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The author challenges the consensus in international relations that the field can explain but not predict political phenomena. He argues that there is little theoretical basis for distinguishing between explanation and prediction, and that modern data and machine learning make prediction empirically possible. The paper outlines three generations of conflict prediction, from early behavioralist ambitions to current sophisticated early warning systems used by entities like the UN and EU. The author contends that focusing on prediction improves theory testing by moving beyond statistical significance to evaluate whether models can actually reproduce data-generating mechanisms. While acknowledging the challenges of 'black swan' events and non-linear complex systems, he asserts that the alternative to scientific prediction is often reliance on unreliable expert intuition.

The paper examines the 'mitigation timing question' for bioenergy, specifically how the time-frame used to calculate carbon payback affects whether bioenergy is seen as a greenhouse gas reduction or increase. The author critiques several existing approaches—including those by O'Hare et al. and Cherubini et al.—for failing to account for emissions trajectories and the disproportionate value of immediate mitigation. The author contends that once a goal of immediate mitigation is adopted, future reductions must be discounted due to the time value of money, technological progress, and the 'option value' of delaying specific commitments. The author suggests a minimum discount rate of 5% per year, which mathematically aligns with a 20-year payback period, similar to the approach used by the European Commission.

The author proposes a cognitive approach to analyze the persistent failure of global climate governance, arguing that human behavior in negotiations is driven by underlying mental representations. The paper introduces cognitive-affective mapping (CAM) as a qualitative tool to visualize these belief systems, including their emotional valences. By applying CAM to UNFCCC participants, the research aims to identify cognitive barriers to cooperation and explore how these mental structures differ between individuals and groups, potentially offering new pathways for diplomatic breakthroughs.

The author characterizes the current global crisis as the collapse of a 'liberal-productivist' model, which combined neoliberal deregulation with a productivist drive that ignored ecological limits. This model failed due to a combination of financial instability (a 'debt economy'), extreme revenue inequality, and a 'climate-energy crisis' where the demand for staple commodities like food and energy crowded out durable goods. The author argues that traditional Keynesian solutions are insufficient because they would accelerate climate change, while 'green-washing' ignores the social inequalities at the root of the crisis. A proposed 'Green Deal' would involve a global redistribution of productivity—prioritizing the reduction of labor time over material consumption—and a shift toward a labor-intensive technological paradigm focused on public transportation and care services. Financing this transition would require the 'monetization of debts' and the creation of new credit strictly oriented toward green investments. The author warns that without a coordinated, democratic transition, the world risks a repeat of the 1930s, where economic desperation led to the rise of fascism and Stalinism.

The author argues that while scaling relations like the IPAT equation and Kaya identity are useful for gauging the scale of changes needed to reduce greenhouse gas emissions, they fail to account for existing capital legacies and the necessity of new investment during large-scale economic shifts. To address this, the paper introduces an extended Kaya identity formulated as a sum of terms, designed to maintain the capacity for rapid exploration of low-carbon pathways while capturing capital-related factors.

The paper analyzes the role of fairness in international climate negotiations, distinguishing between intention-driven fairness (based on current motives) and consequence-driven fairness (based on historical responsibility). Using game-theoretic models, the authors argue that increasing fairness perceptions in developing countries can shift negotiation dynamics from non-cooperative states (like the Prisoners' Dilemma) toward cooperative ones. The study evaluates how different support mechanisms—such as carbon sequestration, adaptation funds, and the Green Climate Fund—can be designed to signal kindness and compensate for historical emissions to foster global cooperation.

The paper analyzes the strategic interactions between countries in pollution control, comparing simultaneous (Cournot-Nash) and sequential (Stackelberg) move equilibria. By introducing a pre-play stage where countries choose their timing, the author demonstrates that while simultaneous play is prevalent when strategies are substitutable, a leader can emerge endogenously when strategic complementarities exist. The study finds that sequential play under complementarity leads to lower global emissions and higher welfare than simultaneous play. The analysis utilizes supermodular game theory to avoid restrictive assumptions like concavity or uniqueness of equilibria.

The paper analyzes international climate finance, distinguishing between mitigation and adaptation transfers. It argues that while mitigation transfers are generally Pareto-improving due to global public good benefits and cost-effectiveness, adaptation transfers primarily provide local benefits and thus lack direct allocative efficiency for donors. However, the author posits that adaptation funding can serve as a strategic tool for 'confidence-building' by addressing historical unfairness (the polluter-pays principle), which may increase the willingness of developing countries to participate in global mitigation agreements. The document evaluates the Global Environmental Facility (GEF), the Least Developed Countries Fund (LDCF), the Special Climate Change Fund (SCCF), and the Adaptation Fund (AF), concluding that the AF's governance structure is most effective for raising trust among developing nations.

The research examines the interaction between local flow pollution and global stock pollution, specifically focusing on abatement activities that can target one or both. By comparing symmetric and asymmetric internalization scenarios, the authors demonstrate that the degree of internalization affects the capital-abatement ratio and long-run pollution stocks. The paper argues that achieving a first-best global welfare optimum requires two distinct policy instruments—such as taxes on both local and global pollutants—and that in asymmetric cases, subsidizing pollution reduction is superior to subsidizing abatement because the latter fails to correct for negative externalities from capital accumulation.