Limiting climate change will require transformation of energy and other systems. This report presents an agent-based, game theoretic model designed to compare the long-term sustainability of alternative carbon emission reduction policies. The model tracks the co-evolution of an industry sector, its technology base, and political coalitions that influence government policy. It uses robust decision making methods to compare alternative policies.
An Evolutionary Model of Industry Transformation and the Political Sustainability of Emission Control Policies
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Research Questions
- How can we assess which market-based policies would most effectively promote the long-term, transformational changes needed to limit climate change?
- How will the co-evolution of markets, technology, and political coalitions affect the long-term sustainability of greenhouse gas emission reduction policies?
- How does the architecture of alternative market-based emission reduction policies affect the political coalitions that form among firms and the resulting emissions trajectories?
- How can we create models that capture the interaction between economics, climate, technological innovation, political constituencies, and government policy?
Limiting the extent and effects of climate change requires the transformation of industrial, commercial, energy, and transportation systems. To achieve its goals, a near-term policy has to sustain itself for many decades. Market-based policies should prove useful in promoting such transformations. But which policies might do so most effectively? How can such policies be designed so that they endure politically over the long-term? While standard economic theory provides an excellent understanding of the efficiency-enhancing potential of markets, it sheds less insight on their transformational implications. In particular, the introduction of markets often also leads to significant changes in society's values, technology, and institutions, and these types of market-induced transformations are generally not well understood. This report presents a simulation framework with both game theoretic and agent-based components designed to model evolutionary changes in the firms belonging to an industry sector and how these may form changing coalitions that influence how government sets a price for carbon emissions. The model captures the complex interactions between market-formation, technological innovation, government regulatory policy and the emergent climate change. It tests a set of outcome measures under different carbon emission control policies. The model is a tool to support the design of a government's regulatory policy by using robust decision making to examine how measures intended to reduce emissions of climate-changing greenhouse gasses may give rise to market-induced transformations that in turn may ease or hinder the government's ability to maintain its policy.
Key Findings
Novel Modeling Tool Tests Alternative Market-Based Emission Reduction Policies
- Once implemented, policies will evolve along paths no longer under the control of the initial policymakers, who must thus use their window of opportunity to choose a policy architecture that increases the chances of achieving their long-term goal. In part, a long-term sustainable policy should create constituencies that will provide ongoing support for the policy.
- It is desirable to construct a general framework that will provide a test bed for experimentation with such policies and the forces that shape their evolution over time.
- We constructed a modeling framework built on an agent-based evolutionary economics model focused on processes of transformation in technology and industry structure. To this we added a component modeling effects of market activities on climatic change and vice versa. We included a generalized game-theoretic treatment of the formation of coalitions and interest groups among suppliers to influence the directions of government regulatory policies.
- Modeling outcomes are affected by assumptions about future conditions. Rather than predictions, we should seek from models the ability to generate credible scenarios and to assist in framing robust policies based on their analysis. We embedded this simulation in a set of methods and supporting analytic tools called robust decision making. This tool seeks strategies that are robust compared to the alternatives over a wide range of plausible futures under conditions of deep uncertainty. This permits comparison of outcomes from alternative near-term decisions regarding the design of market-based policy architectures for reducing greenhouse gas emissions.
Recommendations
- Considering the co-evolution of technology, political coalitions, and the game-theoretic interactions between firms and the government as the latter sets emissions control policies can prove important to long-term emission reduction trajectories when there are abundant technological opportunities and when the government is susceptible to lobbying.
- Robust decision making appears particularly useful for evaluating policies in such situations because it is designed to provide policy-relevant conclusions under conditions of deep uncertainty.
Table of Contents
Chapter One
Introduction
Chapter Two
Design of Robust Decision Making Analysis
Chapter Three
Model Design
Chapter Four
Calibration
Chapter Five
Representative Analysis
Chapter Six
Next Steps
Appendix A
Computation of the Social Cost of Carbon
Appendix B
The Lobbying Game
Appendix C
Adaptive Learning Model for R&D Decisions
Appendix D
Starting Cases
Appendix E
Representative Analysis Details
Appendix F
Parameter List
The research described in this report was sponsored by the National Science Foundation and conducted in the Environment, Energy, and Economic Development Program within RAND Justice, Infrastructure, and Environment.
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