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Abstract Japan's regional convergence of productivity levels throughout the twentieth century can be best described as a cumulative process of ‘catching up, forging ahead, and falling behind’. Using a novel dataset spanning 135 years (1874–2008), this study finds support for a crucial role played by structural transformation in convergence. The pace of productivity catch‐up and convergence accelerated in the mid‐1950s with the help of structural transformation, particularly in the period from 1955 to 1965. Structural transformation explains, on average, about 30 per cent of the aggregate productivity growth, and its effect intensified in prefectures with faster movements of labour across sectors and larger sectoral productivity gaps. However, since the early 1970s, its contribution to the convergence was frequently offset by within‐sector productivity growth, in turn thwarting the pace of convergence. These counter‐balancing effects contributed to the diverse pathways of productivity catch‐up at the prefecture level.

This paper studies the optimal design of climate, fiscal, and monetary policies in response to climate-specific shocks within a climate-DSGE framework. We show that carbon taxes significantly mitigate the effects of climate shocks on output, consumption, and welfare, while optimal monetary policy is largely unaffected and fiscal policy adjusts via lower labor taxes. Extending the model with a richer climate module and abatement costs, we find that the assumed damage function is crucial: under a standard quadratic specification, climate policy has little effect on conventional macroeconomic shocks, but a highly convex, Weitzman-type damage function makes carbon taxation materially relevant. Accounting for climate fiscal outlays further raises optimal abatement and reduces emissions. Our results highlight the importance of integrating both macroeconomic and environmental considerations when designing policy.

Critical-mineral supply chains have become a strategic constraint for the energy transition because upstream disruptions propagate through interconnected supplier, resource, and technology dependencies. While existing studies have substantially improved criticality assessment, propagation modelling, and resilience planning, these analytical components are generally developed within separate modelling frameworks. This paper develops a calibrated multilayer analytical framework that integrates structural dependency representation, empirical calibration, counterfactual stress testing, and resilience planning within a common mathematical architecture. Supplier-resource relationships, technology–resource requirements, and economy-specific technology portfolios are represented through a unified family of calibrated propagation operators. The framework characterizes structural vulnerability using the dominant spectral properties of the calibrated propagation architecture, evaluates counterfactual supplier disruptions under a common benchmark calibration, and formulates constrained resilience planning on the same structural representation. The empirical analysis shows that heterogeneous transition-capacity losses are explained by differences in propagation architecture rather than by supplier diversification alone. By deriving structural diagnosis, counterfactual propagation, and resilience planning from a single calibrated representation, the proposed framework provides a coherent and reproducible methodology that complements existing critical-material assessments for resilience-oriented energy planning.

The European Green Deal identifies energy diversification and environmental sustainability as two central pillars for achieving a secure, resilient, and climate-neutral energy system. Although previous studies have examined the determinants of environmental sustainability and the energy transition separately, limited evidence exists on how energy diversification, globalization, financial development, natural capital, and structural change jointly shape environmental sustainability within the European Green Deal framework. This study addresses this gap by investigating the macroeconomic determinants of environmental sustainability across 26 European countries during 1995-2023. The analysis employs dynamic System GMM as the primary estimation method, complemented by CS-ARDL to examine long-run relationships and machine-learning models with SHAP explainability to assess the relative importance of the explanatory variables. The results reveal strong persistence in environmental sustainability over time. Structural change is the only significant short-run determinant, while energy diversification and political globalization exhibit significant negative long-run effects, whereas financial development and natural capital show no robust long-run influence on environmental sustainability. These findings suggest that energy diversification alone does not guarantee environmental sustainability unless supported by renewable energy deployment, technological innovation, and effective environmental governance. By integrating dynamic econometric techniques with explainable machine learning, this study provides new evidence on the macroeconomic drivers of environmental sustainability and offers policy insights for implementing the European Green Deal more effectively.

Growing ecological concerns have intensified skepticism among stakeholders and environmentalists regarding whether firm growth leads to greater environmental pollution, higher greenhouse gas emissions, and increased waste generation. Hence, we investigate the connection between firm growth and carbon efficiency and how coercive (i.e., environmental taxation) and normative forces (i.e., environmental technological innovation) shape this connection in the EU context. Drawing on panel data comprising 14,089 firm-year observations for the period of 2015-2023, we find that firm growth is negatively associated with carbon intensity justifying the efficiency perspective. This negative association is strengthened through coercive (i.e., environmental taxation) and normative forces (i.e., environmental technological innovation). The results highlight country-level institutions’ role in ensuring sustainable firm growth. The results move beyond treating RBV and institutional theory as competing explanations by theorizing institutional pressures as boundary conditions that determine when internal growth resources translate into carbon mitigation. Thus, we show that the growth is not inherently “dirty” or “green”; its environmental consequences depend on institutional alignment.

Russia's invasion of Ukraine reshaped energy markets and intensified tensions between energy security, energy transition, and social protection. This study constructs a country-year panel for 233 economies (2000–2024) by combining World Bank Sovereign ESG, Worldwide Governance Indicators, World Development Indicators, and Tracking SDG 7 data. Environmental, social, and governance pillars are reconstructed from transparent indicator-level scores. The core comparison uses 2018–2021 as the pre-war period and 2022–2023 as the post-invasion period; governance tests extend through 2024, while the primary environment-energy specification uses raw 2022 outcomes because the 2023 renewable-energy-share series is carried forward. The empirical design combines two-way fixed effects, event-study evidence, placebo shocks, detrending, heterogeneity analysis, and rolling-window diagnostics. A clear hierarchy of findings emerges. The primary identified result is that a one-standard-deviation increase in pre-war energy import dependence is associated with a 0.035 standard deviation relative decline in post-2022 governance, equivalent to roughly seven years of average annual governance change. This relationship survives delayed-post, detrending, placebo, event-study, and rolling-window checks, and concentrates in regulatory quality and government effectiveness. Average global ESG performance did not uniformly collapse after 2022; dispersion widened instead. Higher pre-war modern-energy access deficits are also cross-sectionally associated with weaker environment-energy outcomes outside Northern America and Europe, but pre-existing convergence and income collinearity prevent causal attribution. Policy design should integrate energy security, vulnerability reduction, and governance safeguards.

Regional climate action plans for decarbonization in the US generally ignore the greenhouse gas (GHG) emissions of renewable electricity generation systems that occur beyond the operational stage. Our analysis of California's prospective electricity sector changes through 2045 highlights the implications of omitting life cycle GHG emissions and their geographic variability in decarbonization planning. We demonstrate that the total GHG emissions of the proposed power sector in California through 2045 will be over 30% higher than reported by California's Scoping Plan for Achieving Carbon Neutrality, even with optimal siting of new energy systems. The lack of life cycle accounting in decarbonization planning may lead to massive infrastructure changes and economic investments towards target emissions reductions that are ultimately insufficient to prevent or that may even contribute to worsening climate change.

The determination of electricity tariff remains one of the most contested aspects of energy governance in developing countries, where regulators must balance affordability, cost recovery, and sector sustainability issues. While existing research has largely focused on consumer willingness and ability to pay, the perspectives of stakeholders who shape tariff decisions and influence compliance have received relatively little attention. This study examines stakeholder narratives regarding electricity tariff structures and payment dynamics in Ghana. Semi-structured interviews were conducted with 38 stakeholders drawn from regulatory institutions, utility providers, government agencies, civil society organisations, consumer advocacy groups, vendors, and community leadership structures across six administrative regions in Ghana using a qualitative research design. Data were analysed using thematic analysis informed by an integrated framework combining political economy, stakeholder, and trust-accountability perspectives. The findings reveal five interconnected themes, with stakeholders consistently viewing tariff determination as more than a technical pricing exercise, highlighting the importance of transparency, meaningful participation, institutional legitimacy, and service quality in shaping compliance. The findings demonstrate that affordability constraints and perceptions of fairness, accountability, and trust in regulatory and utility institutions influence the willingness to comply with electricity payment obligations. It argues that sustainable tariff reforms require governance arrangements that stakeholders perceive as transparent, inclusive, and accountable. This study contributes to the literature on electricity governance by developing an integrated explanation of tariff compliance that links political-institutional power relations, stakeholder engagement, trust and legitimacy, and compliance outcomes.

More than 600 million people in sub-Saharan Africa lack access to electricity and the demand-side constraints have been recognized as essential factors impeding universal access. Electricity infrastructure planning decisions are often aided by tools designed to predict demand in areas without access, which often do not consider the non-randomness of the roll-out of electricity access. We use survey data from Burkina Faso to consistently estimate the demand for grid electricity and predict it in off-grid areas. We further contrast our estimates with data on stated preferences concerning connection to the network, and we find that households in off-grid areas appear overly optimistic about their willingness to connect. Our results suggest that not accounting for selection might result in significant upward bias. We further find that the willingness to pay for high-quality electricity service among connected households is significantly higher than what households in off-grid areas are willing to pay monthly for access to the grid. Finally, we find that households located in areas with better service quality are more likely to be connected to the grid.

China's low-carbon power transition, marked by the phase-out of coal and the rise of renewables, has redefined regional employment landscapes, presenting both opportunities and challenges. This study develops a regional employment impact model that integrates employment coefficients with a multi-regional input-output framework to assess power sector employment across regions, skill, and gender under transition scenarios. We find that power sector employment is projected to rise through 2060, with non-fossil jobs displacing coal, while carbon capture partially offsets coal-related losses. Employment for workers with basic and higher education in the fossil energy sector is expected to decline significantly, while the non-fossil energy sector is projected to create more job opportunities for workers with higher education. The power transition may alleviate gender structure imbalances to some extent; however, women workers may encounter heightened vulnerability during regional employment transitions. Moreover, fossil energy job losses and non-fossil energy job creation show temporal and spatial mismatches and relocation risks, with North and Northwest China facing the highest exposure. Skill structure mismatches are more pronounced in direct employment than in indirect employment. Specifically, North and Northeast China experience higher risks of direct employment skill structure mismatches, while Northwest China faces the most severe indirect employment skill structure mismatch risks. A comprehensive scenario comparison reveals that the 100% non-fossil energy scenario poses higher employment structure mismatch risks than the coal-power guaranteed supply scenario. Thus, transition policies should adopt a more inclusive approach, addressing potential risks of employment structure mismatch to ensure a just transition.

