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American households are about to take a wild ride through the basics of global economic policy, thanks to their country’s Big Beautiful Leap Forward. Or the Great Leap Onshoreward, if you’d prefer.

This is being signaled very clearly by Thursday’s stock-market moves. Are stocks the economy? No. But they have direct effects on the capital costs of companies, who are the economy (especially during an ongoing project to strip the public sector of power). And stocks can provide a pretty good outlook of what investors expect.

Today, at least, investors see a big reckoning for the American consumer. For a while now, the American Pitch has been that if you sacrifice universal healthcare, you can buy cheap screens and nice clothes, and maybe dream of becoming very wealthy and powerful despite your worsening statistical chances. This deal used to involve homeownership, but that was ages ago (before 2008).

Now the White House’s narrow focus on bilateral trade balances threatens to end the rest of the Cheap Stuff party.

That will probably have broader economic implications. But first, let’s step back and look at the shares of companies that sell Stuff.

They’re tanking, predictably, because countries like Bangladesh, Cambodia, Indonesia, Sri Lanka, Thailand and Vietnam all face the biggest “reciprocal” tariff burdens, and are big exporters of consumer goods like textiles and electronic parts. We’ll call these the American Stuff Stocks:

As you can see above, the S&P 500’s biggest losers today include retailers like Ralph Lauren, the mega-Americana brand, and Deckers Outdoor, the maker of Uggs. About 35 per cent of RL’s suppliers are in China and Vietnam, which got hit with tariffs of 34 per cent (on top of the existing ones) and 46 per cent, respectively.

Toymaker Hasbro and electronics retailer Best Buy are both down bad too. Same goes for Williams-Sonoma, which sells higher-end home goods.

Home-goods store RH (fka Restoration Hardware) has fared even worse on Thursday. As its CEO said in the company’s earnings call today, with our emphasis:

I mean, I guess, the stock went down based on some of the numbers we reported and then it got killed because of a – oh, really? Oh, shit, OK.

Sure, you could argue that all of this will be offset by substitution effects and domestic investment within the US.

But the Secondary Stuff Stocks, whose profits rely more on consumer spending than tariffs, aren’t looking so hot either:

Synchrony Financial isn’t an importer! It does, however, sponsor the retailers’ store cards that shoppers use to sign up for discounts. So it’s down bigly as well. Airline and cruise stocks, which are also tied to consumer demand, are also falling (their capital spending is big, but rarer and often financed separately).

This trade pretty clearly goes beyond the mechanical tariff impacts, though. Gambling stocks are selling off hard, and they don’t really sell Stuff! But people do gamble less if they don’t have money to spend. Ideally.

And then we have the Staple Stuff stocks:

On the other side of the vice ledger from gambling, shares of cigarette maker Philip Morris are doing just fine.

Investors also appear to be more bullish on soup (Campbell Co) and processed grains (General Mills). No need to worry about GMO grains or Red-40 if you can only afford to have cereal for dinner!

The best performer in the consumer staples sector? That’s Lamb Weston, which sells frozen potatoes.

And this is all before we even get into the rates market, which is sounding the siren of recession. The US yield curve is now inverted as Hell, to use the technical term.

As Unhedged’s Rob Armstrong pointed out late last year, Americans are “fundamentally people who buy things”.

This type of trading heralds an identity crisis.

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To mark Liquidation Day, all three charts in last week’s quiz were made from OECD international trade data. The theme to guess was fish.

Here’s what you should have said:

That’s 2022 total value of international trade of fisheries commodities, as made apparent by those mirror-image Norway and Japan bars.

Chinese Taipei on the export side is the big clue above. It’s live fish (data code HS17_0301).

China leading on exports but with zero imports? Japan third for imports with zero exports? France importing and exporting almost exactly the same amount? It can only be caviar (data code HS17_160431).

Only one correct entry this week, so no need for the FTAV wheel of fortune. It was from Sean Lightbown of T Rowe Price. To him, congratulations. To everyone else, come back Friday for another go.

By now you’ll surely have seen the Trump administration’s self-cancelling and probably back-engineered tariff formula, as summarised below by a Stinson Dean tweet:

But it’s not the only bit of padding in the tariff policy note posted overnight. In the “references” section is an academic paper not mentioned in the main text: Trade Wars with Trade Deficits (2024) by Pau Pujolas and Jack Rossbach.

