“Was the government to prescribe to us our medicine and diet, our bodies would be in such keeping as our souls are now.” -Thomas Jefferson

Let me introduce you to Sam. Sam has obesity, Type 2 diabetes, heart disease, and high blood pressure. His diet consists mostly of refined grains and trans fats. He’s got cabinets full of dirt-cheap junk food and sky-high healthcare costs to address its effects. He takes home $27,000 a year, but spends $36,000. He’s in debt up to his jaundiced eyeballs, and he wants his niece to foot the bill for weight-loss medication.

As a real-life niece of my Uncle Sam, I’m concerned about his diet. Some 56.2 percent of the daily calories consumed by US adults come from federally subsidized food commodities: corn, soybeans, wheat, rice, sorghum, dairy, and livestock. While these calorie-dense foods once made sense for a government preparing for famine or total war, in recent decades they’ve instead helped make us fatter and sicker. 

Obesity is a top driver of healthcare costs. One study compared the health of people who eat mostly foods the federal government subsidizes to those who eat fewer. Those who follow the revealed preferences of what the government subsidizes (rather than the diet it consciously recommends) are almost 40 percent more likely to be obese and face significant diet-related health issues. Those with the highest consumption of federally subsidized foods also have significantly higher rates of belly fat, abnormal cholesterol, high levels of blood sugar, and more markers of chronic inflammation. All these are increasing contributors to the most common causes of death in the developed world.

The negative impact of subsidized crop consumption on health — while it can’t be called causal — persists even after controlling for age, sex, and socioeconomic factors. But life does not control for those factors.

The Great Grain Giveaway

The federal government recommends one diet to Americans, and subsidizes another. The Dietary Guidelines for Americans from the USDA and HHS promote eating fruits, vegetables, whole grains, protein, and moderate dairy, while limiting saturated fats, sugars, salt, and refined grains. According to data compiled for Meatonomics, American agribusiness receives about $38 billion annually in federal funding, with only 0.4 percent ($17 million) going to fruits and vegetables. Just three percent of cropland is devoted to fruits and vegetables, despite USDA guidelines’ insistence that they should cover half of your dinner plate. Just 10 percent of Americans consume the recommended amount of fresh produce, and the poor consume the least. (Fruit and vegetable producers’ exclusion from the federal direct payments program provides a valuable example of a food industry thriving without significant subsidies. They do, however, rely heavily on migrant labor to lower costs.)

Instead, the US spends tens of billions annually to subsidize seven major commodities. The three largest farm subsidy programs contribute 70 percent of funds to producers of just three crops — corn, soybeans, and wheat. Approximately 30-40 percent of US corn, over half of soybeans, and nearly all sorghum feed livestock, heavily discounting high-fat, lower-nutrition meat and dairy (especially compared to grass-fed options). The prevalence of grain-fed livestock generates demand for commodities used to feed them, completing the circle. 

Subsidies also contribute to our consumption of refined grains, sugary drinks, and processed foods. About five percent of corn becomes artificially cheap high-fructose corn syrup (which allows it to compete with tariffed natural sugars), and half of soybeans are processed into oils, which also contribute to obesity.

My Uncle Sam is sick because he eats the food the government makes artificially more affordable. Those foods are poorer in quality and more harmful to health than their unsubsidized alternatives. We are paying to make ourselves sicker.

Diet-Related Health Issues Fuel Healthcare Costs

For more than 20 years, the FDA has known that trans fats and refined grains harm health, damage metabolism, and cause disease. Diet-related illnesses like obesity, Type 2 diabetes, and high blood pressure are increasing, while heart disease remains the leading cause of death. These epidemics are intertwined at the artery level, and both contribute hugely to rising US health care costs.

In an economic order awash with subsidies and regulation, agricultural policy is health policy. Government subsidies for agricultural products have shaped the current American nutritional environment, and they are exacerbating obesity trends.

An article in the American Journal of Preventive Medicine confirms: “Current agricultural policy remains largely uninformed by public health discourse.”

Johns Hopkins physician (and current Commissioner of the US Food and Drug Administration) Marty Makary called out the disconnect clearly. “Half of all federal spending is going to health care in its many hidden forms,” he told an interviewer in October, but Americans continue “getting sicker and sicker… Chronic diseases are on the rise. Cancers are on the rise. And we have the most medicated generation in human history.”

We’re getting more medicated every day — and more of it is at taxpayer expense. 

A Better Answer Than Ozempic?

