This study examines how the American Medical Association (AMA) helped shape the development of the U.S. health insurance system in the critical period after World War II. Working with the political public relations firm Campaigns, Inc., the AMA launched a nationwide campaign to weaken support for National Health Insurance by framing it as “socialized medicine,” while simultaneously enrolling people in private health insurance plans to shift demand away from a public alternative. Drawing on newly assembled archival data, we find that greater exposure to the campaign explains about 20% of the rise in private health insurance enrollment and a comparable decline in public support for a national program. The campaign also appears to have influenced policymaking through coordinated messaging, resolutions passed by civic organizations, congressional rhetoric, and political donations. These findings suggest that the rise of private health insurance in the United States was not solely due to macroeconomic forces or collective bargaining; rather it was also enabled by a strategic, interest group-financed effort to shape citizen views and influence policy.

We introduce an empirical framework for valuing markets in environmental offsets. Using newly collected data on wetland conservation and offsets, we apply this framework to evaluate a set of decentralized markets in Florida, where land developers purchase offsets from long-lived producers who restore wetlands over time. We find offsets led to substantial private gains from trade, creating $2.4 billion of net surplus from 1995 to 2020 relative to direct conservation. Offset trading also generated new hydrological externalities. A locally differentiated Pigouvian tax would have prevented $1.6 billion of new flood damage while preserving more than two-thirds of the private gains from trade. (JEL D47, D62, H23, Q24, Q54, Q57, R14)

The influence of on-the-job training and supervisors, especially in high-stakes settings like policing, is poorly understood. Examining a central behavior in the debate surrounding police reform, we investigate the impact of a field training officer (FTO) on a recruit’s use of force. Leveraging a setting with conditional as-good-as-random assignment, we demonstrate a causal link between FTO and recruit use of force. A 1 standard deviation increase in FTO force propensity leads to a 14 to 18 percent rise in recruit force, persisting for at least two years. This underscores field training’s impact and reveals a promising avenue for reform. (JEL D91, J24, J45, K42, M53)

We show that bank shocks to firms propagate along the production network with stronger upstream than downstream effects. Our identification relies on (i) administrative datasets from Spain covering supplier-customer transactions and bank loans, (ii) bank credit supply shocks from the global financial crisis, and (iii) a general equilibrium model of a production network with financial frictions, estimated structurally. We find network propagation amplifies the impact of bank shocks on GDP growth by nearly 50 percent. Moreover, bank shocks to firms’ distant suppliers and customers contribute similarly to this aggregate effect as bank shocks to firms’ direct customers and suppliers. (JEL D22, D85, E23, G01, G21, G32, L14)

This paper shows that the wage assimilation of immigrants is the result of the intricate interplay between individual skill accumulation and dynamic labor market equilibrium effects. When immigrants and natives are imperfect substitutes, rising immigrant inflows widen the wage gap between them. Using a production function framework in which workers supply both general and host-country-specific skills, we show that this labor market competition channel explains about one-fifth of the large increase in the average immigrant–native wage gap across arrival cohorts in the United States since the 1960s. The results further reveal substantial heterogeneity across different groups of immigrants. (JEL J22, J23, J24, J31, J61, K37, O33)

We study social preferences in settings where someone who chooses on behalf of others knows how those individuals rank the available options but may lack cardinal information concerning those comparisons. Contrary to majoritarian principles, most people place more weight on preventing least preferred outcomes for others than on enabling most preferred outcomes. Ranks matter both intrinsically and because they provide a basis for inferring cardinal utility. Ordinal aggregation principles are stable across domains and countries with divergent political traditions. Designing attractive social choice mechanisms is challenging in practice partly because aggregation principles that make manipulation difficult yield outcomes people consider normatively unappealing. (JEL C91, D71, D72)

Weekly lotteries determine which politicians ask the UK prime minister a question in front of a male-dominated, noisy chamber. Lottery winners receive 4 percent higher vote margin in the next election, but women are 12 percent less likely to submit questions than same-cohort men. The gender gap does not close with lottery-induced experience asking a question, but it closes after a format change, with questions asked to a smaller, quieter audience. The switch differentially draws in women with quieter voices. Our findings support institutional change, rather than experience, as a response to gender gaps in adversarial settings like the UK Parliament. (JEL D44, D72, J16)

A common interpretation of Pareto-efficient policies is that, for some cardinal utility representations of preferences, they maximize utilitarian welfare. We show in the context of income taxation that such cardinalizations are often extreme, requiring unbounded curvature of utility with respect to consumption. Taxes can be justified as utilitarian without these extreme cardinalizations if and only if revenues are decreasing and concave in a class of narrowly targeted tax cuts. We reformulate this condition as a sufficient-statistics test. The test fails whenever elasticities of taxable income are too heterogeneous within some income level, as we argue is empirically likely. (JEL D81, H21, H23, H24, J22, J31)

