Artificial intelligence (AI) will likely be the most transformative technology of the modern era. What if machines—AI for cognitive tasks and AI plus advanced robots for physical tasks—can perform every task a human can? This essay makes three main points. First, even though US growth rates have been stable at roughly 2 percent per year for 150 years, it is distinctly possible that automating intelligence leads economic growth rates to accelerate. Second, this acceleration is likely to be slowed by the presence of “weak links.” While we each have access to 100 million times more transistors on our desktop computer than people in the 1970s, we are not 100 million times more productive. Computers can invert matrices at lightning speed, but we humans must still decide what matrix to invert, what hypothesis to test, and so on. Accelerating economic growth requires the vast majority of the weak links to be automated away, which delays the large gains. Finally, even though weak links slow the benefits, they may actually speed up the risks. When a chain is only as strong as its weakest link, damaging one link in the chain can be very costly. A powerful AI that is superhuman at software engineering could be misused by a bad actor to do substantial harm by hacking the financial system or a virology lab.
Most empirical economists have encountered the warning that instrumental variables can be “weak,” but the underlying issues—what makes an instrument weak, why weakness distorts inference, and what to do about it—are less widely understood. This article offers an accessible introduction to the weak instruments problem for the common just-identified case of a single endogenous regressor and a single instrument. We explain why the usual two-stage least squares t-ratio and its “±1.96 times the standard error” confidence interval can yield incorrect inferences, much as homoskedasticity-only standard errors do when errors are not homoskedastic. We then describe practical, robust-to-weak-instrument solutions—including the Anderson-Rubin and tF methods—that deliver valid confidence intervals whatever the instrument's true strength, and we offer some do's and don'ts, notably why the popular “F greater than 10” rule has no theoretical justification in this setting.
The Trump administration has enacted a series of significant taxes on imports, including an across-the-board tariff on nearly all imports. Tariffs are now expected to raise nearly 1 percent of GDP in revenue. Given tariffs' growing importance as a source of revenue, it is important to understand their implications for federal finances and the wellbeing of households. This paper describes and reviews current revenue and distributional analyses of tariffs.
The American Economic Association awarded the 2025 John Bates Clark Medal to Stefanie Stantcheva of Harvard University. Her research ranges widely in the field of public economic. It includes theoretical contributions to optimal income taxation, empirical contributions to the study of how income tax rates across countries and states affect the mobility of inventors and the level of innovation, and contributions in the development and execution of on-line surveys to measure respondents' beliefs about economic primitives, such as the distribution of income or the rate of inflation, and the way these beliefs influence policy preferences. She has demonstrated that randomized controlled trials can be embedded within on-line surveys and used to the way informational interventions and other treatments affect economic beliefs and policy preferences.
We use a newly assembled, tariff-line-level dataset spanning the full history of US trade policy to revisit the evolution of tariffs since 1789. We document the institutional shift from Congressional setting to multilateral negotiation, the steady growth in granularity of the tariff code alongside expanding administrative capacity, and the under-appreciated role of specific tariffs, which feature prominently throughout US history and whose ad valorem equivalent moves mechanically with prices. We discuss the implications of this relationship for how we interpret past liberalization episodes and for empirical identification of tariff effects. Finally, we outline how the new data can advance research on the political economy of tariff-setting and on the macroeconomic and distributional consequences of trade policy.
We describe the emerging business-to-business market for large language model (LLM) inference and document key empirical patterns in its supply, pricing, and dynamics, using data from OpenRouter. First, supply has expanded rapidly: the number of commercially available models, model creators, and inference providers has grown sharply, driven heavily by opensource entrants. Second, the price of intelligence has fallen roughly a thousandfold, and opensource models now cost about 90 percent less than comparable closed-source ones. Third, the market is highly dynamic, with frequent turnover among leading models and creators. Fourth, we document substantial horizontal and vertical differentiation: no single model dominates across use cases, and demand for intelligence varies widely across applications. We place these patterns in historical perspective alongside earlier general-purpose technologies.
Global imbalances denote the distribution of countries' current account balances, identically equal to the difference between two forward-looking aggregate variables: national saving and domestic investment. Industrial and trade policies have traditionally not been considered important drivers of aggregate saving or investment, and therefore of current account balances. The former because most industrial policies are small in scope; the latter because permanent tariffs have no intertemporal effect in the textbook model, with an offsetting appreciation of the real exchange rate. The rapidly growing use of both industrial and trade policies in recent years calls for a reassessment. This paper presents a framework to think about the role of both policies. For industrial policy, we make the important distinction between the traditional sector-specific policies via subsidies or other targeted instruments (“micro industrial policy”) and broader policies (“macro industrial policy”) that aim to promote industrial developments and competitiveness through the deployment of more aggregate instruments such as financial repression, foreign reserve accumulation, or capital controls. A key finding is that micro industrial policy tends to increase external balances if it fails to raise aggregate productivity. By contrast, macro industrial policy can, under some conditions, boost the current account, forcing other countries to adjust. Yet, these policies often come at the cost of suppressed domestic consumption and possibly domestic welfare. Our analysis confirms that tariffs are a weak tool to improve current account balances. Finally, traditional macroeconomic drivers—such as fiscal policy, demographics or credit cycles—remain critical drivers of global imbalances, especially for the United States and China.
