuses, or whether the urbanisation of younger generations will
continue in numbers sufficient to offset it?
The map below shows population change at the Dissemination Area level in
Nova Scotia between the last two censuses: the concentration of purple (growth)
in urban areas, in contrast with the pink and red (shrinkage) of the rural
areas, indicates urbanisation. 
Population change 2011-2016, Statistics
Canada 2016 Census
Just 29% of Atlantic Canadian Baby Boomers would consider purchasing a
condo, the lowest rate in the county.
Recall that the stat comes from a survey of home buying intentions…and recent trends have been for downsizers to opt
for rental apartments over condominium apartments. There is certainly incoming supply of
apartment units: CMHC statistics on housing starts over the past few decades
show a distinct shift from single-family construction to apartments: 
…though the rest of Nova Scotia is a different story:
The breakdown of the same housing start data shows a distinct rental
intention:
…which again is driven almost entirely by the Halifax pattern:
...while the rest of the province still shows a clear preference for
offering options for home ownership, with very little constructed for either
the rental or the condominium market:
On the demand side, the province appears largely influenced by the
statistics for Halifax, with vacancy mirroring the same ups and downs over the
past three decades, though vacancy is a bit tighter in the city (overall 2% in
NS and 1.6% in Halifax in October 2018).
Demand is strong: vacancy rates have been falling since 2014, even as
the inventory of rental units has been steadily increasing.
In the years ahead, expect continued growth in demand for higher
density residential forms, especially of the rental variety. This trend is driven by the Halifax market,
and offers an appealing lifestyle (low maintenance, low commitment), combined
with the option to live off the equity unlocked from the sale of the family
home. It is not far-fetched to
extrapolate that demand for multi-unit rental apartments may also exist in
smaller municipalities in the province, but that rural housing economics (lower
housing prices but similar construction costs) have thus far constrained the
supply side of the equation.
Turner Drake & Partners’
Economic Intelligence Unit follows closely trends in real estate and the
factors that can impact its value, from demographic patterns and preferences,
to climate change. Custom reports
translate data into conclusions. For
more information on how we can assist you, please call or email Alexandra Baird
Allen: 902-429-1811 x323 or abairdallen@turnerdrake.com.
Happy
GIS Week! We were working recently on an assignment in the
Annapolis Valley, the land of orchards and sloping vineyards…and that got us
thinking about the impact of elevation on land area. Ultimately, the question is one of land
value: inherent in the value of agricultural land is potential crop yield. More land area equals more growing potential equals
more value. Where slopes are acceptable
or even advantageous, they may serve double duty in that sloped land is larger
than it seems. Our Valuation Division’s MO is to maximise your property
value…this is an Economic Intelligence Unit blog post, and this is GIS Week, so
we’re going to geek out on how to ensure you’re counting all your land, using a GIS, a little high school math, and a fair
bit of Pythagoras[i]. Pythagoras’ Theorem defines the relationship between the
sides of a right triangle with the equation a² + b² = c². Side “c” is the hypotenuse, and is always the
longest of the three sides.
For illustrative
purposes, we created a convenient, perfectly rectangular, parcel. It measures 500 x 1,150 m, for a total area
of 575,000 m² (57.5 hectares).
That is:
 But the land comprising
this parcel is sloped. The contour lines
added to the image below demonstrate the degree of the slope; on average, there
is an elevation differential between the highest and lowest elevations of 140
m.
Thus, the 500 m parcel dimension is effectively 519.2 m: 
and
the effective land area is 597,080 m²
(59.7 ha.), a difference of 22,080 m²
– over 2 hectares of extra space for crops!
This
is a highly simplified example of the impact of slope on land area. There are many other factors to take into
account, such as the tipping point between beneficial slopes and unusable
inclines. But in a world where “land:
they’re not making any more of it,” holds true, the most informed decisions are
the best ones. Where a precise figure is
required, you’ll need to call in a professional land surveyor. But when an area scaled from a map is fit for
purpose, using a GIS and a little high school math can yield a more useful
number than you’d get from a regular map.
P.S.
a related fun fact was shared at Wednesday night’s Geomatics on the Town event (part
of the 2018 Geomatics Atlantic Conference): tree planters space their seedlings
at a certain distance from each other.
For one tree planter, this was the equivalent of 3 steps on flat ground,
but on sloped terrain, it was 12 steps in order to leave sufficient room
between trees!
[i]
Mainly for defining the relationship between the sides of a right triangle, but
a little bit for first floating the idea that the Earth is a sphere...it comes
into play in measuring distance. There
are two methods of measurement in a GIS, Cartesian and Spherical. The Cartesian method calculates distance and
areas based on data as projected onto a flat surface (like scaling from a paper
map), while the Spherical method accounts for the curved surface of the Earth
(like scaling on a globe). The distances
in this example were measured in MapInfo using the Spherical method.