The paper starts with an idea associated with Canadian economist Harry Johnson: trade wars in general are counter-productive nonsense, but the country with the higher elasticity of substitution between domestic and imported goods can still claim victory. A trade deficit is similar to having a more elastic demand than the trading partner, say the authors.

Here’s what the lead author, Pau Pujolas of McMaster University in Canada, told FT Alphaville by email:

The work was done using the trade war between the US and China in 2018, it is not about the tariffs just announced.

Our paper shows that bilateral trade deficits change the way we have been understanding trade wars so far. I suspect that is the reason why the Trump administration is using the paper. It became somewhat well-known when we first put the pre-print on SSRN, as it is changing the way people should look at trade wars.

In a nutshell, the way people have been thinking about a trade war is like the Prisoner’s Dilemma: if I set tariffs and you don’t, I win, and you lose. If we both set tariffs, though, we are both made worse off.

But our results show that this result starts to crumble when there is a trade deficit: if I buy products from you and you don’t buy them from me, I can tariff you but you can’t tariff me, so I will reap the benefits of a impoverishing you, and you can’t do anything about it.

Hence, when trade deficits arise, the question about a trade war is quantitative: how much does the mechanism we uncover matter?

The paper uses a big-data trade model to figure out what tariffs a country should set and the likelihood of victory. Its authors add in a Spanish-language blog post published in January that the US could theoretically win a trade war against China, but the tariffs imposed in Trump’s first term were so poorly designed that both sides lost.

Pujolas told FTAV:

For a country like the US against a country like China (with a large trade deficit and also with rather large tariffs from China to the US) the US wins from starting a trade war. Similarly, against Canada. But we find that the US should not do that against, say, the European Union. Also, we find that the tariffs should be in the range of 10 per cent to 25 per cent. Making them higher is a bad idea for the United States.

And this is where the discrepancies between our work and the table that President Trump showed arises. Our results arise from a heavily computational exercise. We use supercomputers to find the optimal tariffs. The Trump administration seems to have taken a bit of a shortcut there. Also, our results suggest that the EU should not be tariffed, and yet they set high tariffs against them. Finally, our range of optimal tariffs is substantially lower than the ones the Administration just announced.

Jack Rossbach, of Georgetown University, the paper’s co-author, added:

I think the announcement shows we’re in a situation where it’s less about the specific numbers, and more a signal of how the administration expects things to proceed. If you want continued access to the US market, the administration is telling countries to come one-by-one to the negotiating table and start making offers.

It remains to be seen how countries will react to this.  We may start seeing countries announce lower tariffs, improved market access, or commitments to buy more American goods to avoid these tariffs.  If you import as much from the United States as you export, then the formula in the announcement says you’ll face zero tariffs.  It’s also possible that countries might start retaliating.  The paragraph in the announcement where they say the elasticity is 2, but we were conservative and went with 4, signals that the United States is happy to double these tariffs if countries try to fight instead of looking to negotiate.  The passthrough talk is a signal that the administration will be closely watching how firms adjust their prices in response to the tariffs.

We’ll have to wait to see what actually happens.  An all out trade war is going to have a very different impact than a joint investment venture.

We also checked in with Anson Soderbery of Purdue University, whose 2018 paper Trade elasticities, heterogeneity, and optimal tariffs gets a Trump citation. He told us:

While I do not believe reducing the US trade deficit through tariffs should be a central policy goal, if policymakers insist on this path, I urge against reductionist policy. That is to say, there are more efficient ways to craft trade policies to reduce trade deficits than a universal tariff ignoring industry and partner specific effects of tariffs.

Another paper cited in the main text, The Long and Short (Run) of Trade Elasticities (2023), is co-authored by University of Michigan’s Andrei Levchenko. Here, in full, is what he told us:

The goal of the import tariffs is to reduce imports: the higher are the tari&s, the lower imports will be. But how much lower? The formula used requires a number that gives the percent change in imports that will result from a 1% change in tariffs (called the “trade elasticity, or e in the document).

Our paper [ . . . ] is cited as a source for an estimate of this number. This note argues that our elasticity estimate should not be directly applied in this tariff calculation. The key reason is that the concept of the trade elasticity holds everything else constant (in technical terms, it is a “partial equilibrium elasticity”). This characterization applies equally to every other estimate of the trade elasticity, including the other papers cited.