We develop a simple and intuitive Pigouvian perspective on optimal trade policy. Our approach unifies a wide range of rationales for taxing trade, from the classical optimal tariff argument to contemporary debates about global carbon emissions and geopolitics. We also clarify when trade policy intervention is warranted and when alternative domestic instruments should be used instead.
We describe competition in the physician market, focusing on how entry barriers and substitution possibilities have changed in recent decades. Regulatory caps on medical school seats and residency slots—especially for high-paying specialties—continue to ration entry, generate high returns for those who gain these slots, and direct the most academically accomplished trainees toward lucrative fields. But trained physicians increasingly compete with nurse practitioners, physician assistants, and other mid-level practitioners in the market for patients. Training of these substitutes has expanded far more rapidly than physician supply. We present key facts about the physician pipeline, a conceptual framework linking specialty earnings to entry barriers, and describe the rise of mid-level providers. These facts mean that effective competition policy in physician markets must look beyond conventional concentration measures and focus on the institutions and laws that govern who can provide medical care.
The dollar shortage debate—Paul Samuelson called it “the big open question of our time”—dominated international macroeconomics in the 15 years following the end of World War II. There were two main views regarding its cause: financial frictions that limited capital flows to Western Europe (Kindleberger); and overvalued fixed exchange rates versus the US dollar (Friedman). According to Kindleberger the dollar shortage was attenuated by two real factors that contributed to current account deficits: a large technological gap between the United States and Europe; and European impatience to improve living standards. Kindleberger believed that the current account deficit would prove chronic because of the persistence of the productivity gap, a view that was challenged by Bloomfield who argued that it would dissipate through income growth in Europe. We argue that Kindelberger’s analytical framework is closely connected to the modern intertemporal approach to current account determination; and, also, that the international reserve function of the US dollar—the Triffin dilemma—did not play a role in the dollar shortage.
The United States relies primarily on private health insurance markets, yet these markets are highly concentrated and becoming more so over time. We document concentration across commercial, Medicare Advantage, and Medicaid markets. We then examine how asymmetric information—particularly adverse selection—interacts with market power to shape premiums, plan design, and consumer welfare. Empirical evidence confirms that insurer consolidation raises premiums. We discuss how antitrust enforcement, risk adjustment, regulation, and informational interventions shape competition and consumer welfare in these markets.
We assess the evolving role of competition in Medicare Advantage and its implications for beneficiary welfare. We describe how competition from the public option, traditional Medicare, and other private insurers within Medicare Advantage act as substitutes in incentivizing plans to deliver value. We show that while historically the choice between traditional Medicare and Medicare Advantage provided a vital competitive dynamic, traditional Medicare's strength as a competitor has declined significantly, driven by generous payments favoring private plans. Consequently, the burden of ensuring value for enrollees has shifted to competition within the Medicare Advantage market. While county-level competition among private insurers has increased, this growth is primarily driven by the expansion of large national carriers rather than new entrants. Insurers still wield substantial market power due to significant barriers to entry, raising concerns about the ability of the program to incentivize private insurers to use public dollars to maximize value for beneficiaries.
Medicaid is one of the largest public programs in the United States—providing health insurance to over 75 million low-income Americans—and over three quarters of its enrollees receive care via private “managed care” insurers. In this article, we make three central points about the economics of contracting out Medicaid to private insurers. First, the empirical evidence on Medicaid privatization is mixed: contracting out has not meaningfully reduced public costs or improved quality of care. Second, we propose a framework, which we call “procured competition,” to describe the unique structure of Medicaid managed care as a hybrid of public procurement and regulated competition. Third, we discuss the key policy levers across procurement, competition, and consumer choice in this model. Throughout, we highlight open research questions, arguing that the enormous variation in how states design these programs—combined with limited evidence on what works—represents a promising area for high-impact scholarship.
