Sep 27, 2023 Macro

Learning the hard way

Debates about a “soft landing” versus a U.S. recession rather miss some of the harder questions investors should really be concerned about.

Björn Jesch

Björn Jesch

Global Chief Investment Officer
  • We tend to see the strength of the U.S. economy in the year to date, which has surprised many observers including us, as likely to prove fleeting.
  • That, in turn, informs our caution for risky assets such as equities.
  • But we are constantly testing the assumptions underpinning this with, in light of incoming evidence.

Like a lot of nonsense you have been reading in recent years, that debate starts with a rough, often quite sensible rule of a thumb for economic and financial forecasting. It is usually a good idea to be skeptical of stories driving markets that sound too good to be true. Monetary policy lowers inflationary pressures by trying to impede growth through various channels, from home mortgages making construction of new houses less appealing, to loans for business investments and your very own credit card charges. More subtly, though, it also can produce winners. For example, those credit card charges are someone else’s income, ultimately benefitting some households. The bulk of household savings is held richer and older ones, which may have lower propensities to consume the additional income form their savings.

Working through all these different channels and finding proxies that served econometric modelers well in the past is a dark art that takes years, if not decades to master. Skilled practitioners learn how to take shortcuts that have worked in practice, even if they make little sense in theory.

That said, experienced practitioners with a solid theoretical foundation will likely know when to pause and reconsider the behavioral assumptions behind their models. Knowing when to make that call is often extremely tricky, even conceptually in the philosophy of science.[1] When is it time to reconsider your worldview in light of the evidence in order to better understand afterwards?

This general question also applies to the world of finance. Many practitioners and market participants ask themselves far too rarely when everything seems as it should be at the surface. Until things turn out differently than “everyone” thinks. That is part of the underlying reason why conventional wisdom in financial markets so often gets stuff wrong, producing nonsense. Insidiously, if enough practitioners make the same type of error on the same question, they have every reason to believe that there is safety in numbers. Making the usual cognitive lapses in the process we have previously outlined[2]

These people have convinced themselves – and others – that “soft landings” are “empirically” hard to pull off and therefore, unlikely in 2023 and 2024. “Common sense” often contributes.[3] Intuitively, it seems exceedingly hard for the Fed to achieve a “soft landing.” Would that not require the Fed – or some other central bank to get everything exactly right, even in the face of badly timed shocks to the supply side – from oil prices to wars and global supply chains? Intuitively, it seems like a safe assumption that times of tranquility, such as the era of the great moderation until the Global Financial Crisis of 2008, tend to have to do with good luck as much as with superior policy making wizardry and may even store up problems for later when the luck runs out.[4]

We certainly have some sympathy with the view central bankers are never quite as omniscient as some of their leaders or public acolytes like to think.[5] However, depending on how you define them and categorize individual cycles, soft landings are not all that rare in recent U.S. economic and monetary history.[6] A moment of thought suggests why. If surprises – whether on the supply or in terms of behavioral changes or model miscalibrations­ are random, that would suggest that luck – and ignorance ­ are going to be helpful roughly as often as harmful from the perspective of central bankers.

Such thinking can be extremely valuable. Many investors may not particularly care where they are wrong in terms of their explanations. They do care, though, about when and how the market as a whole might be wrong. Knowing about the pitfalls of common sense and intuitive reasoning of most other participants is a powerful tool for doing so.

 During periods of heightened underlying uncertainty, investors and business alike tend to react instinctively. This can create inefficiencies and forecasting errors. As the economist Andrew Lo likes to put it: “Financial markets are driven by our interactions as we behave, learn and adapt to each other, and to the social, cultural, political, economic, and natural environments in which we live.”[7]

Such collective learning works well, when conditions are stable. But if and when the environment is hit by sudden shocks, or a series of shocks, from a global pandemic and a war to an inflation surge not seen for decades, adoptive expectations can be very different from what looks rational with the benefit of hindsight. Add measurement issues and previously reliable correlations, for example between consumer sentiment and actual spending breaking down, and the fog is currently unusually thick.[8] In inflationary times, after all, it is not that unusual for behavior patterns to change, potentially interacting in ways you cannot guess from just looking at historical data.