Effective and equitable energy policy requires a comprehensive understanding of the spatial and social patterns of household incomes and energy expenditures. Domestic and transport energy costs are higher in rural than in urban areas while housing costs show the opposite pattern. We examine this tradeoff by systematically analyzing 6.2 million households’ observed incomes and car fuel, domestic energy, and housing expenditures for the first time. We determine the marginal effects of sociodemographic and built environment characteristics with a disaggregate econometric modeling framework. Vulnerable groups like disabled and unemployed households, households with children, and single-adult households have the lowest residual budgets and devote the largest share of these budgets to energy carriers, resulting in high vulnerability to energy price shocks. After correcting for these sociodemographic patterns, we find that similar households have lower car fuel expenditures in high-density areas whereas proximity to train stations has a limited effect. Domestic energy costs are lowest for residents of urban apartments and terraced dwellings. Policy may further reduce apartment dwellers’ domestic energy bills by supporting homeowners associations in installing solar panels and heat-pumps. Private rent and mortgage costs are higher in high-density, centrally located areas. These higher urban housing costs outweigh savings on domestic and transport energy if residents cannot obtain social housing. At the same time, households do devote a larger share of their residual budget to energy carriers when living in remote rural areas. We recommend policy aimed at urban social housing, building renovation, and the accessibility of electric vehicles.

Energy communities are no longer peripheral experiments in Europe but central actors in the energy transition. Their growth and institutionalization is particularly observable in the Dutch context. By 2024, 702 cooperatives engaged over 139,000 members across nearly 90% of municipalities - evidence that the energy transition is societal as much as technical. In the Dutch context, communities can accelerate and democratise change by raising acceptance of renewable energy projects, mobilising local capital and building energy literacy and trust. The Netherlands is a uniquely fertile testbed for integrating bottom-up change: a polycentric governance setting, a dense cooperative ecosystem, rapid digitalisation and high distributed generation all push communities beyond renewable energy deployment towards new activities, such as storage and demand-side flexibility. Yet, practice still outpaces legal, policy and technical frameworks. Unresolved tensions in regulation, legitimacy, justice, impact evaluation, system integration, and scaling reveal that energy communities remain under-leveraged. This perspective advances a research agenda to close that gap, co-created with Energie Samen, the Dutch federation of energy communities, and informed by targeted literature synthesis, roundtables, and practitioner interviews, to pinpoint where knowledge is most urgently needed to align rules and markets with citizen-led innovation. While our perspective is focused on the Netherlands, the lessons are transposable if contextualized to other legal, market and social conditions. Accordingly, we suggest that without deliberate coordination between research, policy, and practice, the potential of energy communities will be left on the table just when it matters most.

The international integration of electricity markets offers numerous benefits but can entail substantial redistribution between consumers and producers, posing political challenges. Several European interconnector projects have recently been canceled because of potential consumer losses, despite being expected to enhance welfare. This article analyzes the distributional effects of interconnector expansion and identifies policy options to achieve Pareto improvements for electricity consumers. We first use an analytical model to analyze trade between two electricity markets and to derive general conditions under which asymmetric sharing of interconnector costs and rents can avoid consumer losses in the exporting market. Second, we employ a numerical model of the European power sector to assess the real-world example of the canceled Hansa PowerBridge interconnector between Germany and Sweden. Under the current electricity market configuration, we find that asymmetric sharing of interconnector costs and rents is likely insufficient to compensate Swedish consumer losses. However, the additional redistribution of increased surplus by Swedish state-owned producers could achieve a Pareto improvement—even under external shocks. Furthermore, with a German bidding zone split, the Hansa PowerBridge is expected to become Pareto-improving without additional transfers. We conclude that the asymmetric sharing of interconnector costs and rents, the redistribution of surplus from state-owned or state-backed producers, and the reconfiguration of bidding zones are effective policy levers to render welfare-enhancing interconnector projects Pareto-improving.

Renewable Energy Communities (RECs) with peer-to-peer (P2P) trading can lower bills and unlock flexibility, but they also reshape supplier revenue and distribution-network headroom. We couple an agent-based REC market model to a Transformer Headroom Index (THI) to evaluate welfare and grid outcomes across seasons. A 20-household feeder in South-East England with PVs, EVs, and heat pumps is simulated with and without P2P under four retail tariffs: Flat, Economy-7, Agile, and a wholesale-linked Dynamic tariff. Metrics include community net bills, supplier profit, and import/export headroom for 50 and 100 kVA transformers. Results reveal a persistent distributional trade-off: tariffs that minimise community bills compress supplier margins. P2P accentuates this by reducing grid purchases in PV-rich periods. P2P improves import headroom via EV load shifting; however, in PV-rich summer it can synchronise prosumer behaviour around price spikes, concentrating exports into short windows that erode export headroom. Nonetheless, across seasons, P2P is consistently part of the Pareto-optimal solution set, though the preferred supporting tariff varies by season. Policy implications derived from these trade-offs include: the need to re-base residual cost recovery onto fixed or capacity charges, the adoption of facilitation fees and THI-based flexibility contracts for value-sharing, the addition of Dynamic Operating Envelopes (DOEs) as guardrails for real-time tariffs, and the regulatory enablement of EVs as flexibility assets.

Building performance simulation (BPS) is an established method for informing building design and demonstrating compliance with building codes and certification programs. However, the accuracy of BPS models depends heavily on occupancy assumptions, which vary significantly across building codes and standards. This paper synthesizes and quantifies the impact of occupancy-related assumptions across 14 international building energy codes and standards on predicted building performance across different climates, covering energy, carbon, and comfort metrics. Four occupancy-based energy conservation measures (ECMs) are then evaluated to study their impact under the different occupancy assumptions: (i) occupancy-based lighting control, (ii) occupancy-based plug loads, (iii) occupancy-based temperature setpoints, and (iv) demand-controlled ventilation (DCV). An application to Canadian office-building archetypes demonstrates that different occupancy assumptions lead to performance variations up to 86% in electricity demand, 60% in natural gas consumption, and 100% in greenhouse gas emissions. Among the tested ECMs, occupancy-based thermostat setpoints significantly reduced peak energy loads and the number of unmet setpoint hours. More importantly, these controls also reduced the sensitivity of building performance to occupancy assumptions, highlighting the importance of aligning heating and cooling loads with actual occupancy patterns to mitigate performance risks. The findings underscore the need for regulators and standard-setting bodies to refine occupancy assumptions in performance-based compliance frameworks and consider a range of plausible occupancy scenarios to improve the reliability of policy outcomes under operational uncertainty. Finally, the study provides an open-access dataset and discusses policy implications.

In the European Union (EU), there is a significant gap in understanding characteristics and performance of the existing building stock. A central element of the Energy Performance of Buildings Directive (EPBD) for evaluating building performance is the Energy Performance Certificate (EPC). In 2018, the Smart Readiness Indicator (SRI) was introduced to complement the EPC. Despite their potential, EPCs have not yet fully achieved their intended impact on energy savings, and the reasons for this have not been fully analysed. This research gap is addressed by the EU-funded LIFE project “tunES”, which unites seven national energy agencies from EU countries and four technical partners from academia, research, and consultancy. This project focuses on analysing and standardizing EPCs and SRIs. The consortium structured its efforts into five key policy development areas: (1) Understanding EPC, (2) Upgrading EPC, (3) Databases and Tools, (4) SRI Development and Deployment, and (5) Integration of Instruments. Following these areas and EU Better Regulation Guidelines (BRG), a survey and interviews were conducted among key stakeholders and experts in participating countries to assess the current state of EPCs and SRIs: 236 respondents filled out the survey and 49 informants were interviewed. The results highlighted the need for enhanced clarity, updated methodologies, and improved integration of instruments to drive future energy efficiency initiatives. National databases of EPCs and SRIs are valued, but enhancements in methodology, comprehensibility, and user value are needed. Improved professional training and SRI-EPC integration are crucial, with regional differences indicating best practice examples for EU-level standardization.

ABSTRACT In this paper, we study optimal prevention in the presence of a correlated nonfinancial background risk. Under positive correlation, cross‐prudence in the nonfinancial attribute reduces optimal prevention. We establish this result in the most direct extension of the standard prevention problem with binary marginal distributions and show that it extends to richer settings. Our analysis highlights a broader implication: in economically relevant cases with loss probabilities below one‐half and positive correlation, cross‐prudence emerges as an additional force that discourages prevention. As a result, optimal prevention can fall below the expected‐cost minimizing level, even when agents are risk‐averse.

ABSTRACT We study social security reforms in economies with segmented labor markets and pension systems. We develop a life‐cycle general equilibrium model with heterogeneous agents and endogenous retirement and sectoral choice across public, formal, and informal jobs. Calibrated to Brazil, the model shows that unifying pension systems and raising the minimum retirement age reduce the pension deficit by nearly 40 percent, while increasing output, capital accumulation, and welfare, despite redistributive effects across age groups, sectors, and along the transition path. Sectoral reallocation plays a central role in shaping reform effects, and ignoring these margins substantially underestimates the macroeconomic consequences of pension reforms.

We investigate the impact of the controversial 2022 amendment to Rule 10b5-1, which imposed a cooling-off period and restricted overlapping and single-trade plans on prearranged insider transactions. Our evidence is consistent with the amendment leading insiders to (i) execute stock sales under 10b5-1 plans with longer cooling-off periods; (ii) curtail opportunistic sales under 10b5-1 plans prior to stock price drops or earnings misses; (iii) limit the backdating of stock gifts; and (iv) decrease the granting of options around material information events. Further evidence suggests a reduction in opportunistic 10b5-1 trades rather than a migration toward non-10b5-1 sales. We find mixed evidence on the amendment’s effect on price efficiency. Finally, terminations of 10b5-1 plans are associated with positive subsequent stock returns, suggesting that insiders avoid selling when they expect favorable news. Overall, our findings indicate that the amendment substantially curtailed the opportunistic use of 10b5-1 plans, its primary objective.

