On Average, American Wage Earners are Better Off Than They Were Four Years Ago

Jeremy Horpedahl5 Comments

As I wrote last November, the question “are you better off than you were four years ago?” is a common benchmark for evaluating Presidential reelection prospects. And even though Biden is no longer running for reelection, voters will no doubt be considering the economic performance of his first term when thinking about their vote in November.

The good news for American wage earners (and possibly Harris’ election prospects) is that average wages have now outpaced average price inflation since January 2021. Despite some of that time period containing the worst price inflation in a generation, wages have continued to grow even as price growth has moderated. Key chart:

For most of Biden’s term, it was true that prices had outpaced wages. But no longer.

The real growth in wages, admittedly, is not very robust, despite being slightly positive. How does this compare to past performance under recent Presidents? Surprisingly, pretty well! (Lots of caveats here, but this is what the raw data shows.)

Behind Last Week’s Stock Minicrash: Unwind of the Yen Carry Trade

Scott BuchananLeave a comment

Last Monday, August 5, the S&P 500 crashed by 3.5% from the previous close. That is a huge daily move, which seems to have been a surprise to most market watchers. The VIX index, a measure of the cost of options and widely seen as a measure of fear in the markets, went off the charts that day. What happened?

The previous week, there was an employment report that showed higher than expected jobless claims. Although that led to angst over a recession, a genuine serious dent in employment would bring the Fed roaring in with interest rate cuts, and the stock market loves rate cuts. In addition, as we have highlighted in recent posts (here and here), there is increasing skepticism that the monster spends on AI will produce the profits that Big Tech hopes. However, the AI skepticism and the employment worries seemed already baked into stock prices by the Friday close.

What apparently happened over the weekend was the unwinding of a big part of the yen carry trade.

What is that, you ask? To frame this, imagine you have $100 to invest in something very safe, like short term Treasury securities. In the simplest case, you go buy a 1-year T-bill which yields 4.5%. You will make $ 4.50 in a year, from this transaction. If you had $100 million to invest, you would make $ 4.5 million.

Now suppose that you could use that $100 as collateral to borrow $1000 at 0.05%. You then take that $1000 and buy $1000 worth of 4.5% T-bills. Voila, instead of making a measly $ 4.50, you can now make  1000*(4.5% – 0.05%) = $44.5. This is nearly ten times as much, a 44.5% return on your $100. Financial alchemy at its finest!

Now, if instead of investing in boring 4.5% T-bills, you had been buying Microsoft and Apple shares (up 25% and 21%, respectively, in the past twelve months), just imagine the profits from this 10X leveraged trade. Especially if you started with a $100 million hedge fund instead of $100.

Where, you may ask, could you borrow money at 0.05%? The answer is Japan. The central bank there has kept rates essentially zero for many years, for reasons we will not canvass here. This scheme of borrowing in yen, and investing (mainly in the US) in dollars is termed the yen carry trade. Besides this borrowing/investing, simply betting that the Japanese yen would decline against the dollar has been profitable for the past 18 months.

What could possibly go wrong with such a scheme? Well, you have to do this borrowing in Japanese yen. So, if you borrow in yen and then convert it to dollars and invest in the dollar world, you can be in a world of hurt if the value of yen in dollars goes up by the time you need to close out this whole trade (i.e. cash in your T-Bills into dollars, convert back to yen, and pay off your yen borrowings.

What happened on Wednesday, July 31 was the Bank of Japan unexpectedly raised its key interest rate target from 0-0.1% to around 0.25%, and announced they would scale back their QE bond-buying, in an effort to address inflation. As may be expected, that raised the value of the yen on Thursday and Friday, though not by much. But the yen made a surge up at the end of Friday’s trading.

Apparently, that caused enough angst in the carry trade community that participants in the carry trade started running for the exits, selling dollar-denominated assets (including stocks) and scrambling to buy yen. Naturally, that shot the price of yen up even more, so on Monday, Aug 5, we had a disorderly market rout.