Alex Baird Allen is the Manager of Turner Drake's Economic Intelligence Unit, and has a high level of expertise and interest in GIS. If you'd like to reach Alex, call 902-429-1811 Ext.323 (HRM), 1-800-567-3033 (toll free), or email ABairdAllen@turnerdrake.com
On
February 5th, Scott Armour McCrea, CEO of The Armour Group, took to
the airwaves to ridicule Alexandra Baird Allen, the Manager of our Economic
Intelligence Unit … the cause of his angst, an earlier CBC radio interview with
Alex on the results of a Halifax Central Business District (CBD) survey which
revealed an office vacancy rate of 17.3%. Labelling her conclusions
“manufactured hysteria” Mr. McCrea disparaged the survey results, questioned
the competence of Alex, her survey team and Turner Drake … and ignited a gender
war: “Mansplainer” was perhaps the most polite invective hurled in Mr. McCrea’s
direction (we are keeping a list… it’s not pretty but quite informative… we
might publish it). So what was it all about?
Scott
Armour McCrea is a developer and a very
important man, as he so informed the CBC, the largest private office landlord
in the city. In sonorous tone and displaying gravitas befitting a man with gaze
firmly fixed on his own navel, Mr. McCrea revealed that “no other real estate
professional uses the Turner Drake data”. In fact, he confided, no actual practitioner agrees with them! He then proceeded to reveal why … the full
Monty so to speak.
Turner
Drake, Mr. McCrea intoned, is a minor player in the leasing field completing
only 2% of leasing transactions while actual
practitioners such as brokers CBRE, do 30% to 40% and publish their own survey.
CBRE pegged market absorption at “about 300,000 ft.2 a year” stated
Mr. McCrea, “not the 25,000 ft.2” calculated by Ms. Baird Allen. The
Armour Group, Mr. McCrea’s company, did their own survey as well and estimated
the vacancy rate at 13% to 14%. … and most vacancies were in buildings most
people would “never, ever want to work in”. And the problem was exacerbated by
the Province who were so concerned about saving taxpayers’ money, they insisted
on consigning their employees to space that only the private sector would
tolerate. But that, he confided, was about to change. The real reason though for
the problem: “if there is a problem in Halifax and I am not suggesting there is”,
was that the City was “under-demolished”.
So
what are the (non-hysterical) facts?
Alex
has been a valued colleague for twelve years, is a Chartered Surveyor and has a
degree from the University of New Brunswick, a Diploma in Urban Land Economics
from the University of British Columbia and an Advanced Diploma in Geographic
Information Systems from the Centre of Geographic Sciences at Lawrencetown, one
of the top three GIS institutes in Canada. She combines her work as Manager of
our research group with her role as a mother of twins. We have never known her
to engage in hysteria, manufactured or otherwise. The office surveys are, we
believe, the most comprehensive conducted in Halifax and cover all rental
buildings 5,000 ft.2 or larger. They are a structured survey using purpose
designed survey instruments and software, deployed by a team of trained
researchers. The survey to which Alex alluded in her CBC interview had a
response rate of 89% (previously we have achieved 98% but this time a large
landlord, The Armour Group, refused to participate). We do have human and
programmatic error traps in place for quality control purposes but recognise
that they are not yet infallible so seek to have as many eyes on the results as
possible and offer the full survey to any participant who would like a copy. 40%
take advantage. One such recipient, was kind enough to point out not one, but two
errors, in our December 2016 Halifax office survey. We are not perfect, but we
are transparent. We corrected the errors, reissued the survey, changed our
software to catch similar human errors and published a correction, apology and
thanks in our Spring 2017 Newsletter to the gentleman who had so diligently
scrutinised the survey, Mr. McCrea.
Our
Market Surveys are undertaken by a research team independent of our Brokerage
Division. The volume of their lease transactions is therefore unrelated to the
amount of research undertaken for the Market Survey. In any event we cannot utilise data gathered
by our Brokerage Division for the Market Surveys because that would be a breach
of confidentiality.
The
CBC interviews were focused on the Halifax CBD. Ms. Baird Allen’s data referred
to the Halifax CBD. Mr. McCrea’s interview focused on the Halifax CBD… unfortunately the CBRE data he referred to did
not. It pertained to the wider HRM
metropolitan market. CBRE’s estimate of the vacancy rate for the Halifax
CBD is very similar to our own (18.5% versus our 17.3%). A world away from the
13% to 14% cited by Mr. McCrea. CBRE’s vacancy rate for the entire HRM office market was 15.5% (we
place it at 14.97%)… probably the source of Mr. McCrea’s confusion. There will always be some differences between
the Turner Drake and CBRE survey results, an important factor being that our
survey does not just focus on larger buildings but covers some as small as
5,000 ft.2. Mr. McCrea’s comment that the “annual market demand was
300,000 ft.2 not the 25,000 ft.2
quoted by Turner Drake” was similarly erroneous. Alex’s figure of 25,000 ft.2
referred to the CBD, which, after all, was the subject of the CBC
interview to which Mr. McCrea was responding. It was based on the average
market absorption over the past five years. CBRE’s estimate of annual market
absorption of 308,944 ft.2, referenced by Mr. McCrea, referred to
the entire HRM market.
