CERES

Political Economy for Inclusive Wealth Governance and Sustainability
CERES

To maintain the basis of human life on Earth, the global commons such as the atmosphere, the oceans and the biosphere must be managed so that planetary boundaries are not exceeded. This requires a paradigm shift in the definition of wealth, which should explicitly include natural capital in addition to physical and human capital. The FutureLab CERES – Ceres, the Roman goddess of agriculture, is also described as a legislator – conducts research at the interface between natural resources and state capacity, and explicitly addresses the interactions between them. Against the backdrop of climate change and the overexploitation of natural resources, the research programme aims at changing the understanding of wealth that incorporates natural capital. This also incorporates the analysis of suitable policy instruments to enable inclusive wealth governance.

The research focusses on countries that play a key role in the protection of natural resources, such as Brazil, Indonesia, Colombia or the Congo. They are severely threatened by climate damage, have a high level of biodiversity and accrue high economic profits from fossil resources, rare earths and/or deforestation.

The central question of the FutureLab is how states can contribute to a fair and sustainable management of global commons. To this end, the FutureLab's research is divided into four work packages:

1. Political Economy realities and barriers to transformation

2. Machine Learning-based ex-post policy evaluation

3. Interaction of state capacity and inclusive wealth

4. Political Economy approaches to international cooperation

1. Political Economy realities and barriers to transformation

This work package aims to take stock of the political economy realities in select countries: Which actors influence the formulation of policy instruments for the governance of inclusive wealth and in what way? What are political economy barriers to transformation? Effective policy measures need to take these contexts into account and integrate them into their design.

2. Machine Learning-based ex-post policy evaluation

Policy-makers have to choose between a variety of possible policy instruments that promise sustainable resource use and emission reduction. However, up to now, researchers have only evaluated individual measures, whereas in political reality packages of measures are almost always implemented. The aim of this work package is therefore to identify effective packages of measures with the help of machine-learning methods. Thus, the work package makes an important contribution to attribution research of effective policies.

3. Interaction of state capacity and inclusive wealth

The climate system and the biosphere are essential for generating and enhancing human wealth. At the same time, we experience unprecedented degradation of natural systems, as the value of conservation is often abstract, invisible or only indirectly experienced. Additionally, many governments lack the informational or institutional capacity to implement effective and socially fair policies. This work package aims to identify priorities for policy making for governments using quantitative methods and a comprehensive perspective on welfare. To enable this, we conduct research that enhances the quantitative foundations on which priorities for policies towards sustainable development can be assessed. Moreover, our research looks at how regulations can be socially accepted and effectively implemented in countries with different state structures. Lastly, building on this, we investigate which steps would be suitable to increase the local acceptance of state measures to protect the global commons.

4. Political Economy approaches to international cooperation

This work package examines policy instruments at the international level to promote ambitious climate action. To that end, it explores how incentives can be created for cooperative action, for example through transfer payments linked to effective climate policies. Furthermore, as political contestation over climate change exists between countries which depends on the energy and environmental assets each country owns, this work package attempts to fully explore the potential geopolitics of different categories of assets under climate change and its mitigation. Methodologically, the focus is on the mathematical modelling of game-theoretical approaches, as well as their empirical-economic validation.

Methods

CERES uses the following methods to analyse the preconditions for the governance of inclusive wealth:

  • Case studies
  • Machine Learning-based ex-post policy evaluation
  • Ex-ante analysis and theory building
  • Agent-based and game-theoretic approaches to political economy

Evidence-based policy advice

The FutureLab's distinctly interdisciplinary cooperation between political scientists, economists and specialists in Artificial Intelligence and Machine Learning aims to set new standards for decision-relevant research. The results are intended to enable decision-makers to identify key levers in the multi-level system of climate governance in an informed and evidence-based manner and to shape them sustainably in accordance with policy recommendations.

Team

The FutureLab CERES is funded by the Werner Siemens Foundation.

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