This is when a solid theoretical grounding and knowledge of economic history comes in handy. It turns out that during inflationary episodes, a decoupling between investment-driven economic momentum on the one hand, and financial markets and other sentiment indicators on the other, is neither all that unusual nor theoretically implausible.[9]

Nevertheless, our house view remains cautious, mainly given the headwinds currently building for U.S. consumers. Signs of labor market weakening come on top of a whole host of drags looming in coming months, from student debt repayments increases and an unfolding autoworkers strike, to higher energy prices. Meanwhile, we tend to see the strength of the U.S. economy in the year to date, which has surprised many observers including us, as likely to prove fleeting.[10] It reflected several factors now likely to fade. In particular, issues such as the timing of tax payments, and higher than expected deficits, supported consumption in the first half. Along with upside surprises in volatile business investments, such as automotives and aircraft, as well as rigid inventories in the second quarter, this suggests to us that upside revisions to economic output for 2023 will come at the expense of weaker growth heading into the new year. That, in turn, informs our caution for risky assets such as equities.

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1. Indeed, the following should be mandatory reading for any financial market, data science or artificial intelligence professional using data to draw “empirical” inferences for “the future”: Goodman, N. (1954) “Fact, Fiction, & Forecast”, Harvard University Press.

2. To find out whether someone is making sense, we recently suggested a newfangled way to identify charlatans in the age of AI, first suggested by Nassim Taleb almost 20 years ago. Simply ask yourself whether what you are reading might have been written by a chatbot, and whether that chatbot might be hallucinating – drawing conclusions based on patterns in the data of limited predictive value for the future. See section 2 of Investment Traffic Lights (dws.com)

3. Common sense in terms of what most people, even highly intelligent ones, would naturally be inclined to do, without the necessary training or mindware in terms of rational thought appropriate for the problem in question. See:  Stanovich, K. (2010) “What Intelligence Tests Miss: The Psychology of Rational Thought”, Yale University Press, esp. pp. 70 – 86.

4. See, from 2008, for a careful look at the actual evidence at the time: The Great Moderation: Good Luck, Good Policy, or Less Oil Dependence? (clevelandfed.org)

5. Even with the benefit of hindsight, the “soft landing” of 1994 to 1995 still leaves scope for healthy debates, including among Fed staffers. How and how much did it contribute to financial turbulences in other parts of the world or the epic U.S. equity market bubble that followed? See Fed’s 1994 rate aggressiveness led to emerging-market turmoil; is this time different? - Dallasfed.org. On the latter, namely the link and between US asset bubbles, a good summary on why this is probably quite a bit more complicated than it may seem to the uninitiated is: The Effects of Monetary Policy on Stock Market Bubbles: Some Evidence (nber.org)

6. Landings, Soft and Hard: The Federal Reserve, 1965–2022 (aeaweb.org)

7. Lo, Andrew (2019) Adaptive Markets: Financial Evolution at the Speed of Thought, Princeton Univers. Press, 2nd edition, p. 188

8. The widely reported breakdown between consumer sentiment and – so far – much higher consumer spending since the start of the pandemic might be an early case in point. For a summary, see: The pandemic has broken a closely followed survey of sentiment (economist.com); also see: Opinion | ‘I’m OK, but Things Are Terrible’ - The New York Times (nytimes.com)

9. Akerlof, G. and Shiller, R. (2009) “Animal Spirits: How human psychology drives the economy, and why it matters for global capitalism”, Princeton University Press, esp. pp. 142-146.

10. An extremely handy tool to keep a close eye on is the GDPNow forecasting model by the Atlanta Fed. Available at: GDPNow - FRBA (atlantafed.org)

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