Mr.
McCrea’s comment that most of the vacancies were in buildings that most people
would “never, ever want to work in” does not accord with the facts. Class A
buildings have an average vacancy of 21.8%.
We
concur with Mr. McCrea that many office buildings will have to be demolished or
repurposed, Alex pointed this out in her CBC interview. However 625,750 ft.2
of the 879,665 ft.2 of currently vacant space would have to be
taken out of service to restore equilibrium to the downtown office market… the
aggregate of the former Bank of Montreal tower, the former Royal Bank tower,
Founders Square and … volunteers anyone? Oh but Mr. McCrea is adding another 125,000
ft.2 at Queen’s Marque… let’s see, what else for the wrecking ball…?
We
politely pointed out to Mr. McCrea his confusion with the CBRE survey
statistics and gave him the opportunity to rectify the error. He did not
respond. As for the mansplainer moniker… nothing we can do about that... we
trust he is not consigned to the couch. Probably have to make his own coffee
from now on though.
For more information on mansplainer consult
Wikipedia. For information on the office market in the Halifax CBD and lots of
other areas in Atlantic Canada, contact Alex Baird Allen the (very calm)
Manager of our Economic Intelligence Unit at 902-429-1811 Ext.323 (HRM),
1-800-567-3033 (toll free), or ABairdAllen@turnerdrake.com
Another few years passed, another resurgence of attention and debate on Nova Scotia’s Capped Assessment Program. Municipalities are once again beating their drum against it, reiterating well-worn criticisms and receiving well-worn rebuttals. The public is largely disinterested, unfortunately, and the Province is loath to make the necessary changes without a strong call to action. The issues are not intuitive, and the impacts are largely invisible, and thus the CAP has immense political inertia.
With governments thankfully enacting open data policies, making publicly funded data publicly accessible, Turner Drake & Partners has now been able to crunch the numbers for more than 140,000 taxable residential assessment accounts in the Halifax Regional Municipality (HRM) to show just how ineffective this public policy has become.
What is the Capped Assessment Program?
The mechanics of the CAP, and the basics of its problems, have been explained many times over. Sources abound, but our own Property Tax professionals have previously covered the topic in our blog, as well as our recent company newsletter.
Normally, assessments are free to track market trends, but in Nova Scotia the CAP limits annual growth in a property’s assessment to inflation. Nova Scotia’s CAP is not like other taxpayer protection measures, such as California’s famous Proposition 13 which limits growth in assessment and total revenue collected. In Nova Scotia, if the total assessment base is reduced because of the CAP, tax rates are simply increased. Based on our analysis for HRM, we see no evidence of an impact on municipal spending. Operating Budgets have grown consistently since 2000:
Therein lies the problem. It is a program that only redistributes the tax burden. Some pay less, but the taxman gets his due, and so others pay more to make up the difference.
What is the Problem?
The problem arises in how the CAP decides who is to pay more. An assessment-based property tax system is not perfect, but one of its strengths is that property values generally correlate well with a household’s ability to pay. Of course this is not always true, and in fact the original purpose of the CAP was to alleviate situations where rural families were being priced off their land because Ethan Hawke bought the island next door. This is a valid issue that deserves a policy response, and we know that the CAP has helped people in this regard. However, by taking a broad based approach to solving a very acute issue, the program has created far more inequity than it was ever able to solve.
The CAP introduces distortion to the assessment system, reallocating tax burden based on occupancy length and tenure type. Most critics frame this issue as being arbitrarily unfair and use maps like the one below to illustrate the random nature of its distortions; houses in the same neighbourhood, with the same services, but carrying different tax burdens.
(Tax Distortion in a Halifax neighbourhood: red overpays, green underpays, sized by magnitude)
The sad truth is that its unfairness is less random, and its benefit more misallocated than most assume. As our Economic Intelligence Unit knows, people tend to sort themselves into similar locations and types of housing depending on their backgrounds, economic status, and life-stage. Thus, the CAP doesn’t just discriminate against certain properties on the basis of eligibility and program mechanics; it by extension discriminates against certain locations and people. This becomes apparent as the map zooms out:
(Tax Distortion in South End Halifax: red overpays, green underpays, sized by magnitude)
Today the CAP is championed as the way to bring “stability, predictability and affordability” to the taxpayers writ-large. In reality, the CAP generally fails to deliver these supposed benefits, while systemically giving the greatest assistance to those that least need it, by taking from those who can least afford it.
