In this paper, we examine the role of state-owned enterprises (SOEs) in the transmission of fiscal policy shocks in China, combining a structural VAR with macroeconomic data and a panel model with firm-level data. We first identify two types of structural fiscal shocks using a Bayesian SVAR with sign restrictions and informative priors on structural elasticities: (1) stimulus shocks, defined as deviations from a policy rule for the budget deficit, and (2) government size shocks, which reflect changes in taxes not necessarily affecting the deficit. These shocks are then incorporated into a local projections framework using firm-level data. Our analysis reveals that SOEs respond fundamentally differently from non-SOEs to fiscal shocks. The results suggest that SOEs are not in strict competition with non-SOEs for government resources: both types of firms benefit from fiscal stimulus, yet SOEs are the ones predominantly subject to crowding out when the size of the government sector expands. At the same time, SOEs in strategic industries consistently receive government support under both government size shocks and tax-cut-led stimulus shocks. Moreover, in nonstrategic sectors, SOE investment exhibits a leading effect over non-SOE investment under tax-cut-led stimulus—an effect that vanishes under spending-led stimulus.

We surveyed economics and finance professionals on the transition to a low-carbon economy, assessing risks, opportunities and stakeholder responsibilities. Findings reveal that respondents view the transition as an opportunity for the financial sector, with a modest increase in banking risks. Most respondents agreed that governments hold the primary responsibility for climate mitigation policies, with carbon tax as the favoured solution. Additionally, respondents perceived the COVID-19 pandemic to have a neutral or positive impact on the transition, while the Ukraine war to have a strong negative impact. Notably, opinions differ based on environmental consciousness and professional roles, with environmentally conscious individuals expressing more optimism.

The modern business corporation emerged from the medieval and chartered corporations. The medieval tradition of legal pluralism was replaced by two ‘pure’ disciplines – Law and Economics – that left no conceptual space to understand its hybrid nature, decentralizing law-making and centralizing market transactions, or to frame its person-thing duality. Under intellectual monopoly capitalism, this hybrid nature has degenerated: corporations have monopolized knowledge, outsourced production to dependent peripheral firms, and become deeply intertwined with financial markets and geopolitical rivalries – lending substance to notions of techno-feudalism, while marking a profound break with the medieval tradition of open science that first made competitive markets possible.

Energy-efficient biomass cookstoves and small solar systems play an important role in the transition to clean energy. Despite their affordability and scalability, uptake remains low among households in sub-Saharan Africa. This paper examines whether household-level behavioural factors help explain this under-adoption. Drawing on data from real-purchase offers in rural Rwanda and Senegal, we analyse how willingness to pay for the technologies varies with risk aversion, innovation resistance, time preferences and beliefs. These traits explain part of the variation in purchase decisions, though effects are generally moderate. The findings improve our understanding of consumer behaviour with regard to innovative consumer goods at the base of the pyramid and inform policy and market strategies of suppliers entering these markets. We conclude by recommending that behavioural approaches be applied conservatively and only in conjunction with efforts to improve affordability and access.

This study investigates employees’ perceptions of artificial intelligence (AI) in the workplace, using data from 1,224 working adults across two samples. Drawing from an extended version of the Technology Acceptance Model, we examine how employees’ trust in AI and their perceptions of AI’s usefulness and ease-of-use at work shape their affective attitudes toward using AI, which in turn influence their intentions to adopt AI in their job. Perceived usefulness and trust in AI predicted employees’ intentions to adopt it at work via affective attitudes toward using AI. The findings for perceived ease-of-use were inconsistent, suggesting potential workplace-specific implications of this pathway. None of the relationships differed by gender, education, or leadership status. The findings bridge the technology adoption and organizational science literature to offer theoretical insights, practical implications, and future research directions for facilitating employees’ intentions to adopt AI at work.