Using linked employer-employee data from Brazil, we document a significant gender pay gap, which is largely attributed to women working at lower-paying employers. To interpret this fact, we develop an equilibrium search model with endogenous firm pay, amenities, and hiring. We provide a constructive proof of identification of all model parameters. The estimated model suggests that amenities are important for both men and women, and that compensating differentials account for half of the gender pay gap. Equal treatment policies partly close gender gaps but are not output- or welfare-improving. (JEL E24, J16, J23, J31, J32, M51, O15)

We use Danish administrative data to examine the effects of parental death on labor market outcomes. Leveraging the timing of sudden, first parental deaths and a matched-control difference-in-differences strategy, we find that men’s earnings decline by 2 percent, while women’s earnings decline by 3 percent following a parental death. Both women and men experience mental health deterioration, leading to increased use of psychological assistance and prescriptions for mental health conditions and opioids. Women with young children experience a comparatively larger earnings decline (around 4 percent) likely due to the loss of informal childcare. (JEL D91, I12, J13, J16, J31)

How does information transmission change when it requires attracting the attention of receivers? This paper combines an experiment that varies freelance professionals’ incentives to attract attention about scientific findings, with several online experiments that exogenously expose receivers to the content created. Attention incentives lead to significantly less information being transmitted, but not more factually inaccurate content. These incentives increase information demand and the knowledge of interested receivers. However, among the majority of receivers who do not demand more information, attention incentives lower knowledge and increase biases in beliefs, revealing a channel through which misperceptions can arise: missing information. (JEL C91, D83, D91)

I study racial disparities in the criminal justice system by analyzing abnormal bunching in the distribution of crack-cocaine amounts used in federal sentencing. I compare cases sentenced before and after the Fair Sentencing Act, a 2010 law that changed the 10-year mandatory minimum threshold for crack-cocaine from 50g to 280g. First, I find that after 2010, there is a sharp increase in the fraction of cases sentenced at 280g (the point that now triggers a 10-year mandatory minimum), and that this increase is disproportionately large for black and Hispanic offenders. I then explore several possible explanations for the observed racial disparities, including racial discrimination that occurs after entry into the criminal justice system. I analyze data from multiple stages in the criminal justice system and find that the increased bunching for minority offenders is driven by prosecutorial discretion, specifically as used by about 20-30% of prosecutors. Moreover, the fraction of cases at 280g falls in 2013 when evidentiary standards become stricter. Finally, the racial disparity in the increase cannot be explained by differences in education, sex, age, criminal history, seized drug amount, or other elements of the crime, but it can be largely explained by a measure of state-level racial animus. These results shed light on the role of prosecutorial discretion and racial discrimination as causes of racial disparities in sentencing.

This paper develops the uniform asymptotic theory for local projection (LP) regression when the true lag order of the model is unknown and potentially infinite. The theory allows for varying degrees of persistence in the data, growing response horizons, and general conditionally heteroskedastic martingale-difference shocks. Based on the theory, we make two main contributions. First, we show that LPs can achieve semiparametric efficiency at a given horizon under classical assumptions on the data, provided that the controlled lag order diverges. Thus the commonly perceived efficiency loss of LPs can become asymptotically negligible with many controls. Second, we propose LP-based inference procedures for (level and cumulated) impulse responses that possess robustness properties not shared by existing methods. Inference methods using two distinct standard errors are considered. The uniform validity for the first method depends on a zero fourth-order cumulant condition on shocks, while that of the second holds more generally for conditionally heteroskedastic martingale-difference shocks. We propose a bootstrap procedure that improves finite-sample performance and extend the standard error construction to structural responses.

I study linear panel data models with predetermined regressors (such as lagged dependent variables) where coefficients are individual-specific, allowing for heterogeneity in the effects of the regressors on the dependent variable. I show that the model is not point-identified in a short panel context but rather partially identified, and I characterize the identified sets for the mean, variance, and CDF of the coefficient distribution. This characterization is general, accommodating discrete, continuous, and unbounded data, and it leads to computationally tractable estimation and inference procedures. I apply the method to study lifecycle earnings dynamics among U.S. households using the Panel Study of Income Dynamics (PSID) dataset. The results suggest the presence of unobserved heterogeneity in earnings persistence, implying that households face varying levels of earnings risk which, in turn, contribute to heterogeneity in their consumption and savings behaviors.

This article surveys the relevant existing literature that can help researchers and policymakers understand the drivers of competition in markets that provide artificial intelligence (AI) products. The focus is on three broad markets: training data, input data, and AI predictions. A recurring theme is that the mobility of data across firm boundaries, including the operation of data markets, is central to the emergence and persistence of market power, but its force depends on interacting bottlenecks such as compute, attention scarcity, platform design, and model openness.

