Blessed by the Potato

I posted yesterday about some bullish (or not-bullish but not-bearish) arguments on housing and why I think they’re overlooking important factors. Michael James hosted an interesting discussion on his blog where he called me his favourite writer (well, not quite). Larry MacDonald left a comment there about an upcoming article he’s writing for the Globe. I hate to preemptively publish, and want to read it and give it a chance before formulating a response, but unfortunately tonight is the only time I’m going to have this week to write.

Larry’s comment was that “interest rates don’t go up in isolation, as he [referring to Ben Rabidoux, but could equally apply to me] appears to assume. Looking at business cycle dynamics over history, interest rates and household income tend to rise together.”

This is another case of something that is true but not helpful. Yes, the economy will likely be doing better when interest rates do finally go back up (next year, or next decade), and that likely will bring wage growth. But that doesn’t obviate the risk of buying an over-priced house now: the impact of rising rates and that of rising wages and employment are vastly different:

• Rates can rise very quickly, increasing payment obligations equally quickly, whereas even robust wage growth takes time to compound enough to influence affordability metrics.
• The impact of modestly higher rates on affordability/mortgage payments is in all likelihood going to be much greater than the impact of the associated wage growth.

Let’s work through a concrete example: say that you’re an approximately average Toronto couple. Together, you pull in $100k/year, and recently bought a house at $575k, taking on a $460k mortgage fixed for 5 years at 3%. Your monthly payment of $2180 is a touch over 26% of your gross pay: with heat and taxes it’s still (barely) below 32%, so this place is officially affordable!

About halfway through your mortgage term, this ridiculous not-quite-a-recession we’ve found ourselves mired in ends. Job growth picks up, and inflation rages at 10%/year. The Bank of Canada (and the bond market) is forced to respond to this double-digit inflation threat, but in this dream scenario mortgage rates merely go back up to 6%.

You don’t pay much attention because your mortgage isn’t up for renewal until 2018, and by that time surely wage growth will take away the sting. Well, following the first two and a half years of pay freezes at work, things indeed started looking up: with consecutive raises of 10% you’re now grossing $128k, and you’ve paid your mortgage down to a mere $393k.

Then you get the bad news: your monthly payment is now $2800, still representing a touch over 26% of your gross pay. If property taxes and heating costs have also increased 28% due to inflation, then your place is still borderline affordable at 32% of your income. But you were one of the lucky ones: what if your wage growth had merely paced interest rates? Using 2.5 years at 6% wage growth would mean your mortgage alone was 29% of your income — with taxes and heat your GDS would be over 34%. Your house would have to fall in value by 14% (in nominal terms) in order for a buyer in the new environment to buy it with the same affordability metrics as you enjoyed back in 2013.

What if you were one of the unfortunate few whose mortgage renewed the very year the economy picked up and rates increased? You’d have been afforded no time for the inflation you heard so much about to increase your wages… so your mortgage payment alone would top 33% of your pay, and the affordability pressure would attempt to push house prices 23% lower.

So what I’m saying is that the effect of small changes in interest rates on affordability is very likely to be much greater than the offsetting effect of wage growth. Interest rate increases raise the cost of buying a house immediately, but wage growth takes time — and we’re unlikely to see the BoC or the bond market allow wage inflation to rage for a few years before getting around to lifting rates off the zero bound.

Perspicacity is one of my favourite words. The dictionary definition mentions understanding and discernment, and I think of it as more specifically referring to the ability to discern what is and is not important from conflicting data. Part of what helped rocket it to near the top of my favourite word list is that it was the defining trait for NASA astronaut selection during the space race:

The quality most needed by a scientist serving as an astronaut might be summed up by the single word ‘perspicacity.’ The task requires an exceptionally astute and imaginative observer but also one whose observations are accurate and impartial. He must, from among the thousands of items he might observe, quickly pick out those that are significant, spot the anomalies and investigate them. He must discriminate fine detail and subtle differences in unfamiliar situations, synthesize observations to gain insight into a general pattern, and select and devise key observations to test working hypotheses.