Pandey et al. (2026) examine whether the auditor independence provisions of Sarbanes-Oxley (SOX) impact accounting careers and human-capital development. I discuss how the paper shows that independence regulation affects not just the economic ties of auditors and clients, but also the organization of work through which auditors develop human capital. I interpret the evidence as identifying both intended and unintended consequences of independence rules on accountants’ learning, networks, and mobility. The paper adds an important labor-market cost dimension to the evaluation of SOX, but I argue it should be read as informing independence regulation rather than making a case against it. The broader implication is that auditor independence and human capital are complementary inputs into audit quality, which creates a regulatory design problem of protecting auditor objectivity while sustaining expertise.

This discussion reviews and reflects on Bernard and Sutherland’s (2026) survey of empirical research on private firms and the economic role of accounting. It traces the emergence of large-sample private-firm research, highlights persistent challenges related to data availability, firm heterogeneity, and causal identification, and questions the applicability of listed-firm conceptions of what constitutes a financial report to smaller private firms. I urge a shift in research toward studying how private firms generate accounting information and select which accounting items to include in their financial reports, and offer conjectures on the determinants of such accounting choices. The discussion also highlights the weaker and more heterogeneous nature of accounting regulation and enforcement across private firms and concludes with a call for broader, more descriptive, and institutionally grounded research on accounting’s economic role beyond that in public firms.

This paper develops a capital structure model with a financial covenant that imposes a lower limit on a firm’s interest coverage ratio. Shareholders reduce their debt level or default whenever this ratio falls below the limit. In the model, firm value, debt repayment policy, and capital structure are derived explicitly. For low levels of the limit, shareholders prefer to reduce their debt every time the ratio reaches the limit. In other words, the covenant acts as early pressure on shareholders and eliminate their incentives to default. Then, it decreases the cost of debt but also lowers equity value by constraining shareholders. Because of this trade-off, the covenant can improve firm value. With the covenant, the firm can begin with high leverage to take advantage of the decreased cost of debt. The covenant tends to improve firm value for higher bankruptcy cost and volatility because these conditions lead to high expected default costs without a covenant. It can also improve firm value for higher growth and tax rates by easing the restriction on future debt issuance. These results are consistent with empirical evidence and support the optimal contracting hypothesis for covenants.

Can investors see through biased information? We examine this question in Chinese IPO auctions, where underwriters issue upward-biased earnings forecasts that institutional bidders use when setting their bids. We find that investors do incorporate underwriters' forecasts into their bids, but place a systematically smaller weight on the forecast when its predictable biased component is larger. Cross-bidder heterogeneity follows a debias-capacity logic: cognitively constrained bidders rely on underwriters' forecasts more, while bidders with stronger information-processing ability or richer private information rely on them less. The debiasing is incomplete, however, as higher forecasts still inflate offer prices and depress first-day IPO returns.

We examine the asset-pricing implications of selection neglect – a failure to correct for censored information – in the fine wine market. Using a Markov Chain Monte Carlo model to account for the endogeneity of trading, we measure this bias as the difference between past observed and corrected returns. We find a strong negative relation between our measure and future returns, indicative of an upward bias in the observed prices that is eventually corrected. This effect is mitigated by investor attention, amplified by ambiguity, and proves to be a short-term mispricing effect, vulnerable to transaction and carrying costs.

This research examines the relationship between co-opted boards and firms' anti-takeover provisions (ATPs). Analyzing 5585 US firm-year observations for the period 2012–2022, we document a positive relationship between co-opted boards and ATPs. We further illustrate that the positive relationship is stronger in firms that exhibit subpar performance and compensate senior executives and directors more than the industry average. Furthermore, our research finds that good governance, board and executive gender diversity, gender equality, and board cultural diversity moderate the positive relationship between co-opted boards and ATPs. Our results remain robust across a battery of tests. The findings of this research have important implications for corporate boards and managers. The study contributes to the mainstream agency theory by demonstrating that co-opted boards exacerbate firms' agency problems by blocking the potential of external disciplinary mechanisms.

This study examines how passive institutional investors reshape corporate venture capital (CVC) investment decisions. We find that increases in passive institutional ownership lead firms to cut back CVC investments in non-core, high-risk, and low-quality ventures, with the reduction being more pronounced among firms subject to more severe managerial agency problems. Futhermore, the reduction of CVC investments leads to higher short-term announcement returns and improved long-term operating and innovation performance. The findings suggest that passive institutional investors mitigate managerial agency problems and improve innovation by disciplining CVC investment decisions.

This paper investigates how peer firms' Corporate Social Responsibility (CSR)-related incidents influence the corporate investment efficiency of non-incident firms. Using a sample of U.S. firms from 2007 to 2021, we document a significant increase in investment-Tobin's Q sensitivity following negative peer events, thereby improving investment efficiency. We identify three non-mutually exclusive channels. First, the effect is stronger among firms with higher analyst coverage, greater stock trading volume, and closer product-market proximity to the incident firm, consistent with the notion of heightened external scrutiny. Second, peer incidents serve as informational shocks that enhance managerial learning from external signals, particularly when firms operate in competitive industries, face high product-market uncertainty, or have more informative stock prices. Furthermore, we find that the performance of focal firms deteriorates following peer incidents and that efficiency gains are greater among firms that were previously overinvesting. Taken together, these findings suggest that peer CSR scandals act as disciplining and learning events that improve investment behavior across the industry.

We present a large-sample analysis of growth equity (GE) investment using 1512 UK private companies over 2000–2021 and compare the post-investment performance of investee firms to matched companies that do not receive investment. Target companies are younger, smaller, more intangible-asset intensive and more rapidly growing than the general pool of UK private companies. We find that GE target companies differ significantly from venture capital and private equity buyout targets, while the transaction structure also differs. Post-investment, GE target firms dramatically outperform a matched sample of non-GE backed private companies with respect to sales and asset growth, employment, and earnings growth. Much of this extra expansion is financed by significantly faster growth in leverage than for non-GE backed firms.

Fund managers cast votes that are more critical of firm environmental and social (ES) practices when the firm has operations located close to fund headquarters. This elevated support for shareholder ES proposals is not mirrored in governance proposals, which likely have less impact on the local community. We find similar pro-ES fund voting practices at firms with operations near the fund manager’s college and prior employment locations and in utility companies that provide electric and gas service to the fund’s address. Manager and sub-advisor turnover events provide additional evidence: tracking the same decision-maker’s votes at a fixed set of firms before and after the move, we find that support for ES proposals increases significantly once the manager gains proximity to those firms. The proximity effect is concentrated at high-polluting plants, consistent with managers responding to personal exposure to environmental harm. We conclude that fund managers exhibit a personal bias in ES voting, being more likely to support ES proposals that impact them personally.

We examine the effects of time-limited disclosure relief under the Jumpstart Our Business Startups (JOBS) Act of 2012. The Act grants newly public firms up to five years of exemptions, and our results suggest that the fixed duration of this relief, as much as its availability, shapes post-IPO behavior. Using an intention-to-treat design, we compare treated firms with smaller reporting companies whose exemptions are similar but carry no fixed expiry date. Equity issuance by treated firms increases significantly as the deadline nears while debt issuance declines, and cash reserves accumulate over the period. Capital expenditure increases relative to controls in the early post-IPO years, while R&D shows no differential response. As expiry approaches, the differential with the control group in internal investment weakens but cash-financed acquisitions accelerate. This shift in investment composition coincides with deteriorating operating performance and declining market valuations relative to IPO levels. Our post-expiry analysis reveals an abrupt reversal in acquisition activity upon transition to full disclosure while internal investment remains unchanged, supporting the argument that pre-expiry behavior was driven by the regulatory timeline rather than natural firm maturation. We conclude that the duration of regulatory relief is as important as its scope in shaping corporate behavior, and that time-limited exemptions from mandatory disclosure can induce anticipatory firm responses that work against the policy's intended objectives.

Which countries drive global inequality? Which states drive US inequality? We characterize the class of inequality measures that can answer these questions, permitting both an additive decomposition by subgroup and a multiplicative decomposition into within- and between-group components. Its central measure is simply the expected ratio of incomes between two randomly selected individuals. We show that global inequality fell since 1990, driven by declining disparities between countries. Inequality is primarily driven by large middle-income countries (India, China) and poor countries (Democratic Republic of Congo, Ethiopia). In the US, rising inequality is explained by widening gaps within states, while between-state inequality remains limited.

This research demonstrates how securing land property rights can mitigate frictions in rural land rental markets, specifically in the form of landlord-tenant disputes. By combining a comprehensive data set of land rental dispute records, farm-level panel data, and complete agricultural firm registration data, we find that rental disputes decreased following China's land titling reform. We corroborate this finding by distinguishing between property rights-related disputes (e.g., ownership ambiguity, boundary issues, or expropriation) and contractual enforcement disputes (e.g., rent collection). Further analysis reveals that the effect is particularly pronounced in rental agreements between farmers and agricultural firms, especially those involving non-local entities.

Natural disasters expose societies to an external environment that requires forward-looking adaptation. This paper argues that societies with greater historical exposure to natural disasters are more likely to develop long-term-oriented norms that emphasize preparation, saving, and future well-being. We test this hypothesis by linking historical exposure to earthquakes, tsunamis, and volcanic eruptions from 4360 BC to 1980 CE to contemporary long-term orientation. Disaster exposure is proxied by a distance-based measure that aggregates proximity to major catastrophic events over long horizons. Long-term orientation is examined using folklore traditions at the ethnic level and survey-based evidence at the individual and country levels. Across all levels of analysis, we find that greater cumulative disaster exposure is associated with significantly stronger long-term orientation. Evidence from folklore and second-generation migrants suggests that these effects operate through cultural adaptation and intergenerational transmission.