In practice, everything else will not be constant. In particular, US exports (labeled xi in the document) could change. That can come from a variety of channels, but one important one is tarff retaliation by trading partners. If a trading partner puts tariffs on US exports to it, they will fall, (at least partially) un-doing the impact of lower imports on the trade deficit.

Beyond this, there are many other ways in which the change in US imports and exports will differ from the formula that directly applies a partial equilibrium trade elasticity. For example, trade elasticity estimates do not account for any impact of the change in tariffs on wages, prices, exchange rates, and the stock market. Those can go in different directions depending on the country, the product, the production technology used, etc.

For small tariff changes on individual products from individual countries, these changes might be small and could reasonably be ignored. However, the change in imports and in the bilateral trade balance implied by the partial equilibrium trade elasticity is likely to be unreliable when the tariff change is large and comprehensive (covering all goods), as is the case today. There is a way of assessing the change in imports and bilateral trade balances with large tariff changes. That would require a large-scale model of world trade with many countries, goods, adjustment mechanisms, etc. Our elasticity estimate would be one of many inputs into such a model.

And we spoke to Brent Neiman, of University of Chicago, whose co-authored work may or may not be cited in the explainer. There’s a citation in the main text to “Cavallo et al, 2021”, which might refer to Tariff Pass-Through at the Border and at the Store: Evidence from US Trade Policy — by Alberto Cavallo, Gita Gopinath, Brent Neiman and Jenny Tang — but there’s nothing in the actual reference section.

 Neiman told us:

It is not clear what the government note is referencing or not from our work [ . . . ] But I believe our work suggests a much higher value should be used for the elasticity of import prices to tariffs than what the government note uses.

 The government note uses a value of 0.25 for ‘the elasticity of import prices with respect to tariffs’, denoted with the Greek letter phi. But our estimates found a value of 0.943 — very close to 1 — for this elasticity. 0.943 is obtained using the very first number in Table 1, which equals -0.057. To translate this to their phi, you have to add 1 to this value, i.e. 0.943 = 1 — 0.057.

In non-technical terms, we write in the introduction to our paper, “ . . . our regressions suggest that a 20 per cent tariff, for example, would be associated with a 1.1 per cent decline in the ex-tariff price, and an 18.9 per cent increase in the total price paid by the US importer.” (Bolding added.) The government note assumes, I believe, that a 20 per cent tariff would only cause a 5 per cent increase in the price paid by the US importer.

I do not agree that the government calculation is an appropriate way to think about reciprocal tariffs. That said, using a value of 0.25 in their calculation, compared to a value closer to 1, results in reciprocal tariffs that are four times larger.

All in all, it’s a bit sloppy.

A paper about how tariffs need to be cleverly designed and carefully applied — and how Trump failed on both measures during his first term — is an odd thing to reference for a policy whose core formula is “divide this by that”. But to be fair, there’s no evidence that anyone involved in preparing the document has read it.

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There’s a lot going on at the moment, but the most interesting might be how the dollar has been absolutely tanked by yesterday’s tariff news.

The DXY dollar index has plunged 1.7 per cent today, taking it to its lowest since last autumn and extending its 2025 decline to almost 6 per cent.

In fact, the dollar is sliding against every single other major currency (oh, and the Swedish krona). Given how so many analysts long proclaimed that tariffs would be dollar positive, this is pretty notable.

Why is this happening? The orthodox view was that tariffs were positive for the dollar because they are inflationary — and therefore keep rates high — and make the US currency scarcer.

However, the dollar’s recent weakness could be indicative that these factors are getting swamped by broad and growing international misgivings over the US. The madness behind the methodology of the recent tariffs certainly doesn’t encourage faith in the coherence of US policymaking. Many analysts are alarmed, but probably none more than Deutsche Bank.

“We are becoming increasingly concerned that the dollar is at risk of a broader confidence crisis,” George Saravelos, head of FX strategy at Deutsche Bank, wrote in a note he sent out to clients this morning.