We survey a growing literature on correlated learning—that is, how information from one choice changes beliefs about others when outcomes are correlated. The core modeling innovation is to represent the unknown mapping from choices to outcomes as the realized path of a stochastic process, most commonly the Brownian motion. We show how the framework has been applied to four canonical economic problems in which correlated learning is key but understudied: ( a ) search and experimentation, ( b ) communication, ( c ) innovation and market competition, and ( d ) attribute problems. We review emerging empirical and experimental evidence on correlated learning and outline new theoretical and methodological directions.

We provide an overview of the explanations for the relative lack of state formation historically in Africa. In doing so, we systematically document for the first time the extent to which Africa was politically decentralized, calculating that in 1880 there were probably 45,000 independent polities that were rarely organized on ethnic lines. At most 2% of these could be classified as states. We advance a new argument for this extreme political decentralization positing that African societies were deliberately organized to prevent centralization from emerging. In this they were successful. We point out some key aspects of African societies that helped them to manage this equilibrium. We also emphasize how the organization of the economy was subservient to these political goals.

Gender-based violence (GBV) and harassment remain widespread, with far-reaching consequences. This review synthesizes the emerging economics literature on GBV, highlighting its methodological challenges, economic impacts, and policy responses. We first examine the difficulties of measuring GBV, including underreporting, definitional variation, and the limits of administrative versus survey data. We then survey evidence on the economic costs of GBV, which span reduced employment, earnings, and educational attainment for survivors as well as broader harms to families, peers, firms, and societies. Finally, we review evidence on prevention and mitigation strategies, including deterrence through sanctions, shifts in workplace and social norms, and survivor support programs. The literature shows that the economics costs of GBV are large, persistent, and measurable, underscoring the urgency of rigorous policy interventions and continued research.

A growing body of evidence shows that businesses in developing economies are systematically smaller, grow more slowly, and exhibit lower turnover than those in advanced economies. These patterns are driven in part by nonemployer and micro businesses, which absorb the bulk of workers in low-income settings. This article reviews macro development research that extends the standard Lucas–Hopenhayn framework to account for the smaller size and more limited dynamism of businesses in poorer economies. Distortions that disproportionately affect high-productivity firms, together with lagging technologies, emerge as central explanatory forces, though they often fall short of replicating the empirical size-to-GDP elasticity. Incorporating nonemployers appears to improve the model's ability to match several dimensions of the data. Identifying actionable sources of distortions and technology gaps and combining firm-level data with individual-level sources are highlighted as additional promising avenues to improve the profession's understanding of sources of the development problem.

This article uses inflation expectations to investigate the mechanisms that linked supply and demand shocks to inflation outcomes during 2021–2024. It describes several theoretical mechanisms through which shocks led to inflation, highlighting the role of expectations in this process. It uses multiple sources of expectations data for the United States, Euro area, and United Kingdom to evaluate each of these channels. Finally, it surveys the literature that has used expectations data to make sense of the 2021–2024 inflation surge. The article applies the results from this investigation to assess how well-anchored inflation expectations were during the surge and at the end of it.

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.

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. Increased supply-side concentration can alter the balance of negotiations between providers and insurers. Prices for patients with commercial insurance are approximately 2.5 times the prices paid by those with public insurance. High and variable prices have minimal link with higher quality, and the United States leads peer nations in health care spending. These dynamics have created ongoing national debates over an “affordability crisis” and generates frustrations with the US health care system. This article discusses sources of rising health care spending and potential policy solutions.

Many high-income countries implement their policy of universal health insurance by individual health insurance in combination with regulated competition among insurers. Supported by public intervention, regulated competition can, in principle, address market failures in health insurance and smooth out some inequities in the financial consequences of ill health and in the ability to pay for health insurance. We compare the national systems in Germany, the Netherlands, and Switzerland to the US Marketplaces, all of which use versions of regulated competition. While they show many similarities (for example, open enrollment, community-rated premiums with subsidies, comprehensive benefit package, risk adjustment), we focus on three major differences and their implications for market functioning: (1) mandatory and universal versus voluntary and partial (applying to only one sector of health insurance); (2) greater or lesser profit orientation of insurers; and (3) reliance on markets or regulation to contain costs.

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.

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.

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.

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.

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.

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.

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.

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.