There have been many articles on the state of the housing market — more every day — but for today I will pick on Larry MacDonald. In part because his dig (or his headline editor’s) at bears for making “unsubstantiated claims” was highly unfair: housing bears are some of the most data-driven people I know. (Though speaking of editors, he may have just drawn the short straw in taking sides for a manufactured debate). And in part because his articles (like many bullish ones) seem to lack perspicacity.

We had the one where he tried to set up an esoteric monetary policy criteria as being necessary for a housing correction, though left unsaid was the market’s vulnerability should such an inversion in the yield curve arise, or how changes to mortgage insurance might have the same effect. The affordability index is a perennial favourite, though it is highly interest-rate dependent. In short, lots of focus and analysis on the measures and factors that are — IMHO — not as fundamental.

The most egregious is also the most recent: “Is Canada talking itself into a housing crisis?” He tries to take a paper by Shiller — Professor Robert “Irrational Exuberance” Shiller! — to make the case for there not being a bubble in Canada, and that all the negative media stories may cause a downturn when the fundamentals are ushering in a soft landing.

In that piece, he picks bits out of the stories to come to strangely opposite conclusions. You can find the Shiller paper online, explaining that buyer expectations help set house prices — and that the media may have helped change those expectations as the market turned in the US around 2006. But that’s negative press precipitating a downturn in an over-valued market that’s primed for it, quite a different matter from Canada “talking itself into a housing crash.” Indeed, in that same article Larry cites a CBC interview with Shiller from September, summarizing Dr. Shiller’s points as “Canada should be spared.” Yet for many others, Dr. Shiller’s take-home message from that interview was “I worry that what is happening in Canada is kind of a slow-motion version of what happened in the U.S.”. He’s not at all saying that housing prices won’t correct or somehow be spared — the suggestion is that such a process won’t take the banks and the rest of the world economy down with it.

Dr. Shiller argued — in advance — that the fundamentals were out of line and that a correction was due in the US. He has not been as vociferous about Canada, but has several times said that Canada in general, and Vancouver in particular, are worrisome. Hell, even when trying to be bullish the bit about the RBC affordability index can’t support the insane singularity that is Vancouver. The paper Larry cites is about perception and media reports affecting the timing of the correction, not causing it. If anything, it’s just as much about how expectations helped fuel the bubble in the first place.

The real world is a messy place, and markets particularly so, with a great deal of data to parse, much of it conflicting. Hell, differing perspectives and valuation schemes are what make a market. So one must proceed with a degree of perspicacity: seeing what is significant, understanding what conflicting data imply, and acting with all due caution.

The Globe has an article out this weekend on Emili, CMHC’s automated housing appraisal system.

To break it down, when someone wants to take out a mortgage, they go to the bank and say something like “I’d like to borrow $500,000 for this house that I just purchased for $550,000, and I’ll pay the other $50,000 with my own money.” The bank then has to make sure that the $500k they lend will be paid back, by looking at the income and creditworthiness of the borrower, and also at the value of the house, so that if there is a default that the value will cover the mortgage. Even with 10% down, a loan for $500k is not very secure if the property is only worth $400k. Emili is an automated system to determine that house value (and, as I understand it, some of the other aspects of the loan), which makes the whole process a lot faster and more efficient than sending an appraiser to check out the house.

The problem pointed out by the Globe is that Emili is too generous. There are lots of reasons given in the article as to why, including this gem:

A CMHC spokeswoman said that staff are aware of “a handful of cases” in which Emili approved a mortgage for a non-existent house.

But let’s think about it logically. Emili could be perfect, always assigning the correct value to the house. Personally, I find that unlikely for many reasons mentioned in the article, such as that Emili can’t see inside the house to assess the state of repair or the level of renovations, and that known errors exist.

