Category: 3. Business

Startup Valar Atomics said on Monday that it achieved criticality—an essential nuclear milestone—with the help of one of the country’s top nuclear laboratories. The El Segundo, California-based startup, which last week announced it had secured a $130 million funding round with backing from Palmer Luckey and Palantir CTO Shyam Sankar, claims that it is the first nuclear startup to create a critical fission reaction.

It’s also, more specifically, the first company in a special Department of Energy pilot program aiming to get at least three startups to criticality by July 4 of next year to announce it had achieved this reaction. The pilot program, which was formed following an executive order president Donald Trump signed in May, has upended US regulation of nuclear startups, allowing companies to reach new milestones like criticality at a rapid pace.

“Zero power criticality is a reactor’s first heartbeat, proof the physics holds,” Valar founder Isaiah Taylor said in a statement. “This moment marks the dawn of a new era in American nuclear engineering, one defined by speed, scale, and private-sector execution with closer federal partnership.”

Criticality is the term used for when a nuclear reactor is sustaining a chain reaction—the first step in providing power. Enriched nuclear fuel releases neutrons, which hit other atoms, which then split apart; neutrons from that process then hit other atoms, and start the reaction over. This process is known as fission. A properly-functioning reactor has just enough reactions to keep that fission chain going, reaching a state of criticality.

“Think of a long chain of dominoes,” says Adam Stein, the director of the Nuclear Energy Innovation program at the Breakthrough Institute, an eco-modernist policy center. “If you have those dominoes spaced out too far, a domino won’t hit the next one. If they’re spaced just right, then one hits the next, hits the next, and you have the reaction you’re hoping for.”

There’s a difference between the type of criticality Valar reached this week—what’s known as cold criticality or zero-power criticality—and what’s needed to actually create nuclear power. Nuclear reactors use heat to create power, but in cold criticality, which is used to test a reactor’s design and physics, the reaction isn’t strong enough to create enough heat to make power.

The reactor that reached criticality this week is not actually Valar’s own model, but rather a blend of the startup’s fuel and technology with key structural components provided by the Los Alamos National Laboratory, one of the DOE’s research and development laboratories. The combination reactor builds off a separate fuel test performed last year at the laboratory, using fuel similar to that Valar’s reactor will use.

Federal Reserve officials face a challenge resolving differences over how to set interest rates with little new economic data to guide tricky judgment calls.

Fed Vice Chair Philip Jefferson offered a case study in the central bank’s predicament on Monday, acknowledging the risk of stubborn inflation and weaker employment conditions—dueling threats that call for opposing prescriptions.

“The evolving balance of risks underscores the need to proceed slowly” with rate cuts, Jefferson said during a talk at the Kansas City Fed.

Beyond that observation, Jefferson’s comments did little to build the case either for a long timeout on rate cuts or for a rate cut at next month’s meeting—a decision that is shaping up to be unusually contentious.

(Bloomberg) — Bitcoin is in free fall — and traders are positioning for more pain.

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The world’s largest cryptocurrency plunged below $91,500 Monday, deepening a selloff that’s erased all of its gains for the year. In the options market, traders are making increasingly bearish wagers, on the conviction that the slide is far from over as deep-pocketed buyers beat a retreat.

The shift in sentiment has been swift and sharp. Demand for downside protection — particularly at the $90,000, $85,000 and $80,000 levels — has surged. Protective options expiring later this month are seeing especially heavy activity, according to data from Coinbase-owned Deribit.

After riding Bitcoin to the highs just weeks ago, traders have snapped up more than $740 million worth of contracts betting on continued declines expiring in late November — far outpacing interest in bullish positions.

“The absence of conviction-based spot demand has become increasingly apparent as buyers who accumulated positions over the last six months now find themselves significantly underwater,” said Chris Newhouse, director of research at Ergonia, a firm specializing in decentralized finance.

The pain has been concentrated in companies known as digital-asset treasuries — firms that stockpiled large amounts of cryptocurrencies earlier this year in an effort to become crypto-hoarding bets in the stock market. While Michael Saylor’s Strategy Inc. just bought another $835 million worth of Bitcoin, some of his corporate peers are facing growing pressure to sell assets to protect their balance sheets.

That selling has created a psychological overhang: A market crowded with investors who are too deep in the red to buy more, but not yet ready to cut their losses.