We examine how within-group inequality, by influencing the group bias of state institutions, affects the cost-benefit calculus of individuals engaging in identity-assertive behaviour, that results in police complaints regarding hate crimes. We develop a two-stage contest model of between-group conflict, where the relative influence of a group over institutions, determined by an initial contest, affects subsequent hierarchy-establishing interaction between individuals belonging to opposing groups. Applying this model to caste conflict in India, we find that greater inequality among non-Scheduled Caste and non-Scheduled Tribe (non-SC/ST) Hindus reduces the registered rate of crimes against SCs by non-SC/ST Hindus, and the rate at which such registered crimes lead to conviction. Using state-level annual crime and household consumption data over 2005–2021, we find empirical support for these hypotheses. Our analysis suggests that greater equality within dominant groups might reduce institution-capture by them and thereby improve both reporting and punishment of aggression against marginalized groups.

This paper compares the “mental maps” of redistribution among politicians and citizens across seven parliaments, using original in-person surveys of sitting MPs and nationally representative citizen samples. Fairness beliefs and ideology are the strongest correlates of support for redistribution in both groups, while misperceptions of wealth concentration matter for citizens but much less for politicians. A central finding is that politicians hold markedly more polarized views on redistribution than citizens, including within the same party families. We also find systematic elite-voter gaps: left MPs are more supportive than their voters (notably on inheritance taxation), whereas right/liberal MPs are less supportive than theirs. These patterns point to a representation concern and to a narrower bargaining space among elites than in the electorate.

Using monthly rainfall data, we study the demographic consequences of extreme rainfall variability, focusing on extreme dry and wet events in rural China. We find that both types of extreme rainfall events increase fertility, with a stronger response for male births, between 1990 and 1999. More than a decade later, children who were exposed to extreme rainfall events in utero, especially extreme wet events, attain fewer years of schooling than unexposed cohorts. The second trimester of pregnancy emerges as the critical exposure window, with shocks during this period generating the largest negative effects on adult educational outcomes. Examining potential mechanisms, we show that extreme rainfall events reduce household income and increase child mortality. These results highlight the persistent demographic impacts of extreme weather shocks.

We conduct an artefactual field experiment in real-existing trade networks to analyze how individual network degree affects bargaining demands and outcomes. We combine data from a bilateral bargaining experiment with data of trade networks in 24 villages in Uganda. To identify the effect of individual degree in the village trade network we experimentally vary the disclosure of participants’ identities in a bargaining pair. We state hypotheses on how degree will affect behavior and find partial support for them. Specifically, we observe that individual degree affects bargaining demands in the predicted direction when one of the bargainers is informed about the network positions but not when either no or both sides are informed. Moreover, network degree affects the likelihood of agreements and earnings, irrespective of the knowledge of the network positions of bargaining partners.

This study uses a large, nationally representative online survey in Chile comparing double list experiments, which reduce social desirability bias, with direct questions on attitudes among supervisors, co-workers, and customers toward gay individuals. Respondents underreported their discomfort with gay individuals by 15-23 percentage points, with the largest bias and lowest comfort levels observed when asked about supervising gay employees. These patterns were mirrored in incentivized donation behavior: individuals who refused to donate in a lottery to LGBTQ-related nonprofits reported lower comfort levels and exhibited greater misreporting. Finally, respondents consistently underestimated the broader societal support for gay employees and co-workers.

The paper presents a novel strategic analysis of narcoterrorism where a weak developing country’s terrorist group extorts home drug farmers to finance terror attacks. A developed country’s counterterror actions are motivated by the harm its residents endure from those attacks. The developed country’s counterterrorism involves efforts to destroy the drug crop abroad. The analysis begins with the drug price being exogenously fixed, followed by a “large-country case’’ with a market-determined drug price. The extension introduces a fourth participant, consisting of the developed country’s consumers whose purchases determine the drug demand. A subsequent extension allows for two drug-exporting countries along with their resident terrorist groups. Now, the drug price depends on terrorists’ extortion rates and the developed country’s counterterrorism associated with the two drug-exporting countries. With the last extension, novel drug-based counterterror transfers of terrorism occur between the drug-producing countries. For alternative scenarios, we show the key influence of the elasticity of the farmers’ counterterror resilience on the extortion rate and terrorism level.

We document that China’s 2018 domestic regulations, which suppressed the future growth potential of its game app market, unintentionally triggered an immediate and significant export expansion in this sector. This expansion was largely accounted for by apps already established in foreign markets, and was significantly stronger among high-quality firms. To rationalize these patterns, we develop and calibrate a dynamic model featuring customer accumulation under capacity constraints. In response to the regulatory shocks, firms proactively reallocate resources toward foreign markets, with higher-quality firms exhibiting a stronger reallocation response. This proactive behavior further amplifies the welfare losses borne by domestic consumers.

Using longitudinal data from the UK, we study the role of industrial segregation for sexual identity-based pay disparities, while controlling for fixed unobserved heterogeneity. We show that industries that have a greater proportion of sexual minorities pay their male employees less. This is of an order of magnitude of a 0.6% marginal reduction in earnings as industrial representation of sexual minorities increases by 1 percent. This compares to an equivalent marginal figure for occupational segregation of approximately 0.9%. In contrast, there is a protective element present for females in the public sector who benefit from a within industry premium to locating in industries with greater LGB representation. However, such effects do not remove the substantial wage penalty faced by gay men, and by lesbian women in the private sector.

Markets are often used to allocate decision-making, from selecting voting rights of shareholders to hiring workers in the gig economy. We study how market selection can influence the composition of strategic thinking types in strategic interactions. Using auctions as the selection mechanism, we demonstrate that after-market decisions in the p -Beauty Contest Game can result in either higher or lower numbers, depending on the incentives. Furthermore, we pinpoint the cause of differences to the market selection of strategic thinking types, rather than the decision-maker altering behaviour due to beliefs about the selection of other players. This highlights the role of institutional factors in determining “who plays the game”.

This paper proposes a model of tax compliance and fiscal capacity in which citizens partially internalize the consequences of concealment by imagining a world in which a share of the population acted similarly, linking their compliance decisions to the perceived value of public spending. A selfish elite chooses between public goods and private rents, taking compliance as given. In equilibrium, citizens’ moral internalization expands the feasible tax base and induces elites to allocate resources toward provision rather than appropriation. When the value of public spending is uncertain, morality enables credible reform: high-value elites can signal their type through provision, prompting citizens to increase compliance and raising fiscal capacity within the same period. The analysis thus identifies a moral channel through which states may escape low-capacity traps even under weak enforcement.

The papers collected in this special issue address two enduring difficulties in the economics of resource allocation. The first concerns the cost of allocation itself: contestants routinely expend resources in pursuit of a prize far in excess of what equilibrium reasoning would suggest, and conflict over resources destroys a portion of the value it reallocates. The second concerns the consequences of allocation: control over a valuable resource frequently fails to translate into improved welfare for the party that secures it. The nine contributions approach these problems from theoretical, experimental, and empirical directions, and several of them bear on the connection between how resources are contested and what follows once control is established. This introduction situates the papers within the contest-theoretic and resource-economics literatures from which they draw, identifies the questions they leave open, and sketches a theoretical bridge between issues of puzzle and dynamics in the resource allocation literature.

Series investment companies (ICs) are single legal entities that offer multiple segregated investment portfolios, each operating as an individual mutual fund. The series IC structure, which has surpassed the single-fund IC structure in both fund count and assets under management in recent years, significantly affects various fund attributes. As a series IC houses more funds, those funds benefit from greater administrative cost savings, assume less idiosyncratic risk, deliver stronger performance, and attract higher flows. Managers’ strategic behavior at the IC level also affects fund risk-taking and performance.

We present a metric for excessive spread developments in the Economic and Monetary Union (EMU), based on the dispersion of sovereign spreads relative to macro-financial fundamentals. To allow for time variation in this relationship and isolate the impact of fundamentals, we present rolling regressions that control for the role of market sentiment. The metric shows that the observed dispersion of spreads occasionally overshot the fundamentals-based benchmark for short episodes. Especially during the European debt crisis and the COVID crisis. These periods coincided with interventions by the European Central Bank to stabilize markets. We conclude that those interventions were effective to counteract excessive dispersion of sovereign spreads among EMU countries.

This paper studies whether behavioral interventions designed to promote resource conservation in one domain generate spillovers in another. Using a natural field experiment involving over 2000 residents, we identify the direct and spillover effects of real-time feedback and social comparisons on water and energy consumption. We implement three interventions: two targeting shower use and one targeting air-conditioning use. We find significant reductions in shower use from both water-saving interventions, but no direct effect of the energy-saving intervention on air-conditioning use. For spillovers, we estimate precise null effects of water-saving interventions on air-conditioning use, and of the energy-saving intervention on shower use.

Weather extremes shape short-run economic activity through both market and nonmarket channels, yet evidence on local consumer-side activity remains limited. Using a municipality-level panel of Portuguese data (2010–2021), we estimate panel VAR and local-projection responses to weather shocks of point-of-sale purchases (a measure of merchant-location transaction activity, not resident household consumption), together with unemployment and house prices. Our central methodological finding is that hourly rather than daily measurement of rainfall variability raises the estimated semi-elasticities by an order of magnitude, suggesting that the existing climate-economy literature systematically understates the importance of high-intensity rainfall. Substantively, the local-projection responses indicate that hourly rainfall volatility raises purchases on impact and reverses the following quarter, consistent with intertemporal reallocation; temperature variability generates a sharp positive impact effect followed by a contraction; and high fire-danger days raise contemporaneous purchases. Unemployment and house prices follow the same patterns more weakly. Regional heterogeneity is substantial, the Lisbon Metropolitan Area and the Algarve sometimes display effects opposite in sign to those in the North.

