Turner Drake Blog

There’s an old episode of the Freakonomics podcast entitled Why Are Japanese Homes Disposable?, which originally aired in 2014.  The upshot of the pod is that while land in Japan retains its value over time (sort of…the pod is worth a listen!), the houses on it do not, so when “used” houses are sold, they are frequently demolished and replaced.  When I came across the episode, we were in the midst of record high lumber prices, not to mention a climate crisis, and I had a hard time wrapping my head around the idea of houses only lasting 40 years or so.  And then I thought I’d like to look a little more into construction costs and their impact on housing prices here.   

There are three common methods of valuing property: the income approach, the direct comparison approach, and the cost approach.  The income approach is only relevant for valuing income producing properties, so not applicable to housing prices per se (though would be relevant for rental properties, but that’s another story).  The direct comparison approach and the cost approach are both based on the general premise that similar things will have similar values.  In direct comparison, you’d pay for a house what everyone else is willing to pay for a comparable house in the same or a similar location.  In the cost approach, the premise is that you’d pay for a house the same amount it would cost to buy some comparable land and build the same house.  Thus, rising construction costs should push up housing prices and vice versa. 

One of the key components of most houses in Atlantic Canada is lumber.  The following graph shows the Nasdaq prices for Random Length Lumber futures contracts (i.e., lumber prices on the stock market) over the past five years.  The orange line shows the daily closing price (values on the left axis) and the blue line shows the aggregate demand for the stock (values on the right axis, measured in thousands of dollars), which I calculated by multiplying the closing price by the volume traded that day, so it’s a rough estimate because prices fluctuated throughout each day.  I find it interesting that as prices climbed in 2020, the gap between the lines for price and aggregate demand grew, and that while there are definitely some sharp spikes in it over the past two years, aggregate demand did not follow the same upward trajectory as did prices.  There is only so much money to be spent on lumber, and when prices go up, demand drops.  But, more to the point on housing prices: when lumber prices go up, so too does the cost to construct, and thus on a cost approach to valuation, house values rise.  

Source: https://www.nasdaq.com/market-activity/commodities/lbs/historical with slightly questionable calculations displayed by the author…maybe those demand spikes occurred when there was a price drop on a particular day, and volume traded shot up, then I’m calculating it on the end of day price…it’s an imperfect analysis!

Labour costs also feed into the cost to construct, and with a noticeable shortage of availability of skilled trades in recent times, it stands to reason that labour costs are up.  The following table shows average hourly wage rates for industrial, electrical, and construction trades; percentages at the end of the lines are the total change over the period 2017 – 2021.    Note the convergence in wages amongst the three Maritime provinces: could this be a marker of increased willingness to move around within the region? 

Source: Statistics Canada. Table 14-10-0340-01  Employee wages by occupation, annual

These are inputs into construction prices, which have tidy price indexes available, and it’s interesting to look at the difference in price changes between types of residential construction: single family houses and townhouses have had the sharpest increase, followed by low-rise apartments, with high-rise apartments bringing up the rear.  The intuitive difference maker is construction material: high-rises are not typically made of wood (yet – here’s one sample article of many on the topic).  The following graph shows the construction price index, quarterly, for a composite of eleven CMA cities, including from Atlantic Canada Halifax, St. John’s, and Moncton.  The patterns for each of these cities individually are similar. 

Source: Statistics Canada. Table 18-10-0135-01  Building construction price indexes, by type of building

Back in February, we published a blog that looked at interest rates and housing prices.  For a quick reference point, I’ll recycle one of the charts from that post:

Source: Turner Drake & Partners Ltd. Compuval™ Residential Database; Statistics Canada. Table 10-10-0145-01  Financial market statistics, as at Wednesday, Bank of Canada.

The next chart brings a few of the previous factors together.  It’s got lumber prices looking like the heart rate of someone doing sprints, the mortgage rate looking quite lifeless in comparison, and the year-over-year percentage change in house prices annually throughout the chart.  Benchmark MLS^® prices are shown with little diamonds and are July to July changes; these prices will include some new construction, but the majority of the inventory feeding into the data is existing housing stock (the sort that might be torn down and replaced in Japan).  New construction prices are shown with circles and are October to October changes.  Notice how the two housing price metrics track each other, and also follow the change in the price of lumber, especially towards the end of the period, when lumber prices were particularly volatile.      

Sources: www.nasdaq.com; Statistics Canada. Table 10-10-0145-01  Financial market statistics, as at Wednesday, Bank of Canada; The Canadian Real Estate Association; CMHC Starts and Completions Survey.

Our Planning team is currently working on a Housing Needs Assessment for the province of Nova Scotia.  Neil Lovitt wrote a blog post on that topic in April of this year, and in it, he noted that “housing affordability has rapidly eroded over the course of the pandemic, and was being degraded more slowly for years before that.”  Lumber prices appear to be coming back to relatively normal levels, though that can change in a heartbeat (take a look at late 2021 to early 2022 on the chart above); interest rates are certainly on the way up, and potentially holding there for a prolonged period.  Inflation has been at generational highs over the past few months, and labour costs will have to continue to increase if wages are to keep pace with the cost of living.  The latter three make construction less appealing, but we cannot afford to slow provision of new housing options if we want any semblance of affordability or attainability in the housing market.  In overly simplistic terms, a lot could be riding on lumber prices.    

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

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[i] “An economic family refers to a group of two or more persons who live in the same dwelling and are related to each other by blood, marriage, common-law, adoption or a foster relationship.” – Statistics Canada.

[ii] “A person not in an economic family is a person living either alone or with others to whom he or she is unrelated, such as roommates or a lodger.” – also Statistics Canada.

 

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.  

…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.

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.  

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.

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.

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! 

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[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.   

On February 5^th, 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

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 17^th 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 .