Government spending on healthcare now exceeds the entire discretionary budget. Excess weight is a significant risk for older Americans, who are also the most likely to both have high healthcare costs and to rely on government health care. Forty percent of Americans over 60 are classified as having obesity, which is a contributing or complicating factor in diseases that kill older Americans: cancers, heart disease, infection, stroke, and cirrhosis.

Late last year, the Food and Drug Administration approved the weight-loss drug Wegovy as a treatment for people at risk of heart attack or stroke. Medicare is forbidden by statute from covering prescription drugs for weight loss alone, but in 2021 regulators approved Wegovy for reducing weight-related risks in patients with diabetes. Medicare Part D plans spent $2.6 billion last year on related compound Ozempic to keep 500,000 patients with diabetes stable. Wegovy’s list price is around $1,300 per month, but that’s still small compared to the $1.4 trillion Americans spend on direct and indirect costs from obesity.

It has a certain economic logic. Instead of waiting for a patient to develop a cascade of expensive comorbidities like heart failure or diabetes, we could consider asking Medicare to pay for anti-obesity meds on the front end. That wouldn’t work as well as lifestyle changes, but all our health and activity messaging over the past several years doesn’t seem to have moved that needle, and significant evidence suggests our efforts are counterproductive. 

The Tangled Web of Farm Subsidies

To understand the insanity of American agricultural and health policy, it’s hard to do better than comedian-illusionists Penn & Teller, who in characteristically salty style (really — you’ll want headphones and a sense of humor to watch the video) explained it this way 15 years ago: 

High fructose corn syrup is a dirt-cheap way to add sweetener and extend shelf life. And why is it so cheap? Because we subsidize corn farmers! Our government gives about 10 billion of our tax dollars to corn farmers every year so they can produce more corn than we need. They then sell the corn at artificially low prices. They spend our money to make corn syrup cheap, and now the same government that uses our tax money to keep soft drinks cheap wants more of our tax money to make soft drinks more expensive. Does anyone else think this is incredibly f—d up?

Yes, Penn. We do. And since that clip aired, obesity rates have worsened 50 percent, and rose 78 percent in children. Medical spending on the consequences of obesity doubled. Over the same period, subsidies to corn growers (which includes disaster aid and insurance) have tripled. 

Rather than cut back on his terrible diet, Uncle Sam wants us to pony up for weight loss drugs — to undo what our food policy has done.

Reports in early December indicate that President Donald J. Trump is preparing to sign an executive order that would block state-level laws regulating artificial intelligence and replace them with a single federal standard. According to early descriptions, the order would bar states from enforcing their own AI rules on safety, transparency, data, or algorithmic accountability.

The administration’s stated goal is to prevent a “chaotic patchwork of state AI laws” that, it argues, would burden interstate commerce and undermine the nation’s competitiveness. The justification is familiar: when the states cannot agree, when new technologies cross borders too easily, only a uniform national standard can provide stability. 

At one level, the reasoning is plausible. Yes, California, Colorado, Texas, Florida, Vermont, New York, and a dozen others have enacted or proposed conflicting approaches to regulating AI. Yes, this makes compliance difficult. But that does not justify a federal takeover of the entire domain of artificial intelligence, especially when the order reportedly envisions not merely preemption of state law, but the creation of a national regulatory framework enforced by federal agencies. The question that should precede any such action is the oldest one in the American political tradition: what powers does the government require in order to protect liberty — and what powers will compromise it? 

I write as someone now completing a book titled “A Serious Chat with Artificial Intelligence,” an extended reflection on the human mind in dialogue with its own creation. That work has made me especially sensitive to a paradox now unfolding: at the very moment when AI is expanding the reach of our intelligence, we risk shrinking the scope of our freedom. The challenge is real, the choices difficult. But the temptation to answer complexity with centralization — the temptation that now animates the push for a single federal rule for AI — has almost always led to stagnation. 

State regulation of AI is not, by itself, an ideal situation. We are indeed seeing 50 variations of concern, from the merely paternalistic to the openly fearful. Some states worry about algorithmic bias, others about deepfakes, still others about data privacy or labor displacement. Several are experimenting with rules requiring disclosure of training data, transparency of model decision-making, or permission requirements for models above certain compute thresholds. This is confusing. It is also federalism working as intended. The states are laboratories of democracy, not subordinate offices waiting for federal consolidation. 

The administration’s answer — federal preemption followed by federal regulation — is not a remedy. It is a cure worse than the disease. The premise behind it is philosophically wrong: that a central authority can foresee the risks of an emergent technology better than the distributed knowledge of millions of actors operating within a free market. That premise was wrong when applied to railroads, radio, electricity, telephony, airlines, and nuclear power. It is even more disastrously wrong when applied to artificial intelligence. 

