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The Fed’s job becomes more difficult


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Good morning. Yesterday, a reference to the film Caddyshack resulted in a lot of endorsement mail. Does that mean most of our readers grew up in the 80s or just have excellent taste? Send other market-applicable movie quotes to: robert.armstrong@ft.com AND ethan.wu@ft.com.

The time for compromise is here

For several months now, we have been complaining about the confusing, contradictory or dubious economic data coming out of the US economy. But recent reports, in a refreshing change, have mostly sung from the same anthem.

Wednesday’s CPI numbers were, on balance, encouraging. A second consecutive month of sheltered inflation declines was particularly welcome. Yesterday’s producer price index was also good. Year over year, core PPI has plunged 10% to 3% in 13 months. “The data on peak inflation continues to be processed,” says Don Rissmiller of Strategas. At the same time, an increase in jobless claims this year adds evidence that the tight job market is weakening. Put together, we have an economy that is slowing down and disinflating.

The graph below illustrates this. It shows smooth data for jobless claims (dark blue), core PPI (pink), and trimmed average CPI (light blue), a measure that excludes the warmest 8% and coldest 8% of the CPI sub-components. Jobless claims are rising, PPI is falling fast, and reduced CPI is following, but slowly:

For a year and a half, the Fed has struggled to make real-time monetary policy decisions using retrospective data. But it had something more: the economy was obviously too hot. Both parts of his dual mandate (price stability and employment) pointed in the direction of tightening. Now, inevitably, the dual mandate is coming into conflict again. We wrote this in July 2022:

In one sense, the Fed’s task is now easy. Inflation is very high and unemployment is very low. What it needs to do — raise rates, fast — is clear. But imagine a scenario where inflation is still too high, say 5%, and falling. At the same time, imagine that unemployment is higher, let’s say it’s approaching 5% again, and rising. What does the Fed do then?

Things are better now than we imagined then. Headline inflation is actually 5% and falling, but the unemployment rate is still only 3.4%. It’s entirely possible that the tightening done so far – 500 basis points of rate hikes, $400 billion in asset run-offs and some bank failures, to boot – is enough to control inflation without much higher unemployment. . The soft landing dream, to our surprise, remains alive.

But even in an optimistic scenario, inflation will take many months to reach anything resembling 2%. Meanwhile, the economy, while relatively strong, is out of balance. It is almost entirely dependent on the US consumer. If the labor market continues to weaken, growth could decline rapidly. And at the peak of a tightening cycle, we should expect more things to break down, making the economic picture worse.

Tough choices are coming for the Fed. A June rate break seems sensible, but the real question is how long to wait before a cut. Mr Futures Market is betting it won’t be long: a 25 basis point cut in September and three by the end of the year. Here Unhedged is still divided. Rob is inclined to say that the Fed will “hold us up longer” in a recession. Ethan thinks the economic deceleration later this year will force some cuts. In a matter of months, our split could very well be mirrored at the Fed. (Ethan Wu)

Uber versus Airbnb

Uber and Airbnb are companies with nearly identical business models built around different assets. Both operate global marketplaces where owner/operators can lease an asset to a customer. In one case, the asset is a car; in the other, a house. Both companies make money by charging the vendor a fee for network usage.

The similarity of the two assets is clearly evidenced by the fact that their values ​​are quite similar and they move together. Here is the business value of the two:

Line chart of firm value (market cap + net debt), $bn showing Similar

However, there is something profoundly different between Uber and Airbnb. One of them makes money and the other doesn’t.

Regular readers will remember that we recently discussed that the right way to think about Uber’s profitability is in terms of what we call true free cash flow: operating cash flow, less capital expenditures, and stock-based compensation (the failure to include stock compensation in any profitability measure is, everywhere and always, A dirty trick). Here is the true quarterly free cash flow of the two companies:

Real Cash Flow (Cash from Operations - Capital Expenses - Stock-Based Compensation) Bar Chart, Quarterly, Millions of Dollars showing Different

Airbnb generated $2.8 billion in free real money over the past four quarters, a revenue margin of more than 30%. This is a very profitable business! In the same period, Uber burned through more than $900 million in cash. Given the similarity of business models, what explains this? I don’t know for sure, but I have a tentative theory that has to do with the fundamental differences between a car and a house.

With companies using a market model (“network”, “platform”), it has been traditional to link profitability with scale. There is a phase during network construction where the business is loss making, but as it reaches a certain size, costs stabilize and money starts flowing. But given that Uber’s revenue, at $33 billion, is four times that of Airbnb, it’s hard to argue that scale explains the difference here.

A closely related, somewhat more compelling theory is that Uber, whatever its size, has decided to invest more aggressively than Airbnb, sacrificing profits now for profits later. In other words, Uber could be profitable at its current scale, but it chooses not to be. It’s true that Uber is growing revenue faster than Airbnb (58% in the past 12 months, versus 32%). It is also true that Uber is adding new services (delivery, freight). There may be some truth to this theory, but I doubt that’s the whole story.

What makes me question is the big difference between the gross profit margins of the two companies:

Quarterly Gross Profit Margin Bar Chart, % Showing Different (II)

For both, revenue is commission charged to the owner/manager of the asset. That’s what Uber He says enters cost of revenue (i.e. costs subtracted from revenue to arrive at gross profit):

Cost of revenues, excluding depreciation and amortization, consists primarily of certain insurance costs related to our mobility and delivery offerings, credit card processing fees, bank fees, data center and network charges, mobile device and service charges, costs incurred with carriers for Uber Freight Services, fare chargeback amounts, and other credit card losses.

AND Here it’s Airbnb:

Cost of revenue includes payment processing costs, including merchant fees and chargebacks, costs associated with third-party data centers used to host our platform, and depreciation of internally developed software and acquired technology .

One difference here is that Airbnb includes technology depreciation on the cost-of-revenue line, while Uber puts it on a different line further down the income statement. But that should make its gross margins higher than Airbnb’s, not lower.

Another, perhaps more important, difference is that Uber reports insurance costs right away. This raises a crucial point: you can’t bring down a house, at least not without some serious effort. I am guess that the insurance costs per unit of Uber’s business income are much higher than those of Airbnb and that these higher costs are almost completely variable, i.e. increase with revenue (whether these insurance costs are borne directly by Uber or the owner of the asset/operators, who then have to be compensated, is irrelevant).

I still have a lot of work to do on these two fascinating companies; insurance could be a red herring. What is clear is that Uber’s cost of goods includes high and variable costs that Airbnb’s do not. I look forward to hearing from readers who know more. (Armstrong)

A good read

Steven Kelly pushes back on the technology/social media theory of bank runs.

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