Bad news sells, and so all the finance headlines on Monday were blaring about the stock price collapse and start of an awful bear market. However, nothing substantive had really changed. By Friday, the S&P 500 had recovered from this big head-fake.

As usual, investors sold stocks (at a low price) on Monday, and presumably bought them back at a higher price later in the week. This is why the average investor’s returns fall well below a simple buy and hold. But that is another subject for another time.

Insuring the suspension of disapproval

mdmakowskyLeave a comment

My wife and I were watching Guy Ritchie’s “Sherlock Holmes” (2009) last night. There is a chase/fight scene where a large commercial ship being repaired along a dock is detroyed as collateral damage. She asked me “What are the consequences of that ship being destroyed?” I had to admit that I didn’t fully know the state of the insurance market in Victorian England, but suffice it to say a few businesses and/or families were likely ruined. Which led to a conversation about collateral damage outside of the main narrative in movies and insurance. Sorry, that’s just what happens when you marry an economist. Things to consider the next time you’re filtering your prospects.

Which got me thinking: how much does the suspension of our disapproval of the protagonist’s actions (similar to the suspension of disbelief) depend on our undeclared faith in the insurance market of a fictional world? We don’t worry about destroyed livelihoods because we assume everything is simply absorbed as a tail event against which everything is insured. Car through front window? Automotive insurance tail event. Plane crashing onto the Vegas strip? Aeronautical tail event. Godzilla’s tail sweeping through a city? Giant lizard tail tail event.

How about the rise of the antihero? How many heists include a character shouting exposition to a crowd of cowering bank customers that they are there to steal money from the insurance company rather than the customers? The filmmaker needs the audience to suspend disbelief that bank’s have multiple customers inside in the age smart phones and suspend disapproval of the morality of the thieves’ actions as they steal from what they can only hope the audience will deem a souless corporation that can absorb the loss without broader consequence.

There’s two intellectual rabbit holes you can go down when you start thinking about insurance. You can dive in vertically, asking how much of our daily lives, including the consumption of narratives, is dependent on the presumption of insurance. You can also start thinking horizontally: how many dimensions of our lives boil down to creating formal and informal sources of insurance. We acquire formal health, home, pet, and automotive insurance. We also join groups, like churches, synagogues, mosques, and (yes) cults for social insurance. One motive to have children is to insure against the limitations and isolation of old age. Anything and everything we invest in, both individually and as a society, that softens the tail events at the expense of the expected outcome is a form of insurance.

It can go on and on. If anything, it takes care at some point to stop seeing everything as a form of insurance. Why did they feature an actor in the poster and the trailer despite their only appearing for 14 minutes in the film? Why were they paid more than double the lead actors? Oh, right. They’re an insurance policy against a catastrophic opening weekend. If the movie is good, but needs word of mouth to spread for people to starting coming out, you need to survive to a second weekend to start making money. Better to eat a chunk of your expected profits on a big name than risk getting dumped from theaters before the audience can find you.

What’s that you say? No one goes to theater’s anymore? Oh. Well, there’s some risk you can’t insure against.

Publish or Perish: A Hilarious Card Game Based on Academia

Joy Buchanan1 Comment

I had the opportunity to play an advanced copy of “Publish or Perish,” a new card game that satirizes the world of academia. Created by Max Bai, this game offers a funny take on the often cutthroat world of academic publishing.

Official website for the game: here

My group of eight friends divided into teams to accommodate the game’s six-player limit, which I’d recommend not exceeding. From the moment we started reading the instructions aloud, we were laughing.

The gameplay is engaging. One unexpectedly hilarious rule involves clapping for each other’s achievements. The game’s core revolves around publishing manuscripts, accumulating citations, and navigating the waters of peer review and academic politics.

I was impressed by the calibration of the trivia questions. They struck a great balance – challenging enough that we often couldn’t answer them, yet not so obscure that they felt unreasonable. This aspect added an educational twist to the fun, sparking interesting discussions.

The humor in “Publish or Perish” is spot-on, especially in the details. The manuscript cards had us in stitches, with journal names like “Chronicle of Higher Walls” (a clever play on the real “Chronicle of Higher Education”) and absurd paper titles.

My favorite paper title was “The Great Avocado Toast Crisis: Socioeconomic Impacts of Millennial Breakfast Choices”
Esteemed friend and economist Vincent Geloso liked “The Economics of Building a Death Star”

The two other full-time academics in our group were so impressed that they pre-ordered copies on the spot. While the game is probably most enjoyable with at least one academic in the group, our mixed party – including a government statistician and several non-academics – found it entertaining.  One of my non-academic friends summed it up as follows: “This game brought several people from different backgrounds and areas of expertise together for a thoroughly enjoyable evening.”

“Publish or Perish” manages to be both easy to learn and refreshingly original. I predict it will carve out its own niche with its unique theme and mechanics. Players can engage in academic shenanigans like plagiarism, P-value hacking, and even sabotaging opponents’ work – all in good fun.

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Recession Prospecting & Fed Tea Leaves

Zachary Bartsch4 Comments

Will a recession happen? It’s famously hard/impossible to predict. Personally, I have a relatively monetarist take. I consider the goals of the Federal reserve, what tools they have, and how they make their decisions. I also think about the very recent trend in the macroeconomy and how it’s situated relative to history. Right now, the yield curve has been inverted for quite some time and the Sahm rule has been satisfied, both are historical indicators of recession.

Recessions are determined by the NBER’s Business Cycle Dating Committee. They always make their determination in hindsight and almost never in real time. They look at a variety of indicators and judge whether each declines, for how long, how deeply, and the breadth of decline across the economy. So plenty of ‘bad’ things can happen without triggering a recession designation.

In my expert opinion, recessions can largely be prevented by maintaining expected and steady growth in NGDP. This won’t solve real sectoral problems, but it will help to prevent contagion and spirals.  The Fed can control NGDP to a great degree. In doing so, they can affect unemployment and growth in the short run, and inflation in the medium to long run.

One drawback of the NGDP series is that it’s infrequent, published only quarterly. It’s hard to know whether a dip is momentary, a false signal that will later be updated, or whether there is a recession coming. So, what should one examine? One could examine leading indicators or the various high-frequency indicators of economic activity. But those are a little too much like tarot cards and fortune telling for my taste.

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A Continually Updated Bernanke-Taylor Rule

James Bailey4 Comments

Despite its many flaws*, I always like to check in on what the Taylor Rule suggests for the Fed. Its virtues are that it gives a definite precise answer, and that it has been agreed upon ahead of time by a variety of economists as giving a decent answer for what the Fed should do. Without something like the Taylor Rule, everyone tends to grasp for reasons that This Time Is Different. Academics seek novelty, so would rather come up with some new complex new theory of what to do instead of something undergrads have been taught for years. Finance types tend to push whatever would benefit them in the short term, which is typically rate cuts. Political types push whatever benefits their party; typically rate cuts if they are in power and hikes if not, though often those in power simply want to emphasize good economic news while those out of power emphasize the bad news.

The Taylor Rule can cut through all this by considering the same factors every time, regardless of whether it makes you look clever, helps your party, or helps your returns this quarter. So what is it saying now? It recommends a 6.05% Fed funds rate:

Fed Funds Rate Suggested by the Bernanke Version of the Taylor Rule
Source: My calculation using FRED data, continually updated here

I continue to use the Bernanke version of the Taylor Rule, which says that the Fed Funds rate should be equal to:

Core PCE + Output Gap + 0.5*(Core PCE – 2) +2

*What are the flaws of the Taylor Rule? It sees interest rates as the main instrument of monetary policy; it relies on the Output Gap, which can only really be guessed at; and it incorporates no measures of expectations. If I were coming up with my own rule I would probably replace the Output Gap with a labor market measure like unemployment, and add measures of money supply shifts and inflation expectations. Perhaps someday I will, but like everyone else I would naturally be tempted to overfit it to the concerns of the moment; I like that the Taylor Rule was developed at a time when Taylor had no idea what it might mean for, say, the 2024 election or the Q3 2024 returns of any particular hedge fund.

