Hydrogen in Renewable-Intensive Energy Systems: Path to Becoming a Cost-Effective and Efficient Storage Solution

This paper examines the integration of hydrogen storage in renewable-intensive energy systems. Current hydrogen storage technology is too costly and inefficient, but reducing hydrogen costs to 12.5% of current levels and increasing round-trip efficiency to 70% could make it com petitive. These are challenging targets but feasible given positive predictions on cost reduction and efficiency attainability currently. Hydrogen storage reduces total energy system costs by partly replacing lithium batteries to lower storage costs, due to its suitability for long-term storage, while increasing grid flexibility to lower transmission costs. Moreover, integrating hydrogen can decrease the share of nuclear and fossil fuels in the generation mix, reducing generation costs. Italy and Germany are identified as primary targets for hydrogen expansion in Europe. In scenarios of limited lithium supply, hydrogen becomes more competitive and essential to compensate for system storage capacity shortages, though it may not reduce total system costs

Public coverage of dental care: universal or targeted?

This paper analyses the impact of public dental care coverage-universal versus targeted-on access, pricing, and public spending in a model with two competing dental practices and heterogeneous patient income groups. We evaluate two types of reimbursement schemes: fixed subsidies and cost sharing. Our findings show that public coverage improves access for low-income patients but increases producer prices due to reduced price elasticity of de-mand. Targeted coverage provides greater access at lower public cost compared to universal coverage, especially under cost-sharing schemes. With fixed subsidies, both schemes achieve similar access, but targeted coverage remains more cost-efficient. The policy that maximises utilitarian welfare is targeted coverage with a fixed subsidy, balancing improved access for low-income patients against higher prices for high-income patients. This trade-off highlights challenges in implementing targeted policies but provides insights for designing efficient and equitable public dental care systems

Addressing Congestion in Time-Expanded Networks: A Lifeboat Allocation Model for Maritime Evacuations

This paper addresses the challenge of congestion in time-expanded networks, focusing on a case study related to maritime evacuations. The problem is made complex by an endogenous relationship between inputs and outputs, where the assignment of flow to an edge leads to increased congestion, which reflects in later arrivals and changes on the overall network topology. This dynamic interaction between flow and congestion is central to the problem, as it results in a feedback loop that complicates the identification of optimal evacuation paths. The study presents an iterative algorithm inspired by the network simplex method, designed to handle the evolving nature of congestion while minimizing evacuation time

Competition matters: uniform vs. indication-based pricing of pharmaceuticals

Pharmaceutical expenditures are rising rapidly, driven in part by the innovation of highly effective but very expensive drug therapies that treat multiple diseases. While these drugs offer substantial health benefits, payers face a critical trade-off between cost containment and access to new medicines. A key policy question is whether producers should be restricted to uniform pricing or allowed to use indication-based pricing, where prices vary across patient groups. We analyse how this choice affects drug producers' incentives to invest in new indications, their pricing strategies, and the resulting surplus for health plans. In a monopoly setting, indication-based pricing yields higher profits and thus strengthens incentives to invest in new indications, while the payer prefers uniform pricing unless the fixed investment costs cannot be recouped. The novelty of our study lies in showing that monopoly-based insights may not hold under competition. Specifically, we identify a softening-of-competition effect, where a uniform pricing restriction serves as a credible commitment to raise prices in the competitive market. In this case, the health plan generally favours indication-based pricing to reduce costs. However, an exception arises, where both parties prefer uniform pricing, if the uniform price generates significant health gains through demand expansion in the original monopoly market. Our findings suggest that neither pricing scheme is universally optimal, underscoring the need for case-by-case assessments across drug classes

Income Equality in The Nordic Countries: Myths, Facts, and Lessons

Policymakers, public commentators, and researchers often cite the Nordic countries as examples of a social and economic model that successfully combines low income inequality with prosperity and growth. This article aims to critically assess this claim by integrating theoretical perspectives and empirical evidence to illustrate how the Nordic model functions and why these countries experience low inequality. Our analysis suggests that income equality in the Nordics is primarily driven by a significant compression of hourly wages, reducing the returns to labor market skills and education. This appears to be achieved through a wage bargaining system characterized by strong coordination both within and across industries. This finding contrasts with other commonly cited explanations for Nordic income equality, such as redistribution through the taxtransfer system, public spending on goods that complement employment, and public policies aimed at equalizing skills and human capital distribution. We consider the potential lessons for other economies that seek to reduce income equality. We conclude by discussing several underexplored or unresolved questions and issues

