‘Town Car’ Vs ‘NYC Cab’ Strategists
By Peter Tchir of Academy Securities
I cannot remember a time when I’ve had so many interesting discussions with so many smart people where there is so little overall agreement. We all agree on some things and are in complete disagreement on other things. That in itself is unusual, as narratives are generally more coherent and consistent than that. Even stranger is that what we agree and disagree on is all over the map. It’s like a bad Rorschach Test.
Not only am I trying to refine and update my view (as well as second guess myself on all of my views), but I’m also really trying to figure out how so many people that I respect and listen to are so all over the map.
Which brings me to the “Town Car vs NYC Cab” analogy.
Town Car vs NYC Cab
When you order a town car (or even an upscale Uber), you have certain expectations. Timely arrival. Probably clean. Air conditioned. Likely a fast (they are paid by the trip), but reasonably smooth ride.
When you get into a NYC cab, you hope for clean, but know there may only be a slight chance of that. If it is a hot day and the windows are up, you have at least the possibility of air conditioning (I would avoid taxis with rolled down windows on hot days, because there is almost no good explanation for that, and lots of bad ones).
From there, it is all about the ride, but more often than not, you are going to get some version of hit the gas, slam the brakes, hit the gas, swerve, brake hard, pedal to the metal, jerk the wheel, brake hard, swear at pedestrians, gas it into a yellow light, only to decide at the last minute to come to a screeching halt. It isn’t as bad as the occasional time you get a driver who uses both feet, but it’s pretty bad and pretty standard.
Right now, there are those of us who are analyzing the economy as though it is a town car and others who are viewing it as a NYC cab ride.
I don’t know which one is correct. I’m in the NYC cab camp, but it is important to understand what this analogy means for analysts and their outlooks.
Models, rate of change, historical comparisons.
For those sitting in the town car, models are extremely valid. Rates of change follow patterns and the data is expected to be “smooth” over time. There is a lot that can be learned from history since the same models, smoothness, and reaction functions exist. This can range from outlooks on jobs (optimistic), inflation (fears about the ability to lower it), and recession odds.
NYC cab riders are lurching about. The ability to get large jumps and rapid directional changes is part of the thought process. Record drops in NY State manufacturing aren’t surprising. Ongoing strength in jobs is surprising. Inflation could jump to 10% or we could be discussing deflation by the end of the year (I’m more concerned about this than I am about runaway inflation). History isn’t as applicable because the starting conditions have never been like this. Massive stimulus, supply shocks, etc., don’t lend themselves well to following historical patterns. We’ve never had significant QT and that is about to start.
Past actions have worked versus past actions keep priming the pump.
Some of this is redundant with the prior bullet point, but those riding in the town car tend to believe that prior policy was largely good. It promotes a faith in policy, which does make it easier to lean on traditional models and historical examples.
Those of us stuck in NYC cab mode see us lurching from one crisis to the next. We put on the gas, slam on the brakes, and hope for the best. For some, this balances out, and we get to the destination in one piece and in a timely fashion. For others, we can’t help but see a series of crises, where each “new” crisis follows the prior “crisis” more closely. The cycles of highs and lows are accelerating. We are basically cringing in the back seat waiting for the brakes to fail, for a tire to pop when it hits a curb, or to rear-end someone and be stuck dealing with that mess (probably too pessimistic, but it does appeal to me).
Continuous versus dislocated. Differential versus non-differential.
This is more at the extreme of both sides, but are there “triggers” that once pulled, cannot easily be fixed? Do economies and people behave in smooth, continuous patterns, which can be adjusted easily? Or are they lurching about, creating the risk of something altering course so much that it is difficult to get back to “normal”? The U.S. blocking Russia’s Central Bank from accessing their dollars may have been a necessary step in what we were doing to attempt to hurt Russia, but I don’t think any country that doesn’t behave like we would want them to will forget that action. It changes things in a way that makes it difficult to go back. If everything continues, we can nudge things along and correct things sooner rather than later. If things have the ability to “jump” and be dislocated, the effects of policy mistakes are that much greater and more difficult to fix. I think the time it took for the last stimulus bill to get approved was problematic – had it been done in February 2020, it made sense, but by the time it got passed, the “problems” it was fixing had largely dissipated.
Once I started thinking about it from this perspective, the arguments started making a lot more sense. It has become much easier for me to start to understand the views more clearly. I don’t necessarily agree with others (nor they with me), but at least I’m seeing how we might be getting there within our own logical frameworks.
Town car strategists will have smoother data and expect longer cycles. Policy will tend to work as expected in their models. Surprises are rare and are more “one-off” than indicative of anything major occurring.
NYC cab strategists are looking for faster shifts in the data. U-turns are possible. Traditional policies don’t work as smoothly as projected, and unusual policies (like QT) create unexpected problems.
I know I’ve drifted into the NYC cab side of the spectrum (anyone who has driven with me would probably agree that this is both figurative and literal). That concerns me and I may have to re-think that, but I’m stuck on a few things:
Wealth destruction, especially in crypto and disruptive companies, is going to hit the economy faster than “traditional” models predict because these things didn’t exist in prior times. Add in the evidence of a slowing housing market and we have a negative wealth effect that I think is unlike others we’ve seen.
Inventory build. I see inventory build as sowing the seeds for deflation. Not only will pricing power diminish, but manufacturing will slow. Chinese exports have slowed and I’m told by some that it is because of production problems. For me, it seems to fit the narrative that we’ve overbought and need to cut back, so manufacturing (globally) will be hurt. This inventory build is occurring in the midst of wealth destruction and rate hikes. However, maybe I’m too negative on this and things will take much longer to play out than I suspect.
Monetary Policy Fixes Everything. This probably scares me the most. It is one reason why (for the past few weeks) I’ve been advocating for buying puts and calls because it has become accepted wisdom. The “bad news” is “good” can only last so long (I think). When you go back to the GFC, monetary policy was quick to respond, yet it didn’t stop the overall decline in markets until almost two years after the policies were enacted. Yes, there were some strong rallies between the summer of 2007 and 2009, but it took a long time to bottom. Yes, the central bankers have learned to act faster and more aggressively (like they did when COVID hit), which is good, but is it sufficient?
I have no idea which side is right, but I’ve found that since I started to think about people as being in town cars vs NYC cabs, I’m having a better time understanding their views, which is a big step towards making me smarter and understanding all the possible scenarios better.
In the meantime, may all your cabs, Ubers, and Lyfts be clean, air-conditioned, and with safe drivers!
Fri, 08/19/2022 – 10:32