Does Bank Consolidation Harm Customers?

By Jeffrey Miron of Cato. 

"Antitrust policy presents a challenge for both libertarians and policymakers. On the one hand, competitive markets are good, which might suggest policy should limit firm mergers. On the other hand, mergers can have beneficial effects (such as economies of scale and scope, or disciplining unproductive firms), so broad opposition to mergers is likely counterproductive.

New research on bank consolidation offers evidence on this tradeoff. Contrary to the belief

that bank mergers reduce competition, increase borrowing costs, and limit households’ access to credit, … [the study finds that m]ergers have no meaningful effect on interest rates, approval rates, or late payments. Merged banks do not appear to use their increased size to charge borrowers more or restrict access to mortgages.

This may be due to

the intense competition in local mortgage markets. The typical county has more than 130 active mortgage lenders per quarter, and the median lender controls just 0.4 percent of its local market. Therefore, even when two banks merge, borrowers generally continue to have many other lending options. In some cases, local competition actually increases after mergers.

Whether these conclusions apply in markets with only a few firms, where mergers might substantially increase market concentration, is harder to know. But this evidence should still remind antitrust and banking regulators to consider the full range of effects from mergers, not just the impact on concentration per se."

By the Time Governments Are Regulating AI, They’re Regulating the Past

By Mark Jamison of AEI.

"AI is changing fast. And spreading fast. Both are problems for people seeking to regulate it.

Regulation works best when regulators understand what they are regulating. That is not the case for AI. Costs are collapsing, having dropped 1000-fold for large language models since 2023. At the same time, capabilities are expanding, business models are changing, and market leaders are turning over rapidly.

These dynamics create both opportunities and problems. Now almost anyone can use AI to manage their household or launch a business. But, as Bill Gates recently noted, they can also create deep fakes, launch phishing attacks, or break into internet sites, as happened to Hugging Face.

This also makes regulation hard: Rules written for the AI that regulators see today will no longer exist by the time the rules take effect.

Nevertheless, many people want regulations that would control AI. The EU has embraced what it calls comprehensive AI regulation, in which regulators judge the relative riskiness of AI applications and systems and then apply controls ranging from outright prohibitions to light-touch oversight. Some people are calling for mandated surveillance of AI users, restrictions on model capabilities, product standards, and computer code review. Gates recommends an international organization layered on top of national all-of-government regulators to oversee all AI risks people imagine. All of these approaches assume overseers who would control innovation.

While it is true that whenever a technology’s costs fall and its abilities grow, people use it more. Sometimes for evil. When Henry Ford put cars within reach of every family, some families created new businesses, but others became bank robbers. When internet service providers spread access across the country, e-commerce exploded, but so did criminal activity on the dark web. In these instances, successful regulatory responses were not to limit cars or the internet, but to use the technologies for regulatory purposes.

The examples of automobiles and the internet illustrate a path forward for AI policy: Let the technology evolve for the good it can do. At the same time, officials and entrepreneurs can protect citizens by developing their own innovations based on a deep understanding of the technologies and their markets.

Recent research published in the Journal of Economic Perspectives provides insights into AI and its markets. The researchers examined the AI most people use, LLMs. LLMs are growing in complexity, now operating in three layers: The Model Layer, where creators such as OpenAI and Meta design and train LLMs; the Inference Layer, where AI providers like OpenAI and Together AI host and run models to respond to user requests; and the Application Layer, where a large ecosystem of startups and established firms embed LLM capabilities into user-facing applications for accounting, legal, retail, and other services.

Activity in each layer has exploded in multiple directions. The Model Layer grew from 1 model in early 2023 to 668 by the end of 2025. There are curious dynamics in this layer. Open-weight models—which allow users to customize systems for specific tasks—charge users 90% less than do closed weight models. Open-weight providers effectively give away their models after spending billions in development and training. Despite what looks like bad economics, there are over twice as many open-weight models as closed-weight models, 449 versus 219.

Customers in the Model Layer also make choices that appear counter intuitive. Even though open-weight providers charge 90% less than do their closed weight counterparts, customers use closed-weight models more than twice as often.

The complexity doesn’t stop there. At the Inference layer, the number of providers grew from 30 to 90 in 2025. These providers largely host open-weight models and their non-price capabilities vary. Closed-weight model creators are more likely to have vertical relationships at this layer.

The growth and interplay of these two layers illustrate why controls can be counterproductive. They limit innovators’ abilities to experiment, meaning that there would be fewer models in both levels. Fewer models at this stage of development means fewer opportunities for customers to express their preferences. And it is unclear whether the two layers will remain separate.

Model diversity is growing in several ways. Measured by the Artificial Analysis Intelligence Index, 80% of the models fell between 0.1 and 0.29 on the scale at the beginning of 2025. By the end of the year, they fell between 0.22 and 0.61, an increase in spread of over 100%.

