system maps

Thoughts on Inflation

I am far from a macroeconomics expert. But I do think that macroeconomics provides a valuable perspective on the world, so occasionally I like to take a step back and try understand some of the macroeconomic dynamics at play.

One topic that’s top of mind for many folks today is inflation. There are two common comments I hear about inflation these days. One is that – prior to the past few months – inflation has been surprisingly low for an extended period of time. Between the government bailouts, the quantitative easing of the Fed, and the increasing amounts of debt in the economy, many folks expected the rate of inflation to be much higher than what has actually occurred.

The second comment is that now things are finally going to change. With the further massive stimulus during COVID, the beginning of the recovery therefrom, and potentially two additional massive infrastructure bills, the risk of runaway inflation is at an all time high.


Let’s start with the first comment. Up until very recently, why haven’t we seen much inflation?

Inflation occurs when prices go up. So let’s look at prices. Below is an old chart from the American Enterprise Institute from 2020:

The first thing to notice is that the amount of inflation strongly depends upon what you’re looking at. Generally speaking, things that have benefited significantly from technology – either because they can be manufactured more efficiently (i.e. TVs) or can scale at near marginal cost (i.e. software, Netflix, etc.) – or from globalization have actually gone down in price, while things that are still require local human labor continue to increase in price. (An interesting exception on the chart is college textbooks). The second thing to notice is that, in aggregate, there still has been inflation of around 2.2% annually on average. So not only has there been inflation, but it varies widely by category. Measures like the Consumer Price Index can mask this.

To a first order approximation, prices are related to the ratio of supply and demand. As I mentioned above, the marginal cost to supply an additional digital good is virtually zero. I don’t have the data, but I’d also assume that there has also been a significant shift by both consumers and businesses to spend more money on software and digital services.

This could partially explain the relatively low rate of inflation. One the one hand, a product or service with nearly infinite supply (software, streaming video, videogames, etc.) can accommodate nearly any increase in demand without triggering a price increase. On the other hand, any money spent on these things is money not spent on things that do have a marginal cost to supply; this controls demand (and thus prices) for those items. Prologue

This explains why we haven’t seen that much inflation over the past two decades. What about moving forward? We’ve recently seen a significant uptick in inflation – surely all of the public and private debt-fueled spending and quantitative easing is catching up with us, right? Isn’t this just the beginning of massive hyperinflation?

I’m not so sure. It is true that we’ve seen a recent spike in inflation. But this seems to me like it may be short lived.

Here’s my reasoning: when COVID hit, there were a few effects that conspired to increase prices. On the demand side, because people were locked down, demand for services decreased while demand for durable goods (TVs, housing, etc.) increased.

At the exact same time, due both to some people not working and significant changes in demand for some items (like masks and other PPE), supply chains faced significant disruptions. This limited the supply of these exact same durable goods. Higher demand and lower supply equals higher prices. So we see inflation.

However, it seems to me that these same dynamics could soon lead to the opposite effect. Because people “pulled forward” their demand for things like TVs, exercise equipment, and home renovations, there is likely to be weakened demand for those things in the mid-term. Simultaneously, as supply chains get unjammed, foreign goods are likely to flood the market with additional supply. More supply and less demand? Leads to lower prices (or at least stagnating ones).

And there’s more. During Covid, employers also “pulled forward” investments in technology to support remote work. These investments are improving productivity. It is true that labor shortages in some areas are creating wage increases. However, if productivity increases faster than wages and other costs remain steady, then the the per-unit cost of production goes down. (e.g. if I have to pay you $60/hr instead of $50/hr but the number of TVs I can produce an hour goes from 100 to 500, my cost-per-TV has still gone down).

As foreign goods comes back into the market, domestic producers will want to try to keep the market share they obtained during the pandemic. Whereas prior to the pandemic they might have been beat out on cost, because of the reduction in their unit cost of production described above, they will have more ability to compete on cost than before, further driving down the price of goods.