We demonstrate the passthrough of Treasury supply to bank deposits through bank market power. We show that a larger Treasury supply crowds out deposits with disproportionate effects in more competitive deposit markets. A larger Treasury supply further curtails bank lending and affects bank funding structure. The explanatory power of Treasury supply is not driven by other shocks to deposit demand and supply. In comparison, monetary policy rate hikes have a larger impact on deposit funding in more concentrated markets, consistent with the deposits channel of monetary policy. Our empirical findings are rationalized in a model of imperfect deposit competition.

We document the capability of large language models (LLMs) like ChatGPT to predict stock market reactions from news headlines without direct financial training. Using post-knowledge-cutoff headlines, GPT-4 captures initial market responses, achieving approximately 90% portfolio-day hit rates for the non-tradable initial reaction. GPT-4 scores also significantly predict the subsequent drift, especially for small stocks and negative news. Forecasting ability generally increases with model size, suggesting that financial reasoning is an emerging capacity of complex LLMs. Strategy returns decline as LLM adoption rises, consistent with improved price efficiency. To rationalize these findings, we develop a theoretical model that incorporates LLM technology, information-processing capacity constraints, underreaction, and limits to arbitrage.

Using Measure 114’s narrow passage in Oregon as a natural experiment, we study how new gun regulations affect firearm demand. Background checks, a proxy for demand, rose 13.9% in anticipation of the referendum and surged 157% immediately following the election. After judicial intervention halted the law’s enactment, demand returned near pre-election levels. Temporal displacement/harvesting does not explain the demand spike: after eighteen months, we still observe a substantial cumulative increase of 63,000 excess firearm-related background checks. Administrative data reveal significant within-state heterogeneity. This evidence underscores the paradoxical effect of gun-control policies, offering a cautionary lesson to policymakers.

Land taxes are widely viewed as an efficient source of public revenue, yet explicit land taxation is rarely implemented. We study a closely related but largely overlooked object: implicit land taxes that arise within standard property tax systems when tax assessments place different relative weights on land and structures than market valuations do. Using parcel-level data on assessed values and transaction prices from U.S. counties, we estimate these implicit land taxes by comparing assessor and market hedonic valuations. We find substantial dispersion in implicit land taxes across and within metropolitan areas. Counties with higher implicit land taxes experience faster growth in population density, business establishments, earnings, and demographic diversity. These patterns are consistent with theoretical predictions that taxing land more heavily than structures encourages denser and more productive development.

This paper studies how tax expenditures shape the distribution of firm-level effective tax rates and their implications for domestic minimum taxes under the global minimum tax (GMT). Using administrative corporate tax returns from 16 countries, we document that tax expenditures are large and that effective tax rates tend to follow a hump-shaped pattern across the firm-size distribution, with particularly low rates among the largest firms. As a result, more than one quarter of the largest firms have effective tax rates below the 15-percent GMT rate, despite substantially higher statutory rates. However, firm-level simulations from five countries with data on subsidiaries of multinationals suggest that GMT-consistent domestic minimum taxes would likely generate modest revenue gains—a few percentage points of baseline CIT revenue—reflecting the small number of firms in scope and extensive deductions.

We assess whether layering an ultra-poor graduation program on Ethiopia’s Productive Safety Net Programme (PSNP) protects women and their households from localized weather shocks. Using panel data from a large cluster-randomized trial matched with detailed weather records, we identify community-level exposure to dryness shocks. Women who are exposed to dryness shocks experience deteriorating nutritional status (in conjunction with declining household food security and assets) and a significant increase in the risk of intimate partner violence. However, access to the graduation program fully buffers women from any increase in intimate partner violence, and partially buffers women and their households against other adverse effects. Further analysis suggests that improved household savings likely drives the program’s protective impact.

In this paper, we study the effects of the Women’s Labor Subsidy (WLS), introduced in 2012, on women’s labor outcomes. We use detailed administrative records for more than 2.5 million women that allow us to analyze employment and income trajectories before, during, and after the implementation of the subsidy. Using a regression discontinuity design that exploits the fact that eligibility is contingent upon falling below a specified vulnerability score cutoff, we analyze how eligibility and being a program beneficiary affect labor outcomes. Our results indicate no significant effects of WLS eligibility on women’s employment, months worked, or income. We also find null effects on labor outcomes for program beneficiaries. The null effect is relatively consistent across different subgroups of eligible women.

The combination of ongoing pandemic-related supply chain issues and the commencement of the Ukraine-Russia war triggered a sharp increase in gasoline prices in 2022, occurring alongside a forty-year high in general inflation. In response, five state governments temporarily stopped collecting excise taxes on gasoline in order to provide ‘inflation relief’ to their constituents. In this work, we examine the incidence of this tax relief and assess whether or not the full amount was passed-through to consumers using multiple methodologies in a natural experiment setting. In aggregate, we find that excise tax pass-through was not complete with about 82% of the excise tax relief passed down to consumers, though state-level event-studies show pass-through was likely complete in two states. Our results imply an unintended subsidy to gasoline retailers of approximately $390 million dollars in exchange for only about $10–15 in savings for each driver. The results highlight the need for alternative policy measures.

Can modes of collective action, including protests, demonstrations, and marches influence court decisions, even without affecting the law or formal institutions? Here, I assess the influence of protests on the results of removal proceedings in U.S. immigration courts. Using a difference-in-differences design and administrative immigration court data, I compare removal proceedings outcomes around the time of the 2006 immigration reform protests. I find some evidence of a small and temporary influence on removal decisions. The probability of removals appears to decrease by approximately 2 percentage points for up to 3 weeks following the protests’ onset. There is little evidence that the overall effect of mobilization has medium or long term influence on outcomes. The effect varies across case, location and judge characteristics.

This chapter examines the incidence and economic burden of cognitive impairment among older individuals in Italy within the long-term care (LTC) system. Using SHARE Wave 9 data (2022), cognitive impairment is measured through standardized memory and numeracy tests, classifying 8.6% of individuals aged 65+ as cognitively impaired. Cognitive decline rises sharply with age and is strongly associated with higher care needs, particularly intensive formal care. While both physically and cognitively impaired individuals rely heavily on informal care, cognitively impaired individuals receive substantially more hours of care. Total LTC costs amount to $35.3 billion (1.66% of GDP), with cognitively impaired individuals accounting for the largest share of expenditures. Informal care represents a greater financial burden than formal care across all groups. The findings highlight significant unmet care needs and underscore the urgent necessity of policy reforms and healthy ageing strategies to ensure LTC sustainability.

Germany experiences an increase in LTC recipients, due to population ageing but also to reforms which made LTC benefits easier accessible for individuals with cognitive impairments. Previous studies documented the cost of long-term care, and how it evolved. However, less is known about the specific case of elderly people suffering from cognitive impairment. Thus, we measure the economic costs of cognitive impairment, which include extensive medical, nursing care and at-home long-term care. We use the SHARE, the Survey on Health, Ageing and Retirement in Europe, Wave 9. We observe 4% of elderly people living at home with severe cognitive impairment (SCI) (Langa et al. (2017) definition). These individuals are 30% more likely to receive any care, and obtain on average 6 more hours of formal care and 6 more hours of informal care per week. The main driver is not the cognitive impairment per-se but the limitation in activities of daily living (ADLs) which SCI leads to. Thus, once controlling for ADLs, SCI does not explain any additional probability to use care. However, because people with SCI are more likely to have ADLs, the annual cost of their care is estimated to 10,000 euros per year per individual on average.

U.S. life expectancy stagnated and declined in the 2010s despite continued growth in real per capita income. We use Preston curves to characterize this pattern as a change in the relationship between income and longevity. Using state-level data from 1980 to 2019 and county-level data from 2000 to 2019, we estimate population-weighted Preston curves relating life expectancy to logged real per capita income. From 1980 to 2010, U.S. states followed the classic Preston curve pattern: rising income was accompanied by rising life expectancy. Counties followed the same pattern from 2000 to 2010. From 2010 to 2019, however, states and counties continued to become richer while life expectancy stagnated or declined. The curves shifted right without shifting up and became steeper, indicating decoupling and divergence: increases in aggregate resources over time no longer produced broad longevity gains, and, in any given year, inequality in life expectancy by income grew. These patterns are robust to alternative temporal anchors around the Great Recession and to substituting education for income. They also appear across sex and racial groups. County-level decompositions are broadly consistent with arguments that longevity has fallen due to widely shared exposures to social deterioration, which may account for the Preston curve reversal. Collectively, we show that the recent U.S. mortality crisis reveals a weakening—and growing inequality—in the conversion of aggregate resources into longevity gains. We conclude that the recent U.S. mortality crisis could be understood not only as a story about particular causes of death, but also as a weakening of institutional and social translation.

Many previous studies have used cross-cohort comparisons and a focus on in utero exposure to document the lingering effects of the 1918 influenza pandemic on survivors’ outcomes later in life. A subset has examined impacts on old-age health and mortality, finding mixed results. This paper contributes to the literature by extending the analysis to evaluate early-life and childhood exposure to the pandemic on old-age longevity along with a set of candidate mechanisms. We employ Social Security Administration death records linked to the full-count 1940 census and employ event-study and difference-in-difference regressions to compare longevity of cohorts with different age-at-exposure who were born in cities with high versus low exposure based on 1918 influenza-related mortality. Our treatment-on-treated calculations suggest that cohorts with age-at-exposure of 3-8 and 9-11 experience 6.4 and 11.2 months reductions in old age longevity; importantly, we note that these cohorts are often used as “controls” in the broader literature. While our main analysis focuses on males due to data constraints, supplementary results suggest smaller and less precise effects for females. An analysis of census data suggests reductions in health, education and socioeconomic scores as potential mechanisms.