Halifax Case Study
To help illustrate the outcomes of the CAP, Turner Drake’s Economic Intelligence Unit compiled data from the Property Valuation Services Corporation’s DataZone for the 2017 assessment year, budget and tax rate data from the Halifax Regional Municipality’s website and Open Data Portal, and socio-economic data from Statistics Canada. Assuming the municipality would uniformly adjust tax rates to offset the 11% increase in assessment under a CAP repeal, our analysis allows us to estimate who is currently paying more and who is paying less, by how much, and whether these outcomes have social or spatial patterns. Every municipality is different, but with HRM comprising the greatest variety of settlement types, 44% of the population, and 55% of the total provincial assessment base, we find the results instructive.
Results
Urban – Spatial patterns in the urban areas are remarkable. Whether your kitchen has a view of the Northwest Arm seems to be the strongest predictor of tax savings, though much of the Peninsula’s west side makes out well. The apartment-heavy downtown and North Dartmouth areas are hit hard, while suburbs (unless recently developed) generally overpay, but just slightly. Aside from a small number of waterfront areas, Bedford and the developing suburbs are not saving much. Sackville and Spryfield are a mixed bag, with recent development in those areas hardest hit.
(Tax Overpay [more red] and Underpay [more blue] – Halifax Peninsula, Central Dartmouth and suburbs)
Rural – Compared to urban areas, rural areas tend to be more random as new construction and sales activity is dispersed while “hot” market areas tend to be highly targeted. The Chebucto Peninsula appears to make out reasonably well overall. The Head of St. Margaret’s Bay area is most favoured, while farther flung locations like Prospect have a more even balance.
(Tax Overpay [more red] and Underpay [more blue] – Head of St. Margaret’s Bay)
Unfortunately for the Eastern Shore, it looks like the shorter the drive to the city, the better your tax relief. Porter’s Lake is a mixed bag, and most communities past Jeddore pay a little bit more. Sheet Harbour is case in point, a very small handful of savers while most overpay mildly. The hardest hit property is a nursing home which pays an additional $5,000 in property taxes under the CAP. In aggregate, the outer rural areas of the municipality pony up an extra $110,000, while the rural areas within city commute distance save nearly $750,000.
Household Median Income – A strong relationship is observed between tax savings and median household income. Thanks to the mechanics of assessments, the more expensive and fast appreciating properties tend to accrue the largest discounts under the CAP. Shockingly, these desirable, expensive areas tend to be occupied by households of higher income. What is truly surprising, however, is the detail and extent to which this relationship holds true. Even within neighbourhoods that generally trail overall median income levels, tax distortions tended to favour the (relatively) higher income areas:
(Tax Distortion and Median Household Income in Fairview: red overpays, green underpays, sized by magnitude, darker grey is higher income, lighter grey is lower)
This relationship varies in strength across the municipality, but only truly breaks down in newly developed areas as new construction starts out uncapped, and tends to attract higher income households due to the premium price of a new home. Spryfield is a case study in getting the worst of both worlds:
(Tax Distortion and Median Household Income in Spryfield: red overpays, green underpays, sized by magnitude, darker grey is higher income, lighter grey is lower)
The level of income detail in rural areas is less fine-grained, but broadly, we see this pattern repeated when comparing the Chebucto Peninsula to the Eastern Shore.
Much Ado About Nothing
Despite the prolific shifting of taxes among tens of thousands of accounts, for most residential rate-payers in HRM the whole program may as well not exist. We estimate 45% of properties have their taxes adjusted (upwards and downward) by less than $200 per year, with the average bill enjoying less than $10 in savings. If we expand our bounds to adjustments of less than $500, we capture approximately 88% of all accounts, though now on average they have to pay $30 extra. Even at the extreme end of this sample, $40 per month is not exactly a significant level of tax relief. For the vast majority of households, the existence of the CAP does little to foster stability, predictability or affordability over an unadulterated assessment system.
Winners and Losers
With the vast middle-ground essentially playing musical chairs with small dollars, the real impacts are felt in the outliers. The maximum overpayment is limited by the artificial inflation of tax rates (roughly 11%), however the maximum discount has no similar limit; it is dependent on local market trends and the length of time a property remains capped. Thus the program tends to siphon tax dollars from a broad base of chronic over-payers and deliver them in considerable amounts to a relatively small number of super-savers.
The 403,000 souls in HRM are organised into just over 173,000 households; groups that occupy a single dwelling unit (usually based on family relations). Most of these pay more under the CAP. About 30% live in apartments that are not eligible for the program, and thus pay rents inflated by higher property taxes. Another 27% occupy eligible residences, but still pay more because the higher tax rate overwhelms their modest assessment discount (or lack of discount if newly purchased). So more than half, 57%, of all households in the municipality are losers, overpaying by an average of $275 per year. The majority of this unfortunate group will always pay more because their residences do not qualify for the program, or their capped assessment will simply not build up a sufficient discount over time. In total, the CAP extracts around $27 million from this bunch – a hefty sum on top of the taxes they fairly pay.
