When are politicians incentivized to vote? To answer this question, we examine politicians’ electoral participation before, during and after their political career. Our dataset combines individual-level register data for all candidates in the 2015, 2019, and 2023 Norwegian local elections with population-wide turnout data. We show that politicians are significantly more likely to vote when they are running for office (relative to pre- and post-office electoral participation), particularly if placed in top-ranked list positions and running for parties with council representation. Candidates in ‘contested’ list positions appear to exhibit higher turnout than those in ‘hopeless’ positions, but this gap disappears when controlling for individual fixed effects. Finally, post-office electoral participation exceeds pre-office participation after accounting for individual fixed effects, suggesting some degree of persistence and habit-formation. Overall, these findings contribute to a better understanding of how candidates’ personal ambitions and electoral incentives interact with institutional features to influence electoral behavior.
The fusion of agentic AI and LLMs marks a new frontier in information warfare.
This article examines how organizations respond to reputational scandals in sponsorship relationships within the fields of art and sport. While sponsorship has been widely explored as a means of building legitimacy, less attention has been given to how legitimacy is actively renegotiated when reputational crises occur. Drawing on stakeholder theory and institutional logics, we investigate how organizations justify either continuing or severing controversial sponsorship ties through strategies grounded in compliance or conformity. Using a comparative case study design and secondary data, we analyse four high-profile scandals involving either discredited sponsors or tainted recipients. The findings reveal that responses are shaped by field-specific reputational dynamics rather than by a simple binary logic. In symbolically rich domains such as the arts, organizations tend to invoke conformity-based arguments aligned with moral and cultural expectations; in performance-driven or lower-visibility sports, compliance-based justifications linked to legality and contractual obligations dominate. Hybrid responses also emerge, influenced by elite stakeholder pressure, media attention, and internal governance considerations. By linking symbolic capital, field structures, and stakeholder salience to sponsorship decision-making, this study contributes to research on corporate reputation, organizational legitimacy, and sponsorship ethics, offering insights for managers facing reputational threats in complex institutional environments.
We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization. Quantum annealers attempt to solve an NP-hard problem by starting in a quantum superposition of all states and generating candidate global solutions in milliseconds, irrespective of problem size. Using existing quantum hardware, we achieve an order-of-magnitude speed-up in solving the real business cycle model over benchmarks in the literature. We also provide a detailed introduction to quantum annealing and discuss its potential use for more challenging economic problems.
The necessary condition analysis (NCA) has become a prominent method for identifying must-have factors required for an outcome. With increasing sample sizes, identifying such must-have factors becomes difficult as extreme responses are more likely to occur. Addressing this concern, we introduce a novel method, the NCA with an effect size sensitivity extension (NCA-ESSE), which allows researchers to better understand the sensitivity of the NCA results to extreme response patterns. We offer guidelines for the NCA-ESSE method’s use and illustrate its efficacy using a well-known job satisfaction model. By extending NCA’s capabilities to assess the sensitivity of necessary conditions, our research enhances the method’s practical utility and helps ensure the robustness and replicability of its outcomes and conclusions.
