Headline Crimes and Misdemeanors
If you spend time skimming financial Twitter, there appears to be a great deal of effort spent exposing chart crimes. This makes sense, in that, if our experience can be extrapolated broadly, there is insatiable demand for the consumption of chart crime-related content. For more on chart crimes, this is a great blog post.
Bloomberg ran a fairly ambitious headline this week about housing affordability, which contained, at the very least, a chart misdemeanor. In it, they compare the average rent of a 2 BR apartment to the BLS’s 2019 median wage for various metropolitan areas (MSAs), ultimately claiming that Orlando is now less “affordable” than San Francisco.
We can get into whether it’s appropriate to compare a median to an average (it’s probably not terrible, in this particular case), but the bigger issue at hand in this chart crime is that the data behind it lacks enough precision and granularity to support its ambitious claims.
That is, in order to distill “median wages” into something consistently measurable, BLS excludes all sorts of earned income, such as bonuses and self-employment earnings, that are both meaningful and differentiated between regions. Similarly, comparing the cost to rent a 2 BR apartment is completely meaningless without a sense of the housing stock composition of each city.
If a chart crime occurs when an author manipulates data to mislead a reader, then a headline crime occurs when an author uses weak or inappropriately imprecise data to make an extremely strong statement.
Speaking of headline crimes, here’s CNBC quoting Zonda data to tell you that certain “home renovations WILL give you the greatest returns” (emphasis added). Apparently, garage door replacements return 94% of money spent in value. The comments section on the LNKD post where I found this seems to take the headline completely at face value. Let’s think about where this data comes from, however.
Big claims require big evidence. Point estimates of value based on limited visible data require REALLY big evidence. How many homes across the country do we think sold within months of a garage door replacement? How many would we need to fully disentangle the impact of that garage door from the impact of geography, time, home characteristics, and random statistical noise that differentiates these various home sales? Also, what was the door like before we fixed it? Was it cracked in half and hanging from one rail, or was it just ugly? Both scenarios cost the same amount to fix, but one offers significantly higher return on investment.
Rest of Resi
Here’s a capital headline crime claiming that a one-month blip in a notoriously noisy number during a time of unprecedented volatility somehow means that the very nature of work is now different forever.
Here’s a deep dive on the lumber shortage. We wrote a note many months ago about why the supply curve in real estate is sticky, leading to fundamental booms and busts whenever demand changes from trend. The lumber story here is a microcosm of the same phenomenon. We have a surfeit of trees and a huge price signal for millers to increase processing capacity, and the time and expense of installing said capacity is not nearly as prohibitive as, say, building an office tower in San Francisco or a molybdenum mine in Colorado.
The problem is, how does a fragmented and relatively thinly capitalized timber industry take the risk of investing millions of dollars in new capacity when they don’t know how long the high prices will persist? Here’s today’s lumber futures curve on the Chicago Mercantile Exchange: