Month: August 2024

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

Continue reading →

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.

IPUMS Data Intensive Workshop & Conference

Zachary BartschLeave a comment

I just returned from the Full Count IPUMS data workshop at the Data-Intensive Research Conference that was hosted by the Network on Data Intensive Research on Aging and IPUMS. The theme of this conference was “Linking Records”.

It was the best workshop and conference that I’ve ever attended. I’d attended the conference remotely in the past. But attending the workshop was exceptional. Myself and about 20 other people were flown to the Minneapolis Population Center and put up in a hotel during our stay (that made the conference a low-stress affair). The whole workshop was well organized, the speakers built on one another’s content, and there was a hands-on lab for us to complete. I felt my human capital growing by the hour.  

Continue reading →

Venezuelans Vote Overwhelmingly Against Maduro

James Bailey1 Comment

Venezuela held an election this week; President Maduro says he won, while the opposition and independent observers say he lost. Disputed elections like this are fairly common across the world, but where Venezuela really stands out is not how people vote at the ballot box- it is how they vote with their feet.

Reuters notes that “A Maduro win could spur more migration from Venezuela, once the continent’s wealthiest country, which in recent years has seen a third of its population leave.”

I don’t think we emphasize enough how crazy the scale of this is. After every US Presidential election, you hear some people who supported the losing side talk about leaving the country, but they almost never do. Leaving your home country behind is a dramatic step, one people only want to take if they think things are much better elsewhere. The US, even with a party you don’t like in power, has generally stayed a good place to live. The total number of Americans who have moved abroad for any reason (I would guess most feel more pulled by the host country rather than pushed by the US) is about 3 million. That is less than 1% of all Americans; by contrast more than 46 million people have immigrated to the US from other countries, and many more would come if we allowed it.

Even in poor countries, seeing anything like one third of the population leave is dramatic, especially when almost all the migration happens in only 10 years as in Venezuela:

Source. Note this only goes through 2020, and emigration has grown since

This makes Venezuela the largest refugee crisis in the history of the Americas, and depending on how you count the partition of India, perhaps the largest refugee crisis in human history that was not triggered by an invasion or civil war.

Instead, it has been triggered by the Maduro regime choosing terrible policies that have needlessly and dramatically impoverished the country:

I hope that the Venezuelan government will soon come to represent the will of its people. I’m not sure how that is likely to happen, though I guess positive change is mostly likely to come from Venezuelans themselves (perhaps with help from Colombia and Brazil); when the US tries to play a bigger role we often make things worse. But what has happened in Venezuela for the past 10 years is clearly much worse than the “normal” bad economic policies and even democratic backsliding that we see elsewhere. People everywhere complain about election results and economic policy, but nowhere else have I seen such a case of people going past simple cheap talk, taking the very expensive step of voting against the regime with their feet.