(Capped Properties That Actually Pay More: plenty of misery to go around)
Around $10 million of this is used to benefit land that is likely vacant but classified as residential, while the remainder is redistributed to the winner households, mostly in small amounts. Yet there are some very lucky recipients of this involuntary largess. Tax discounts in excess of 60% are not uncommon, and there is more than one tony street address that receives a larger tax break than the combined saving of entire mobile home parks.
The top 1% of households are afforded an average tax break of $1,500 per year. In total, this group enjoys more than $2.5 million of tax savings. In other words, it’s likely that the top 1% of beneficiaries are receiving around 15% of the total benefit collected by households, and much of this flows to high-income areas.
(Top 1% of Tax Savers: not quite so widely spread)
The System We Want?
Ultimately, tax policy is public policy, and the most fundamental test of public policy is whether it achieves its ends. It is a good and worthy goal that families not be forced from their homes by sudden tax spikes. It is also good that funding for local government be raised in a way that gives households stability, predictability, and affordability. Does the CAP achieve any of this, and to the extent that it does, is it worth the cost?
Property values and ability to pay are closely aligned, but not perfectly. There are always those who will have difficulty when taxes on the former unexpectedly outstrips the latter. They deserve protection, but the CAP is not a precise tool; for every property owner truly assisted, many others receive unneeded relief, or are undeservedly burdened. Beyond this, most households would experience stability and predictability in their property taxes regardless of the CAP, and the majority would actually have improved affordability without it, if only mildly.
So this is the outcome of the CAP, ten years after full implementation. Are we achieving these feeble results at an acceptable cost? Can we only provide peace of mind in taxation through a system that demands someone else’s sacrifice? Is it acceptable that we systematically target people like rural nursing home residents, low income apartment dwellers, first-time home buyers, and downsizing seniors to make those sacrifices? And is it acceptable that we provide only meagre relief to the residents of mobile home parks and housing co-ops, while systematically directing the greatest savings to neighbourhoods with lowest need? Surely we can do better than this.
©2017 Turner Drake & Partners Ltd. all rights reserved. Contains information licensed under the Open Data & Information Government Licence – PVSC & Participating Municipalities, and the Open Government Licence—Halifax. Analysis and conclusions are the product of Turner Drake & Partners Ltd., and do not necessarily reflect the views or endorsement of Property Valuation Services Corporation, the Halifax Regional Municipality, or any other entity. Whilst every effort has been made to ensure the accuracy and completeness of this document, no liability is assumed by Turner Drake & Partners Ltd. for errors or omissions. This is distributed without charge on the understanding that the contents do not render legal, accounting, appraisal or other professional services.
For more information on this analysis, contact Neil Lovitt, our Senior Manager of Planning & Economic Intelligence at 429-1811 ext. 349 (HRM), 1 (800) 567-3033 (toll free), or nlovitt@turnerdrake.com.
Our Economic Intelligence Unit is always on the hunt for new data sources to bolster our maps and feed our spreadsheets: any good analysis begins with high quality data. The majority of our databases are populated with a wealth of information via a process of blood, sweat, and tears (though increasingly data is graciously released by provincial gatekeepers) and it could be that our next trove of valuable data is being cultivated on farms across the Maritimes. The movement of food from field to plate involves numerous stops along the agricultural supply chain and, when property tracked, that data can prove valuable for a host of analytical tasks.
The ability to track an item from Point A to B in a large-scale supply chain is known as traceability. The theory behind it is relevant in all aspects of our lives: be it an Amazon package or a donair pizza, consumers - and businesses - have discovered that real-time knowledge of where a product is, physically, at any point in time is a competitive advantage in terms of marketing and efficiency. Agriculture is no exception. Traceability is already in use as a health risk management tool: it allows for rapid response to health emergencies by identifying exactly where and when afflicted produce or livestock stopped along the supply chain. Efficiently pin-pointing sources of contamination (think E.coli outbreaks) and creating cost-effective responses, such as targeted treatments and recalls, are critical in a modern, globally connected agricultural sector.
In addition to the obvious benefits of using traceability from an epidemiology perspective, there is also major potential for economic spinoff benefits from tracking the movement of agricultural goods. At a recent gathering of Nova Scotian Agrologists, speaker Chris deWaal of Getaway Farm (of Seaport Market fame) touted the very real benefits of offering consumers the entire life history of their food as a competitive advantage over mass-produced “mystery meat.” The introduction of the “Trace My Catch” program for canned seafood provides an example of how seafood processors are embracing traceability as a marketing tool, and provides an indication of the feasibility of doing so. In a province with a growing love affair for all things local it is no surprise that demand for local meat and produce is on the rise.
Benefits beyond health and marketing can be opened with traced agricultural data. Used in conjunction with GIS, the location and density of animals, farms, stockyards, abattoirs, and processing facilities become inputs for site selection and trade area analysis and indicators of economic health in rural economies - an issue of pressing concern for many Nova Scotian communities.