In recent years, there has been Congressional interest in changing various policies related to research and development (R&D). Recent legislation has included provisions that would modify federal funding for R&D investments and tax provisions affecting the after-tax price of R&D. The Congressional Budget Office (CBO) has developed analytical frameworks for estimating how changes in R&D investments affect the economy and the federal budget. This paper describes the agency’s current analytical framework for modeling the economic effects of changes in federal funding for R&D, focusing on two distinct approaches that CBO has developed: an R&D capital stock approach and an R&D components approach.

Prospective merger simulations are a commonly used tool in industrial organization and antitrust, but evidence about their accuracy and predictive ability is limited. We study 101 mergers in consumer packaged goods and compare the realizations of price changes with predictions from merger simulations. In our sample of consummated mergers, predicted price changes from merger simulations are typically larger than realized ones. Despite the overprediction, we find that full merger simulations are more effective than both structural presumptions and approximations of the merger effect at identifying mergers with large price changes.

In monopsony models, wage markdowns induce deadweight loss and are therefore inefficient. Yet markdowns also arise in models with backloaded efficiency pay, where they are designed to induce effort among early-career workers and are thus efficient. To reconcile—and empirically distinguish—these two mechanisms, we build a dynamic model incorporating labor market power and endogenous effort. Estimating a team production model on novel data on U.S. public accounting firms, we find evidence of both: markdowns for junior workers and markups for senior ones reflect incentive-providing backloading, while monopsony power induces a ‘lifetime’ wage markdown of 15%.

We estimate the causal impacts of GLP-1 treatment on labor market outcomes using linked Danish administrative data and a matched stacked difference-in-differences design. We compare patients who initiate GLP-1 treatment during the first two years of Semaglutide availability to observably similar patients who initiate four years later. We find that GLP-1 treatment reduces long-term sickness leave by 17.3%. We estimate total fiscal benefits of GLP-1 initiation of approximately 1.3–1.5% of annual labor income per employed individual. We do not detect statistically significant or economically meaningful impacts on income, labor force participation, or employment over four years.

Employers facing limited labor market competition may suppress wages below socially optimal levels. Unions can counteract wage suppression through collective bargaining, though they may also push wages above the socially optimal level and lead to job rationing. We estimate a structural model of labor supply, labor demand, and Nash-in-Nash bargaining over wages between local teacher unions and school districts in Pennsylvania’s K-12 public school system from 2013 to 2019. We compare negotiated equilibrium wages and employment to oligopsony wage posting and social planner scenarios. On average, oligopsony reduces wages 7 percent below the social optimum, while collective bargaining raises wages 8 percent above it. Averages mask substantial district-level heterogeneity driven by bargaining power variation. Twenty-eight percent of school districts have salaries lower when public schools are unionized than when they are not due to cross-district externalities, where high salaries at one school cause hiring reductions that increase labor supply elsewhere.

Health shocks are a major driver of retirement. However, the existing literature on this topic tends not to consider the marital context in which retirements occur. Using the 1992-2022 Health and Retirement Study and staggered difference-in-differences methods, we investigate how spousal health shocks impact retirement transitions. We also investigate whether these effects differ by gender and health insurance status. We consider multiple definitions of health shocks, including self-reported health declines, additional diagnoses, hospitalizations, increases in out-of-pocket medical spending, and functional deterioration. Our results suggest that the probability of retirement increases by 1.2 to 1.3 percentage points (12 to 13 percent) after a spouse’s new health condition diagnosis or hospitalization. These retirements tend to occur earlier than anticipated. They also tend to be concentrated among women and respondents with employment-based health plans that include retiree coverage for their spouse.

Households' most consequential economic decisions are usually made jointly, yet behavioral interventions are typically targeted to individuals and optimized to overcome intra-personal constraints. We use a randomized controlled trial to study whether behavioral interventions targeted to couples can overcome interpersonal constraints related to intra-household decision-making. In rural Liberia, we layer a facilitated joint financial planning exercise atop a large unconditional cash transfer, assessing effects relative to cash only and a pure control. Relative to cash only, adding planning increases the amount of the transfer spent on productive investment and consequently improves economic outcomes by 0.16 standard deviation units. However, for households with the highest ex-ante conflict risk, these gains come at the cost of additional intimate partner violence.

Governments often intervene to prevent firm closures during crises, fearing that financially constrained but viable firms may fail. We develop a firm dynamics model with incomplete financial markets and show how financial frictions generate excessive firm exit. A key statistic governing this dynamic inefficiency is the marginal propensity to exit with debt. Using confidential U.S. Census data, we estimate the relationship between debt and exit and use it to discipline the model. The calibrated model implies that eliminating financial frictions reduces firm exit from 9.3% to 5.0% and generates welfare gains of 3.6% in consumption-equivalent terms. We show that the welfare costs of financial frictions rise sharply during financial crises but change little during standard productivity recessions. Finally, we compare government-guaranteed loans and grants, quantifying the trade-off between fiscal cost and effectiveness in preventing excessive exit.

One way of examining how mental health has changed over time is to use information available in large national surveys. While these survey-based measures are valuable in principle, and have been widely employed in prior research, a number of challenges may limit their practical usefulness or require considerable care in their application. This study uses data on U.S. 18-64 year olds from five major household surveys over the period 1999-2019 to investigate three specific questions. First, do different measures or the same indicator from different data sets consistently show how mental distress has changed over time? Second, how does the performance of single-item measures compare to those of psychometrically validated screeners based on multiple questions? Third, what are the benefits or potential costs of using different functional forms of these measures? The answers to these questions are as follows: 1) the estimated trends vary, often dramatically, across measures and, for the same indicator, across data sets and, as a result, some proxies provide a misleading understanding of how mental health has changed over time; 2) the single-item measures do as well or better than those based on multiple questions; 3) no single functional form demonstrates clear superiority over the others. After demonstrating these points, lessons are elucidated for researchers attempting to use survey data to examine trends in mental health.

Empirical researchers increasingly use large language models (LLMs) to extract structured features, such as sentiment scores, classifications, and expectations, from unstructured data and treat these generated features as observed covariates in downstream estimation. This practice can invalidate inference when systematic, input-dependent errors in generated features, such as hallucination and look-ahead bias, distort the downstream moment conditions. Even after correction, generated features remain noisy proxies whose error profiles differ across models and prompts. We introduce AI-Powered Inference (AI-PI), a method-of-moments framework for valid and efficient inference that combines three components: a moment-specific bias correction based on a small human-labeled calibration set; adaptive weights that optimally combine multiple model-prompt pairs; and an optimal calibration-set design that concentrates costly human labels where the generated features are least reliable. We establish consistency and asymptotic normality of the AI-PI estimator, allowing for data-adaptive labeling designs, cross-fitted LLM-pipeline tuning, and overidentified GMM. Simulations confirm substantial gains over naive LLM regressions and over debiasing without optimal weighting or labeling design. In an application to news-based sentiment and stock returns, AI-PI produces stable conclusions where naive analyses vary substantially across LLM and prompt choices, with a confidence interval roughly half as long as using the human-labeled data alone.

Divorce reshapes family life, yet little is known about one of its most consequential features: the allocation of child custody. We study the impact of joint versus sole custody on both parents and children using rich administrative data from Sweden linked to over 25 years of newly-collected court custody rulings. To address selection concerns, we exploit random assignment of custody disputes to judges who differ sharply in their propensity to grant joint custody. For fathers, joint custody substantially raises earnings and improves mental health, consistent with sustained paternal involvement enhancing labor market attachment and psychological well-being. In contrast, there are no measurable labor market or mental health effects for mothers. Turning to children, joint custody increases standardized test scores and school quality without affecting mental health outcomes. Joint custody increases fathers’ chances of remarriage, keeps separated parents in closer geographic proximity, and has no effect on intimate partner violence allegations against either partner. These findings inform longstanding debates over the role of child custody in shaping post-divorce family life.

We develop a unified framework that combines shock volatility with sign and narrative restrictions and provides the theoretical foundation for the computationally efficient sampler HARS. HARS preserves the heteroskedastic likelihood and can be combined with any posterior simulator for the heteroskedastic model. In monetary policy, oil market, and fiscal policy models, the same restrictions deliver substantively different economics once shock heteroskedasticity is accounted for. Homoskedastic SVARs put uncertainty in the wrong place, pushing shock-scale variation into impulse-response uncertainty. Heteroskedasticity sharpens dynamic responses, alters economic conclusions, and restores 90% credible intervals as a practical standard for economic inference.

Discrete policy thresholds are pervasive in tax and regulatory systems and can substantially distort behavior. We show that notches acting as barriers to mobility within a distribution generate distortions extending far beyond the threshold. The same mechanism biases conventional difference-in-differences estimators, and we propose a new methodology to recover causal effects. Applying the method to the abolition of a size-based payroll tax notch, we find that the notch reduced the number of firms above the threshold by 18 percent and lowered treated firms’ employment, capital stock, and value added by 10 percent, whereas conventional difference-in-differences estimates imply negligible effects.

Demand flexibility at scale is likely to be an important part of the future energy system. This study evaluated the world’s first nationwide domestic and commercial demand flexibility program. We analyzed the policy using a natural field experiment, with a sample of 2.7 million, assigning 119,999 customers to a control group and the rest to receive randomized encouragement to sign up to the demand flexibility program. The program paid consumers to reduce their demand below a predicted baseline at peak demand across 16 events (i.e., when the system was stressed) during the Winter of 2023–24. Customers who opted into events reduced demand during events by 23.1% among compliers, at an average cost for the system operator of £2,325 per MWh. The adoption of solar panels and batteries, heat pumps, and EVs all increased demand response.

Buyers of complex goods and services often rely on the advice of expert intermediaries who are themselves imperfectly informed about the quality of the available options. How well do these intermediaries learn about that quality and act on it? We study this question in the setting of referrals from primary care physicians (PCPs) to specialists, using data on 4.5 million joint replacement surgeries for Medicare beneficiaries. We first document substantial heterogeneity in specialist quality and costs within geographic markets, and we present design-based evidence showing that PCPs adjust their referrals specifically based on the outcomes of their own patients. We then employ a structural learning model of PCP referral choices to quantify the losses from informational frictions and to simulate possible reallocations with improved information. Beyond learning, the model also accounts for limitations on possible reallocations due to habit persistence and capacity constraints. We find that about one-quarter of patients would be referred to a different specialist in the absence of informational frictions, with small but meaningful improvements in patient outcomes.