We examine the impact of the free supply of diphtheria antitoxin, the first effective medical treatment for an infectious disease, on the historical health transition in Massachusetts. Using newly collected municipality-level data on the distribution of antitoxin and information from over 1.5 million death certificates from 1880 to 1914, we find that the rapid availability of antitoxin treatment significantly increased life expectancy at young ages. Our findings suggest that medicine, combined with an effective public health policy, played a more important role in improving life expectancy in the early twentieth century than previously thought. (JEL H75, I12, I18, J13, N31)

We show that exposure to extreme temperatures significantly increases international migration from El Salvador, where nearly a quarter of the population lives in the United States. Extreme temperatures reduce corn yields, leading producers to decrease their use of postharvest inputs and demand for agricultural workers. These income losses, combined with established US migration networks, increase emigration. Our findings highlight how international migration serves as a response to extreme temperatures when destination networks are strong and migration remains financially feasible. This pattern is not unique to El Salvador: Roughly 30 million farms globally are in low-income settings with access to remittances. (JEL F24, J15, J23, J43, O15, Q12, Q54)

Many routine daily activities—such as cooking and commuting—cause large recurring pollution spikes that may impact health without significantly affecting average exposure. We study pollution spikes by combining experimental variation in cooking technology with high-frequency data on individual pollution exposure and time-use in Kenya. Improved cookstoves reduce PM2.5 spikes while cooking by 51.3 μg/m 3 (41 percent) and cause a 0.24 standard deviation reduction in self-reported respiratory symptoms. However, even after more than three years of daily use, we find no clinical health improvements, possibly because we detect no impact on average exposure. Clinical health improvements may require reductions in ambient concentrations. (JEL I12, O12, O13, Q51, Q53)

We study the role of international financial integration in buffering natural disaster shocks, using a large sample of advanced and emerging economies. Natural disasters are largely unpredictable and unrelated to the state of financial integration. We document that integration improves the absorption of such shocks: Output, consumption, and investment are significantly higher after a natural disaster in states with high than in states with low integration. The benefits are most clear for advanced economies. Emerging markets tend to profit from financial integration, too, but the estimates are less precise unless we condition on institutional quality or consider only debt assets. (JEL E21, E22, E23, F32, F33, F34, Q54)

This paper develops a structural model of endogenous product attribute choice in the presence of indirect network effects to study electric vehicle (EV) subsidies. Using data on the German EV market, I find that a support scheme almost doubled EV sales but substantially affected EVs’ price and driving range. These adjustments create a trade-off between optimizing different policy objectives when designing subsidies. Large purchase subsidies maximize EV sales, whereas large charging station subsidies maximize consumer and total surplus. The results suggest that maximizing EV sales can lead to unintended consequences in the form of price and range adjustments. (JEL D12, D22, D85, H25, L14, L62, R41)

A large literature has documented that fiscal policy is procyclical in emerging markets/developing countries and acyclical/countercyclical in advanced economies. This paper analyzes fiscal procyclicality in commodity-exporting countries. The paper makes two novel contributions. First, based on the “when it rains, it pours” phenomenon (that is, contractionary fiscal policy amplifies the business cycle), the paper shows that, on average, government spending magnifies the business cycle by 21 percent of the initial drop in output following a fall in commodity prices. Second, the paper estimates the welfare costs of fiscal procyclicality at 36 percent of the commodity business cycle. (JEL E32, E62, F14, H50, O19, Q02)

Incarceration is often justified by a defendant’s risk of future crime. To what extent do biased beliefs about predictors of crime distort incarceration decisions? We survey prosecutors about how violent rearrest rates vary by defendant age and criminal history. Surveyed prosecutors make systematic errors: They underestimate the decline in rearrest with age and overestimate the increase with criminal history. By linking prosecutors’ beliefs to their quasi-randomly assigned cases, we show that prosecutors’ beliefs predict incarceration patterns by defendant age and criminal history in their cases. Finally, we find that prosecutors with more accurate beliefs simultaneously reduce violent rearrest and incarceration. (JEL D83, K14, K41, K42)

We examine whether vertical integration of hospitals and skilled nursing facilities (SNFs) could lessen competition by foreclosing rival SNFs’ access to lucrative referrals. We find that it could: Among integrated providers, a 1 percent increase in SNF reimbursement for a given patient discharged from the upstream hospital increases the self-referral rate to the hospital’s downstream SNF(s) by 1.8 percent. We find no evidence of offsetting benefits for patients and payers: These increased self-referrals have an imprecisely estimated zero effect on patient outcomes and Medicare spending. (JEL G34, I11, I13, J14, L14, L22)

We estimate the direct and spillover effects of cannabis legalization on longstanding racial disparities in criminal justice outcomes. We find that legalization reduces cannabis possession and sales arrests for White and Black populations, narrowing but not eliminating disparities. We also find spillover increases in hospitalizations involving cannabis and other illegal drugs. However, spillovers on arrests, incarcerations, and crimes involving serious violent or property offenses are insignificant or even decrease. Other illegal drug sales arrests decrease across populations, while illegal drug incarcerations decrease only among White populations. Spillovers on other low-level offenses are insignificant for White but mixed for Black populations. (JEL I12, J15, K14, K41, K42)