We’ll quote at length here, given the importance of the topic. Deutsche Bank’s emphasis below:

We have been warning about the importance of the correlation breakdown between US risk assets and the dollar for a while — European losses on US assets are now exceeding those seen during the 2022-2023 crisis. The safe haven properties of the dollar are being eroded and this is imposing a significant cost on unhedged dollar holdings. Beyond that, developments since the start of the year make us worried about a broader undermining of confidence in the US economic outlook and the medium-term desirability of dollar allocations.

All of this risks a self-fulfilling unwind of extreme US asset overweights from countries that have exported capital to the US over the last decade. Most of the developed world belongs to this category. At the end of the day, the US has a large current account deficit, and the currency is reliant on capital inflows for stability. A drop in the dollar, a drop in US equities and a rise in term premium in US treasuries would be the strongest market signal that a process of US disinvestment is accelerating. A rise in term premia on US treasuries has not materialized yet, but it would be a very negative signal if it did.

Our overall message is that there is a risk that major shifts in capital flow allocations take over from currency fundamentals and that FX moves become disorderly. We would caution that if the dollar decline accelerates, it would be a highly unwelcome development for global central banks. The last thing the ECB wants is an externally imposed disinflationary shock from a loss in dollar confidence and a sharp appreciation in the euro on top of tariffs. Expect pushback. We are in the midst of dramatic regime change in markets.

Christopher Mahon is head of Dynamic Real Return in Multi-Asset Investing at Columbia Threadneedle Investments.

In February, the Bank of England updated its estimates for the lifetime losses of the asset purchase facility, the vehicle through which it conducts quantitative easing.

Its prediction for APF losses had crept up: from £95bn in September, to £115bn at the year end. The scale of these figures — and the change, in a matter of months — dwarf the £14bn of savings chancellor Rachel Reeves announced in her spring statement.

Now, some might argue that comparing a lifetime figure to an annual budget is unfair. And the purported benefits of QE — supporting the economy during some of its darkest days — risk being overlooked if the focus lands too much on the bottom line. But these are big, unignorable numbers — so how should we think about the financial out-turns of the BoE’s QE programme? 

Recap: How QE works

To recap the mechanics of these losses: under QE, the BoE borrowed cash to buy government bonds (and the bonds of select companies) to support the economy. Financially speaking, this appeared to work well while cash rates were zero and locking in a 1 per cent yield on a 30-year gilt looked attractive. 

But fast forward to today, with cash rates at 4-5 per cent or higher, and the same 1 per cent yield locked in for 30 years isn’t quite such a good deal. In fact, it is immensely costly, as a result of the “negative carry” on those low-yielding bonds.

How the BoE losses compare

One way to think about these losses is to compare the BoE against other central banks. Each supported their economies more or less successfully through QE, so we can look at which central bank provided this help for the lowest cost, in the most efficient manner. 

However, with each central bank using its own accounting methods — with varying degrees of transparency — this is no easy task.

What we do know is what type of bonds each central bank bought, the dates of the purchases and how the bonds have performed since. Combined with certain other approximations, we can create rough mark-to-market estimates of the profit and loss of each of the central bank’s government bond holdings. 

It won’t be perfect, but this approach allows for a rough and ready like-for-like comparison. On this basis, our broad estimates of the cumulative losses since QE began are shown below:

The picture is much worse for the Bank of England than its peers, with losses nearly four times the Fed’s. Why is this?

Well, here’s a handy cheat sheet of the key choices the BoE made compared to the Fed:

The first two rows are the most significant. The ~4x worse losses on the BoE’s government bond holdings boil down to the BoE owning roughly twice as many gilts, and them being twice as rate sensitive as the Fed’s treasuries:

Maturity risk vs maturity mismatch

A big chunk of the losses come from the long maturity bonds that were more of a focus for the BoE. As an example, during QE in May 2020 the BoE bought a series of 2061 gilts at a price of £101. Under QT it has been selling the same securities at prices as low as £28, a loss of 73 per cent.

Arguably, these longer-dated maturities did not need to be bought at all. As an example: UK household borrowings are far shorter than in the US (think 5-year mortgages vs 30-year in the US). The transmission mechanism to the wider economy from buying a 30 or 50-year gilt was always fairly limited.

With the Fed choosing to focus QE only on certain parts of the curve, there was a good reason for the BoE to consider doing similarly, tailoring their focus to suit local conditions, rather than buying quasi-passively all the way along the curve.