Standard macroeconomic data do not cleanly separate the systematic and nonsystematic components of monetary policy. We show that incorporating unstructured text data into the structural estimation of a DSGE model can sharpen this distinction. We augment a standard state-space model with a non-core measurement block that links structural shocks to time series derived from FOMC transcripts, using a spike-and-slab prior to let the data select which series are informative. In a medium-scale New Keynesian model for the U.S., incorporating text improves predictive performance and materially alters structural inference: the new model estimates a lower response of the policy rate to inflation, higher price stickiness and lower price indexation, implying a flatter and less backward-looking price Phillips curve.

This paper provides a novel framework for assessing the effect of ambiguity on asset values within the Klibanoff-Marinacci-Mukerji (KMM) smooth ambiguity framework. By shifting the analysis into a continuous space of prior probabilities, we establish that ambiguity leads to an adjustment of beliefs (“ambiguity-adjusted probabilities” or “distorted probabilities”) characterized by First-Order Stochastic Dominance (FSD). Leveraging this property, we introduce a systematic economic decomposition of asset valuation separating the baseline risky valuation from the structural cost of uncertainty. Our continuous framework shows that increased ambiguity aversion depresses optimal asset demand.

This paper explores how diagnostic thresholds and a written consent requirement affect decision making between patients and transplant surgeons regarding the use of deceased donor kidneys. Combining administrative data on the universe of organ donors and transplant recipients in the United States, we show that age-based discontinuities within the Expanded Criteria Donor system (ECD), which was in place from late 2002 to late 2014, led to 4.0 and 5.4 percentage point differences in the rates at which otherwise indistinguishable kidneys were discarded. A discontinuity within the subsequent presentation of the Kidney Donor Profile Index (KDPI) led to a 2.6 percentage point difference. We present evidence that diagnostic thresholds have nuanced effects on decision making and information acquisition; procurement biopsy rates, for example, rose substantially at the ECD system’s age-based discontinuities. We further show that written consent requirements triggered within the ECD and KDPI labeling systems substantially reduced the number of potential recipients to whom kidneys were offered prior to being discarded. This channel can explain the majority of the increased rate at which “High-KDPI” kidneys are discarded under the current system.

AI predicts; humans use its predictions to make decisions. These predictions are combined with human verification and analysis, queries to other statistical models, and so on. The economic value of an AI, therefore, depends on how it interacts with the surrounding decision environment. We describe the value of AI as part of this "composite experiment" where AI makes a coarse prediction of the state of the world, show what this means for optimal model training via a geometric argument, explain why optimal training can be discontinuous in economic variables, and study how heterogeneous users or monopoly model trainers affect these results. In particular, maximizing the unconditional accuracy of AI predictions is generally suboptimal.

Between 1945 and 1970, the U.S. Department of Defense was one of the country's largest funders of university research, and the most important in the physical sciences and engineering. Political pressures subsequently led to this funding declining nearly two-thirds by the mid-1970s and never fully recovering. We show that these cuts were felt across the U.S. research system, with ensuing declines in university scientists, PhD production, and research output. Early career scientists who were DoD-funded in 1970 were more likely than peers to leave universities, with many moving to industry. Though some became more likely to patent, in the aggregate, this appears to have reduced science-linked innovation in related technologies and compressed U.S. leadership in formerly DoD-driven fields. These effects extend to outcomes more closely related to military objectives: fewer PhDs entered the defense industrial base, and an initial increase in science-linked defense patenting in the most exposed technology areas gave way to a long-run decline.

We study no-poach cartels using a wage-posting model that puts worker poaching at the center of labor market competition. Even when just two out of ten employers in a local labor market collude, wages fall by almost 5% market-wide. The reason is that no-poach agreements suppress competition along the job ladder, with spillovers to non-colluding firms. We then compare no-poach agreements to two other forms of anti-competitive conduct in the labor market: noncompete agreements and wage fixing. No-poach agreements have by far the largest negative wage effects.

We study how firms and workers adjust when previously restricted migrants gain full and portable work rights in a labor market with substantial informality. We exploit the 2007 EU accession of Bulgaria and Romania, which granted unrestricted work rights to Italy's largest migrant group. Using matched employer–employee administrative data and an IV-DID design, we find that firms suddenly and persistently shift employment composition toward EU07 workers, compressing the native employment share without reducing native hiring or increasing separations. We don't detect any significant change in wages for either natives or EU07 workers. For migrants, this null effect reflects offsetting compositional shifts as newly observed and incumbent EU07 workers enter the formal workforce with different wage trajectories. Consistent with a shift in bargaining power toward workers, EU07 migrants experienced significant gains in job mobility and job security. Overall, the evidence suggests that removing legal restrictions reshaped firms’ personnel choices and altered migrants’ employment relationships, improving their outside options, bargaining position, and access to more secure jobs.

Political contributions generate access and influence for firms, but their public visibility exposes firms to reputational risk. We study how firms adjust their political spending when the reputational cost of political ties rises sharply. To identify this response, we exploit fatal school shootings and mass shootings as exogenous shocks to the salience of gun violence in the United States. We implement a staggered difference-in-differences design on a panel of corporate PAC contributions to U.S. House candidates, 2000–2024. We find that corporate PACs divest selectively and temporarily following gun violence shocks. Contributions to Republican candidates fall by 70.3% after fatal school shootings in competitive districts and return to baseline within nine months, with no substitution toward Democratic candidates. A parallel penalty of 60.9% emerges for Republicans in safe Democratic districts but is absent in safe Republican districts. Mass shootings generate similar perturbations in corporate contributions. These patterns indicate that firms withdraw only where the reputational risk of continued association is high or its strategic value is low. The observed divestment appears across industries and is stronger for firms with greater consumer exposure. Our findings reveal that firms treat political ties as time-varying liabilities, temporarily withdrawing visible financial support when issue salience spikes and resuming once public attention fades, leaving firms’ long-run political investment intact. Since public pressure is limited and dissipates quickly, and corporate divestment is transient rather than durably reallocated, the underlying financial incentives facing policymakers remain unchanged in the long run, sustaining the policy status quo.

When a new technology promises large private benefits but may impose social costs that markets do not price, demand need not reveal how citizens want it governed. We examine this using a nationally representative U.S. survey experiment (N=5,556) on human enhancement technologies (HET). The experiment randomizes benefit domain, mechanism, heritability, purpose, and risk across vignettes; for each respondent’s assigned vignette, we elicit stated adoption, preferred regulation, and ethical and societal concerns. Overall, about 53% would adopt. Framing the technology as enhancing rather than restorative lowers adoption by about five percentage points, as much as a severe side-effect profile. About 28% would not adopt at any benefit. This refusal is driven overwhelmingly by the enhancing framing rather than by risk, consistent with a non-compensatory constraint for a substantial subgroup. Most who would adopt still favor strict regulation, and most who would never adopt do not wish to forbid others from doing so. Productivity enhancement generates the most ethical concern of any attribute but attracts the least regulation, and respondents favor subsidizing rather than taxing its adoption, consistent with a concern about access rather than safety. Private demand is therefore an unreliable guide to the governance citizens want, and the divergence we document provides a basis for regulators seeking to align the direction of technical change with societal values and priorities.

We study how equilibrium patterns of production, trade, and input sourcing in complex supply chains are shaped by aggregate risk. We develop a quantitative multi-country model with multi-sourcing across stages. We show that sourcing shares equal an input’s expected output elasticity — its expected marginal contribution to output across states of the world. Risk has a positional effect on sourcing and welfare, operating through offsetting cross-stage complementarity and within-stage substitutability; which one dominates is a quantitative question. An increase in a country’s own risk always lowers its welfare; risk elsewhere has ambiguous, sometimes positive, effects through relative prices. We also show analytically that risk attenuates comparative advantage, as countries shift sourcing away from their most productive suppliers. Quantifying the model for 50 countries and 3 production stages, we show that supply-chain complexity lowers volatility for the riskiest countries, and rising Chinese-origin risk reallocates production and lowers welfare unevenly across the chain.

Trade networks underpinning the energy transition are endogenous economic objects, and their structure is a source of market power. Using bilateral trade data for thirteen electrification metals over 1995–2023, we show that trade in these materials has reorganised into a hub-and-spoke system centred on China, in sharp contrast to the diffuse, multilateral structure of fossil fuels. This centrality did not follow from resource endowments: China holds few of the underlying reserves. It was built through processing investment, industrial policy, and commodity-targeted development finance—an equilibrium outcome rather than a geographical accident. We formalise this in a stylised model in which a country chooses how central to become, and show that centrality maps into pricing power: the world price response to a strategic supply cut is stronger when the network is more concentrated and downstream demand and fringe supply are more inelastic. Constructing text-based, commodity-specific supply shocks and estimating local projections, we find that supply contractions in critical metals raise US and EU consumer prices by roughly twice as much as comparable fossil-fuel shocks, and more persistently. Centrality is therefore not merely descriptive: it creates leverage over global prices. The green transition reduces strategic dependence on hydrocarbon exporters but reconstitutes it around mineral supply chains.

