A recent visit by Angela Choi (Deloitte) to my market analysis class provoked me to reconsider the ways in which a building could add value to businesses using that building. Old style thinking emphasized that a business needs to locate somewhere and that real estate expenses were best if lowered. That made sense when a building was basically a box. Innovations in information technology has some people talking about “cognitive buildings” and people like Angela talking about disruption in the real estate industry.
The media coverage of price trends in Toronto’s residential housing market has been confusing. Most people look at recent reports and conclude that past trends have stopped or, at least, paused. Some people point to examples where old patterns of behaviour (i.e. paying more than list price or selling in a couple of days) reappear and reach a different conclusion. These conflicting stories illustrate how difficult it can be to analyse market conditions when there is no simple trend.
Turning points are challenging because a different logic of analysis is needed. I teach classes on the simple analytics of trends. Since there is general agreement on the direction, that analysis focuses on measurement and estimating precisely.
At a turning point, the general agreement falls apart. Illiquidity in real estate markets means Continue reading
According to Moneysense, and our Mayor, the best city in Canada to buy a home is Guelph. While I agree that Guelph is a nice place to live, I think that it is silly to make that claim.
More importantly, should I believe anybody who says that they know? Moneysense’s ranking uses public information and massages it in some way. Lots of people do this kind of exercise for many reasons (best country to live in (Canada is #2 in 2017, best country for business (Canada is #10 in 2016), …). It would be better to know if information is relevant. In other words, understanding the methodology is critical. Professional statisticians and high quality data sources talk about methodology a lot. If a methodology is not given, as was true of this exercise, attempting to reverse engineer it can raise important questions.
Based on the information provided by Moneysense, it appears that Continue reading
Academic research can seem rather odd to people not at a university. Most of it seems obscure, until somebody needs to find the expert on a particularly troublesome topic.
This podcast explores some research done about 15 years ago by one of the members of GREG. The discussion at the top of the page by the interviewer shows how this work shifts thinking on the connections amongst list prices, selling prices and how long it takes to sell, and is followed by the podcast. (Click on the green arrow at the bottom to listen to the podcast itself.)
Understanding this very old problem has implications for understanding some current dilemmas. Continue reading
Previous posts have explained why it is silly to look to facts as if one of them was a magic bullet which would reveal the Truth. The facts matter but in combination. This post notes that, sometimes, even properly-weighted facts may not be enough.
For example, people have been debating whether or not there is a price bubble in Canadian residential real estate for nearly a decade. To a true believer on either side, the fact that the price is “high” is no longer important, either because it is added proof that prices will crash in the very near future or because it reveals some previously-unconsidered explanation. As a researcher, I can say that it is hard for experts to identify bubbles in advance.
Weights matter when interpreting facts because debating the correct weights opens a new dimension to the discussion. When arguing with somebody who attaches radically different weights to facts than you do, having the important facts may not be enough to convince somebody. Communicating effectively, not just analysing correctly, turns facts into wisdom and action.
Facts matter but a collection of facts rarely tells a simple story. It is not as though any one analyst can look at the Toronto residential market and say that “the price bubble that will end on Thursday and will be followed by 3 years of decline”. Previous posts have noted that the not all data sources are equally important nor are they perfectly precise. Both of these reasons explain why good analysts attach weights to facts to measure their importance.
Thinking about the weight which should be attached to each fact helps when making decisions because there will be evidence both for and against a decision. Regardless of what the decision is. Continue reading
Good decisions in the real estate industry are based on facts. Facts come from many sources (such as government, consultants, proprietary, …) but not all facts are equally important. Some facts would have a big effect if they changed while a change in other types of facts have little to no effect. This posting notes that some facts are unimportant because, even if they were to change, it is not clear whether the change is real or random. Randomness introduces another reason to attach weights to facts.
In part, the importance of a fact depends on how much you can rely on it. Facts as numbers are more reliable since (mostly) they are governed by the rules of statistics. Facts as words are more slippery since the reliability of the fact depends on who is saying it and on whether the words can mislead. Weighting facts is a way to recognize these considerations. Continue reading
Well, that was an interesting election. It also adds special significance to a comment made by a student in my Real Estate Market Analysis course: the job of an analyst seems really difficult. Or, more poetically, “Prediction is very difficult, especially if it’s about the future.” (Nils Bohr, supposedly).
When expectations differ from reality, somebody is surprised. In this election, the media have settled on the word “stunning”.
Being a long term investment, the real estate business is full of such stress. The outcome, and sometimes the best business strategy, depend on unknown market conditions. That is why market analysis is both difficult and unavoidable.
Election night in the US offers two memorable examples which should remind you of best practices. Continue reading
It is fashionable to say that economic ideas are wrong, at best, and, at worst, dangerously misleading. This fashion is not new. Since the most familiar pieces of the traditional economics model have survived for many decades, it is worth seeing how they appear in the world of real estate. Continue reading
Real estate projects are big, complicated and involve many actors. Therefore, success often depends on a legally binding contract to ensure that things get done with as few disputes as possible.
The first barrier to finding an answer is to describe the situation accurately: e.g.
- What is the source of uncertainty? If there is none then it is too easy to detect misbehaviour.
- are there only two outcomes (“success” and “failure”) or a continuum between really good to really bad?
A clear theory helps immensely.
The second puzzle is that changing the incentive changes the anticipated behaviour, which changes the outcome and the degree of risk. Think how the behaviour of a real estate agent might change if Continue reading