That said, people have now created enough different versions of the Taylor Rule that they can produce quite a range of answers, undermining one of its main virtues. The Atlanta Fed maintains a site that calculates 3 alternative versions of the rule, and makes it easy for you to create even more alternatives:

Two of their rules suggest that Fed Funds should currently be about 4%, implying a major cut at a time that the Bernanke version of the rule suggests a rate hike. On the other other hand, perhaps this variety is a virtue in that it accurately indicates that the current best path is not obvious; and the true signal comes in times like late 2021 when essentially every version of the rule is screaming that the Fed is way off target.

Taxes, Children, and the Zero Bracket

Jeremy HorpedahlLeave a comment

Recently there has been some discussion in the Presidential race about the taxation of parents vs. childless taxpayers. The discussion has been ongoing, but it was kicked up again when a 2021 video of J.D. Vance resurfaced where he said that taxpayers with children should be lower tax rates than those without children. There was some political back-and-forth about this idea, much of it tied up in the framing of the issue, with the usual bad faith on both sides about the fundamental issue (in short: most Democrats and a small but growing number of Republicans support increasing the size of the Child Tax Credit).

Let’s leave the politicking aside for a moment and focus on policy. As many pointed out in response to Vance’s idea, we already do this. In fact, we have almost always done this in the history of the US income tax — “this” meaning giving taxpayers at least some break for having kids. For most of the 20th century, this was done through personal exemptions which usually included some tax deduction for children, and later in the century the Child Tax Credit was added (after 2017, the exemptions were eliminated in favor of a large CTC). Other features of the tax code also make some accounting for the number of children, most notably the size of the Earned Income Credit.

The chart below is my attempt to show how the tax breaks for children have affected four sample taxpaying households. What I show here is sometimes called the “zero bracket” — that is, how much income you can earn without paying any federal income taxes. The four households are: a single person with no children, a married couple with no children, a single person with two children (“head of household”), and a married couple with two children. All dollar amounts are inflation-adjusted to current dollars

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Will the Huge Corporate Spending on AI Pay Off?

Scott Buchanan2 Comments

Last Tuesday I posted on the topic, “Tech Stocks Sag as Analysists Question How Much Money Firms Will Actually Make from AI”. Here I try to dig a little deeper into the question of whether there will be a reasonable return on the billions of dollars that tech firms are investing into this area.

Cloud providers like Microsoft, Amazon, and Google are building buying expensive GPU chips (mainly from Nvidia) and installing them in power-hungry data centers. This hardware is being cranked to train large language models on a world’s-worth of existing information. Will it pay off?

Obviously, we can dream up all sorts of applications for these large language models (LLMs), but the question is much potential downstream customers are willing to pay for these capabilities. I don’t have the capability for an expert appraisal, so I will just post some excerpts here.

Up until two months ago, it seemed there was little concern about the returns on this investment.  The only worry seemed to be not investing enough. This attitude was exemplified by Sundar Pichai of Alphabet (Google). During the Q2 earnings call, he was asked what the return on Gen AI investment capex would be. Instead of answering the question directly, he said:

I think the one way I think about it is when we go through a curve like this, the risk of under-investing is dramatically greater than the risk of over-investing for us here, even in scenarios where if it turns out that we are over investing. [my emphasis]

Part of the dynamic here is FOMO among the tech titans, as they compete for the internet search business:

The entire Gen AI capex boom started when Microsoft invested in OpenAI in late 2022 to directly challenge Google Search.

Naturally, Alphabet was forced to develop its own Gen AI LLM product to defend its core business – Search. Meta joined in the Gen AI capex race, together with Amazon, in fear of not being left out – which led to a massive Gen AI capex boom.