A sentiment index compiled by data-analytics platform CoinMarketCap — tracking price momentum, volatility, derivatives, and more — indicates crypto participants are mired in a state of “extreme fear.”

Larger economic forces are weighing on sentiment, too. Traders are eyeing Wednesday’s earnings from Nvidia Corp. — a bellwether for tech and speculative risk — as well as shifting expectations for a possible interest-rate cut from the Federal Reserve in December. The S&P 500 fell more than 1%, hitting sentiment for risk assets of all stripes.

“I think the Fed and AI bubble talk are two major headwinds for crypto and risk assets heading into the end of the year,” said Adam McCarthy, a research analyst at Kaiko. “The AI risk is likely compounding and affecting risk sentiment in crypto, adding that to the chatter from FOMC officials, you’re looking at a sustained downtrend for Bitcoin.”

Ethereum’s token, Ether, is proving especially vulnerable. The world’s second-largest cryptocurrency slumped to $2,975, bringing its decline to 24% since early October.

“Ether is very vulnerable to this theme as the biggest digital asset treasury firms are currently underwater on their positions,” said Greg Magadini, director of derivatives at Amberdata.

The broader market has been reeling since a sharp liquidation wave in early October erased about $19 billion in digital assets. Open interest in crypto futures contracts has dropped, particularly in smaller tokens like Solana, where positioning has fallen by more than half, according to Coinglass data.

“That riskoff tone spills into crypto markets, where sentiment remains fragile — the latest drawdown reflects broader macro jitters rather than structural flaws,” said Thomas Perfumo, global economist at crypto exchange Kraken.

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Thank you to the Society for the honor of addressing your annual meeting.¹ In doing a little research on the SPE’s history, I noted that one goal cited by the business economists who founded this group was creating a forum to discuss the divergence between real-world challenges and economic theory. That task is pressing when business profits, losses, and the jobs of employees are on the line, and the stakes are also high for economic policymakers, who face those very challenges today.

Economies are confoundingly difficult to understand because, in a sense, they are the largest and most complex things ever created by humans. Economists try to make sense of this complicated world and explain in logical and clear terms how to understand it. We develop rigorous theories that yield testable hypotheses, and we test those hypotheses to see if they are supported or rejected by the data. Being both an economist and economic policymaker, my objective today is to follow in that tradition and use economic theory and various types of data to describe my outlook for the U.S. economy and my views on the appropriate course of monetary policy. It may seem odd to come all the way to London to speak about the U.S. economy, but I hope it will be of interest—and I did warn the organizers about what I would talk about. Monetary policymakers like to use forward guidance to avoid surprises.

Formulating my outlook has been complicated recently by the 43-day government shutdown, including the agencies that produce key economic data. As I will argue, I believe the challenge presented by this missing data has been overstated in many quarters. Policymakers and forecasters are not “flying blind” or “in a fog.” While it is always nice to have more data, as economists, we are skilled at using whatever available data there is to formulate forecasts. Despite the government shutdown, we have a wealth of private and some public-sector data that provide an imperfect but perfectly actionable picture of the U.S. economy.

So, what is that data telling us? First, that the labor market is still weak and near stall speed. Second, that inflation through September continued to show relatively small effects from tariffs and support the hypothesis that tariffs are having a one-off effect raising price levels in the U.S. and are not a persistent source of inflation. Accounting for estimated tariff effects, underlying inflation is relatively close to the Federal Open Market Committee’s (FOMC) 2 percent target. Third, despite realized inflation running close to 3 percent and above target for five years, medium- and longer-term inflation expectations remain well anchored. And, lastly, even excluding the temporary effects of the shutdown, growth in real gross domestic product (GDP) has likely slowed in the second half of 2025 from its fast pace in the second quarter.

This reading of the data leads me, at this moment, to support a cut in the FOMC’s policy rate at our next meeting on December 9 and 10 as a matter of risk management. As I will discuss in more detail, risk management, in fact, provides some practical guidance in dealing with two questions that seem to have flummoxed some people: Is the job-creation slowdown in the U.S. this year mostly supply or demand related, and how should monetary policy respond?