The role of active QT

It is too late to salvage most of these losses. But, when it comes to reversing QE though quantitative tightening, the BoE again finds itself on its own. Only the BoE is actively selling their holdings into the market — no other major central bank is pursuing QT in this way. Others are simply opting for the passive method of allowing their bonds to mature without replacement. The Fed is still partially reinvesting coupons.

The BoE argues this difference makes little impact. Others take a different view.

Research published by NBER last year highlighted how the BoE’s QT programme has had a negative impact on long-term bond yields4. 

Researchers found a ~70 bps impact on long term gilt yields, against a 15-20bps impact from QT in the US — with a good portion of the difference being driven by active QT:

Certainly, the underperformance in gilts versus treasuries since QT began is noteworthy. Our own view is a combination of active QT, a faster pace of QT, and no coupon reinvestment has been weighing on gilts and perhaps adding about 30-40bps to yields versus comparable markets:

How to reconcile the Bank’s benign view against these more pessimistic assessments? The BoE’s own research tends to focus on the lack of evidence of market dislocations. But prices can be pushed down by a large seller without disorder and without liquidity worsening.

The incurious MPC

Perhaps surprisingly given the scale of the losses — and unlike decisions on interest rates — decisions about QE typically see unanimous votes by the MPC. Few public differences are aired or orthodoxies challenged. There is little reflection on the strengths or weaknesses in the UK’s approach. And there is no real acknowledgment of the alternative configurations that were — and still are — possible.

The BoE has avoided allowing consideration of profits or losses to drive changes in policy. Deputy governor Sir Dave Ramsden stated: “The MPC does not take into account financial risk or profit when taking monetary policy decisions, including about the gilt portfolio”.

Well, maybe it should. After all, taxpayers have to fund these losses. And if other central banks can do it cheaper, maybe there are lessons to be learnt.

Even at this late hour, if we are right about active QT exacerbating the supply demand imbalance in the gilt market, cancelling the extra sales from active QT and returning to central bank norms could be worth an ongoing £1bn per year saving to the Treasury in lower interest costs. 

Please, Governor, can we have no more?

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Americans were told reciprocal tariffs would be simple. “Reciprocal, that means they do it to us, and we do it to them,” said President Donald Trump on Wednesday. “Very simple, can’t get any simpler than that.”

Then the full list of countries’ tariffs came out, and it was . . . not simple. At least not in the “easily understood” meaning of the word.

The rates were supposedly based on the US Trade Representative’s calculations of “tariffs imposed against US products”. But they didn’t come from any obvious rates that were actually imposed, as Paul Krugman pointed out.

So how did they come up with these numbers in the first place? Turns out that there is some method to the madness! It’s just a nonsensical method, if it’s what we think.

Here’s what the White House and its crack team of trade investigators seems to have done: Take the US’s goods trade deficit with any particular country, and divide it by the total amount of goods imported from that country. Cut that percentage in half, and there’s the US’s “reciprocal” tariff rate.

We can confirm this fits* the numbers for the first 24 countries listed, which we checked by hand because we could hardly believe it and also because we refuse to use AI for anything. Kudos to @orthonormalist and James Surowiecki, who both put it together, more or less.

Let’s look at Bangladesh as an example. The US imported $8.4bn of goods from Bangladesh in 2024, giving it a $6.2bn trade deficit with the country. 6.2 divided by 8.4 is 0.738.

And what do you know? The White House says that the country has “charged” 74 per cent “tariffs” against the US, “including currency manipulation and trade barriers”.

Trying to assign a macro narrative to this calculation method is enough to make even a hack strategist’s blood run cold.

Is the US . . . implying that all trade deficits are the result of unfair practices or currency manipulation? What about comparative advantage? David Ricardo is surely spinning in his grave. What about bananas? They don’t grow in the US! Is it worrying that some posters got this method when they asked major LLMs about easy ways to impose tariffs? This is bananas.

Unnamed officials doubled down on the methodology to the New York Post:

The specific “reciprocal” tariff rate was roughly half of the current trade imbalance because “the president is lenient and he wants to be kind to the world,” a Trump aide told reporters.

“The numbers [for tariffs by country] have been calculated by the Council of Economic Advisers … based on the concept that the trade deficit that we have with any given country is the sum of all trade practices, the sum of all cheating,” a White House official said, calling it “the most fair thing in the world.”

