Public Policy and Decision Science
Policy-making and decision science
When creating policies, decision-makers must often negotiate fundamental uncertainties in the underlying data and construct mathematical models to help them assess or trade off between different policy alternatives. ML can help alleviate some of this uncertainty by extracting information from satellite imagery, sensors, social media posts, policy documents, and other source and provide new techniques for working with models commonly used by decision-makers (e.g. integrated assessment models, multi-objective optimization, etc.) ML can also help retroactively, by analyzing the text of existing policies and by performing causal inference on historical data.
Generally speaking, carbon markets aim to reduce GHG emissions by setting limits on emissions and enabling the trading of emission units, which represent emission reductions. ML can help predict prices in carbon markets and analyze the main drivers of these prices to improve their efficiency. In terms of the design of market-based strategies, such as carbon tax or cap-and-trade programs, it is necessary to understand how effectively each strategy will reduce emissions, as well as how the underlying socio-technical system may be affected. ML can help assess the outcomes of market-based strategies to ensure they are effective and equitable.
There are several sources of data at various global, regional, and national levels, all of which are useful for modeling the impact of policies, as well as markets
- World Bank ClimateSmart data portal: focuses on the needs of practitioners working in developing countries on low-emission development and climate resilient projects.
- Environmental Treaty Status Data Set, 2012 Release (1940–2012): provides information on the status of country participation in international environmental agreements.
- Vulnerability to Climate Change Dataset: quantifies the vulnerability of 233 countries to three major effects of climate change (weather-related disasters, sea-level rise, and reduced agricultural productivity).
- CO2 “price” in European ETS: Data about the European Union Emissions Trading System (ETS), coming mainly from the EU Transaction Log.
- IPCC Socio-Economic Baseline Data, v1 (1980, 1990, 1991, 1992, 1993, 1994, 1995, 2025): dataset for the evaluation of climate change impact curated by the Intergovernmental Panel on Climate Change (IPCC)
- IPCC Fourth Assessment Report (AR4) Observed Climate Change Impacts, v1 (1970–2004): database with observed responses to climate change for multidisciplinary studies curated by the IPCC.
Methods and Software
Given the importance of representing the impacts of decision-making and market-based strategies, interactive simulation tools and packages for multi-objective optimization are particularly useful in this application. Some of these are listed below:
- Carbon market simulation tool: demystifies how to develop and implement a carbon portfolio management strategy, and demonstrates that results are driven by design.
- Python packages for multi-objective optimization:
- Evolutionary Multi-Objective Optimization (EMOO)
- Platypus - Multi-objective Optimization in Python: Platypus is a framework for evolutionary computing in Python with a focus on multiobjective evolutionary algorithms (MOEAs), providing optimization algorithms and analysis tools for multiobjective optimization.
- Matlab package for multi-objective optimization: Matlab package for multi-objective optimization, accompanied by tutorial videos and explanations.
- Resources for Effective Climate Decisions. (Ch. 4) Informing an Effective Response to Climate Change. (2010)
- Dryzek, J.S. et al., Climate Change and Society: Approaches and Responses. (2011)
- Holt, R.F. et al., Assessment and Decision-making for Climate Change: An Overview of Four Approaches (2012)
- Adge, N.W., Social Capital, Collective Action, and Adaptation to Climate Change. (2003)
- Intergovernmental Panel on Climate Change (IPCC). Social, Economic, and Ethical Concepts and Methods. (Ch. 3). (2014)
- World Health Organizaition. From Science to Policy: Developing Responses to Climate Change. (Ch. 12). Climate Change and Human Health - Risks and Responses. (1996)
- Roelich, K. and Giesekam, J. Decision making under uncertainty in climate change mitigation: introducing multiple actor motivations, agency and influence. (2018)
- Zambrano-Barragán, C. Decision Making and Climate Change Uncertainty: Setting the Foundations for Informed and Consistent Strategic Decisions. (2019)
- European Environmental Agency. Climate Change Policies (2016)
Markets and Pricing
- Kolk, K., Pinkse, J. Market Strategies for Climate Change. (2004)
- Anderson, S.E. et al. The Critical Role of Markets in Climate Change Adaptation. (2018)
- Center for Climate and Energy Solutions. Market-based strategies. (2019)