Market leadership changes often. In the Application Layer, the market leader for science-oriented models changed eight times in 2025, while the market leader for legal services changed five times.

What does this mean for regulators? The innovators, investors, and customers driving AI are creating tremendous value, estimated to be approaching $1 trillion. Regulatory controls handicap legitimate AI providers and create market opportunities for those less inclined to follow the rules.

The lesson isn’t that government has no role in AI’s evolution. It is that seeking to control AI is counterproductive. AI policy should let the government be a leading AI user without limiting legitimate users of AI. This is more like what good governance has always done: punish harmful conduct and protect citizens by adapting its own capabilities as the world changes."

Mark Cuban and Healthcare Competition

Market competition accomplishes what decades of regulation haven't

By Ryanne Swanson & Raymond J. March of The Independent Institute. 

"Payton Herres successfully underwent heart transplantation surgery as a preteen. A year later, she began taking everolimus—a vital medication used to prevent her body from rejecting the transplant. Her insurance provider soon after denied coverage, leaving her with an indispensable but largely unaffordable prescription.  

Herres’ situation was alarming, but not uncommon. About 30% of Americans find themselves with uncovered treatment despite having health insurance. Unfortunately, medications for rare and/or chronic conditions, in some cases, have no generic alternatives. Not covering expensive but seldom-utilized treatments is an easy way for health insurance providers to cut costs. Unfortunately, these decisions can leave unsuspecting and financially strapped policyholders with few options. 

This is when Mark Cuban stepped in.  

Mark Cuban Cost Plus Drugs, an online pharmacy, helps many people in these situations access affordable medications, even without health insurance. Once unaffordable, his pharmacy now supplies Herres with a 90-day supply for about $300. In comparison, she likely faced bills ranging from $400 to $13,000 per month elsewhere.  

Cuban’s efforts are laudable, and in this case, probably lifesaving. And thankfully for many other patients, other efforts have been just as successful.  

Diabetic patients who need insulin can also face insurance gaps limiting access to life-prolonging medication. Like everolimus, insulin can be alarmingly expensive without coverage. Yet despite political promises and actions to make insulin more affordable, competition has quietly delivered for decades. Perhaps the most recognized example is ReliOn, which is available for about $25 a vial at Walmart pharmacies across the country. In some states, ReliOn is available over the counter.

During the nearly two-year GLP-1 shortage, many patients hoping to treat severe and complex forms of obesity were left without regular access to Ozempic, Mounjaro, and other injectable weight loss treatment options. Fortunately, copycat pharmacies and telehealth providers worked to help patients access generic-like treatments, even as insurance coverage struggled to keep pace with challenging market conditions. In this case, online pharmacies were so effective that they forced brand-name GLP-1 treatments like Zepbound to half their prices during a national shortage. Prior to the copycat and telehealth competition, some patients found themselves facing $1,000 prescription drug costs.  

These and other examples highlight a vital- but often overlooked- lesson about competition. The US healthcare industry is extremely regulated, particularly pharmaceuticals. And despite literal decades of political promises to expand coverage and lower prices, we’ve yet to see reform provide solid and consistent examples of either. Conversely, a relatively small online pharmacy and other unexpected retailers were able to provide what a larger health insurance provider and a torrent of regulations did not or could not- affordable medication. 

Sometimes a small dose of the right treatment is all you need." 

The never-ending ferry tale: Why Washington shouldn’t subsidize ferries

By Steve Swedberg of CEI.

"The Trump administration recently announced $664.8 million in federal grants for ferry infrastructure, including $28.2 million for North Carolina’s Cherry Branch Ferry Terminal. That caught my attention because before joining CEI, I was a transportation fiscal analyst for the North Carolina General Assembly. I had firsthand exposure to the North Carolina Department of Transportation (NCDOT) and its Ferry Division, including touring its vessels and shipyards.

The timing of the grant is particularly curious. North Carolina is now undertaking a performance audit of the Ferry Division, with the State Auditor required to report its findings by January 15, 2027. So as Raleigh asks how to make its ferry system more sustainable, Washington is sending North Carolina $28 million. That raises a more fundamental question: why is Washington paying for ferries?

North Carolina has spent years wrestling with the costs of its ferry system. Several routes historically carried passengers and vehicles without charging fares, while NCDOT reported insufficient funding for capital needs, including millions of dollars in unfunded vessel replacements. A 2017 General Assembly evaluation found opportunities to increase fare collections and reduce costs by adjusting fares and cutting low-demand crossings.