We study the effect of stricter enforcement of the dividend-withholding tax (DWT). We focus on a 2016 Danish enforcement reform and compare Denmark to its Nordic neighbors. Throughout the Nordic stock markets, shares on loan spike sharply around dividend dates. These spikes are consistent with abuse of the DWT system. Postreform, spikes in Denmark disappear, and annual DWT revenue increases by 130 percent. Enforcement does not harm the investment climate as measured by Danish stock returns, investment rate, and dividend yield. (JEL G18, G35, G38, H26, K22, K34)

We estimate the causal impacts of universal preschool by leveraging a quasi-experimental design based on Israel’s implementation of free public preschool for children ages 3 and 4 beginning in September 1999. We focus on the Arab population, who were the main beneficiaries of the first phase of the law’s implementation. Using a difference-in-differences (DID) research design, we find that universal preschool enhanced individuals’ academic performance from elementary school through high school, improved the learning environment, and increased postsecondary enrollment. Additional benefits include reduced juvenile delinquency among males and decreased early marriage among females. (JEL I21, I24, I28, J15, J16)

We study rental income tax compliance using novel third-party information and a large-scale randomized field experiment. The third-party information combines register data on the ownership and occupancy of apartments. The RCT used this new third-party information in the targeting and design of experimental treatments, and increased the propensity to report rental income and the amount of reported rental income net of expenses. Our research design also allows us to identify members of ownership networks and analyze spillover effects in tax enforcement between them. We find positive reporting spillovers. We do not find evidence of real effects on asset market transactions. (JEL C93, D83, H26, K34, R31)

I investigate the intrahousehold labor and resource allocation consequences of an employment guarantee targeting rural households in India. The guarantee insures household earnings, replacing women as added workers and shutting down a motive for saving. Despite sizable program-job take-up, the guarantee decreases participation in other working activities and, thus, labor force participation of married women and total time worked by their husbands. The guarantee accounts for up to 30 percent of a recent countrywide decrease in rural female labor force participation. Though it increases household consumption, the guarantee reduces the command of women’s household earnings and, thereby, their well-being. (JEL D13, G51, I32, J16, J22, J68, O12)

I study the effects of charters on student racial segregation, identifying a novel mechanism: the assignment of White and non-White students to regular classrooms within their school-grade. Exploiting almost 100 entries of elementary charters in North Carolina from 1997 to 2015, I show that the announcement of an opening significantly increases classroom segregation within public schools nearby, relative to schools farther away, especially within non-majority-White schools and for charter openings that enroll a relatively large share of White students. Accounting for classrooms is unlikely to reverse the literature’s conclusion that the charter effects on student segregation are modest in magnitude. (JEL H75, I21, I24, I28, J15)

We evaluate a tax reform in Ecuador that introduced generous deductions from personal income taxes (PIT), encouraging consumers to request receipts. The reform addresses tax evasion by targeting small self-employed businesses that mainly sell goods or services not subject to value-added taxes (VAT) but that often evade income taxes. Exploiting plausibly exogenous variation in receipt demand due to the distribution of taxpayers across regions and professions, we find significant increases in reported profits among self-employed businesses exposed to the reform. We document spillover effects on VAT. Our net-revenue impact analysis suggests the additional tax payments outweigh the foregone tax revenue. (JEL H24, H25, H26, J23, K34, O17)

Financial crimes are costly to society but less severely punished than other nonviolent crimes. We investigate whether prison sentences reduce financial crimes. Using random assignment of judges in Finland to identify causal impacts, we find a prison sentence reduces defendant reoffending by 42.9 percentage points three years postsentencing. Given prior evidence of financial misconduct “contagion,” we also explore spillovers on colleagues. A prison sentence reduces the likelihood that a financial crime defendant’s colleagues commit crimes by 27 percentage points, suggesting broader deterrent effects of harsher punishments, but only for fraud cases. Last, we show financial crimes are not victimless crimes. (JEL K14, K22, K41, K42)

States sometimes back rebellions abroad to signal resolve. We study this reputation-building logic in international relations, focusing on co-ethnic links between countries as an objective source of variation in a state‚s incentives to demonstrate resolve. We formally derive two interconnected predictions from the mechanism: (a) a state is more likely to endorse the uprising of a foreign group when facing a larger audience, resulting in (b) greater political inclusion for the group. We build a comprehensive panel dataset of co-ethnic rebellion sponsorship, and find evidence consistent with both predictions.

We conducted a randomized trial in Indonesia to study how information about labor intermediary quality shapes migration behavior. All else equal, intermediary-specific quality disclosure reduces the migration rate, cutting use of low-quality providers. Those who do migrate receive better pre-departure preparation and have improved experiences abroad. These results are not driven by changes in beliefs; nor does selection explain improved outcomes for those who migrate with quality disclosure. Our findings are consistent with an increase in the option value of search: with better ability to screen offers, workers search longer, select better intermediaries, and have better migration experiences.