Emili could be good enough, but with a few mistakes made here and there. That’s a fairly likely scenario, after all many times those small matters of internal shape are not that important to the valuation, especially if there’s a decent margin of safety built in or if the land value is a significant component of the valuation. If Emili is mostly accurate with a few inescapable random errors, then we should see mistakes made in both directions. We should hear reports of buyers caught in the emotion of a bidding war, only to find their mortgage rejected because Emili won’t support the valuation, or of Emili erroneously denying a mortgage because it reports a vacant lot after a house was destroyed by fire (not having the record of the replacement), or coming in too low on valuation for some other reason. I’ve been keeping my eyes open for these sorts of anecdotes for years, and haven’t seen them.

That leads me to what I believe is the actual situation: Emili systematically over-values real estate.

Now, some over-valuation is to be expected. Lenders don’t want to turn away business by cutting the appraisal too fine, and the insurers will build this into their models. They may also assume that prices generally go up (at a modest rate), and since it generally takes time for a default to occur some upward bias can be tolerated. But when extreme dislocations occur — such as bidding wars leading to “winning” offers hundreds of thousands of dollars too high, or certain neighbourhoods seeing annual appreciation way above the norm (like 20%/year) — then the system should be flagging those as problems and denying the loans. That would act as a natural brake on a bubble.

Though it is important on a national, system-wide basis to avoid bubbles, nobody on an individual level has much of an incentive to implement brakes. The banks want to lend (especially if they have CMHC covering their butts), the buyers want to buy, the sellers want to sell, and the ancillary agents want transaction volume. CMHC is one of the few entities that could play the role of a disinterested, rational appraiser, yet they too have no political will or desire to stop housing momentum and break deals by being strict with qualifying criteria. Indeed, contrary to Robert McLister’s opinion that “CMHC knows the risk of it botching property valuations en masse. It has the public, press and regulators breathing down its neck around the clock,” I’d say that the public, press, banks and mortgage brokers are breathing down its neck to allow transactions to proceed. So instead, Emili accounts for many things including the “…housing market conditions in which the property is located…” which to me reads as “becomes loose and permissive in hot housing markets.”

Rob McLister of CMT counters:

“Inevitably, people will read the Globe’s story and think that CMHC is using some back-of-the-napkin formula to judge property risk. That’s so far from the truth. Emili is not some 100-line computer program written by a college intern. It is multi-million dollar mission critical technology benefiting from the best available data and over two decades of R&D.”

For what it’s worth, I don’t doubt that. But it’s not open source, and we don’t know the assumptions that went into making that expensive, sophisticated valuation engine. For example, does it implicitly assume that buyers are rational? A single over-heated bidding war might raise a flag, but would 3 or 10 in an area upgrade the valuations of everything, as it’s then a pattern? Though fraud becomes less likely, the loans really are no more better supported in the long run. Similarly, in assessing risk the core assumption seems to be that valuation changes affect severity, while unemployment affects default rate — the two factors combining to make up the losses that CMHC may face, and the two factors being completely separate and orthogonal. Yet in the aftermath of a bubble, valuation changes also affect default rate as speculators walk away (even though they may remain gainfully employed), and unemployment as well (as construction grinds to a halt). But if that wasn’t observed in the dataset used to build the models, then it may not be accounted for.

As a parallel, consider the subprime mess in the US. I’m sure the ratings agencies had expensive teams of people and fancy computer systems to come up with the “mission critical” ratings for CDOs, yet every AAA handed out was in error, due to some flawed underlying assumptions and a lack of checks. For instance, an underlying assumption of building many of the CDOs and securitized portfolios is that not all the crappy subprime debt goes bad at once, so you can have a AAA slice from something made up of junk. Michael Lewis also highlighted one of the other flawed assumptions: that “average credit rating” meant something, when in fact a pool of 100 mortgages to people with a credit score of 650 is rather different than 50 mortgages to people with a 700 and 50 to those with 600.