Imagine opening a meat processing and distribution facility to feed growing demand for local, organic products while still maintaining capacity for foreign exports. A standard GIS-based site selection analysis would use static location data (suppliers, purchasers) with network data (highway, rail, sea) to build a short-list of potential development sites which minimize transportation costs for both inputs and outputs. Additional variables such as workforce availability, machinery and equipment suppliers, veterinary services, and property taxes can all be integrated with locational data to suit the needs of the processor. But a standard analysis does not take into account how many animals are produced by individual farms or the variability in production from year to year.
Traceability data can enhance GIS analysis by optimizing site selection so it is based on not just the density of farms within a trade area, but the capacity to bring high volumes of livestock (or produce) efficiently to market. Historic tracking data of individual animals could forecast future production including where livestock are ultimately processed and sold. A savvy processor would use this data to identify opportunities for expansion and generate reliable, defendable business projections.
The agricultural sector already collects traceability data for use in health risk management; leveraging that same wealth of data for marketing and day-to-day business operations is the logical next step. The agricultural sector is a ray of light in the gloom of rural Nova Scotia: according to Statistics Canada’s census, between 2006 and 2011, Nova Scotia was the only province in Canada to see an increase in the number of farms, total farm area, and number of farm operators. Should the 2016 census indicate continued growth, it will clearly indicate that it’s time for all players in the agricultural game to leverage their existing data infrastructure to gain a competitive advantage at home and abroad.
For more information on how spatial analysis can benefit your business, call James Stephens at 902-429-1811 ext. 346 or visit: Economic Intelligence Unit
When you think of the ideal office space, what are your must-haves? An environmentally friendly building? Open work spaces? Proximity to your home or city amenities? These are considered some of the most commonly desired traits in office space by HRM tenants. Office space that fit this bill is becoming more available in the downtown core. Does this mean that the recent trend of moving into office space in the suburbs will come to an end?
HRM comprises eight urban and suburban sub-markets: Central Halifax, Central Dartmouth, Downtown Peripheral Halifax, Suburban Halifax, Peripheral Dartmouth, Burnside/City of Lakes, Bedford and Sackville. Notable changes to these submarkets since 2011 include 950,000ft.2 of new office space added to the rental market in Central Halifax, Bedford, Burnside/City of Lakes and Suburban Halifax.
With the current lagging economy, it is not surprising to learn that vacancy has almost doubled in the last five years, especially considering the plethora of new office space brought on stream throughout HRM. Vacancy increased in every submarket, but the changes in vacancy rates indicate a shift in where demand for office space is flowing – to suburban business parks. For example, Burnside/City of Lakes and Suburban Halifax experienced among the lowest increases in vacancy. The chart below reflects how the distribution of total rentable area by sub-market has changed in the last five years.
It’s not all bad news for the CBD, though… vacancy in downtown Halifax saw a below average increase in vacancy. This begs the question: because suburban space was highly available, are tenants moving there because they wanted to, or because of its availability? With more space coming on stream in the downtown core consistent with commonly desirable office traits, does this mean tenants will start to shift back toward the downtown core?
In the last year, vacancy increased in the downtown core, not because of tenants vacating the area, but because there is more inventory available. Urban space is competing against new, modern office developments in suburban business parks (previously the only option for new office space in the city) and the population is concentrating in the urban core. With rental rates stagnating as vacancy rises, this is the prime opportunity for tenants to move into new space… and perhaps that space will be in the downtown area.
Click here to read more, including a map showing the spatial distribution of vacancy rate changes since 2011. This topic was covered in detail in this month’s TDP Trends, a free service provided to decision makers with property portfolios in Atlantic Canada. Each month, it provides information on demographic, psychographic, migratory, income and wealth distribution, investment, technological, space utilisation, and other trends influencing property values now or in the future. TDP Trends are archived on the public area of our website.
As a recent addition to the Turner Drake team, one of the first major jobs I worked on was collecting data for our December 2015 Market Survey of leasable office and warehouse space in St. John’s, Newfoundland. Given my experience of Newfoundland was limited to a couple trips to visit my girlfriend’s family, being tasked with getting a handle on an entire city’s office and warehouse market seemed a daunting task. However, it has proven to be one of the best learning experiences during my first year at Turner Drake. As a newcomer to the real estate industry, speaking with building owners and managers gave me insight into the issues they were facing, and a more intimate understanding of the market in Newfoundland than I expected to develop in such a short period of time. After such a positive experience, I was excited to be tasked with collecting data on the St. John’s market again for our June 2016 survey.
The June survey is smaller than the December survey: we only gather data on the office markets, with the exception of HRM, where we surveyed both the office and warehouse markets. Don’t think that this means it was an easy job: at Turner Drake, “smaller” rarely means small.
To ensure our data collection met the rigorous standards of our ISO 9001:2008 quality standard certification, our surveyors undertook a month-long data gathering process. We began by compiling an inventory of every new office or industrial space with a minimum rentable area of 5,000 ft.2 in our five target markets (St. John’s, Moncton, Fredericton, Saint John and Halifax). As the number of cranes on our cities’ skylines attest, this was no mean feat. However, this was just the beginning.