Yes, government regulation is justified in cases where AI demonstrably is being used as a weapon of war or is modified specifically for crime. Governments successfully regulated nuclear weapons for three-quarters of a century. When state governments turned to regulating nuclear power to satisfy fears and doomsday fantasies, the nuclear power industry froze. Only now are we realizing that had its growth continued, the entire (dubious) “catastrophe” of climate change might instead have been stillborn.

The historical analogy that looms largest is the regulation of the airwaves. For decades, federal licensing of broadcast frequencies created a rigid, centralized, and stagnant media environment dominated by three giant networks. Only when cable television emerged — outside the FCC’s jurisdiction — did that system collapse and innovation resume. The market corrected the government’s mistake. It did so not through national uniformity, but through decentralization. What was true of the airwaves is true of AI: innovation is born at the periphery, not the center.

‘Regime Uncertainty’ 

The deeper economic argument against a single, national AI rule is the one articulated by the historian and economist Robert Higgs, who coined the term “regime uncertainty.” 

Higgs examined why private investment collapsed in the late 1930s even as the Great Depression was easing. The answer: business owners no longer trusted that the rules governing their property, contracts, and earnings would remain stable. With each new intervention, tax, or regulatory threat of the New Deal, the future became unpredictable. And when the future is unpredictable, capital retreats.

That insight perfectly describes the present moment in AI. Innovators are already facing a barrage of unpredictable interventions worldwide: the European Union’s AI Act, which classifies models by risk and bans categories of algorithmic use; China’s “Generative AI Measures” requiring adherence to state ideology; Congress floating licensing schemes for large models; the proliferation of state laws in the United States with incompatible compliance burdens; and now, a looming federal plan to centralize authority over the entire sector. To paraphrase Higgs, when government insists on being the co-author of every technological step, innovation freezes in anticipation of the next decree. 

The Higgs argument is only half the story, however. Higgs tells us why government intervention discourages innovation. Hayek tells us what regulates innovation when the government does not. 

Spontaneous Order 

For Friedrich Hayek, the central lesson of economics was that no single decision-making body — no panel of officials, no federal agency — could ever match the distributed intelligence of a free society. The knowledge required to understand a complex market is not held by any single mind. It is dispersed in millions of judgments, preferences, price signals, reputational cues, and feedback loops operating simultaneously. Out of this decentralized coordination emerges what Hayek called spontaneous order: an evolving, self-adjusting system far more responsive than regulation. 

Applied to artificial intelligence, Hayek’s argument is decisive. AI is not a static technology. It evolves weekly, often daily. It is shaped by user feedback at scale: billions of queries, millions of corrections, and innumerable signals of trust or distrust. When an AI product errs, offends, misleads, or harms, the market reacts immediately. Companies patch vulnerabilities, revise guardrails, withdraw faulty features, or lose customers. The constraint is real. It is continuous. And it is informed by vastly more data than any federal oversight board could ever obtain. 

If a teenager becomes obsessed with an AI avatar and suffers emotional fallout, public outcry registers instantly across social media and news cycles. Every user of the platform casts an implicit vote — continue using it, abandon it, or demand change. The company involved must respond or perish. That is regulation — regulation by consent, not compulsion. And it is the only kind of regulation agile enough to match the speed of AI. 

In other words, Hayek answers the most important question that arises from Higgs: if government does not restrain innovation, will innovation run wild? No. Because the free market restrains it — not by freezing it, but by continuous mid-course corrections. 

However, the push for a single federal rule for AI often implies that only uniformity can protect the public. History suggests the opposite. Uniformity is a great danger when officials do not know what they do not know. A rigid national standard, especially one drafted at the dawn of AI’s development, will inevitably reflect the fears, preferences, and misconceptions of a small political elite. It will enshrine those views long after they have been discredited by experience. Regulators will be tempted to err on the side of caution — of prohibition, delay, or excessive reporting — because no one at a federal agency is ever criticized for being too cautious. They are only blamed when something goes wrong. 

But when regulators overreact, the harms are invisible: the startup never launched, the medical breakthrough delayed, the scientific tool never invented, the small firm unable to afford compliance, the innovative business pushed offshore. These losses are real, even if they are unseen. 

