Weekly Thoughts: Taxi Trouble, R&D Spending and Juking the Stats
Here are three things that caught our eye this week:
This week, we learned about the fascinating free-market supply and demand dynamics driving disruption in the New York City taxi industry. Historically, to legally operate a NYC taxi, each vehicle must have its own medallion, which is a tightly regulated, city-issued permit. The owners of these permits then rent their vehicles out to groups of operators, who perform the actual taxi driver service. These drivers pay the medallion owners a fixed daily fee, and profit from the difference they make in cab fares and gratuities. Under this oligopolistic structure, NYC’s taxi industry has thrived, medallion values have surged, and the yellow taxi-cab has become as emblematic of the Big Apple as the Empire State Building.
Given the attractive historical performance, ability to rely on steady, set income streams, and low interest rate environment, many medallion owners have built sizable portfolios by liberally using leverage. From an owner’s perspective, it was a virtuous cycle. As long as they made enough money to cover debt payments – and as long as medallion values continued to increase – they could simply refinance their loans to subsidize personal spending habits or make additional investments.
As a result, some medallion owners expanded aggressively, and ownership became concentrated into a “Cabbie Cartel.” The de-facto leader of this group was Gene Friedman, the so-called “Taxi-King,” who at one point owned more than 900 medallions, which each reached a peak value of $1.3 million in April 2014 (making Friedman a paper billionaire).
As you might have already guessed, the virtuous cycle has turned vicious, as city regulators have allowed new competitors to enter the market, putting significant pressure on the traditional taxi-cab industry. Uber has been extremely aggressive in its expansion into NYC, and today, there are more Uber related vehicles than traditional taxi-cabs. Since peaking in June 2013, NYC taxi trips and farebox amounts have dropped 12% and 16% respectively. More critically to the medallion owners, Uber has also been actively recruiting taxi drivers, forcing medallion owners to drop the daily rates for which they rent their taxis to keep their cars in operation. The Street explains:
“Because of operating leverage, every incremental 10% drop in farebox revenue translates into roughly a 25% decline in medallion owner net income. Earnings for a typical owner-operator have already declined by approximately 24% since June 2013….. When taxi drivers bring in less revenue, the profit margin on the medallions decreases even more because of fixed costs, like payments on the medallion loan.”
The NYC medallion situation is a great reminder that, regardless of asset class, the “it’s different this time” or “that can’t happen” rationale is an ever-present psychological trapdoor in the investment world. The pattern of over leveraging investments based on the faulty practice of extrapolating seductive return streams into the foreseeable future has happened many, many times before. As we go forward with our investments, we hope that even if we fall victim to faulty investment theses, we have the good sense to avoid over leveraging ourselves in the process.
Economically speaking, its pretty straightforward that today’s investment will turn into tomorrow’s growth. For this reason, many analysts look to research and development spending trends as an indicator of the outlook for a particular country or economic region.
Historically in the United States, government did much of the heavy lifting from a R&D standpoint. Consequently, many of the revolutionary technologies we utilize today have their roots in decades old federal research studies. As Marc Kastner, a former dean of the School of Science at MIT, notes in a recent report he co-authored with other MIT faculty, federally funded research into the working of cells and early directional drilling technology have led overtime to a proliferation of sophisticated anti-cancer therapies and the fracking revolution respectively. Peter Diamandis expanded on this point in a recent blog post:
“Even Google probably wouldn’t be around had it not been for government funding. In 1994, NSF, DARPA and NASA funded the Digital Library Initiative to index and sort through the growing number of websites coming online. One of the six grants from the Digital Library Initiative went to two graduate students at Stanford — Larry Page and Sergey Brin — who would later commercialize their research and call it ‘Google.'”
Unfortunately, the problem with R&D spending is that by nature it involves an uncertain payoff and a certain risk of failure. As such, when fighting for space in the federal budget, basic research often draws the short straw, a dynamic that has caused a secular decline in government R&D spending since the late 60’s as shown in the chart below:
To compensate, the private sector has picked up the slack, with R&D spending topping 1.8% of GDP in the first quarter, a post World War II record. While the upward trend is clearly a reason for optimism, the allocation of this R&D spend is still subject to the same risk aversion. From a recent Bloomberg article on the topic:
“Back when IBM and AT&T had virtual monopolies, they spent lavishly on [R&D] without worrying about upstart rivals pressuring their margins. Today, with a more competitive market and more focus on short-term shareholder value, basic research is a much harder sell to the average chief executive. As a result, companies spend more of their R&D budget on enhancing existing technologies rather than discovering new ones. ‘It’s the difference between coming up with evolutionary products instead of revolutionary ones,’ says Robert Atkinson, president of the Information Technology and Innovation Foundation (ITIF), a Washington-based technology policy think tank.”