Health matters for marital outcomes, but health information may remain concealed until marriage. Our matching model, which incorporates socioeconomic status (SES) and health, predicts that the removal of health information should shift sorting toward SES, potentially reducing child health and welfare, particularly for those with low SES. We empirically examine this in the context of rural China, following the repeal of compulsory premarital health examinations (PHE). Our difference-in-differences estimation, which compares provinces with varying levels of exposure based on pre-policy PHE rates, confirms a larger shift in sorting patterns in provinces with higher treatment intensity. The decrease in health-based assortative matching negatively affects child health outcomes, which is followed by a decline in postmarital subjective well-being. Women and low-SES individuals experience larger losses than their counterparts within the same highly affected provinces, highlighting persistent gender and socioeconomic disparities.

Using data from the euro area SAFE, a novel survey of firms’ inflation expectations including a randomized controlled trial (RCT), we show that firms’ inflation expectations exhibit significant heterogeneity, challenging the predictions of full-information rational expectations models. At the same time, we document that firms form beliefs consistent with rational Bayesian updating under incomplete information, with geographic location playing a dominant role in shaping expectations. Firms extrapolate from regional and national inflation to form euro area inflation expectations. A basic “Lucas island” model calibrated to euro area data replicates key empirical moments and highlights the structural “pass-through” from national to aggregate expectations. Our findings underscore challenges in anchoring inflation expectations in a heterogeneous monetary union.

This paper proposes a new mixed vector autoregression (MVAR) model to examine the relationship between aggregate time series and functional variables in a multivariate setting. The model facilitates a reexamination of the oil‐stock price nexus by estimating the effects of demand and supply shocks from the global market for crude oil on the entire distribution of U.S. stock returns since the late 1980s. We show that the MVAR effectively extracts information from the returns distribution that is more relevant for understanding the oil‐stock price nexus beyond simply looking at the first few moments. Using novel functional impulse response functions (FIRFs), we find that oil market demand shocks tend to increase returns, while both demand and supply shocks reduce volatility, and have an asymmetric effect on the returns distribution as a whole. In a value‐at‐risk (VaR) analysis, we also find that the oil market contains important information that reduces expected loss, and that the response of VaR to the oil market demand and supply shocks has changed over time.

We propose an efficient, reliable, and interpretable global solution method, the Deep learning‐based algorithm for Heterogeneous Agent Models (DeepHAM) , for solving high‐dimensional heterogeneous agent models with aggregate shocks. The state distribution is approximately represented by a set of optimal generalized moments. Deep neural networks are used to approximate the value and policy functions, and the objective is optimized over directly simulated paths. In addition to being an accurate global solver, this method has three additional features. First, it is computationally efficient in solving complex heterogeneous agent models, and it does not suffer from the curse of dimensionality. Second, it provides a general and interpretable representation of the distribution over individual states, which is crucial in addressing the classical question of whether and how heterogeneity matters in macroeconomics. Third, it solves the constrained efficiency problem as easily as it solves the competitive equilibrium, which opens up new possibilities for normative studies. As a new application, we study constrained efficiency in heterogeneous agent models with aggregate shocks. We find that in the presence of aggregate risk, a utilitarian planner would raise aggregate capital for redistribution less than in absence of it because poor households do more precautionary savings and thus rely less on labor income.

Traditional dynamic discrete choice model—Conditional Choice Probability estimator (DDCM‐CCP) literature considered identification using the likelihood of longitudinal choice only. However, such an approach has a limitation in identifying flexible dynamics for latent state due to the discrete and typically small‐dimensional nature of choice. This paper extends this literature to utilize imperfect measurements, called proxies, for a latent discrete state. I first show that proxies improve identification and discuss how survey design on proxies affects identification conditions. I then extend the estimator from Arcidiacono and Miller (2011) to pool information from an unbalanced panel of noisy proxies, enabling estimation of more flexible latent state dynamics than Markov chains. As an application, I estimate a dynamic model of labor supply and mental health, where dynamic mental health only imperfectly observed—plays a central role. The results reveal more complex dynamics than a standard Markov chain.

I build a model of many‐to‐one matching with nontransferable utility involving many agents on both sides of the market, for example, workers and firms. Under parsimonious assumptions on preferences and assuming that matches are stable, I provide a tractable asymptotic characterization of the joint distribution of match characteristics. I find that one can identify the joint surplus of a match, but cannot separately identify workers' and firms' preferences from data on realized matches. Within‐firm variation in matched worker characteristics, only available in many‐to‐one matching data, can help identifying and estimating unobserved firm heterogeneity in the surplus function.