Blue: Inflationary Dynamics. Brown: 2nd-Order Deflationary Ones.


I thus think it’s reasonable to expect that we see a significant reduction in inflation – or perhaps even mild deflation after this transitory inflation spike. We have a situation where technology is reducing the unit cost of production of goods while likely reducing the demand for labor (thus lowering wages and thus consumer spending), all set against a backdrop of significant debt. Unless that debt is invested in such a way as to produce cashflows adequate to service that debt and reinvest (which, in aggregate, I doubt), then it simply pulls forward demand to the present, thus limiting demand in the future. Lower demand and cheaper, more abundant supply leads to lower prices and disinflation.

While there are scenarios that could potentially lead to hyperinflation (e.g. the Fed being given authority to spend or a decision to intentionally debase the currency to reduce debts), I think the more likely scenario is transitory inflation followed by disinflation or even deflation. From a portfolio perspective, this would suggest positioning oneself for an expectation of mid-term (dis/de)flation (e.g. cash, defensive equities, long-duration treasuries) with a hedge to try to protect against extreme hyper inflation (gold, real estate, crypto, equity puts, etc.)

As I mentioned at the outset, I’m no expert in this space. But this is my current thinking. Let me know where I may be wrong.

The Disney Synergy Map

Those of you who know me well know I love maps, diagrams, and systems. I also love when people combine “left-brain” and “right-brain” thinking. This is one of the reasons I love architecture: it’s engineering and art combined.

Walt Disney was a genius at this. He is obviously known for his masterful animation, storytelling, and his vision for Disneyland. But what many not appreciate is the incredible number of technical advances that he and his team pioneered to enable such art to be created. (If you haven’t seen it and are interested, the American Experience documentary on his life is fascinating).

Given this, imagine my delight when I first found this diagram that Walt created in 1957 to lay out Disney’s strategy. It was known as the “Synergy Map”:

There are so many reasons why I love this. The scope of the vision. The understanding of how the pieces fit into the whole. The brilliance of the feedback loops. And – in pure Disney Magic – the characters running around the map.

I’ve had this saved on my computer for several years now and recently had a copy printed and framed on my wall. It inspires me every time I look at it.

Systems of Poverty

Several years ago, I participated in the AdvancingCities Initiative run by JP Morgan Chase – cities and/or regional groups were to propose projects that addressed one or more of several key ‘focus areas’ for the initiative, all generally based around improving the major cities within the region. As I am based in St. Louis, I got involved there.

E2E: Education to Employment

My particular proposal was the development of an ISA-financed “Education to Employment” pathway where various stakeholders (i.e. government, employers, schools and non-profits) would coordinate their activities to provide educational and other support services needed to help folks from low-income backgrounds get living-wage jobs. These investments would be financed by an ISA, where the student would start paying back a percentage of their income once they started earning over a threshold amount. The proceeds from this payment would then be divided across the various organizations within the ecosystem according to an agreed upon formula.

It was my hope that this would provide an economically sustainable way to continually reinvest in our communities.

Mapping the System

My proposal wasn’t chosen and we ended up going in a different direction. But in the course of those discussions I learned a lot about the causes of poverty and the feedback loops that often make it very difficult both to escape individually and/or address systemically.

When faced with complex problems like this, one of the things I like to do for my own sake is to develop what I call “causal maps”: basically simple digrams that map out the cause-effect dynamics at play.

The way to read the maps are simple – it’s mainly [Cause] –> [Effect]. I find that doing this often helps me distill a lot of complexity down into something that I can understand, while also highlighting the interconnected nature of the problem.

Draft effect map of poverty
Draft Cause-effect map of poverty

Above is an example of a simple one I created to understand the dynamics of poverty. Now I certainly don’t claim that this is complete or that I am any type of expert. I am mainly sharing in case others find it interesting and to encourage trying this mapping approach and see if it works for them.