The key point is that the shift of the R&D burden from the state to the private sector risks abandoning projects whose scope or potential benefits might not fit in a traditional private investment framework. As Marc Kastner noted in the MIT report, innovations that create a public good (think clean air) create value that cannot be captured by an investor. Similarly, there are projects that involve such high risk or technological complexity (i.e. quantum computing or fusion energy) that their uncertainty renders them uneconomic, despite the dramatic impact success might have. Ultimately, if the private sector is responsible for the majority of R&D spending, it will be up to the markets to identify and support those companies that are willing to put short-termism aside and commit capital toward investments whose payoff, however great, may be some way off in the future.
Juking the Stats
We recently listened to a fascinating TED talk by Zoe Chance, a professor at the Yale School of Management, on the topic of addictive behavior. Professor Chance somewhat humorously chronicles her experience with a pedometer which, while a great tool for encouraging a more active lifestyle initially, eventually became an all consuming obsession requiring the submission of other parts of her life to the never ending accumulation of steps.
“When I was using the Striiv, I was doing 24,000 steps a day. You do the math. I am not a distance runner. And if you’re walking, the only way you can reach 24,000 steps a day is by not stopping. So that’s what I did. I would arrive at work, I would grab an article, anything I didn’t need a computer to do, and I would pace, down the corridor outside my office. I would come home and while I was eating, or reading, or eating and reading at the same time, or while my husband was trying to talk to me, I would be going in a circuit between the living room and the kitchen and the dining room and the living room and the kitchen and the dining room….
…I had become so neurotic that I was spending hours a day counting my steps and I found that even when I wasn’t moving, I was still counting. “
We completely empathize with Professor Chance’s experience because we have been there ourselves. As recent owners of a Fitbit, we understand completely the incentive to achieve the buzz-inducing 10,000 step mark, and to strive for those few extra steps in our Workweek Hustle challenges. We have even experienced the late night urge to run up and down the stairs a few times for good measure. That said, upon reflection, it occurs to us that by focusing so intently on our daily step count we sometimes lose focus on the nature of our original goal, namely to increase our overall fitness. While useful in some respects, step count tells us nothing about our progress with regards to strength, flexibility, aerobic capacity, balance, etc, and by concentrating exclusively on the easily quantifiable metric, we are tempted to ignore activities that might develop these other less measurable criteria.
This observation is representative of a larger issue related to the relevance of the metrics we use to evaluate behavior of all sorts. While we fully agree that what can be measured can be improved, we feel it is as important to make sure that what you measure is in fact directly linked to the outcome you desire. A recent New York Times article presented the issues as follows:
“The problem is this: The things we can measure are never exactly what we care about. Just trying to get a single, easy-to-measure number higher and higher (or lower and lower) doesn’t actually help us make the right choice. For this reason, the key question isn’t ‘What did I measure?’ but ‘What did I miss?'”
Any casual observer of earnings announcements, polling results, test scores or anyone who counts themselves a fan of HBO’s Baltimore focused drama, The Wire, knows that “juking the stats” is a time-honored way to present data in a favorable light. While we concede the point that it is easy to lie with statistics, we believe it is also important to recognize that the increasing use of unrepresentative metrics can incentivize sub-optimal behavior even for those with the best intentions.
The point is not that accumulating steps is a bad thing, nor that a pedometer is a poor tool for measuring those steps. Instead, the key is that steps on their own don’t tell you much about your overall wellness, which is a problem if one is focusing on this metric as an indicator of health. The world is becoming more quantified as the internet of things ensures that measurement of all life activities is increasingly possible. Going forward then, we’ll need to make sure we spend as much time thinking about defining our goals, as we do concentrating on actually hitting those targets.
Your Chenmark Capital Team