Meanwhile, the state’s ferry fleet has grown older and more expensive to maintain. Many vessels date to the 1980s and 1990s, and the Ferry Division has struggled to keep pace with maintenance needs. Its shipyards lack sufficient capacity to handle all necessary work, which has required NCDOT to turn to outside contractors for some repairs, at taxpayers’ expense.

After decades of subsidized ferry service, North Carolina is finally asking users to pay more. A 2026 law requires NCDOT to begin collecting tolls on all ferry routes by January 1, 2027, although the toll rates have not yet been finalized. That may be a step toward fiscal responsibility, but it comes after the state has accumulated substantial maintenance and replacement needs.

North Carolina isn’t the only state or recent grant recipient in this same boat. Alaska’s Marine Highway System acknowledges that fares alone don’t cover operating costs. Washington State Ferries recovered less than half of its operating costs from fares in 2024. Maine requires state support for half of its ferry operating costs and funds the system’s capital expenses, while Virginia’s Jamestown-Scotland Ferry charges users nothing.

These ferry systems operate under different circumstances and conditions. Yet in all cases, users do not pay the full cost to provide the service.

This is where economist and Nobel Prize winner Ronald Coase’s famous analysis of lighthouses provides enlightenment. The lighthouse was once the textbook example of a service that government supposedly had to provide because charging individual beneficiaries was difficult — the very definition of a public good. Coase challenged that conventional wisdom by showing that privately operated lighthouses existed and that ships could be conveniently charged for their use.

A ferry has an even more straightforward financing mechanism because its beneficiaries are readily identifiable, and passengers and vehicles can be charged directly. If a ferry provides enough value to justify its cost, its users should bear much more of that expense. This “user-pays” principle applies to transportation generally — even the gas tax is a user fee for road use.

And if policymakers believe a route is worth providing despite its inability to cover its costs, they should have to justify that decision to the taxpayers who fund it. There is no reason to make taxpayers in Ohio or Idaho finance a ferry in North Carolina.

The problem gets worse when the administrative state joins the financing equation. The Federal Transit Administration can cover up to 80 percent of eligible ferry capital costs, including vessels, terminals and related infrastructure. When Washington pays most of the capital bill, state policymakers have less reason to ask whether the people benefiting from that investment are willing to finance it.

Without that subsidy, policymakers would face harder questions: Is the route worth operating? How often should it run? What should users pay? How much should taxpayers subsidize? Is there a better way to provide the service? Federal subsidies make it easier for states to avoid answering those questions because someone else is footing most of the bill.

Ferry service may be important to the communities that use it, but that does not make it a federal responsibility. Federal subsidies shift the costs of state and local ferry service onto taxpayers who may never use it. Washington should stop turning local transportation choices into national obligations. Otherwise, the question, “Who pays the ferryman?” will have a simple answer: the taxpayer."

Hit the Brakes Hard on Trusting Government

From Don Boudreaux.

"Here’s a letter to the Wall Street Journal.

Editor:

Peggy Noonan is so frightened of AI that she not only calls on investors to stop funding it, but on government to “hit the brakes hard” on this technology (“Pause AI for Humanity’s Sake,” September 11).

Ms. Noonan imagines AI unleashing a terrible dystopia. Yet what we imagine should be informed by the past. Ms. Noonan’s imagination isn’t. Were she to consult the past, she’d encounter a few realities beyond the obvious one that countless technologies that we today celebrate were, when introduced, reproached as imperiling humanity.

One such reality is that when insiders stir up alarm about their own industries, they’re often angling for regulation that shelters them from competition. As classic case involves AT&T: it warned that telephony would collapse into chaos unless regulated as a natural monopoly. Established bankers played the same game during the Depression, warning that, without government-imposed interest-rate ceilings, ruinous competition for deposits would breed financial crises. In each case the peril lay less in the absence of regulation than in the ‘cures’ – a fact that points to a second and more fundamental reality: a far greater danger than new technology to humanity is government authority to regulate technology.

History gives us every reason to distrust government with the awesome power to determine just how new technologies will develop, and how and when we should be permitted to uses these technologies. In short, history teaches that the wealthiest and safest societies are ones in which innovation is, as Adam Thierer calls it, “permissionless.” If we’re to hit the brakes hard, it should be on the ages-old, fear-fueled impulse to put control of economic forces and technological advances into the hands of politicians and bureaucrats."

Why Congress Shouldn’t Change SNAP’s New Payment Error Approach

By Angela Rachidi of AEI.

"Payment errors in the Supplemental Nutrition Assistance Program (SNAP, formerly food stamps) have received considerable attention in recent months. While much of the debate has revolved around the One Big Beautiful Bill Act’s (OBBBA) new requirements surrounding SNAP payment errors and the impact on states, many have overlooked the people most affected by improper payments—low-income households.