I think that based on first principles and the housing market insanity we’ve seen in the last few years, it’s clear that whatever is inside the black box that is Emili is biased to the upside in its valuation methodology. While that doesn’t cause a housing bubble, it allows it — a tragedy given that CMHC is the ultimate holder of risk and should have its systems tuned to be more conservative.

You’ve all heard about “supply and demand” even if only as a back-handed excuse given for why something costs so much. It’s pretty basic economics stuff: even a scientist can follow it. As the price of something goes up, suppliers will be willing to sell more product (and will make changes or substitutions to bring that product to market) while consumers will demand less (and find way to substitute other goods for the expensive ones). Graphically, that looks like:

The shape of the supply and demand curves vary depending on exactly what system you’re talking about, but they have that general property of supply moving up and to the right while demand goes down as you move up in price. (Note that economists usually treat price as the independent variable, and thus have their graphs backwards, but let’s leave that alone – the relationship works either way around). Where the lines meet should be your equilibrium: the same quantity coming to market for both the supply and demand side at a certain price point.

You can then do things to those curves to find what the new equilibrium would be. For instance, if the above graph represents the market for potato chips, we could imagine what might happen in a scenario where say Nelson’s chip truck breaks down. With less supply available, the supply curve would slide to the left, and the price would go up while fewer bags of chips were sold.

For housing, the demand curve is very flat: most people go through their lives without ever really analyzing the largest purchase they’ll make (and a again, remember the backwards axes of economists – a “flat” curve is actually nearly vertical). They simply get to a point where they figure they can afford it, and they go out and pay whatever the price is to get a house because that is what one does. There are a small number of people at the fringes who can’t afford to buy as prices go up (giving the slight negative slope through the middle), and prices would have to go down a lot before anyone would consider buying a second house. But through most of the range of typical prices, the quantity of demand is pretty stable.

Supply is a little less flat, but still fairly stable compared to many other markets with more substitution options and more responsive supply sources. Above a certain point and you can keep your construction crews operating profitably so away you go. As prices start to get really high supply can start to really ramp up as people get drawn away from other professions to recover supply from the margins (fixer-uppers) or subdivide existing large single units into multiple smaller ones (as seen not only in condos going up over SFHs, but also in Vancouver row houses).

But it’s never this simple in the real world. Supply and demand can be perverse when speculation comes into play. Then you have not just prices versus number of units sold, but also price history as a factor.

If prices were to rise too far too fast, our simple model of supply and demand suggests that more supply should come into play and demand should drop because of the influence of high prices, creating pressure to bring the market back to the equilibrium point. In a mania though, the opposite happens: the price history turns rational buyers and sellers into speculators. Buyers buy more, either borrowing demand from the future in the form of the buyer who’s afraid of being priced out if prices continue to go up, or from speculators buying multiple units with dollar signs in their eyes. Supply is a little more complicated, as it does definitely respond to the higher prices – that’s evidenced in the real-world by the plague of cranes in Toronto and Vancouver slapping together ever taller and smaller condos. But supply also shrinks a bit with strong price history in what’s referred to as “speculative holding” (at least relative to the supply dump we’d otherwise see). With prices on the up-swing, those moving (or moving in together) decide that rather than sell the old place, they’ll hold on to it, sometimes explicitly for investment purposes, but there are anecdotes of those who do it “just in case” even though they would have never considered that holding if price history was less favourable.

So we see that as prices move up, both supply and demand can increase in proximity to each other, feeding the beast ever upwards (no equilibrium restoring pressures), and the whole time it will superficially appear as though supply and demand are in balance.

What happens when prices stop rising at a break-neck pace? When they go down a bit – or even just stop increasing – in the so-called soft landing? In a normal market, the lower prices should bring more buyers out of the woodwork to support the new equilibrium. However if it’s not a normal market, but rather one driven by mania and attention to price history, then declining prices are not seen as cheaper but rather a shattering of the speculative world-view. Instead of finding new support for the equilibrium, the speculation in the market dries up. The demand snaps back to the inherent demand curve (which at the high prices, is a lot less quantity) while the same happens to supply (speculative holdings flood the market and listings go up). Supply and demand are – very suddenly! – far apart and there is a lot of pressure for prices to drop back to the original equilibrium.