Before I delve into the outlook, I’d like to say a bit more about data availability. The official sources delayed by the U.S. government shutdown are important but by no means the only source of information for Fed policymakers about the economy. At any time, my colleagues and I rely on a range of data to form our views on economic conditions and the outlook. That can be “hard” data, such as official government statistics, or “soft” data, gleaned from surveys or conversations with a variety of people. Often, different sources of data are consistent with each other, but at critical times they can conflict. When that happens, it takes our skills as economists to reconcile this conflict.

Let me cite two examples of my own experience to illustrate this point. First, back in 2022, the Fed was combating rampant inflation, and this required large and rapid increases in our policy rate. Standard Phillips curve models predicted that this would cause a sharp slowdown in economic growth and high unemployment. However, I had more trust in the Beveridge curve, which relates the unemployment rate to the job vacancy rate, as my guide to thinking about how the labor market would respond to these large rate hikes. I argued that we were on the steep part of the Beveridge curve, which meant that we could tighten policy and that the brunt of the effect would be borne by a decline in job vacancies, and crucially, not by the higher unemployment many predicted. A critical assumption I made was that a spike in layoffs would not occur. This assumption was controversial, since previous hard data showed that this was not the typical outcome. But all of my business contacts at that time were telling me about their struggles to find and keep workers since the COVID-19 pandemic and that they had no intention of letting workers go if aggregate demand eased. This “soft” data helped convince me that my view of the labor market was correct, and subsequent “hard” data confirmed my theoretical prediction.

The second example of reconciling conflicting data is from this past summer. From late spring through June, the soft data, including anecdotes from business contacts, suggested the labor market was in a “no hire, no fire” equilibrium. Firms repeatedly said they were holding off on hiring for a variety of reasons. Yet the hard data at that time indicated a robust job market, with job creation rising from a monthly average of 110,000 in the first quarter to 150,000 in the second quarter. It was clear to me that, once again, something wasn’t quite right with the labor market despite the official data. After the June FOMC meeting, I said that the labor market was more fragile than the hard data indicated and that the Committee needed to cut the policy rate to head off substantial weakening in the labor market.² This was clearly an out-of-consensus view that raised more than a few eyebrows. But when the July jobs report was released on August 1, the second-quarter jobs numbers were revised down dramatically—from an average of 150,000 per month to 64,000 a month, which vindicated my view. So, once again, the soft data gave a better signal of the state of the labor market than the hard data.

Now let me turn to the outlook, and I will start with U.S. economic activity. In my last speech, I discussed an apparent conflict between some forecasts of GDP growth in the second half of 2025 and the story that the labor market is weakening.³ In the absence of more official data but with additional private-sector forecasts and surveys, it now appears to me that economic activity is not accelerating and, therefore, is tracking more closely with the weak labor market data than appeared to be the case when I spoke on October 16. For example, private-sector forecasts, as seen by the median of respondents to the Blue Chip survey, are pointing to real GDP growth for the second half of this year that will be close to the modest first-half pace and a significant slowing from the pace of last year.

Of course, one factor lowering economic growth in the fourth quarter is the shutdown, which lasted longer than many expected. I continue to assume that any loss in real GDP growth in the fourth quarter will boost growth by roughly the same amount early next year. But besides that one-off boost from the shutdown, a possible warning about future economic activity is coming from a survey of consumer sentiment conducted by the University of Michigan. While over the decades this survey has not been closely correlated with near-term spending, large and persistent drops in consumer sentiment have occurred heading into recessions. In the United States, personal consumption expenditures are about 70 percent of GDP, so a slowdown in spending has dramatic implications for GDP growth. The Michigan survey is down significantly since July and fell unexpectedly sharply in October to near its record low reading. The dour view expressed by consumers, which may have been affected by the shutdown, lines up with what I am hearing from U.S. businesses, which report slackening demand from middle- and lower-income consumers.

One interesting detail from that survey is that deteriorating consumer sentiment was widespread among different demographic groups, with the exception of those who own stocks. While the booming stock market is supporting spending by a narrow band of well-off consumers, it does not reflect financial conditions for most Americans, and that is a vulnerability for the economy. The rise in the stock market is substantially driven by artificial intelligence (AI)–related businesses that only account for a small share of employment.⁴ Even while AI’s share of stock market growth and corporate profits grew significantly from 2021 through 2024, employment in AI-related firms held steady at less than 3 percent of nonfarm employment. While I believe AI will create jobs in the medium term, the AI boom on Wall Street isn’t doing so yet.