One of the most telling developments in recent months is that some leaders of the AI industry itself are calling for regulation. At a Senate hearing in 2023, OpenAI CEO Sam Altman openly encouraged the creation of a federal licensing regime for advanced models. Senators were delighted. But smaller competitors were alarmed. The CEO of Stability AI warned that such regulation would entrench incumbents and “crush innovation.” The founder of Hugging Face noted that requiring federal permission to train a model would be like requiring a license to write code. These concerns are not abstract. Regulation tends to protect the powerful and eliminate the weak. 

Hayek would have recognized this immediately: when industries embrace regulation, it is often because regulation will serve them. It will not serve the future competitors who would challenge them. It will not serve the young minds with new ideas. It will not serve the yet-unknown innovators who cannot hire a team of lawyers and lobbyists. 

Critics of AI regulation often are asked: “But without government, how do we address the real risks?” The question assumes that centralized regulation is the default condition of order, and freedom the dangerous alternative. That assumption is historically and philosophically backward. 

The real alternative is not government versus chaos. It is government as a centralized overseer versus the spontaneous order of free participants responding to incentives, information, and feedback. The rigid mind versus the adaptive mind. Foreclosing the future versus learning from it. 

Artificial intelligence is a domain uniquely suited to the latter. Its risks are evolving. Its errors become visible instantly. Its user base provides rich data on whether features are helpful, harmful, or somewhere in between. The companies building it are extraordinarily attentive to public trust; reputational failure is death in this field. Where harms arise — fraud, impersonation, privacy breaches — existing law already provides remedies. Where harms are novel, civil courts can adjudicate responsibility, creating precedents rooted in real cases rather than speculative fears. 

Risk Is Inevitable, But Not the Risks of Regulation 

To demand comprehensive regulation now is to demand answers in advance to questions not yet understood. It is to regulate the unknown. And to regulate the unknown is almost always to prohibit it. 

No one denies that AI presents risks. So did electricity, the printing press, the automobile, the telephone, aviation, antibiotics, nuclear power, and the internet. Every one of these technologies was met by prophets of doom who were certain that catastrophe was imminent. The Swiss physician and naturalist Conrad Gessner (1516-1565) feared an “overwhelming abundance of books” would corrupt the human mind. Early critics of the telephone warned that it would annihilate privacy and eliminate face-to-face interaction. President Benjamin Harrison refused to touch the electric switches installed in the White House. Radio was denounced for corrupting children. In every era, fear accompanied invention.

Sometimes the fears were reasonable. But preemptive restraints would have prevented the very learning process that revealed how to use the new technologies safely. A muggy household without air conditioning would have seemed less dangerous to some than a building wired with electricity. But electricity ultimately became safer and more indispensable than anyone predicted. What mattered was not fear, but adaptation. 

The difference between the fears of the past and the fears of today is that today we are tempted to freeze innovation before it teaches us anything. That temptation is strongest in the political class. Bureaucracies do not benefit from rapid change; they benefit from stability, scope, and control. Innovation threatens all three. 

And now, under the proposed federal AI order, we are at risk of taking the first step toward nationalizing the evolution of intelligence itself. It would be an irony worthy of Swift if the American government — long the champion of free enterprise, experimentation, and engineering boldness — became the agent of technological paralysis.

The inevitability of a “single federal standard” is a myth. The United States does not need a national rule for AI. It needs national protection of the freedom to innovate, and national restraint upon those who would regulate prematurely. The problem of state-by-state inconsistency is real. But the proper federal role is to enforce the constitutional principle that states may not obstruct interstate commerce, not to impose a federal regulatory regime in the name of uniformity. 

Federal Deregulation Can Defeat State Chaos 

If the administration wishes to prevent states from impeding AI innovation, it has a simple tool: federal deregulation, not national regulation. Congress can preempt states from restricting AI deployment or training while simultaneously refusing to give federal agencies new regulatory powers over the technology. That would be the correct application of federal power: not central planning of innovation, but protection of the freedom to innovate. 

In my own conversations with AI while preparing “A Serious Chat with Artificial Intelligence,” I found myself returning to a single question: who will protect us from our protectors? It is easy to imagine dangers from unrestrained technology. It is harder to imagine dangers from unrestrained regulation. Yet the latter has done far more damage throughout history. Every great technological leap has been delayed, distorted, or nearly destroyed by those who feared its consequences more than they valued its promise.

The greatest danger is not that AI will escape our control. It is that we will surrender our control of our own minds — our capacity to imagine, invent, experiment, and err — in exchange for the illusion of security. If the federal government adopts a single national AI rule, that illusion will become law. 