This paper examines relationships between AI occupational exposure and workforce patterns in U.S. federal agencies from 2019–2024. Using administrative employment data, we document systematic associations between agencies’ concentrations of AI-exposed occupations and employment dynamics. Agencies with higher AI exposure exhibit declining routine employment shares, expanding expert roles, and wage compression effects. We develop a theoretical framework incorporating institutional constraints distinguishing public organisations: employment protections, standardised compensation systems, and political oversight. The model features strategic interactions between budget-maximising directors and electoral-sensitive overseers, predicting workforce evolution under institutional constraints. Our identification exploits fixed occupational exposure scores, so observed changes in agency-level exposure reflect workforce composition shifts rather than measurement artefacts. Patterns suggest agencies with greater AI-susceptible occupations experience reallocation rather than displacement, providing insights for understanding technological change in institutionally constrained environments and informing governance frameworks balancing modernisation with democratic accountability.

This article proposes sequential randomized tests to locate the presence of jumps on the paths of efficient asset prices in a continuous-time model. The randomized statistics are generated by artificially adding randomness to the robust approximations of the locally averaged returns of the efficient price. In the case of finite activity jumps, we derive the asymptotic distribution of the maximum of all the local statistics unaffected by jumps, which makes it feasible to control the limiting probability of the global type I error and demonstrate the power of the test. We also present the theoretical results to illustrate the behaviors of the test statistics in the presence of infinite activity jumps. Simulation studies indicate the favorable performance of the proposed test in finite samples, and we also apply the test to the stock price data of Apple and Microsoft.

Marco Lippi was born in Rome in 1943. An indefatigable and inspiring pedagogue, he has been teaching mathematics, economics, the history of economic thought, and econometrics to generations of students at the Universities of Perugia, Rome (La Sapienza, Tor Vergata, and LUISS), Modena, the Scuola Superiore Sant’Anna in Pisa, and the European Center for Advanced Research in Economics and Statistics (ECARES) in Brussels. As a fellow of the Einaudi Institute for Economics and Finance (EIEF), he still teaches, with the indomitable enthusiasm that has become legendary among his students and colleagues, Master and Ph.D. courses offered by this renowned Roman institution.

We analyzed the determinants and potential of U.S. agricultural exports to South Asian, Southeast Asian, and Southern African countries by employing a stochastic frontier gravity model. Our estimated results suggest that importers’ GDP, institutional quality, globalization level, and participation in Trade and Investment Framework Agreement significantly promote U.S. exports, while geographic distance and landlocked status act as major constraints. The derived technical efficiency scores reveal considerable underperformance of U.S. exports. We recommend that the United States can expand and strengthen its Trade and Investment Framework Agreement, institutional cooperation, interconnectedness, and direct policy focus toward countries with the largest export gaps.

This article explores the macroeconomic consequences of a sharp US dollar depreciation against the backdrop of high US policy uncertainty, fiscal imbalances and growing geopolitical fragmentation. Using the NiGEM global macroeconomic model, we simulate three scenarios: (1) a combined shock to currency and investment risk premia; (2) a broad-based currency risk premium shock and (3) a currency risk premium shock specifically benefiting the euro. The first scenario results in a global slowdown, with pronounced effects on the US economy. In contrast, the latter two scenarios suggest potential gains for the Euro Area, conditional on the euro’s enhanced international role. Realising such gains would require measures to increase the supply and liquidity of Euro Area safe assets. The analysis also highlights risks beyond the model’s scope, including the potential for a financial crisis triggered by a sudden loss of confidence in the US dollar.

This paper examines how structural reforms can boost long-term growth and welfare in the U.S. economy. Using a model calibrated to historical data, we compare three reforms: reducing regulatory costs, increasing public investment, and eliminating rent-seeking. Our results show that all three improve welfare, but through different channels. Cutting regulatory burdens delivers quick efficiency gains with minimal adjustment costs. Raising public investment has the most substantial impact on growth and welfare, though it requires short-term trade-offs. Eliminating rent-seeking improves efficiency and leisure, but its growth effect is smaller. Overall, public investment emerges as the most powerful lever for growth, while regulatory simplification and institutional reform provide complementary benefits by reducing distortions, improving resource allocation, and reinforcing the efficiency gains from fiscal policy.