This paper studies approximation error in the quasilinear utility model. Error arises because individuals do not perfectly optimize, and instead satisfice. We investigate the consequences of individual satisficing for modeling aggregate demand, providing an approximate aggregation theorem. We present a simple method for statistical inference on the minimal level of satisficing needed to explain aggregate data. In an illustrative application to scanner panel data, we find that individual‐level data require a nontrivial degree of satisficing, but aggregate data admit a representative agent that maximizes a quasilinear utility function.

We show that U.S. shale oil producers exhibit a high degree of short‐run price responsiveness, primarily through the timing of well completions and refracturing. Using a novel monthly well‐level panel covering over 120,000 shale wells across ten states from 2005 to 2019, we document significant supply adjustments to price signals. The response varies significantly across states and firm types, highlighting the importance of accounting for micro‐level heterogeneity in production behavior. Mechanisms include accelerating completion of drilled but uncompleted wells and refracturing older wells when forward‐looking price signals are favorable. These findings challenge the common assumption of short‐run supply inelasticity and call for oil market models that incorporate operational flexibility and forward‐looking behavior of shale oil producers.

Linear factor models are generally not identified. We provide sufficient conditions for identification: Under a natural sparsity assumption (the presence of local factors that affect only subsets of observables), the true loading matrix is the sparsest rotation and can be recovered by minimizing the ℓ 1 ‐norm of the loading matrix. This enables economically meaningful interpretation of the individual factors. More generally, our ℓ 1 ‐rotation criterion offers a novel approach to simplify the loading matrix and performs well relative to existing methods (e.g., Varimax, Kaiser (1958)) in our simulations. We illustrate our method in two economic applications. The R package l1rotation implements the method and facilitates adoption.

We provide a comprehensive examination of the predictive accuracy of panel forecasting methods based on individual, pooling, fixed effects, and empirical Bayes estimation, and propose optimal weights for forecast combination schemes. We consider linear panel data models, allowing for weakly exogenous regressors and correlated heterogeneity. We quantify the gains from exploiting panel data and demonstrate how forecasting performance depends on the degree of parameter heterogeneity, whether such heterogeneity is correlated with the regressors, the goodness‐of‐fit of the model, and the dimensions of the data. Monte Carlo simulations and empirical applications to house prices and CPI inflation show that empirical Bayes and forecast combination methods perform best overall and rarely produce the least accurate forecasts for individual series.

This paper proposes a debiased estimator for causal effects in high-dimensional generalized linear models with binary outcomes and general link functions. The estimator augments a regularized regression plug-in with weights computed from a single convex optimization that approximately balances link-derivative-weighted covariates and controls variance; it does not rely on estimated propensity scores. Under standard conditions, the estimator is $\sqrt{n}$-consistent and asymptotically normal for dense linear contrasts and causal parameters. Simulation results show the superior performance of our approach in comparison to alternatives such as inverse propensity score estimators and double machine learning estimators in finite samples. In an application to the National Supported Work training data, our estimates and confidence intervals are close to the experimental benchmark.

This paper introduces a robust specification test for linear regression built on a rank-score empirical process. The proposed test is distribution-free, easy to implement, and accommodates a broad class of score functions. We derive the asymptotic properties of the test statistics under the null, fixed alternatives, and a sequence of local alternatives. To implement the test in finite samples, we employ a simple multiplier bootstrap procedure with establishing its asymptotic validity. Simulations and an empirical application indicate reliable size and strong power with notable robustness to heavy-tailed errors and outliers.

The synthetic control method (SCM) is widely used for causal inference with panel data, particularly when the number of treated units is small. It relies on the stable unit treatment value assumption (SUTVA), ruling out spillover effects. However, interventions often affect not only treated but also untreated units. This study proposes a novel panel data method that extends standard SCM to account for spillovers and estimate both treatment and spillover effects. The approach extends the SCM framework by incorporating a spatial autoregressive (SAR) panel data model that captures spillover patterns across units. We also develop a Bayesian inference procedure using horseshoe priors for regularization. We apply the proposed method to two empirical studies: (i) evaluating the effect of the California tobacco tax on cigarette consumption, and (ii) assessing the economic impact of the 2011 Sudan division on GDP per capita.

Though air-quality alert systems (AQAS) cover more than 1.7 billion people worldwide, there has been little analysis of the net benefits of these systems. This paper presents a theoretical framework for deriving lower bounds on the net benefits of an AQAS and applies it to a South Korean system currently covering over 51 million people. Estimating a regression discontinuity design, we find that an alert issuance reduced youth respiratory expenditures by 30% and adult cardiovascular expenditures by 23%. The overall system reduced externalised health expenditures by 28.6 million dollars during 2016−2017, with a minimum benefit-cost ratio of 7.1:1. Including dynamic impacts of alerts increases the minimum benefits (benefit-cost ratio) to 36.7 million dollars (9.2:1). Our findings imply that the AQAS generates significant net benefits and suggests that manipulation of air quality data, which has been observed in other contexts, may negatively impact social net benefits.

