## Monday, September 14, 2020

### How To Misuse Statistics, Coronavirus and Real Estate

The coronavirus pandemic has been a fascinating case study on how statistics can be used to mislead people. Below I'll show a few examples and connect it with real estate. As a disclaimer, none of this discussion is meant to minimize the tragedy that has been caused by coronavirus, it's just a critique of how the media has been using statistics in a misleading way.

## Context Matters When Discussing Statistics

Here are two headlines just from today on CNN:

Let's look at the first headline / article. The writer / editor is clearly trying to generate drama by throwing in the 194,000 number. Most people see 194,000 and they think, "whoa, that is a ton of people, coronavirus is killing people like crazy..." They are, of course, partially right, 194,000 is a lot of people and coronavirus is killing people. However, the headline and even body of the article are missing a lot of the context around that number. Here are just a couple of questions that you should ask to really figure out what this number means. One, over what time period is the 194,000? Is this over two months, three months, nine months? Seems like an important piece of info. Two, what's the typical age of these people dying? Also seems important. I think any reasonable person can agree that an 85-year-old dying in a nursing home from coronavirus is different from a perfectly healthy 20-year-old marathon runner. Three, how many of the 194,000 died OF coronavirus vs WITH coronavirus? I have a brother that's a doctor in a department that treats very old sickly people and something he's told me is a good portion of the patients that die in his department don't have a clear cause of death. Many are so old and sickly that there's any number of things someone could claim they died of. This is an issue that's largely ignored by the media when discussing coronavirus deaths. Four, related to Three, how many of those people would have died from something other than coronavirus, like the flu? The point here is, are these 194,000 causing excess deaths over that period of time, or, put another way, how many more deaths has coronavirus caused over that period of time than you would typically expect based on historical data?

More likely than not, the answers to those four questions would make the 194,000 number less scary. The context matters.

The second headline / article is more or less the same thing. Throw out a big number that sounds scary. Again, context matters. How many of these 45,000 are really sick? How many are false positives? How many have been hospitalized? How many have died? In these cities with the colleges, has there been much spreading of coronavirus off-campus? Have deaths spiked in the cities? Etc... Again, answering these contextual questions would likely give us a better idea of how we should digest the number and I suspect it would make the number seem less scary.

This same principle applies to real estate. Whenever someone gives you a statistic about a market's performance, a property's historical performance, an asset class's historical performance, etc..., you need to be aware of the context surrounding that statement. For example, someone might tell you Submarket X is a great submarket. The demand it's been experiencing is off the charts. In fact, net absorption in the market has been 100k SF / year. You might be tempted to buy a property with a lease-up play in mind based on that info. However, what if I told you that developers have been building at a pace of 200k SF / year, implying vacancy has actually been going up by 100k SF / year. What if there was 500k SF scheduled to deliver over the next 2 years as well? Maybe the 100k SF / year of net absorption isn't that great after all. Make sure you understand the context.

## Misidentifying Underlying Driving Forces of Statistics

This is the classic issue that can be exemplified with the following thought process: "Rain dancing at the beginning of April make the Gods happy and brings rain in the following months..." I think we all know at this point that it's not actually the rain dance that brings rain, it's just the natural cycle created by how the Earth works. Even though we understand this silly example, we still fall victim to this issue of confusing underlying causation when statistics are presented.

The media makes this exact mistake repeatedly with the coronavirus. Here's a CNN headline / article from a few weeks ago:

The headline / article suggest students gathering at universities is leading to massive outbreaks and leading to coronavirus spreading like crazy. I.e., people gathering together, even with very strict protocols, is the causation for all of these positive tests. Very scary stuff. However, no where in the article does it mention the fact that every kid at these colleges were getting tested for coronavirus like crazy at the beginning of their semesters (late August, early September every student had to be tested to even go on campus and then once they're on campus there is extremely tight testing for anyone with symptoms and a tracing system). This is an important point. Most college-aged people are asymptomatic, or at most have very mild symptoms and are likely to not get tested. This begs the question, is it really being on college campuses that's driving the increase in cases, or are kids on college campuses just being tested at a much higher rate which is driving case counts. If the latter is true, then colleges aren't necessarily helping spread coronavirus and it might just be that what was always the case (college age kids had a lot of cornoavirus cases) is finally being reflected in official stats.

The same principle applies in real estate. Maybe you're thinking of buying a property and the submarket's two-year historical performance has been great. Vacancy has stayed low, there's been consistent rent growth, etc... At first glance maybe you think it has great demand drivers that will continue into the future. Then maybe you start digging in a bit more. You look at demographic projections and see population, median income and median home price is expected to decline. Well that's not a sign of a healthy submarket. Then you dig in more and figure out that prior to two years ago the submarket actually had increasing vacancy and declining rent rates and that the only reason things started improving two years ago is one of the large buildings in the market was demolished for a new development project, i.e., there was a one-time reduction in supply that caused a bunch of demand in other buildings. Clearly, the underlying demand driver that started two years ago was a one-time reduction in supply, which is not sustainable.

## Conclusion

Don't just trust stats that the media tells you and don't just take stats that brokers, colleagues, etc... give you at face value. Be skeptical. Dig in to figure out the context. Reason out in your own mind what the true underlying causations are.