It is my firm belief that the decline in sales volumes seen in Toronto and Vancouver this summer/fall are the first stages of that.

Now, many are saying that sellers won’t accept lower prices, that they will pull their listings rather than sell at a lower price. This is supported by our conventional view of supply-and-demand, and indeed this is what I expect will happen in the short term. But the speculation also affects the sellers. Those with speculative holdings may no longer be quite so enamoured with the land-lording life (or worse yet, the cash-sucking vacant “just in case” condo), so they may sell a bit below the peak (though the early ones will walk away with personal profits). As price momentum turns negative, the thoughts of holding out for better days turn to fear that negative price movements will persist, and panic sets in. Meanwhile, the builders who pulled out all the stops to meet the crazy demand of last year can’t stop on a dime.

There are many pundits out there with a basic understanding of “supply and demand” and who try to change their vision of the real world to fit that – in other words, they play up evidence that demand is legitimate (whether from immigration or a secular shift in how much of their paycheque the average Canadian is willing to put towards housing expenses) in order to explain high prices. But that simple model doesn’t really leave room for bubbles, manias, and speculation. Of course, I might be wrong – I still have to stop and think about those damned backwards axes every time – but at least the mental model I’m working from has the possibility of generating a bubble. For some bulls, they don’t think there’s a bubble not because of the weight of evidence, but because an overly simplistic model of supply and demand simply doesn’t allow for the possibility.

Last week TD came out with a brief research report titled “Canadian Housing – How Bad Could This Get?” that looked at what the impact of a housing downturn would be on Canadian banks.

As a bit of background, banks are in the business of borrowing money from investors and lending that money out to borrowers (as well as other businesses like transaction facilitation and capital markets and what-not). A big component of the money lent out by a bank comes in the form of people taking out mortgages. If something happens in the housing market that affects borrowers and their mortgages, then that can affect the banks.

The two basic ways that banks can be affected is through the balance sheet or through the income statement.

If people stop repaying their mortgages entirely, as happened with many underwater borrowers in the US and Ireland (and was particularly severe in subprime pools), then the bank starts the foreclosure process to get their money back from the borrower, and will likely have a small loss due to the costs of foreclosing (particularly if the size of the mortgage is high relative to the value of the house). If the security that backs the loan (the house) is also worth less because housing prices have fallen, then even after foreclosing and auctioning off the house, a large part of the mortgage may be unrecoverable, and the bank takes a big loss on that. This is a balance sheet problem: the assets (mortgages) are worth less while the bank still has to pay the investors that lent it money. This is a crisis for a bank, and can lead to the bank having to raise more money, get a bailout, or go into bankruptcy.

The TD report says that Canadian banks are not at risk of a balance sheet crisis from a housing market slowdown, and I generally agree: even though we may see some severe price reductions and increases in mortgage defaults in certain Canadian cities, the banks here have been very good at getting rid of their exposure to that risk through insurance and securitization. The mortgages they do hold generally have low loan-to-value ratios, so that even with fairly severe price corrections they won’t have a critical imbalance between their own borrowings from investors and the value of the mortgages they’ve lent out.

The other impact can be felt in the income statement: since mortgages are a big part of a bank’s business, they also make up a large part of where the profits come from. If fewer people are buying houses, and taking out smaller mortgages to boot after prices come down, then the banks will be making less money because of the effect of writing fewer mortgages.

Jason Bilodeau says that there will be some impact of a correction there, but that it won’t be large: he estimates that for a 5% reduction in mortgage growth, the banks would report 7% lower profits. I found that rather surprising: that the impact to profits would be higher than the reduction in activity, though in hindsight it should have been expected of any business with fixed and variable costs.