Consolidation in the last few decades has reshaped the organization and structure of US health care markets, among both providers and insurers. Nearly all US hospital and insurer markets exceed established regulatory thresholds for competitive markets, and over half of physicians are now employed by a hospital or health system, which can increase spending for patients, payers, and taxpayers. As one example, Figure 1 shows that market concentration is the norm in the hospital industry. Increased supply-side concentration can alter the balance of negotiations between providers and insurers, and unsurprisingly, prices for patients with commercial insurance are approximately 2.5 times the prices paid by those with public insurance. High and variable prices demonstrate a minimal link with higher quality, and the United States leads peer nations in health care spending. Over 40 percent of Americans with insurance report difficulty managing health care expenses, and a nearly equal number carry some level of medical debt (Sparks et al. 2026). Health care consolidation trends therefore sit uncomfortably in the midst of these consumer realities and ongoing national debates over an "affordability crisis" (Saad and Brenan 2025).
This essay, commissioned to serve as an introduction to the JEP symposium on current competition in health care, provides a historical perspective on the role of both competition and regulation in the financing and delivery of health services since the implementation of Medicare and Medicaid in the mid-1960s. At the beginning of this period, few could perceive a role for competition in healthcare given the key role played by physicians in providing and ordering care and concerns that lower prices might signal lower quality. Initial attempts to slow rapidly rising costs involved various regulatory tools, but over time, regulation increasingly incorporated incentives for providers, to control costs. Competitive approaches began to develop in the late 1970s, in part reflecting broad changes in the nation’s political culture. Competitive approaches are now are quite widespread, but regulation plays an important role in the structuring of competition and in addressing areas where competition is seen as having less potential.
This article examines the economics of paid sick leave from both theoretical and empirical perspectives. Research on paid sick leave has evolved dynamically over the last decade, primarily driven by the spread of US sick pay mandates, which have increased paid sick leave access from 63 percent to 77 percent in all US jobs. We begin by discussing the economic rationales for government regulation of paid sick leave, particularly the negative externalities associated with contagious diseases when individuals work while sick. After that, we discuss the key trade-offs in the general design of paid sick leave schemes, along with the trade-offs when setting specific policy parameters. Finally, we review economic modeling approaches to study optimal paid sick leave policies.
Alain Enthoven (2018) once wrote: "Universal health insurance is not synonymous with 'single payer'." Instead, many high-income countries implement their policy of universal health insurance by individual health insurance in combination with regulated or "managed" competition among insurers to finance health care and protect enrollees against the financial risk of illness. In varying degrees and depending on the country, insurers are also expected to limit health care costs, encourage access to cost-effective care for both the sick and the healthy, charge community-rated premiums, maintain open enrollment, offer choice of the form and extent of insurance coverage, foster innovation in health care delivery, undertake population-based preventive programs, and promote coordination of care. Some of these objectives run counter to the short-term business interests of competing health insurers and must be enforced, either by regulation or by pressure to adhere to social norms. An individual health insurance market may seem an odd choice to implement social health policy. After all, insurance markets are notoriously subject to market
For people with private health insurance in the United States, contracts between insurers and providers are important to fostering health care competition and improving efficiency. However, insurer-provider contract provisions do not always advance competition and consumer welfare. This essay discusses the contracting strategies used by insurers to increase competition, and four anticompetitive contract terms: anti-tiering or anti-steering, all-or-nothing, most favored nation, and gag clauses, that may be used by dominant health systems to protect themselves from competition. I conclude with a discussion of policy responses that can be used to address provider use of anticompetitive clauses and that can reduce the negative impacts of provider market power. Understanding anticompetitive contract provisions and the potential policy responses to limit their impact is critical to health care competition.
The AKM model introduced by Abowd, Kramarz and Margolis (1999) has become a workhorse to study worker and firm heterogeneity, and to understand the sources of wage dispersion in the labor market using linked employer-employee data. In this article, we introduce the model and estimator, discuss some best practices for estimation, and review some empirical findings on the role of worker and firm heterogeneity in wage dispersion. While the AKM methodology has proven useful to analyze a host of questions in a variety of settings within labor economics and beyond, we also point to the need for methodological developments.
I assess the effect of continued sub-replacement fertility on age-adjusted consumption per capita. Channels assessed include transfers from working-age adults to children and the elderly, the effect of the labor force growth rate on required capital investment, sustainability of government debt, the interaction of population size with fixed natural resources (including a clean environment), and the effect of population size on the speed of technological progress. To isolate the effect of low fertility from other ongoing demographic changes, I use simulation models as well as projections from the United Nations and Social Security Administration that vary fertility rates while holding other factors constant. My main finding is that the impact of low fertility is likely to be negative but small. In addition, this negative impact arrives only after a long adjustment period. An increase in fertility back to the replacement rate would lower the standard of living for several decades.