A factor that I believe will weigh on spending in the coming months is that most households are facing strains in purchasing large assets, such as housing and autos, in part because of the expense. While home price increases have slowed recently and even declined in some parts of the country, prices rose significantly in the past few years. That is especially true for lower-value homes, which is making it harder for first-time buyers.

Although mortgage rates have declined a bit this year, they are still above 6 percent and much higher than the average for the decade or so before rates began rising in 2022. Housing affordability is near a record low. Since 2020, the income needed to afford a median priced home has risen by 50 percent, while median income through 2024 was up about 26 percent.⁵ And while the growth of mortgage debt has slowed, that in part reflects how high mortgage rates are weighing on demand for mortgages.

Turning to auto loan growth, it has been relatively weak this year, likely reflecting a combination of weak demand from households and pressures in car affordability. To a greater extent than housing, the cost of purchasing an auto mostly reflects the price, but interest rates play a factor in the monthly payment. Auto loan rates continue to be elevated relative to their average in the years before the pandemic. For example, in 2019, the average five-year loan carried a 5.3 percent interest rate, whereas the average is now 7.6 percent.⁶ Reflecting the combination of higher auto prices and interest rate expenses, the weeks of median income needed to purchase an average new vehicle remains elevated, rising from 32.8 weeks in November 2019 to 37.4 weeks in September this year.⁷

To sum up, I consider the costs of housing and autos to be an ongoing challenge for consumers, especially lower- and middle-income consumers. This is likely weighing on spending growth and would become a more acute problem if the labor market continues to weaken.

Now let me turn to inflation, which, even with the delay in price data is the more straightforward side of the FOMC’s dual mandate to discuss. Twelve-month consumer price index inflation through September was 3 percent, and estimates are that inflation based on personal consumption expenditures—the FOMC’s targeted measure—was about 2.8 percent. Tariff effects have been smaller than many forecasters expected and the fraction borne by consumers will only modestly boost inflation—an effect that has been quite gradual so far because of the slow drawdown of inventories that was built up in anticipation of tariffs.

Despite inflation that has been above target for five years, inflation expectations are well anchored in the medium and longer run. To me, this shows that financial markets understand that they need to look through one-time price-level shocks and that they have confidence the FOMC will achieve its 2 percent target in the medium term. With the evidence of slower economic growth and the prospect of only modest wage increases from the weak labor market, I don’t see any factors that would cause an acceleration of inflation.

Let me now focus on the side of the FOMC’s economic mandate that has more of my attention—maximum employment. In the absence of federal data on the labor market, states have continued to report on initial and continuing unemployment insurance claims and private-sector sources have continued to publish their data as well. While there are methodological differences in these private data—some of it that is less than comprehensive and some that does not meet the strictest statistical standards—the private data do contain useful information.

According to the Labor Department, we know that job creation in the U.S. stalled from May through August, and with expected revisions that have been previewed and will become official next year, it is likely that employment actually fell over that period. A private-sector measure of job creation that has continued since August, produced by the payroll services firm ADP, mirrored the drop in official data from May through August, reporting a monthly average of 27,000 jobs created over that period, compared to the 143,000 a month that ADP counted for the six months up to May. While the ADP data are quite volatile and have some other shortcomings that make them less reliable than government statistics, I do think these data are telling us something. And in September and October, ADP reported that businesses created a net total of only 6,500 jobs a month. And the latest weekly data are even weaker.

Slowing labor demand is also being echoed in surveys of employers and workers. There has been a steady decline this year in the Conference Board index of job availability reported by employers. Fewer small businesses are saying it is hard to fill jobs according to the National Federation of Independent Business. Meanwhile, job postings by Indeed continued to drift lower in October. A new survey of large employers found that these companies are predicting that 2026 will be the worst job market for new college graduates since the pandemic year of 2021, when the unemployment rate was around 6 percent at graduation time.⁸

One series of government labor market data that we do have, continuing state-level claims for unemployment benefits, have risen, on net, in recent weeks and are running above levels in 2023 and 2024, although they are still fairly low by historical standards. This increase reflects the fact that it is taking unemployed individuals longer to find jobs than in the recent past. This is consistent with the well-known news lately about large corporate layoffs. Such announcements are anecdotes and may not be fully reflected, at least yet, in initial unemployment claims. But the numbers are eyepopping. The staffing firm Challenger, Gray & Christmas reported announcements of 153,000 job cuts in September and around 1 million so far in 2025, which is up 65 percent from 2024. By all accounts, many businesses may be cutting jobs, or allowing levels to fall by attrition, in connection with actual or anticipated productivity gains from AI.