UPDATE: You can also find what the US Trade Representative says about reciprocal tariff calculations here. Long story short: The White House wants to shrink the US’s trade deficit, it seems. This does not bode well for fans of coffee or bananas or other produce that doesn’t grow in the US.

Risk markets hated the news, predictably. S&P 500 futures were down 2.7 per cent around 10pm in New York. Nasdaq futures were down 3.4 per cent. And here’s betacoin Ethereum:

Anyway, we’ll see how long it lasts, we guess? There has been some debate about what legal authority the White House can claim to impose tariffs, and officials seem to have picked all of them that could apply in the latest Executive Order: The International Emergency Economic Powers Act; the National Emergencies Act; and sections 604 and 301 of the Trade Act of 1974.

When it comes to the total impact, lots of bizarre numbers have been thrown around. But the Budget Lab at Yale did a nice analysis, and found Wednesday’s tariffs boosted the US’s effective rate another 11.5 percentage points to 22.5 per cent, the highest level since 1909.

If trade wars are indeed class wars, this was a pretty noisy and chaotic shot across the bow.

*The only discrepancies we found in that group were Sri Lanka, which had 87 per cent instead of 88 per cent, and what could be some messy rounding. The next 24 countries were a little messier, but could still more or less be explained by sloppy rounding, with the exception of Jordan, Tunisia and Kazakhstan, which were all off by a percentage point or two.

Update: Toby’s cross-referenced the numbers and produced “the stupidest chart you’ll see today”. Bon appétit!

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Compared with the past, the present always feels uncertain. To the attentive analyst — or even human — risks abound. 

Today certainly feels pretty risky and uncertain. But how does it really measure up? 

Back in 2022, a couple of Federal Reserve economists — Dario Caldara and Matteo Iacoviello — published a paper in the American Economic Review that attempted to quantify geopolitical uncertainty. 

They built upon an historical database containing tens of millions of newspaper articles, and scanned a further 30,000 articles in a month from English-language newspapers (including the Financial Times). They then assessed the frequency of newspaper articles discussing adverse geopolitical events as a percentage of total articles.  

Having released replication packages to allow others to reproduce their results, and kept their website updated with close-to-current data, the Caldara/Iacoviello model has become fairly widely used. Here’s how it looks:

Their model has done a pretty good job in spiking at the times you’d expect a geopolitical risk index to spike. And although its latest readings are uncomfortably high, it isn’t in event-shock territory. So risky, but not super-risky.

But when we move away from broad measures of geopolitical risk and towards measures of policy uncertainty the picture darkens.

In 2016, three academics — Scott Baker, Nicholas Bloom, and Steven Davis — put together an index of US economic policy uncertainty based not only on newspaper articles, but also upon the number of federal tax code provisions set to expire, and a measure of disagreement among economic forecasters. Furthermore, they built topic-specific subindices of policy uncertainty.

How do things look at the headline level?

Yikes!

Okay, so a big input into this index is an historically normalised news-based component, and we’ve included this component to show how much uncertainty is being transmitted through the American media. But still, we’re approaching the kinds of uncertainty readings seen only during a global pandemic that included the economy being pretty much shut down.

What about uncertainty across different categories of economic policy? Here we move back again to news-only indices.

We’ve popped the relevant Baker/Bloom/Davis model data into a chart below — use the filter to toggle between uncertainty indices as they relate to Monetary Policy, Fiscal Policy, Health Care policy, Entitlement programs, etc:

While there isn’t an unprecedented level of uncertainty in many of these areas (trade policy being a notable exception), uncertainty readings are close to extremes in quite a large number of policy areas.

Alphaville highlighted the global version of this uncertainty index back in February, and how it had become disconnected to market measures of uncertainty used in options pricing. It seems that markets have since caught up.

Why does this matter? Businesses are basically planning machines. If they lack confidence in the future they’re less likely to invest or hire people. Not great.

Now, we know what you’re thinking. How would all these categorical uncertainty index data look in an animated interactive radar chart that plotted values for each category of economic uncertainty in the form of its percentile reading relative to its own history. Don’t worry — we’ve got your back:

As FT trade guru Alan Beattie has reminded us all for the last two months, when it comes to US policy, Nobody Knows Anything.