Nvidia has reportedly estimated that for every dollar spent on their GPU chips, “the big cloud service providers could generate $5 in GPU instant hosting over a span of four years. And API providers could generate seven bucks over that same timeframe.” Sounds like a great cornucopia for the big tech companies who are pouring tens of billions of dollars into this. What could possibly go wrong?

In late June, Goldman Sachs published a report titled, GEN AI: TOO MUCH SPEND,TOO LITTLE BENEFIT?.  This report included contributions from bulls and from bears. The leading Goldman skeptic is Jim Covello. He argues,

To earn an adequate return on the ~$1tn estimated cost of developing and running AI technology, it must be able to solve complex problems, which, he says, it isn’t built to do. He points out that truly life-changing inventions like the internet enabled low-cost solutions to disrupt high-cost solutions even in its infancy, unlike costly AI tech today. And he’s skeptical that AI’s costs will ever decline enough to make automating a large share of tasks affordable given the high starting point as well as the complexity of building critical inputs—like GPU chips—which may prevent competition. He’s also doubtful that AI will boost the valuation of companies that use the tech, as any efficiency gains would likely be competed away, and the path to actually boosting revenues is unclear.

MIT’s Daron Acemoglu is likewise skeptical:  He estimates that only a quarter of AI-exposed tasks will be cost-effective to automate within the next 10 years, implying that AI will impact less than 5% of all tasks. And he doesn’t take much comfort from history that shows technologies improving and becoming less costly over time, arguing that AI model advances likely won’t occur nearly as quickly—or be nearly as impressive—as many believe. He also questions whether AI adoption will create new tasks and products, saying these impacts are “not a law of nature.” So, he forecasts AI will increase US productivity by only 0.5% and GDP growth by only 0.9% cumulatively over the next decade.

Goldman economist Joseph Briggs is more optimistic:  He estimates that gen AI will ultimately automate 25% of all work tasks and raise US productivity by 9% and GDP growth by 6.1% cumulatively over the next decade. While Briggs acknowledges that automating many AI-exposed tasks isn’t cost-effective today, he argues that the large potential for cost savings and likelihood that costs will decline over the long run—as is often, if not always, the case with new technologies—should eventually lead to more AI automation. And, unlike Acemoglu, Briggs incorporates both the potential for labor reallocation and new task creation into his productivity estimates, consistent with the strong and long historical record of technological innovation driving new opportunities.

The Goldman report also cautioned that the U.S. and European power grids may not be prepared for the major extra power needed to run the new data centers.

Perhaps the earliest major cautionary voice was that of Sequoia’s David Cahn. Sequoia is a major venture capital firm. In September, 2023 Cahn offered a simple calculation estimating that for each dollar spent on (Nvidia) GPUs, and another dollar (mainly electricity) would need be spent by the cloud vendor in running the data center. To make this economical, the cloud vendor would need to pull in a total of about $4.00 in revenue. If vendors are installing roughly $50 billion in GPUs this year, then they need to pull in some $200 billion in revenues. But the projected AI revenues from Microsoft, Amazon, Google, etc., etc. were less than half that amount, leaving (as of Sept 2023) a $125 billion dollar shortfall.

As he put it, “During historical technology cycles, overbuilding of infrastructure has often incinerated capital, while at the same time unleashing future innovation by bringing down the marginal cost of new product development. We expect this pattern will repeat itself in AI.” This can be good for some of the end users, but not so good for the big tech firms rushing to spend here.

In his June, 2024 update, Cahn notes that now Nvidia yearly sales look to be more like $150 billion, which in turn requires the cloud vendors to pull in some  $600 billion in added revenues to make this spending worthwhile. Thus, the $125 billion shortfall is now more like a $500 billion (half a trillion!) shortfall. He notes further that the rapid improvement in chip power means that the value of those expensive chips being installed in 2024 will be a lot lower in 2025.

And here is a random cynical comment on a Seeking Alpha article: It was the perfect combination of years of Hollywood science fiction setting the table with regard to artificial intelligence and investors looking for something to replace the bitcoin and metaverse hype. So when ChatGPT put out answers that sounded human, people let their imaginations run wild. The fact that it consumes an incredible amount of processing power, that there is no actual artificial intelligence there, it cannot distinguish between truth and misinformation, and also no ROI other than the initial insane burst of chip sales – well, here we are and R2-D2 and C3PO are not reporting to work as promised.