The meat and potatoes of the data gathering process is distributing and following up on more than 550 surveys for our June report (and more than 900 for the December version). We begin by sending every one of our contacts an Inventory Form for each of the buildings they are responsible for. This year, we took a bold step forward and sent the survey forms by… email! If we’re lucky, the respondents complete the form with information on the size of their buildings, the current vacancies, the rental rates they are realizing, and a few other pertinent details. Then they check the little box saying “Please send me a copy of the final report” and we’re done. However, things are rarely that easy, and Turner Drake surveyors won’t rest until the job is done! If we don’t receive a response, we send a follow-up email, and if that isn’t returned, we call, and if our calls aren’t returned, we call again… and again… and again… until we get the data we need.
After all of the data has been gathered, it is entered into our CompuVal™ system. CompuVal™ allows us to track vacancy and rental rates over time for both individual buildings and entire markets, as well as analyze the data to predict future trends. To ensure no errors are made, our surveyors review each other’s work, “cleaning up” typos or other mistakes.
All told, the data gathering process can take several hundred hours to complete. For our June surveys, our four surveyors spent more than 330 hours gathering data. This is the point where we turn things over to our Economic Intelligence Unit, who work their magic by taking the raw data and turning it into a vibrant picture of the local market.
If you’re interested in learning more about our Market Surveys or purchasing a copy, give our Economic Intelligence Unit a call at (902)-429-1811 or visit our website.
Written by Colin Walsh, Consultant in our Lasercad® and Valuation Divisions. To learn more about Colin, visit our Facebook page to see his Featured Consultant article.
Immigration into Canada is nothing new: the country admits an average of 253,875 immigrants each year. This number is responsible for almost two-thirds of the national population growth from 2005 to 2015. Based on a housing demand projection study conducted by the Canada Mortgage and Housing Corporation (CMHC), a 1% increase in immigrant population causes housing demand to rise by about 0.66%. However, the Maritime housing market is facing a projected decline in the coming years due to three interdependent facors: an aging and shrinking population, a dearth of immigration and very low rates of economic growth. This is not new information: alarms were given by various sources and it’s time to halt the slide.
History has proven that an aggressive immigration policy can help smooth the impact of an aging population (e.g. Ontario and Vancouver). It is not surprising, therefore, that increasing migration into the Maritimes is an effective way of addressing the adverse effects of our aging population. New immigrants will not only help increase the production of goods and services but will also directly increase the demand for housing.
Becoming a Maritime immigrant myself, I have a special interest in exploring the relationships between immigrant and housing trends in this region. I came to Canada in late 2012 as an international student and have seen several immigrants who decided to stay and purchase a house here. Many of them are below age 40, well-educated, and economically independent. Do they represent the majority immigrant group in the Maritime Region? I decided to dig into the data to find the answer.
The Maritime Immigration Trends
Immigrants comprise less than 6% of the Maritime Provinces’ total population, but 20.6% of the national population. Immigrant inflows to the Maritimes fluctuated dramatically from 1991 to 2006, however in the last decade, trends have been rising. This can be attributed to new policy initiatives (e.g. provincial nominee program, skilled worker express entry) aimed at attracting more immigrants to the Maritime region. From 2006 to 2011, the number of immigrants to PEI rose six-fold. Not surprisingly, employment growth in PEI caught up with the national average during the same period. Although this growth is from a small base, it still means the island is attracting more than twice as many immigrants compared to its share of the total population.
Maritime Immigrants: Countries of Origin and Demographic Profile
The United States and United Kingdom were the top two source countries of the Maritime immigrants during the 1980s. The position was taken over temporarily by some Middle Eastern countries (in the aftermath of the Gulf War) and China in the 1990s. In the last decade, the US and UK again became the top two sources of immigrants, but China and other Asian countries are listed among the top five.
The map above shows the percentage of the total population formed by Maritime immigrants in in 2015, along with the most common countries of origin. Immigration to the Maritimes is heavily slanted in favour of Halifax County (NS), Queens County (PE), Westmorland County (NB) and York County (NB). However, according to the immigration demographic profile report provided by the Atlantic Metropolis Centre, more than one-fifth of immigrants who arrived in the Maritimes from 2006 to 2011 declared their intended destinations to be outside a Census Metropolitan Area (CMA), which indicates the potential for allocating new immigrants to rural areas.
The age profile of immigrants in the Maritimes is dominated by the lower age group according to the most recently released Statistics Canada data. About 75% of immigrants who arrived from 2011 to 2015 were under age 45, and 7.5% were under age 25. The corresponding numbers for resident Maritimers aged under 45 and under 25 in 2015 were 44.3% and 14.7% respectively.
