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Public Policy and Decision Science: Difference between revisions
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''This page is about the intersection of policy-making and machine learning. For an overview of policy-making and decision science, please see the [https://en.wikipedia.org/wiki/Policy Wikipedia page] on this topic.''
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== Machine Learning Application Areas ==
===
* [[Data management, cleaning and imputation|'''Data management, cleaning and imputation''']]: ML can help with cleaning, merging and completing datasets that are relevant for policy-making.
*'''[[Remote Sensing|Remote sensing]]''': Satellite data can provide a lot of valuable information to policy makers, for example by helping map infrastructure, land use and ecosystem health. The field of remote sensing has seen large improvements with ML.
* '''[[Computational text analysis]]:''' Text documents are an important source of information to inform climate policy. Natural language processing can help to analyze large corpora of text.
=== Decision
* '''Decision science'''
* [[Multi-criteria decision-making|'''Multi-criteria decision-making''']]: Multi-criteria decision-making can also help policy-makers manage trade-offs between different policies. Computational approaches and machine learning can help with finding solutions to these optimization problems.
* '''[[Agent-based modeling]]:''' ABMs are used in simulating the actions and interactions of agents in their environment, and ML can help integrate data-driven insights into these models, for example by learning rules or models for agents based on observational data.
* '''Energy system modeling'''
* '''Urban planning:''' With new techniques such as [[surrogate modeling]], ML can help with complex planning tasks.
* '''[[Power System Planning]]:''' Algorithms for planning new low-carbon energy infrastructure are often large and slow. ML can help speed up or provide proxies for these algorithms.
* '''[[Integrated Assessment Models (IAMs)|Integrated assessment models]]:''' IAMs are large simulations used to explore future societal pathways that are consistent with climate goals, which can be improved with ML.
=== Ex-post policy analysis ===
* '''[[Causal inference with machine learning]]:''' To analyze whether a policy intervention has had the desired effect, causal inference is an important tool.
== Background Readings ==
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*'''Resources for Effective Climate Decisions. (Ch. 4) Informing an Effective Response to Climate Change (2010''')<ref>{{Cite book|url=https://www.nap.edu/catalog/12784/informing-an-effective-response-to-climate-change|title=Informing an Effective Response to Climate Change|last=Council|first=National Research|date=2010-07-21|isbn=978-0-309-14594-7|language=en}}</ref>: A chapter from a report published after a series of five coordinated activities convened by the National Research Council in response to a request from Congress. [https://www.nap.edu/read/12784/chapter/6#126 Available here.]
*'''Social, Economic, and Ethical Concepts and Methods. (Ch. 3). (2014)'''<ref>{{Citation|title=Social, Economic, and Ethical Concepts and Methods|url=http://dx.doi.org/10.1017/cbo9781107415416.009|publisher=Cambridge University Press}}</ref> : a report by the Intergovernmental Panel on Climate Change (IPCC) regarding the social and economic aspects of climate change. [https://www.ipcc.ch/site/assets/uploads/2018/02/ipcc_wg3_ar5_chapter3.pdf Available here.]
*'''Climate Change Policies (2016)'''<ref>{{Cite journal|last=Del Río|first=Pablo|title=Climate Change Policies and New Technologies|url=http://dx.doi.org/10.4337/9781781000885.00016|journal=Climate Change Policies|doi=10.4337/9781781000885.00016}}</ref>''':''' A report by the European Environmental Agency on defining successful, impactful policies for climate change. [https://www.eea.europa.eu/themes/climate/policy-context Available here.]
*
▲==== Markets and Pricing ====
== Online Courses and Course Materials ==
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*'''[https://www.iaee.org/en/conferences/ International Association for Energy Economics (IAEE) Conferences:]''' Main venue for academic and professional energy analyst, with a strong policy focus (international and regional).
*'''[https://www.appam.org/events/ Association for Public Policy Analysis and Management (APPAM) Conferences]:''' Conferences and events dedicated to improving public policy and management (international and regional).
*[https://www.ippapublicpolicy.org '''International Conference on Public Policy (ICPP):''']
=== Major societies and organizations ===
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*'''[https://www.iaee.org International Association for Energy Economics (IAEE)]:''' A major society for academic and professional energy analyst, with a strong policy focus.
*'''[https://www.appam.org/about-appam/general-info/ Association for Public Policy Analysis and Management (APPAM)]:''' Society dedicated to improving public policy and management by fostering excellence in research, analysis, and education.
*'''[https://www.ippapublicpolicy.org International Public Policy Association (IPPA)]:''' A non-profit organization with the aim of promoting scientific research in the field of Public Policy, and to contribute to its international development.
== Libraries and Tools ==
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:
* Python packages for multi-objective optimization:
**[https://projects.g-node.org/emoo/ Evolutionary Multi-Objective Optimization (EMOO)]
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=== Climate policy databases ===
* [https://app.climatepolicyradar.org Climate Policy Radar]: an open resource of climate laws, policies and action plans from every national government. The database offers full text search of documents via the website.
* [https://www.iea.org/policies Policies database of the International Energy Agency (IEA)]: one of the largest international climate and energy policy databases, integrating the IEA/IRENA Renewable Energy Policies and Measures Database, the IEA Energy Efficiency Database, the Addressing Climate Change database, and the Building Energy Efficiency Policies (BEEP) database.
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*[https://sedac.ciesin.columbia.edu/data/set/ipcc-socio-economic-baseline 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)
*[https://sedac.ciesin.columbia.edu/data/set/ipcc-ar4-observed-climate-impacts 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.
*[https://data.oecd.org OECD Data]: The OECD publishes many economic and social indicators that are relevant for climate policy.
== References ==
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