The alternative is more demanding, but far more hopeful: trust the spontaneous order of a free society. Trust the judgment of millions of users. Trust competition to discipline excesses. Trust courts to address real harms. Trust innovation to solve the problems innovation creates. Trust, above all, the human mind — the free, adaptive, self-correcting engine of progress. 

Higgs teaches us why not to freeze innovation. Hayek teaches us what will regulate innovation when we refuse to freeze it. Together, they answer the demand for regulation not with anarchy but with confidence. Confidence in liberty. Confidence in knowledge dispersed. Confidence in evolution through experience. 

Artificial intelligence will not destroy us. But fear-driven regulation might. If we lose the courage that built our civilization, we will lose the future AI promises to create.

Dallas Fed President Lorie Logan recently proposed ditching the federal funds rate target as the Fed’s main policy tool. Her proposal would ensure that the Fed can continue to effectively implement monetary policy, but it fails to address one of the main flaws of the post-2008 monetary system.

The Fed’s Operating Target

In order to explore the merits of Logan’s argument, it helps to consider the context of what the Fed tries to do and how it tries to do it. The Fed’s job is to achieve maximum employment and price stability. To do that, it influences borrowing costs across the economy. Everything from mortgage rates to credit card APRs is affected by Fed policy. But it can’t set those rates directly. Instead, it tosses a small pebble into the financial pond—a change in its operating target—and counts on ripples through the financial system to spread outward towards its macroeconomic objectives.

Throughout its history, the Fed has used different pebbles to start those ripples: the quantity of bank reserves, the money supply, and, since the mid-1990s, the federal funds rate – the overnight rate on money that banks lend to each other.

Before 2008, targeting the federal funds rate worked smoothly. The Fed hit its target by adjusting the supply of money in the banking system. When banks were short on money, they would look to make up the shortfall in the federal funds market. Reducing the federal funds rate target made it cheaper for banks to obtain funds, which allowed them to pass lower rates on via their own lending. The ripples eventually reached households and businesses through cheaper loans and easier credit, stimulating spending and investment.

At the moment, adjusting the federal funds rate still produces the Fed’s desired ripple effect. But Logan is raising the alarm: it might be time to reach for a new pebble.

A Fragile Link

Before the Global Financial Crisis, the federal funds market was vibrant. Banks with excess reserves lent to those with shortfalls. The interest rate on those overnight loans is what we call the federal funds rate. 

The financial landscape changed dramatically after the crisis. The Fed flooded the banking system with money through quantitative easing and began paying banks interest on the funds held on deposit at the Fed. Suddenly, money in the banking system was no longer scarce, and banks had little need to borrow from one another. With trillions of dollars now sloshing through the system, both borrowers and lenders largely disappeared.

The market didn’t vanish entirely. A few players, most notably the Federal Home Loan Banks (FHLBs), continue lending because they cannot earn interest on their balances at the Fed. On the demand side, foreign bank branches in the US stepped in to exploit small arbitrage opportunities between the federal funds rate and the Fed’s interest on reserves.

That narrow participation keeps the market alive, but only barely. It now sees about $100 billion in daily volume, compared to trillions of dollars in secured repo markets. As Logan warns, with so few participants, the connection between the federal funds rate and broader money markets is fragile. If the FHLBs were to pull back—say, during a crisis like the Silicon Valley Bank episode in 2023—the market could dry up.

And, if that happens, the Fed could toss its pebble into the pond…and find that no ripples follow.

A New Pebble?

What should replace the federal funds rate? Logan argues that the Fed should consider targeting a Treasury repo rate, such as the tri-party general collateral rate (TGCR).

Repo markets are where borrowers obtain short-term funding by pledging high-quality assets, like Treasury securities, as collateral. Logan describes a number of advantages in moving to a Treasury repo rate target. The most obvious is the size and breadth of the market. TGCR transactions account for more than $1 trillion in daily volume across a broad set of financial institutions. This makes it unlikely to be affected by the behavior of individual institutions, which stands in sharp contrast to the influence of the FHLBs in the federal funds market.

There is also a strong link to other money markets. Since TGCR represents the marginal cost of funds for a meaningful segment of the financial system, changes to it will almost certainly pass through to other short-term interest rates. This again stands in contrast to the federal funds rate, which primarily results from the arbitrage activities of a small number of foreign banks. The possibility of throwing a TGCR pebble and not getting the desired ripple effect is slim.