Cognitive and Emotional Aspects of Leading in the Face of Competing Demands: A Phenomenological Study of Top Executives

This dissertation explores how executives cognitively and emotionally relate to competing demands. As organizational life becomes increasingly complex, leaders’ ability to address organizational paradoxes may determine organizations’ short-term performance and long-term prosperity. Through a phenomenological study of 10 top executives, the study elicits two understudied precursors of paradoxical leadership—cognitive complexity and emotional equanimity—and explores how these are related and how they influence executives’ decision-making. The study further investigates the interrelation between the executives’ paradox mindset (i.e., cognitive complexity and emotional equanimity) and the management teams’ dynamics. The findings indicate that executives’ cognitive complexity forms dynamic cognitive patterns of differentiating and integrating opposing mental frames. Moreover, executives build emotional equanimity through personal values-based purposes and continuous self-care. Recurrent emotional strain tied to leading in the face of competing demands may indicate tolerance limits and serve to protect leaders with high cognitive complexity from over-complication. Executives with medium to high levels of paradox mindsets adopt distinct decision-making processes characterized by slow, circular, and values-based decisions. Finally, the study of the management teams indicates that a higher level of executive paradox mindset is connected to distributed authority, emergent processes, and openness to challenging assumptions in the management team. The study impacted the participants and the researcher through mutual sensemaking (a.k.a., double-hermeneutic process), changing how we view the leadership of complexity. Keywords: cognitive complexity, competing demands, decision processes, emotional equanimity, organizational paradoxes, paradoxical leadership, and phenomenology

The Cost of Weather: Modeling Weather Delay in Bulk Shipping

Weather is an ever-present factor influencing shipping operations at every stage, including port operations. This paper examines the determi nants of weather-induced delays in port operations, the probability and duration of such delays, the predictive capability of various statistical models, and the potential for improving upon standard industry methods for estimating port margins. A wide range of models are investigated, including Generalized Linear (GLM) models, Cox Propotional Hazard models, and Autoregressive Conditional Duration (ACD) models. The findings reveal that a GLM with gamma distributed dependent variables provides the best fit for data on delay duration, while a linear multiple regression offers the highest predictive accuracy for delay duration. Similarly, probit and logit models are found to perform comparably well for both predicting delay probabilities and data fit. Moreover, the analysis demonstrates that there are significant potential cost savings when using a linear regression model with a probit model to predict delays compared to a common industry rule-of-thumb of half a day delay. These results underscore the potential for improving operational efficiency and accuracy in port margin estimation through statistical modeling techniques

Insurance in a Changing Climate: A Retrospective Study of Water-Related Claims and Pricing Strategies in Norway

Climate change has posed significant challenges to socioeconomic systems across the world, with the insurance industry at the forefront of facing climate risks. Recognizing the growing importance of climate risk management in insurance practices, this study investigates the impact of weather events on water-related home insurance claims by utilizing a unique dataset from a leading Norwegian insurance company. We propose an effective statistical model to address the zero-inflation and over-dispersion inherent in claim count data and introduce a retrospective approach to reconstruct historical claim profiles leveraging high-resolution weather data. Our results reveal geographical variations in weather-related risks for home insurance in two largest Norwegian cities and identify seasonal patterns in insurance claims. Furthermore, we evaluate both reactive and proactive pricing strategies based on the retrospective analysis, providing actionable insights for insurers to adjust premiums in response to evolving climate risks. This research offers a robust framework for integrating weather data into actuarial modeling and contributes to the adaptation of the insurance industry to a changing climate

Business model digitalization, competition, and tax savings

We examine the effect of business model digitalization on competition and how corporate tax savings through digitalization may augment this relationship. Global policymakers express concern that digitalization-related tax savings unfairly benefit the competitive standing of rival firms over their competitors. Using textual analysis techniques to identify firms’ business models, we show that rivals’ adoption of a digital business model leads to negative economic effects on the performance of their non-digitalizing competitors. We estimate that a one standard deviation increase in the share of digitalized rivals in a market reduces a competitor’s market share by 4.6%. Suggesting significant tax savings from digitalizing, we also find that digitalizing rivals substantially reduce their effective tax rates, mostly by increased use of tax havens. However, when we test whether the detected competitive externalities vary depending on the share of digitalizing rivals with versus without substantial digitalization-related tax savings, we find the economic magnitudes of their effects are quantitatively similar. Therefore, contrary to policymakers’ concerns of digitalization-related tax savings unfairly shaping competition, our findings suggest that tax savings from digitalization is not a key driver of altering competition between digitalized and non-digitalized firms