The national SNAP payment error has hovered around 10 percent in recent years, accounting for almost $10 billion in erroneous SNAP benefits yearly. Some of this is fraud, but much of it involves correctable mistakes by participants or government eligibility workers. Thanks to the OBBBA, states are now financially incentivized to lower their payment error rates because states are required to fund a portion of SNAP benefits if they climb above a payment error rate threshold.

Facing the prospect of substantial financial penalties if they do not lower their error rates, states have begun to tighten their eligibility process. As Congress works toward reauthorizing SNAP through a new farm bill, it must resist calls to weaken this cost-sharing requirement or otherwise alter SNAP’s payment error formula.

The OBBBA requires states to contribute a share of total SNAP benefits issued in their state starting in fiscal year (FY) 2028, unless their SNAP payment error rates fall below a 6 percent threshold or they are otherwise exempt. Only 10 of the 53 states or territories met this threshold in FY2025. If a similar trend holds for FY2026, states will be required to pay up to $11 billion collectively in annual SNAP benefit costs in future years. This stands in stark contrast to the period preceding the OBBBA, in which the federal government covered benefit costs entirely, leaving states to face little to no penalty for high payment error rates.

Given this blunt reality, some have called for delaying the payment error cost share or ending it entirely. Some have even suggested that states will discontinue SNAP if the payment error cost share is not delayed. Other arguments have pointed to a lack of symmetry in the payment error calculation itself, which penalizes underpayments. These arguments may fall on sympathetic ears, with Senate Republicans proposing to delay OBBBA’s payment error requirements in an attempt to pass a farm bill. However, these arguments overlook the negative effects that SNAP payment errors have on low-income families. The best approach is to leave the SNAP payment error formula as it is and fully implement the payment error cost-share requirement as OBBBA intended in FY2026.

Delaying or eliminating the cost-sharing requirement accepts the current high level of SNAP payment errors. While it is true that the vast majority of SNAP payment errors are overpayments rather than underpayments, SNAP households are still negatively affected by overpayments. For example, federal regulations require that state agencies establish a claim against households that receive an overpayment, in an attempt to collect on those claims. Once overpayments are discovered, recouping them can happen by reducing the amount of future SNAP benefits, which can put a strain on a household’s budget or potentially discourage them from participating altogether.

Although research suggests that less than 20 percent of overpayments are eventually recovered, this process can disrupt assistance, requiring recipients to submit additional paperwork or lose eligibility. Avoiding overpayments will ensure that families consistently receive the resources that they need to meet their food needs.

Furthermore, while changing the payment error formula could create symmetry in the treatment of overpayments and underpayments, the consequences of underpayments are immediate and directly harmful to low-income households. This is likely why overpayments will always be more common than underpayments. State workers may be particularly sensitive to underpayments due to the immediate consequences they can have for recipients—an important consideration for treating underpayments differently than overpayments. However, state workers also need strong incentives to avoid overpayments. Requiring a state financial contribution when payment errors exceed a certain threshold will save the federal government money, but it will more importantly avoid disrupting SNAP benefits for participating households.

The Agriculture Improvement Act of 2018 has been operating on a one-year extension since FY2023, making Congress overdue to pass a new farm bill. The farm bill not only sets agriculture policy for the country but also authorizes SNAP, including the treatment of payment errors. The House of Representatives passed a new farm bill in April 2026 that maintained OBBBA’s payment error approach, but the Senate failed to pass a companion bill even after agreeing to delay the payment error cost share. The Senate’s failure offers a good opportunity to leave OBBBA’s payment error approach as intended."

Growth through innovation bursts: Why industrial policy should not bet on size

By Giuseppe Berlingieri, Maarten De Ridder, Danial Lashkari and Davide Rigo. Excerpts:

"Industrial policy is back on the agenda across advanced economies, with a growing channelling support towards large incumbent firms on the premise that they are the most capable innovators. This column uses data on French manufacturing firms to argue that this premise deserves scrutiny. Firms become large primarily through occasional, large 'innovation bursts' rather than by innovating at persistently higher rates. The arrival of these bursts involves an element of chance, so a firm's current size says little about how much it will innovate in the future. Policies that entrench the position of incumbents may therefore slow down the churn that sustains aggregate growth."

"This column is not an evaluation of any specific industrial policy programme, and our discussion has abstracted from any strategic and security motives behind much of the current debate. Our results also do not imply that scale is never efficient: some technologies – notably intangible-intensive ones with high fixed and low marginal costs – feature genuine returns to scale and ignoring this would be costly (De Ridder 2019, 2024, Lashkari et al. 2024). Our findings do suggest that policymakers therefore face a trade-off between accommodating such scale effects, and entrenching incumbents whose size reflects the luck of past innovation bursts. An industrial policy that shields incumbents from that displacement risks slowing the growth it aims to promote."