This paper examines optimal currency demands for global equity and bond investors in a large cross-section of developed and emerging markets over the 1975-2023 period. It extends the framework of Campbell et al. (2010) by incorporating both optimal portfolio-risk minimizing currency exposures, accounting for empirically measured hedging costs arising from deviations of Covered Interest Parity (CIP), and optimal expected-return-driven currency demands based on non-zero expected excess currency returns arising from empirically measured deviations of Uncovered Interest Parity (UIP). The analysis shows that the main conclusions of their portfolio risk-minimizing framework hold for this larger and longer panel of countries and that they are robust to deviations from CIP. Specifically, it is optimal for portfolio risk-minimizing equity investors to hold exposures to the U.S. dollar and the euro while avoiding exposure to all other currencies, whereas bond investors should hedge all currency exposures. In contrast, observed deviations from UIP are sufficiently large and persistent among currencies with high average relative interest currencies, especially Emerging Markets currencies, to generate expected return-driven currency demands that offset, and in some cases reverse, portfolio-risk minimizing demands, even for investors with low risk tolerance. The average excess returns on those currencies are large enough to compensate investors for their substantial return volatility and strong positive covariance with equity returns.

Over nearly two centuries, US inventions have become increasingly dissimilar: not just fewer head-to-head collisions between inventors, but growing distance between neighboring inventions. We document this secular decline in similarity using validated neural language models applied to the full text of claims in over 11 million US patents (1836–2023), corroborated by a 98% decline in patent interference rates, a measure of independent simultaneous invention. Measuring this correctly requires validation, since different representations of the same patent text can yield opposite conclusions about whether inventions are converging or spreading out. Our validation framework, the first systematic comparison for patent text, selects among these representations. We develop a spatial competition model in which inventors choose locations in idea space. The model explains spreading out and connects it to several independently documented patterns — rising R&D investment per inventor, increasing patent values, weakening knowledge spillovers, and declining research productivity. The mechanism is spatial; as inventors spread out to capture new territory, inventions become more valuable but also more costly for others to absorb. In doing so, the model turns spillover intensity, innovation step size, and research productivity from fixed primitives into outcomes of inventor positioning. A calibrated decomposition attributes roughly 40% of the long-run decline in US research productivity to these spatial forces, alongside traditional explanations such as fishing out and the burden of knowledge. Where inventors stand relative to each other in idea space matters as much for growth as how many of them there are.

We construct a novel stock-level measure of volatility disagreement as the cross-sectional dispersion of realized variance forecasts built from heterogeneous information sets and machine learning models. Sorting single-name delta-hedged straddles on this measure yields a long-short return of −5.14% per month, robust to known option return predictors and not subsumed by disagreement about first moments or the variance risk premium. A one-standard-deviation increase in volatility disagreement is associated with a 30% rise in option position opening. The cross-sectional patterns of our disagreement measure align with recent theoretical advances of beliefs and pricing of variance claims. Evidence on attention, ownership, and arbitrage costs is more consistent with mispricing than risk compensation.

We study human capital in venture capital (VC) using a new dataset covering over 100,000 professionals affiliated with U.S. VC firms. Investment success is extremely concentrated: fewer than 40% of VCs with any investments are ever credited with a successful investment, and 90% of investment profits are generated by 5% of VCs. Differences in education, prior work experience, and demographics predict career progression and investment outcomes, consistent with persistent investor-specific skills. Quasi-experimental variation from marginal inclusions on the Forbes Midas List shows that achieving superstar status increases access to highly-valued startups, complementing other human capital and contributing to concentration.

Physicians in the U.S. military health care system are quasi-randomly assigned to combat deployments, leading to gaps of varying durations in their clinical practice. We leverage this unique setting to provide novel causal evidence on skill depreciation (forgetting) and learning-by-doing among physicians. We find robust evidence that readmission rates increase by 48% in the first two months after a surgeon returns from a deployment. However, surgeons return to baseline performance within 6 months of resuming practice. In contrast, obstetricians maintain elevated cesarean section rates for up to 9 months, implying a deeper change in clinical judgment. Finally, we interpret these patterns through the lens of a learning model and estimate learning-by-doing rates for surgeons and obstetricians. A doubling of recent procedure volume reduces readmission and C-section rates by 17% and 11% for surgeons and obstetricians, respectively.

The rise of superstar firms has made dominant companies central to modern economic life, and antitrust enforcement is one of the main policy tools for regulating their market power. Public opinion can shape the political and regulatory environment in which antitrust enforcement takes place, yet there is little direct evidence on what drives these preferences. We conduct a pre-registered information-provision experiment with 4,000 American households. Respondents were told about one of five real antitrust cases and randomly assigned to information treatments designed to study four potential drivers of support for antitrust enforcement: perceived market share, perceived consumer harm, perceived unfair competition, and perceived negative image. All four treatments moved the beliefs they were designed to affect, but their effects on demand for antitrust differed sharply. Information about consumer harm had the most systematic effects: it increased plaintiff support and support for break-up and conduct remedies, with effects remaining visible one month later, and also spilled over to broader support for antitrust policies. By contrast, and contrary to expert forecasts, information about market share had no meaningful effect on demand for antitrust enforcement. The findings suggest that the public thinks like economists in one key respect: they do not care about market share per se, but respond instead to consumer harm. One factor outside the core economic framework, perceived unfair competition, also matters, though its effects are more limited in scope. We discuss implications for policymakers and regulators.

We study the causes and consequences of bank runs. By applying large language models to historical newspapers, we create a comprehensive database of bank runs in U.S. history with information on 3,984 runs on individual banks from 1863 to 1934. Our novel data allow us to establish that runs are considerably more likely in weak banks but also occur in strong banks, especially in response to negative news about the real economy or the broader banking system. However, runs typically only result in failure for banks with poor fundamentals. Strong banks survive runs through various mechanisms, including signaling strength, interbank cooperation, and temporary suspension. At the local level, runs on banks with poor fundamentals translate into substantially larger declines in deposits, lending, and manufacturing activity than runs on strong banks. Our findings imply that poor fundamentals are central to explaining both when runs occur and when they have severe economic effects, tempering the view that small shocks can generate discontinuous jumps to bad equilibria through self-fulfilling run dynamics.

This paper uses administrative data to analyze wealth flows from Norway to offshore tax havens before and after a major improvement of global financial transparency: automatic exchange of bank account information between tax authorities. We present three results suggesting that the policy is a significant deterrent of offshore tax evasion: First, taxpayers who become wealthy are much less likely to shift wealth to offshore banks. Second, when wealth does flow to offshore banks, it is much less likely to reduce domestic tax payments. Third, there is no increase in the use of complex ownership structures for offshore wealth flows.

In this paper we survey recent advances in the economic theory of identity formation. We restrict our analysis to models which conceptualize identity formation as embedded into an inter-generational cultural transmission process, and therefore have implications for the dynamics of social identity. Through the lens of a general framework linking identity formation to cultural evolution, we discuss issues related to the dynamics of oppositional, racial, or minority attitudes, cultural polarization, identity switching, and openness to alternative identities. An application of the set-up to multidimensional identities constructed from combinations of characteristics, provides conditions under which societies converge (or not) toward narrow identities centered on salient markers such as religion, ethnicity, or race. We conclude by outlining promising avenues for future research.

We investigate the impact of equity crowdfunding exemptions on new venture creation. We further explore whether the effect varies across industries with different levels of external finance dependence, and whether this heterogeneity is influenced by regional industrial structures. Empirical evidence shows that, while the average effect of crowdfunding exemptions on new venture entry is not statistically significant, the impact is positive and significant in industries with higher external finance dependence. Moreover, this positive effect is further amplified in regions characterized by greater related variety. Complementary analyses show that the increase in new venture creation does not appear to be accompanied by a decline in entry quality. These findings highlight the importance of firm-level financial constraints and regional industrial context in shaping the effectiveness of crowdfunding policies.

This study investigates the “stars effect” of recruiting overseas scholars as deans and its impact on academic output in China from 2001 to 2019. We find that appointing a returnee dean increases a department's English publications by 40% annually. This positive effect applies to both top-tier and non-top-tier journals, without crowding out Chinese publications. The magnitude of the effect correlates with the dean's international connections and the ranks of the destination and source institutions. Returnee deans enhance output through knowledge spillovers, expanded networks, and increased overseas personnel, but not additional research grants. Our findings demonstrate the positive role and extensive influence of power-granted talent initiatives in developing regions.

This study investigates how technologies emerge to sustain technological sovereignty in response to exogenous shocks. We focus on the efforts of the Finnish state to overcome the shortage of mineral oil-based lubricants during the Second World War and identify tar oil as a central technology in this endeavor. By analyzing the emergence and decline of the Finnish tar oil industry, we elaborate on the life cycle and key mechanisms of temporary technologies as well as their role in maintaining technological sovereignty. These findings lead to a definition of temporary technology as a distinct form of technology evolution. Our findings contribute to the technology evolution literature by theorizing a form of technology that has a limited long-term impact, making it suitable for addressing temporary shocks without altering long-term technology evolution. For the technological sovereignty literature, we extend understanding of how sovereignty can be maintained in the face of unanticipated exogenous shocks and how that involves cooperation between the state and non-state actors.

Abstract Research Summary This study examines how legal design shapes contractual governance in public–private partnership (PPP). We argue that PPP‐specific laws do not simply strengthen institutional safeguards; by varying in detail, they also alter the flexibility available for project‐level contracting. Highly specific laws better constrain governmental discretion but raise adaptation costs, making user‐pay contracts, where private partners bear demand risk and rely on market‐responsive adjustment, less attractive. Less specific laws preserve greater contractual discretion and are therefore associated with more user‐pay arrangements. We also show that countries with weaker political constraints adopt more specific PPP laws, suggesting that legal design compensates for weaker institutional checks. Using 3986 PPP projects in 53 countries from 1997 to 2021, we find support for these claims. Managerial Summary Governments often pass public–private partnership (PPP) laws to attract private capital into infrastructure projects. This study shows that what matters is not only whether such laws exist, but how detailed they are. Highly specific laws can make government commitments more credible, especially where political checks and balances are weak, but they can also limit the flexibility private partners need when revenues depend on users, such as tolls or fees. Across 3986 PPP projects in 53 countries, we find that more detailed laws are linked to fewer user‐pay projects, while less detailed laws are linked to greater use of user‐pay arrangements. Our analysis suggests that legal certainty and flexibility must be balanced: specific legal regimes can protect private investment while narrowing the range of viable investment models.