The impact of global warming on the global economy has been widely discussed in literature offering a broad variety of estimates. Some papers have examined global impacts of climate change, whereas some studies have focused on regional or local consequences. Taking into account various different publications, the first part of this master’s thesis proposes individual functions at a country level that illustrate the impact of global warming. These functions are further used to simulate the countries’ behaviour over time using dynamic programming. We provide an analysis of the interaction between the abatement costs, the ecological impact caused by a certain temperature increase and the abatement efforts made by the countries. A detailed analysis of their behaviour including the formation of coalitions rounds out the first part of the thesis.
The second part considers recent proposals from the academic and political world. The 21st session of the Conference of Parties (COP21) in December 2015 was described as a fundamental breakthrough in climate negotiations by many commentators. However, several issues such as the establishment of binding quotas for the Parties being linked to
the 2C global mitigation target remain unsolved. We simulate the efforts of the Parties to reduce their emissions based on individual abatement targets.
To the best of our knowledge, our approach is the first one to analyze the behaviour of countries in a climate change context using dynamic programming. All components of the Matlab program providing the results are flexible and can be changed according to the assumptions.
Table of Contents
1 Introduction
2 Model without policy intervention
2.1 Methodology of dynamic programming
2.1.1 Backward programming
2.1.2 Forward programming
2.2 Elements of the total cost function
2.2.1 The abatement cost curve
2.2.2 The temperature impact
2.2.3 The ecological impact
2.2.4 Considering the Parties’ expectations
2.3 Evaluation of results
3 Model with policy intervention
3.1 Academic and political background
3.2 Elements of the total cost function
3.2.1 The abatement cost curve
3.2.2 Assigning individual requirements
3.2.3 Determining a penalty for not meeting the requirements
3.2.4 Adding randomness
3.2.5 Accounting for the emissions of developing countries
3.2.6 Considering the Parties’ expectations
3.3 Evaluation of results
4 Comparison of both models
5 Conclusion
Objectives and Research Themes
This master's thesis aims to analyze country-level emissions abatement decisions using dynamic programming. The central research question addresses how nations determine their optimal abatement efforts in the absence of policy intervention and how binding policy mechanisms, such as individual abatement requirements, can influence global emissions trajectories and mitigate the ecological impacts of climate change.
- Simulation of country-level behavior in a climate change context.
- Comparative analysis of models with and without policy intervention.
- Evaluation of top-down mechanisms for distributing abatement requirements.
- Investigation into the impact of economic incentives and penalty-based compliance mechanisms.
- Modeling of stochastic elements and future expectations in climate policy.
Excerpt from the Book
2.1 Methodology of dynamic programming
Dynamic programming enables us to determine a country’s abatement efforts at a certain time by evaluating the so-called state variables, that describe the evolution of the system. Using Bellman’s equation, we determine the optimal strategy for each player given certain assumptions about future developments. In the model without policy intervention, three state variables can be used to describe the world from the perspective of a single country: the emissions of that country, the emissions of all other countries and the global temperature change since the starting year. As we simulate the emissions of different players over time, two additional state variables i and t have to be added, such that the current state can be described by the state vector si,t = (Ei,t, \sum_{j \neq i} Ej,t, Δϑt). Table 2.1 sums up all state variables.
We propose a program (written in Matlab) to simulate the behaviour of different players over time. The key assumption of our model is that Parties act in an economically optimal way and try to minimize their total costs. The individual total cost function1 C(si,t, xi,t) of each Party depends on the current state of the system si,t and the abatement decision xi,t of player i at time t ∈ {1, ..., T}. The following components are used to determine the total costs: Firstly, the abatement costs A(si,t, xi,t) are described in detail in Section 2.2.1. Secondly, the ecological impact I(si,t, xi,t) caused by global warming is discussed in Section 2.2.3. Finally, the expected value Et(·) takes into account the expected future costs.
Chapter Summaries
1 Introduction: Provides an overview of the global climate change problem and the motivation for using dynamic programming to model national abatement behavior.
2 Model without policy intervention: Details the mathematical framework for modeling countries' economic decisions to minimize costs based on abatement and ecological impact, using dynamic programming.
3 Model with policy intervention: Proposes and evaluates mechanisms for assigning individual emissions quotas to countries and analyzes the impact of penalties on national decision-making.
4 Comparison of both models: Synthesizes the results of the two modeling approaches to assess how policy intervention alters national incentives and global outcomes.
5 Conclusion: Summarizes the key findings, acknowledges model limitations, and suggests future research directions regarding compliance mechanisms and climate policy.
Keywords
Dynamic programming, climate change, emissions abatement, cost function, policy intervention, global warming, ecological impact, carbon trading, compliance mechanism, game theory, COP21, INDC, Matlab simulation, abatement costs, economic modeling.
Frequently Asked Questions
What is the primary focus of this master's thesis?
The work focuses on modeling and simulating the abatement decisions of countries regarding CO2 emissions using dynamic programming, both with and without explicit international policy interventions.
Which scientific methods are utilized in the research?
The author employs dynamic programming to solve cost-minimization problems for individual nations, utilizing Bellman's equation and stochastic modeling to account for future uncertainties and climate impacts.
What are the core research themes?
The core themes include the distribution of abatement duties, the economic impact of global warming, the role of international cooperation (coalitions), and the effectiveness of compliance mechanisms like penalties.
What is the purpose of the proposed models?
The models aim to demonstrate how different economic assumptions and regulatory frameworks influence a nation's willingness to abate emissions compared to a 'business as usual' growth scenario.
What does the "variations" term in the model signify?
The variations term represents the emissions of developing countries, allowing the model to dynamically adjust the global abatement target to maintain ecological integrity.
How does the author define the "trust-parameter"?
The trust-parameter measures the level of confidence each player has in the abatement efforts of the rest of the world, which significantly influences the projected abatement strategies of individual nations.
Why are cold countries modeled as potential beneficiaries of climate change?
The author utilizes modified findings from Tol's research, which suggest that moderate warming can result in a net economic benefit for certain cold-climate regions due to decreased energy demands and potential agricultural gains.
What role does the "buyer liability" concept play in the analysis?
In the context of designing a compliance mechanism, buyer liability is discussed as a method to create self-enforcing economic incentives for countries to ensure the permits they purchase are reliable.
- Arbeit zitieren
- Christoph Schlembach (Autor:in), 2016, Country-Level Emissions Abatement Decisions, München, GRIN Verlag, https://www.grin.com/document/317498