As you may know, there is a vigorous debate in the U.S. about whether the low job-creation numbers are the result of declining labor supply or declining labor demand. Simply looking at job-creation numbers isn’t sufficient to answer the question—one must look at other data that correspond to these changes.

To help sort things out, let’s think about a standard supply and demand diagram. Consider a situation where there is a decline in labor supply that is greater than a decline in labor demand. This would shift the supply curve inward more than the demand curve. The result would be a reduction in employment, which is what we have seen. But it would also lead to upward pressure on wages due to labor shortages. We should also see an increase in job vacancies and a higher quits rate as workers chase higher-paying jobs. Furthermore, workers should be reporting that job availability is increasing, and firms should be saying that it’s becoming more difficult to hire workers. Now consider the opposite situation: a contraction in labor demand that is greater than the decline in labor supply. Again, this would lead to a reduction in employment. But it would also correspond to downward pressure on wages from an excess supply of labor as well as declines in vacancies and quit rates; workers would be reporting that job availability is falling, and firms would be saying that hiring is getting easier.

So, which of these two situations are the data telling me we are in? It is clear to me that the data are saying that there has been a greater reduction in demand than supply. I’m not seeing or hearing stories of an acceleration in wage growth, an increase in job openings, or a rise in the quits rate. The overwhelming share of the data I have cited so far supports the weaker demand story. There is definitely a reduction in supply, but, to me, that is masking the extent of the reduction in demand that I am concerned about. When outcomes are uncertain, policymakers must manage the risks, and the evidence is pointing toward a greater risk that low job creation is predominantly demand driven. This has implications for monetary policy.

So let’s talk about the implications of this hard and soft data. With underlying inflation close to the FOMC’s target and evidence of a weak labor market, I support cutting the Committee’s policy rate by another 25 basis points at our December meeting. For reasons I have explained, I am not worried about inflation accelerating or inflation expectations rising significantly. My focus is on the labor market, and after months of weakening, it is unlikely that the September jobs report later this week or any other data in the next few weeks would change my view that another cut is in order. I worry that restrictive monetary policy is weighing on the economy, especially about how it is affecting lower-and middle-income consumers. A December cut will provide additional insurance against an acceleration in the weakening of the labor market and move policy toward a more neutral setting.

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1. The views expressed here are my own and are not necessarily those of my colleagues on the Federal Reserve Board or the Federal Open Market Committee. Return to text

2. For a discussion of the tension in the hard and soft labor market data, see Christopher J. Waller (2025), “The Case for Cutting Now,” speech delivered at the Money Marketeers of New York University, New York, New York, July 17. Return to text

3. See Christopher J. Waller (2025), “Cutting Rates in the Face of Conflicting Data,” speech delivered at the Council on Foreign Relations, New York, New York, October 16. Return to text

4. Between 2021 and 2024, the workforce of AI-related firms stayed at levels equivalent to less than 3 percent of the entire U.S. nonfarm labor employment—that is, a small number of firms are accounting for an increasingly larger share of corporate profits but are not growing their share of labor demand at a commensurate pace. Return to text

5. See https://www.bankrate.com/real-estate/home-affordability-in-current-housing-market-study/#:~:text=See%20more-,Income%20needed%20to%20afford%20a%20typical%20home%20verges%20on%20$117,000,2025,%20according%20to%20Bankrate%20data. Also see https://fred.stlouisfed.org/series/MEPAINUSA646N Return to text

6. See “Finance Rate on Consumer Installment Loans at Commercial Banks, New Autos 60 Month Loan,” Federal Reserve Economic Data. Return to text

7. See Cox Automotive (2025), “September Incentives Hit High, but Record Prices Keep New-Vehicle Affordability Tight,” October 15, https://www.coxautoinc.com/insights-hub/sept-2025-vai. Return to text

8. See Lindsay Ellis (2025), “Companies Predict 2026 Will Be the Worst College Grad Job Market in Five Years,” Wall Street Journal, November 13. Return to text