Thing is, he calls this 5% reduction a “worst case”. That is not the worst case, not by a long-shot: hell, sales are already down 25% in Toronto and over 30% in Vancouver. Those two cities hold roughly 20% of Canada’s population, but the dollar-volume (i.e., the size of the mortgages for the banks) is even higher than that because house prices are also higher. With a bit of back-of-the-envelope math, it looks like the mortgage growth is already in negative territory by about 10% even if the rest of the country was perfectly stable.

One other important factor is that housing activity can change without necessarily changing the size of the banks’ books: a lot of housing activity consists of people who already have houses and mortgages selling to one another. In those cases, it’s possible that no new net mortgages will be written, so there is a case to be made for changes in first-time buyer activity being the important metric, not overall sales. But, I think it’s a reasonable to assume that first time buyers will move with the rest of the market, or if anything, to drop even more in times like these (in rising markets, there’s a sense of “buy now or be priced out forever” leading to more first time buyer activity, and larger mortgages at that as they jump in without downpayments).

So what would the worst-case-scenario look like? Well, in 1989, Toronto had about a year where housing activity was cut in half, and activity only picked up again after price declines set in. Even if the correction was limited to Vancouver and Toronto, with a sales decline of 50% (or some combination of sales declines and price correction) the overall national change in mortgage activity would be more like 17% lower.

At some point I may run through the financial statements of a bank to pull out how much of the increase in profitability over the past 10 years has been due to mortgage credit expansion, and what a correction of ~30% in prices with some decrease in volume would look like to earnings. But unfortunately dear readers, I simply don’t have the time right now. Instead, let’s just extrapolate from TD’s numbers in the report: if a 5% reduction in activity lead to a 7% decrease in EPS, a 17% decline in activity might lead to a 24% hit to EPS.

That’s not necessarily killer: I wouldn’t be shorting banks on that basis, but I wouldn’t be buying them either. Also keep in mind that this still isn’t the worst-case, since many other cities will also likely follow Toronto and Vancouver’s lead. First-time buyers might drop out of the market entirely for a few years, to correct the imbalance in the ownership rate. And people may start making downpayments if they aren’t rushing in to beat price increases.

Using this historical experience as a guide, our sensitivity analysis suggests that our 2013 estimates could be roughly 7% lower, all else the same, if the market were to experience what would be the worst housing correction on our record.

Part of where the low numbers come from is looking at the effect of past housing busts: 1989 was bad in Toronto (and indeed, many regional trusts collapsed), but the rest of the country was fairly unscathed, with Vancouver powering on for 5 more years. Nationally, the banks (and mortgage volume) came out ok. In 1994 Vancouver had a correction, but that was when Toronto was pulling out of its decline. These regional housing corrections have never lead to major problems for the banks before because they were regional and uncorrelated. This time around is going to be much worse than the historical record would suggest because there’s a lot of correlation. Alberta managed to blow off a bit of steam with a soft landing over the past 3 years, but could be sucked in for another 10% down-leg. Ottawa, Montreal, Halifax, Winterpeg and Regina are all equally affected by record-low interest rates and primed for a correction as well.

“In addition to the earnings risk, as is often the case, the cycle would likely be marked by poor sentiment and compressed multiples driving share underperformance. Typically, the group underperforms early in the decline, before recovering as the market looks through to the bottom and eventually improving conditions.”

There are enough investors worried about this, apparently, that multiple compression has already set in. Despite fairly good EPS numbers, most of the banks have gone nowhere since powering out of the 2009 crisis, more-or-less plateauing since the spring of 2010. Once earnings growth turns negative, there will likely be another round of share price decreases, at which point I may look at buying back into the sector.

As an aside, this report begins with the statement “We continue to believe that we are in the midst of a material slowdown in Canadian housing activity.” It’s a very devious statement: throwing in that “We continue” makes it seem like they forecasted this some time ago, rather than, say, just starting to say this last week. Indeed, back in the summer in a report on Genworth, they believed there would be no material slowdown.