Notably, the Fed is already trying to influence repo markets by encouraging use of its Standing Repo Facility (SRF). The SRF is designed to keep market repo rates – like the TGCR – in sync with the federal funds rate. Financial institutions appear hesitant to use the SRF. Targeting TGCR directly would be a more straightforward path to achieving the Fed’s goals. 

From Pond to Pool

Logan’s proposal addresses a legitimate concern – the fragility of the federal funds rate – but it doubles down on a bigger problem with the post-2008 monetary system: the financial pond has been transformed into a Fed-controlled pool.

Prior to 2008, the contours of the financial pond were largely determined by market forces. The Fed would toss its pebble in, and the desired ripples would be produced by its interaction with the supply and demand for money in the banking system. In other words, the Fed could control the federal funds rate, but it had to account for existing market conditions to achieve its target range.

After 2008, the Fed massively increased the amount of money in the banking system, to the point where banks no longer borrow and lend to each other. Under this system, the federal funds rate ceases to be a market-clearing price reflecting supply and demand – instead, it becomes a fixed price arbitrarily set by Fed decision makers. The price signals that result from banks trading funds with one another are suppressed, and the Fed becomes the dominant supplier of short-term funding. The financial pond is transformed into a pool requiring the Fed’s regular maintenance.

Logan advocates keeping the current system – that is, keeping a large supply of money in the banking system – even after moving to a repo operating target. This is where her proposal runs into trouble. Maintaining the Fed’s outsized role in the financial system weakens market mechanisms that help to allocate credit efficiently and discipline bank risk-taking. It also raises political concerns: the more interaction the Fed has with the financial system, the greater scope it has for influencing credit allocation and picking “winners” and “losers”.  

In contrast to Logan’s proposal, two other Fed officials – Governor Michelle Bowman and Kansas City Fed President Jeffrey Schmid – have recently advocated shrinking the Fed’s role in the financial system. In a November 13 speech, Schmid noted this could “promote a more efficient allocation of liquidity, an allocation influenced by price signals and market forces.” 

Treasury Secretary Scott Bessent has made similar critiques of the Fed’s current framework.   

Conclusion

Reducing the Fed’s role in the financial system – letting the pool evolve back into a pond, with market forces directing the ebb-and-flow – would be a step in the right direction. This evolution will take time, though. 

Logan’s proposal has the virtue of highlighting that the link between the federal funds rate and the broader financial system may break down before that evolution is complete. A well-rounded reform should address both issues – finding an effective, new pebble while also facilitating the evolution back towards a pond.  

Inflation was lower than expected in November, the Bureau of Labor Statistics (BLS) reported yesterday, in the first official inflation release since October following the extended government shutdown earlier this fall. Over the two months from September to November, the consumer price index (CPI) rose 0.2 percent, down from a 0.3 percent increase in September alone. On a year-over-year basis, headline inflation edged down to 2.7 percent in November from 3.0 percent in September.

Core inflation, which excludes food and energy prices, also rose 0.2 percent over the two-month period, unchanged from September. Core inflation, measured year-over-year, eased to 2.6 percent in November from 3.0 percent in September.

Energy prices were the main driver of inflation over the period, rising 1.1 percent. Food prices also increased modestly, up 0.1 percent, along with prices for household furnishings and operations, communication, and personal care. By contrast, prices for lodging away from home, recreation, and apparel declined.

Tariffs continue to put upward pressure on prices, but their effect appears to be easing, consistent with Federal Reserve Chair Powell’s view that tariffs are likely to result in a one-time increase in the price level. Combining September’s 0.3 percent increase with the modest rise in prices over October and November implies inflation is running at roughly a two-percent annual rate late in the period, though the absence of October data warrants caution.

Recent core CPI data tell a similar story. Core prices rose 0.2 percent in September and increased just 0.2 percent over the two months from September to November, implying a slower pace late in the period.

Taken together, these readings mark a notable shift from the late-summer pattern. In the July–September data, inflation was running at roughly a 0.3 percent monthly pace — equivalent to an annual rate near 3.7 percent — well above what the year-over-year figures suggested at the time. The most recent readings, by contrast, indicate a materially slower pace of price increases, with both headline and core inflation now running much closer to the Fed’s two-percent target, though again, the lack of October data complicates this assessment.

Although the Federal Reserve officially targets the personal consumption expenditures price index (PCEPI), CPI data remain a timely and relevant gauge for policymakers. The two measures generally track one another closely, though CPI tends to run somewhat higher than PCE inflation. As a result, the latest CPI readings provide a useful — if slightly overstated — signal of the inflation environment facing Fed officials as they assess the stance of policy.