All this makes a case that the huge spends by Microsoft, Amazon, Google, and the like may not pay off as hoped. Their share prices have steadily levitated since January 2023 due to the AI hype, and indeed have been almost entirely responsible for the rise in the overall S&P 500 index, but their prices have all cratered in the past month. Whether or not these tech titans make money here, it seems likely that Nvidia (selling picks and shovels to the gold miners) will continue to mint money. Also, some of the final end users of Gen AI will surely find lucrative applications. I wish I knew how to pick the winners from the losers here.

For instance, the software service company ServiceNow is finding value in Gen AI. According to Morgan Stanley analyst Keith Weiss, “Gen AI momentum is real and continues to build. Management noted that net-new ACV for the Pro Plus edition (the SKU that incorporates ServiceNow’s Gen AI capabilities) doubled [quarter-over-quarter] with Pro Plus delivering 11 deals over $1M including two deals over $5M. Furthermore, Pro Plus realized a 30% price uplift and average deal sizes are up over 3x versus comparable deals during the Pro adoption cycle.”

The median voter remains (probabilistically) undefeated

mdmakowskyLeave a comment

The median voter wanted a younger candidate. The median voter appears to now have a younger candidate. The immediate result:

Polymarket doesn’t have it crossing over yet, but Biden at his nadir before dropping out was at 34%. Today shares of Harris winning are at 45%. Put in equity terms, a share of the Democrative candidate winning has increased 33% in a month on Polymarket.

Biden got the nomination and eventually won in 2020 by appealing to the median voter, even while pundits from his base whined. Harris will, if she wants to win, do much of the same. It will be interesting to see if the Republican candidate responds in kind, but its difficult to the see the dimensions on which they can depart from their candidate’s highly, ahem…specific brand.

Culture Parenting Chatter

Joy BuchananLeave a comment

I’ve been traveling. Here are some things I noticed (on the internet, not on my travels). (On my travels I learned that rental golf carts are as fun as they look.)

  1. “Jennifer Aniston slams JD Vance over ‘childless cat ladies’ comment from resurfaced interview“

2. This is a poastmodern election. “Campaigners use the internet medium to dunk on their opponents instead of offer solutions to problems.”

“deeply online left wing instagram women are meeting, for the first time ever, deeply online right wing twitter guys. both have developed intricate, sacred language foreign to the other. both are waging war they thought already won. fyi in case you’re wondering about the meltdown”

I thought that meeting happened months ago with the “bear in the woods” discourse.

3. If it wasn’t so serious, American politics would be too funny for television.

4. This woman who gave up professional dancing and now has 8 kids.

One does wonder if the skills that get a person into Julliard relate to the ability to turn family into an Instagram sensation. Is this Ambitious Parenting?

“My day with the trad wife queen and what it taught me” This article about Ballerina Farm reads like the anti-“Hannah’s Children” (reviewed by my former student here)

Hannah Neeleman, the mom at Ballerina Farm, has told her story in what appears to be her own words here: https://ballerinafarm.com/pages/about-us Neeleman says that when she was living in Brazil, she would vacation at, “farms and ranches. A place where you could eat farm fresh cheeses and meats, learn about animals, watch chores being done, etc. We were hooked.” I’m tempted to say that it’s weird to say she was into watching other people do chores. But maybe the word “weird” just has lost all meaning after this week.

Jeremiah Johnson points out that, “It doesn’t matter that their farm isn’t a very productive farm, because the husband’s family founded JetBlue.” My take is that these are rich people who are taking a reality-show approach to their lives like wholesome Kardashians. The Neelemans are into watching people do farm chores. (Yes, they do chores themselves, too, but clearly a large professional staff runs the place.) Good for them. As I said at the beginning, I’m into renting golf carts now.