Since the 1990s, growing interest in the relationship between clusters and economic growth has highlighted the importance of understanding their internal structures and life cycles. Still, the mechanisms underlying cluster emergence remain largely unknown, especially regarding the influence of public policies in this initial stage. This paper examines the emergence of a metalworking cluster in the Spanish steelmaking pole of Asturias, focusing on Francoist industrial policy and the regime’s relationship with regional firms.

Findings indicate that Asturias presented favorable conditions for cluster formation since the late eighteenth century. However, only the establishment of the national steelmaking champion Ensidesa in 1950 triggered the appearance of self-reinforcing dynamics, finally boosting the cluster’s emergence. This process resulted from the indirect externalities generated by the steel industry and was never part of the Francoist industrial agenda. Despite the recognized sector’s potential, the regime prioritized strategic base industries and systematically ignored calls for direct support for metalworking firms.

This paper develops a parallel between prudence and population ethics. I argue that developing a standard guiding the evaluation of the comparative prudential value of different lives is challenging because it shares a similarity with population ethics: In both contexts, we assess the comparative value of populations of person-stages/people, which may vary in number and level of well-being. Based on this analogy, I show that Arrhenius’ fifth impossibility theorem can be applied to prudence. I develop and compare five possible escape routes: Critical-Level Views, Totalism, Limited Aggregation, Nebel’s Lexical Threshold View and what I call the Negative Lexicality View.

We describe the main insights from the papers included in this special issue, Challenges for the Development of Latin America in the Anthropocene: Current Research in Environmental Economics. The contributions are organized around three themes: the economic and welfare impacts of temperature variability, the role of institutions and user rights in shaping environmental governance and the effectiveness of regulatory instruments for managing ambient and atmospheric pollution. Together, these papers show that environmental outcomes in Latin America are deeply shaped by institutional capacity, governance quality and social inequality. By combining rigorous empirical analysis with attention to local contexts, they demonstrate how environmental economics can inform policy responses to the triple planetary crisis of climate change, biodiversity loss and pollution.

Geographical indications (GIs) are information signals based on a product’s geographical origin. They reduce information asymmetry for consumers and protect producers from imitation. This paper examines the local economic impact of GIs by focusing on the renowned Champagne AOC in France. Champagne is protected under the Appellation d’Origine Contrôlée (AOC), the EU’s strongest GI classification. My identification strategy leverages the fact that the municipal-level boundary of the Champagne AOC was historically determined by political decisions, rather than viticultural qualities (i.e., terroir). Using granular geographic, economic, and fiscal data, I provide causal evidence that this institutional protection improves local economic outcomes beyond the wine sector. Despite a sharp increase in vineyard prices over the past two decades, there is no evidence of crowding out of other economic activity over time. These findings suggest that the projected expansion of the Champagne AOC could stimulate further regional economic development for newly admitted municipalities.

In machine learning-based mortality models, interpretation methods are well established, and they can reveal structures resembling the age or time effects in traditional mortality models. However, in the reverse direction, using such traditional components to guide the initialization of a neural network remains highly challenging due to information loss during model interpretation. This study addresses this gap by exploring how components from pre-fitted traditional mortality models can be used to initialize neural networks, enabling structural information to be incorporated into a deep learning framework. We introduce Kolmogorov–Arnold Networks (KAN) and first construct two shallow models, KAN[2,1] and ARIMAKAN, to examine their applicability to mortality modeling. We then extend the Combined Actuarial Neural Network (CANN) into a KAN-based Actuarial Neural Network (KANN), in which classical model components calibrated via generalized nonlinear models or generalized additive models are naturally used for initialization. Three KANN variants, namely KANN[2,1], KANNLC, and KANNAPC, are proposed. In these models, neural networks assist in improving the accuracy of traditional models and help refine the original parameter estimates. All KANN-based models can also produce smooth mortality curves as well as smooth age, period, and cohort effects through simple regularization. Experiments on 34 populations demonstrate that KAN-based approaches achieve stable performance while balancing interpretability, smoothness, and predictive accuracy.

This paper presents a macroeconomic framework for carbon markets. We set up a global climate-economy with carbon-intensive energy inputs, renewable energy, natural carbon sinks, and a carbon capture technology to show that (i) within a comprehensive carbon pricing system, a carbon tax alone implements any given path of carbon emissions; (ii) ‘additionality’ is not a property of the optimal carbon pricing system; and (iii) without a carbon tax, renewable subsidies, preservation of carbon sinks and a price for carbon capture are needed.

This article considers whether Members of the World Trade Organization (WTO) can develop a collective response to a globally welfare-damaging situation that impacts individual Members differentially. We conclude that collective action remains within the letter and spirit of the WTO Agreements. We set out the enabling procedures for collective action in a WTO dispute setting, in particular, the use of the rarely used situation complaint. We were motivated by the United States’ move to redraw its trade relations and break from its international trade commitments through bilateral negotiations in which it holds asymmetric leverage, buttressed by a pre-emptive announced escalation in response to any attempt by counterparties to join in forging a collective response. We conclude that, if undertaken, collective action can raise each Member’s voice into a countervailing choir and, more importantly, it can reinforce the mutual benefits derived from the multilateral trading system. Collective action thus serves a double purpose in engaging domestic concerns and the collective interests of those intending to preserve the multilateral system on which each Member depends.

Indonesia’s banking sector faces digital transformation challenges, with mobile banking growth of 52% projected for 2025, while digital literacy gaps (49.68% financial literacy) and cultural barriers threaten workforce engagement. This study investigates how Indonesian bank leaders foster meaningful work during digital transformation by examining technology factors, workforce readiness, and growth acceleration strategies within Otoritas Jasa Keuangan regulatory oversight and collectivist cultural contexts. Using qualitative methodology, in-depth interviews were conducted with 10 senior executives across 8 Indonesian banks representing government-owned, private, foreign, and digital institutions between December 2022 and February 2023. Data analysis followed the Gioia methodology, progressing from first-order concepts to theoretical themes and aggregate dimensions. The findings reveal six critical leadership practices enabling meaningful work creation: agile leadership promoting experimentation and psychological safety, tech-forward leadership integrating AI strategically, emotional intelligence managing virtual teams, recognition systems celebrating innovation, regulatory–ethical balance maintaining compliance while enabling innovation, and co-creation approaches involving customers. These practices operate across micro (individual), meso (team), and macro (organizational) levels, requiring sophisticated leadership orchestration rather than simple technology adoption. The study contributes theoretically by extending the human–individual–technology–organization–process framework for Indonesian contexts, refining meaningful work theory for digital environments, and developing an integrated leadership typology. Practically, the research provides evidence-based frameworks for banking leaders and transformation officers implementing human-centered digital transformation that preserves relationship-oriented values while enabling technological innovation within regulatory frameworks.