Although the recent data suggest that inflation may be easing, the BLS relied on certain methodological assumptions when calculating the November CPI to account for the missing October data. Some analysts have raised concerns that those assumptions may have temporarily biased measured inflation downward. If that is the case, the apparent slowdown in inflation may be due to measurement error rather than a genuine change in the underlying momentum.

Still, financial markets appear to be interpreting the data favorably. Major stock indices rose and bond yields fell following the release. While the CME Group’s FedWatch tool suggests that markets expect the Federal Reserve to hold rates steady at its next meeting, the relative likelihood of a rate cut ticked up modestly after the November CPI report. That shift is consistent with the view that inflation is moving closer to target and lends support to Chair Powell’s recent claim that monetary policy is close to neutral.

Despite the uncertainty surrounding the data, the November CPI report is welcome news on the inflation front. After remaining stubbornly elevated for several years, inflation now seems to be moving back toward target. Even so, upcoming releases of the personal consumption expenditures price index and next month’s CPI should clarify whether the apparent cooling reflects a genuine slowdown in price increases or a temporary measurement distortion.

The title of Dan Wang’s book Breakneck focuses on the People’s Republic of China (PRC) specifically, but it is really about the self-conscious great-power rivalry between China’s Communist Party leaders and the United States. Along the way, we encounter all the popular points of controversy between the two great nations, covering everything from bullet trains, iPhone factories, and Trump tariffs to zero-COVID lockdowns, rare-earth mineral supply chains, and the demographic long tail of the One Child policy.

This isn’t just another case of two big nations clashing—as big nations tend to do from time to time. For finance analyst and university research fellow Dan Wang, the US and the PRC are uniquely paired in world affairs. In his introduction, he writes, “…no two peoples are more alike than Americans and Chinese,” citing their shared love of consumerism, pragmatic natures, and appreciation for technological progress.

Wang sees the US and PRC economies, in particular, as complements, which explains the rapid growth of trade between the two in the twenty-first century: “It is almost uncanny how much the United States and China have been complementary of each other.”

Yet at the same time, he says that, on a political level, “the two systems are a study in contrasts.” Fair enough, as they’re obviously very different. Yet in other passages, he frames the US and PRC systems as “inversions” of each other. This is seen in each society’s attitudes toward innovation and technology adoption, and to politics in general. It would take a sublime Confucian scholar to disentangle these contradictions. Perhaps the two nations are the phoenix and the dragon of world politics, the cobra and the mongoose, or simply each other’s evil twin.

Focusing on differences, Wang describes a Chinese government run by relentlessly practical but unsentimental engineers, who excel at building impressive infrastructure projects yet often disregard the negative impact on individual citizens. By contrast, America—the home of legal proceduralism and bureaucracy—has, in recent decades, erected a bewildering array of roadblocks to major projects, but does a much better job of recognizing and safeguarding individual rights.

This summary of strengths and weaknesses naturally suggests that each nation could benefit from borrowing elements of the other. The Chinese would be better off in certain ways by becoming more American, and vice versa. The first nation to adopt its counterpart’s advantages, Wang argues, will—like a comic book villain or mythic hero—bring balance to the force of good governance and “win” the twenty-first century.

It’s a reassuring prescription in a way, implying that there are no fundamental conflicts between the two nations that can’t be resolved through better understanding. Yet it contrasts sharply with the rhetoric coming out of both Beijing and Washington, D.C., where policy hawks from each country frame a twenty-first-century showdown that many fear could lead to war in the Taiwan Strait or elsewhere.

It also recalls the attitudes of some Western academics and center-left pundits during the Cold War, who assumed that the US and Soviet systems were similarly paired and would eventually converge in ways beneficial to both societies.

As late as 1988, for example, famed Affluent Society author John Kenneth Galbraith co-published a book with Marxist economist Stanislav Menshikov that imagined a future of increased trade and cooperation between the US and the USSR. They also, as Publisher’s Weekly put it at the time, “…criticize[d] establishment interests on both sides that seek to perpetuate the cold war.”

Galbraith and Menshikov were right that the Cold War would soon end—but not in a way that left the Soviets with a 50 percent stake in the world’s political future. If the collapse of the Soviet system—at a time when some Western economists were still predicting that the Warsaw Pact countries were on track to surpass the West economically—arrived so unexpectedly, one wonders what yet-unseen surprises the Chinese Communist Party has in store for the twenty-first century.