The Housing Situation and Needs of Immigrants
There have been many reports and studies exploring the current economic and population trends in the Maritime region: evidence shows Maritimers are now on the brink of an extended period of decline. The unavoidable aging trend is weakening the Maritime housing market and will continue to do so unless effective action is taken. The key to slowing down the aging trend is to be open to the outsiders by targeting and attracting skilled immigrants to the region.
In last month’s TDP trends, we explored the HRM residential house market tipping point. In the Atlantic Region, most first-time buyers are aged 25 to 34, followed by a small portion in the 35 to 59 group. Second-time buyers are also primarily aged 25 to 34. Finding suitable and affordable housing is an essential step in immigrant integration. With relatively lower housing prices (compared to Ontario and Vancouver), the Maritimes have advantages in attracting potential younger aged immigrant home buyers. Such a future can have only one outcome: reversed housing declines in demand for the aging population trend, which will boost the regional economy.
Written by Chen Shi, Consultant in our Economic Intelligence Unit. To learn more about Chen, visit our Facebook page to see her Featured Consultant article.
With low fertility rates, an aging workforce, and an increasing dependency ratio, Canadian demographics are transitioning from a tailwind to a headwind on property values. In Atlantic Canada, this is doubly true. The Maritimes are the vanguard of the Canada’s aging population, but generally lack the simulative effect of immigration. This sets us on a collision course with important tipping points in real estate economics.
While much has been said about the effect of a stagnant and aging population on economic growth and social services, we find little consideration has been given to its impact on real estate. This is an enormous oversight; not only is real estate generally the largest single asset held by private citizens and often businesses, but it is by far the largest driver of both revenues and expenses for local government.
On September 17th 2015, from 7:30 am until 9 am, we will host a breakfast seminar at the Halifax World Trade and Convention Centre on the demographic changes sweeping the region, and their impact on real estate values in Atlantic Canada. Experts from our Economic Intelligence Unit and Planning Division will outline the implications of Nova Scotia’s demographics for real estate, and discuss how the way we plan and develop our communities should adapt.
This breakfast seminar will be of interest to decision makers with property portfolios in Nova Scotia as well as municipal planners and professionals active or advising clients in real estate; lawyers, commercial loans officers, accountants, developers. To reserve your hot breakfast contact Gen Lecour at glecour@turnerdrake.com or (902) 429-1811 Ext. 345. There is no charge but we will accept donations to the Salvation Army and Oxfam at registration.
For better or for worse, the real estate industry is known for using terrible euphemisms to describe space, but the truth that lies behind some clichés can be leveraged to your advantage when you are choosing a location for a new, expanding, or relocating business.
Location, Location, Location
Real estate is intrinsically linked to physical space and yes, location is key. But what makes one location great for a particular business may be the exact reason it is a terrible location for some other venture – being next to a main thoroughfare with easy access to the Trans-Canada highway is great for a shipping business, but less appropriate for a childcare centre. The ideal location for some businesses is near other businesses of a similar nature (think groupings of clothing stores along certain roads or in malls), whereas others will do better if there’s a bit of distance between themselves and the next one (think convenience stores). In terms of getting along well with your neighbours, the right location can be of more help than the proverbial good fence by avoiding the “not-in-my-backyard” scenario that incompatible land uses inevitably spur.
If You Build It, They Will Come
Businesses each have a specific target market…if you build it, they might come, but you could save yourself a lot of energy and marketing time if you just built it where they already are, or where they are headed anyway. Demographic indicators, from age groups, gender proportions, daytime population, and indicators of wealth and income, all play a huge role in the success of a business – and the relative merits of one location over another. The Greater Halifax Partnership has a great GIS tool for the properties in their database (http://halifax.zoomprospector.com/. If you need something more customised and specific, or located outside of Halifax, we can help).
Timing is Everything
If you are looking to build a large development, you want to time it so that your project comes to market when demand is high, competing supply is low, and preferably as the economy is trending upwards. Our recent Market Survey of office space in five of the major centres in Atlantic Canada highlights this: vacancy is pushing upward across Nova Scotia and New Brunswick. See the results for yourself in the News & Research section of our website (www.turnerdrake.com/newsresearch/index.asp, then explore the Media Centre and Surveys tabs).
All Over the Map
The beautiful thing about real estate is that because it has, by definition, a physical location, you can map it. Then you can map other pertinent things around and relating to it, such as competing or complimentary businesses, roads, public transit stops, parks…you get the picture (or will, once you see it all on a map). Demographic data can be plotted and aggregated for existing and potential locations. This wealth of information can be analysed and studied in great detail or with a “quick & dirty” report, depending on how in depth you need the answer to the question “where?” to be, and the level of professional advice you require. It really does pay to “look before you leap”…after all, “nothing in life is certain except death and taxes” but making an educated decision is better than “flying by the seat of your pants."
Wise words from Alexandra Baird Allen, Senior Manager of Turner Drake's Economic Intelligence Unit. If you're looking for the perfect location for your new, expanding or relocating business, give Alex a call at 1 (800) 567-3033 or email her at abairdallen@turnerdrake.com .
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