Exploiting a 1960s government trial in Copenhagen, we study the long-run effects of preventive health care for toddlers. We combine administrative data with handwritten nurse records to document universal treatment take-up. Treated children enjoy a five percent of a standard deviation increase in a good adult health index. While initial trial cohorts experience positive health and labour market impacts, those are absent for the final cohorts. Impacts are largest for children with initial health disadvantage and females, and we identify childhood health improvements as a core mechanism. The heterogeneity of trial effects across individuals’ initial health status and cohorts documents that universal toddler care can alleviate health inequalities at low costs, and that the counterfactual policy environment matters.

Systematically biased forecasts are typically interpreted as evidence of forecasters’ irrationality and/or asymmetric loss. In this paper we propose an alternative explanation: when forecasts inform policy decisions, and the resulting actions affect the realisation of the forecast target itself, forecasts may be optimally biased even under quadratic loss. The result arises in environments in which the forecaster is uncertain about the policymaker’s reaction to the forecast, which is presumably the case in most applications. We motivate our theory by reviewing some stylised properties of Greenbook inflation forecasts. Our results point out that the presence of policy feedback poses a challenge to traditional tests of forecast rationality.

Political polarisation has reshaped electoral competition in many democracies, presenting traditional programmatic political parties with a dual challenge: finding ways to make policy-based campaigning resonate with voters without exacerbating partisan divisions. We partner with a mainstream opposition party to implement a field experiment during the 2019 Philippine Senatorial election to compare two common campaign strategies—direct policy-focused canvassing and an emotional engagement component—to assess both their electoral effects and their implications for polarisation. We find that, even in polarised contexts, in-person engagement providing policy information increases votes for the party. Both strategies increase learning, and importantly, neither strategy produces backlash among pro-incumbent voters; if anything, evidence suggests cross-cutting moderating effects. These results suggest that mainstream parties can communicate policy effectively even in highly polarised contexts, and that direct policy and emotional engagement need not exacerbate partisan divides.

This paper investigates whether tax evasion opportunities can increase tax revenue. Past theoretical discussions have presented mixed outcomes as to whether allowing taxpayers to opt into uncertainty could indeed enhance overall tax revenues. In this study, we conducted a series of original real-effort experiments in an online setting with almost 6,000 participants to test this hypothesis empirically. Our findings show significant positive labour supply responses to the opportunity to evade (increased labour supply by 30%). More importantly, the expected tax revenue significantly and substantially increased by up to 40%. Strikingly, this effect persists when comparing effective tax rates: Lowering effective tax rates through probabilistic enforcement (the opportunity to evade) is more efficient than simply lowering statutory tax rates. Our findings suggest that the opportunity for tax evasion can increase tax revenues beyond what a corresponding decrease in nominal rates would achieve.

Partisan vitriol has become a defining feature of American politics, evident in survey responses and social media discourse. Conventional wisdom holds that these expressions reflect deeply rooted hostility. Yet they may also function as social signals, reinforcing loyalty and conformity within partisan groups. In this view, animosity is less about entrenched ideological divisions and more about fostering cohesion among co-partisans. We test this proposition in two settings. First, using the 2012 American National Election Studies, which recorded interviewer partisanship, we exploit within-interviewer variation to examine whether respondents adjusted their reported hostility depending on the partisan identity of their interviewer. Respondents expressed significantly more animosity when interviewed by a co-partisan and less when facing an opposing-partisan interviewer. Second, in an online experiment with 1,510 participants, we find that revealing a partner’s partisan alignment—when it matched the participant’s—encouraged more frequent out-group attacks and in-group promotion. These behaviours were strongly shaped by social norms: participants were substantially more likely to attack when their partner had done so in the previous round. Together, these findings suggest that partisan hostility is contingent on immediate social context, not solely on deeply held animus.

Using machine learning and product-level data on single men’s and single women’s consumption patterns, we develop an index that quantifies the „gendered‟ nature of consumer goods. We use the index to investigate how gender-specific labour market shocks influence spending patterns within heterosexual households. Our findings reveal that industrial robot adoption, which worsened men’s relative economic position, shifted household consumption toward products predominantly purchased by single women. In contrast, the expansion of fracking, which boosted demand for young and less skilled men, yields suggestive but less robust evidence of increased spending on goods favoured by single men. Although neither shock significantly altered total spending on children’s products, robot exposure led to a reallocation of spending toward goods more commonly purchased for daughters than for sons.