The Party, after all, has delivered plenty of dramatic—and mostly unpleasant—shocks to its own people over the decades. Wang takes deep dives into two of the most infamous: the One Child policy and the zero-COVID containment strategy. The former was certainly more horrific, although the latter’s impacts are far more recent and the responsibility of the current government, giving the pandemic lockdowns more resonance for younger Chinese citizens.

The PRC’s One Child policy was enforced, in successive iterations, from 1980 to 2015, and as a two- and three-child policy until 2021. The statistics, as Wang recounts them, are grim. In 1983, for example, the government sterilized 16 million women and aborted 14 million babies. Women who tried to resist were pressured, harassed, and sometimes even kidnapped by enforcement squads. Official propaganda claimed the procedures were voluntary, but in reality, they were the result of well-organized coercion: “…women [were] hauled before mass rallies and harangued into consenting to an abortion.”

Unsurprisingly, the policy was extremely unpopular among the women and families subjected to it, and the regime did little to blunt the pain it inflicted. “It didn’t help,” Wang dryly notes, “that the abortion posses literally carted off women in hog cages.”

The PRC’s COVID containment strategy was similarly authoritarian. Despite officials praising themselves for initially managing the pandemic well, by early 2022, rising infections were creating growing anxiety among Politburo members in Beijing. The government eventually imposed some of the largest forced quarantines in modern history, confining most of Shanghai’s population, for example, to their homes from March onward.

The lockdown lasted roughly five months—in a metro area of 25 million people, three times the size of New York City. Officials failed to ensure that residents could maintain reliable access to food and clean water. Chaos and panic were widespread, with many forced to adopt digital hunting and gathering as a full-time strategy to supplement the unpredictable and insufficient official provisions.

Wang quotes the unexpectedly poetic—and horrifying—propaganda broadcast throughout the city via drones: “Please comply with COVID restrictions. Control your soul’s desire for freedom,” the floating loudspeakers intoned.

Compared with scenes like that, the 3,000-page environmental impact statements and NIMBYism of US lawyerly society hardly seem so bad. Certainly, if most Americans had to choose between enduring the persistent defects of the United States and living under a system designed by the Chinese Communist Party, they would almost certainly opt for slow trains and the Bill of Rights.

Also, as Wang describes in a chapter on dissatisfied PRC expats, plenty of Chinese nationals with the money and initiative to leave have done so. Some of them, in line with popular narratives, have come to the US to get STEM doctorates and apply for H1B engineering jobs, but plenty have also become beach bums in Thailand or slam poets, democracy activists, and bookshop proprietors in global outposts.

Ultimately, Wang’s equal-but-opposite framework shows the limits of its evenhandedness. While understandably not wanting to depict his family’s home country as evil and vicious, it is difficult to “both sides” the human rights atrocities of something like the One Child policy. Are fast trains and tall bridges as admirable a civilizational achievement as respect for freedom of speech, religion, and the press? Should we pretend that the PRC could have had all of the former if they had brought themselves to embrace the latter?

More prosaically, the “each should be more like the other” framing muddies the question when it comes to issues like housing affordability and supply, which Breakneck repeatedly identifies as a problem in the US today. Wang argues that US institutions of government haven’t built enough.

“American cities have broadly failed to build adequate housing or infrastructure,” he writes. But in a market economy with robust property rights, it is not the government’s job to build housing—that’s what D.R. Horton, Pulte Homes, hundreds of smaller companies, and thousands of work crews are for. The problem is that major American cities have made it nearly impossible for the private sector to actually do its job.

Our problem is not, as many industrial policy proponents claim, a “lack of state capacity,” but precisely the opposite. We have empowered governmental institutions far beyond their constitutional limits with too much capacity for spending, debt, obstruction, and veto. We are being strangled and impoverished by the state capacity we have now. Making San Francisco and New York more like the land of ghost cities and abandoned theme parks will not be an improvement. Does anyone really believe that the most indebted nation in the history of the world is being chiefly held back because its government agencies aren’t able to borrow even more money and saddle future taxpayers with even more debt?

Granted, Wang generally does an admirable job of holding Americans’ feet to the fire with respect to our own problems around productivity and growth, which are significant. We would, after all, not want to end up like the CCP itself, which is notoriously bad at processing bad news and dealing with dissent, leading to consequences ranging from farcical to nightmarish.

We also wouldn’t want our industrial strength to decline so far that we end up like Europe, which Wang dismisses as a “mausoleum economy.” Americans, both as citizens and policymakers, will need to step up to compete with the machinations of the Communist mandarins in Beijing. We should, however, be careful not to copy their worst policies along the way.