"Those who conflate the science and policy roles of prediction and modeling trade short-term political or public gain with a substantial risk of a more lasting loss of legitimacy and political effectiveness" (Roger A. Pielke Jr /
The Role of Models in Prediction for Decision - Cary Conference IX: 28 February 2001)
Governments around the world have been responding to computer-generated models of climate change and global warming by commissioning economic models designed to support policy to address both the causes of the problems and likely human responses, in ways calculated to minimise adverse impacts in their respective societies.
While arguments over the realities of global warming have largely abated, others regarding its causes and what to do about it continue apace - when it gets down to confronting the costs of possible solutions, there are too many vested interests in play for consensus on action to be easily or swiftly attained. In the meantime a sense of urgency at ground-level resonates with the fear that "we sit around modelling while the planet burns." This edition of WWWTools for Education presents a webliography for readers who want to know more about the pros and cons of computer modeling as a tool for government policy-makers, with special reference to environmental and economic modeling.
The next edition of WWWTools for Education will consist of a webliography supporting understanding of the range of mitigation and adaptation strategies being proposed, with special reference to Emissions Trading Schemes.
Climate Change.
The problem begins here. This selection of resources is not comprehensive, but provides ample background:
Climate Change (Bureau of Meteorology, Commonwealth of Australia: 2008)
Terminology and Ready Reference.
A few references to help fill the gaps:
Economics (
Wikipedia) - the social science that studies the production, distribution, and consumption of goods and services.
Neoclassical economics (
Wikipedia) - focuses on the determination of prices, outputs, and income distributions in markets through supply and demand. See among Criticisms, a key assumption that individuals act rationally.
General equilibrium (
Wikipedia) - a branch of theoretical microeconomics seeking to explain the behavior of supply, demand and prices in an economy with several or many markets.
Computable General Equilibrium (
Wikipedia) - CGE models are a class of economic model that use actual economic data to estimate how an economy might react to changes in policy, technology or other external factors.
Pareto Optimality (
Economy Professor) - a situation which exists when economic resources and output have been allocated in such a way that no-one can be made better off without sacrificing the well-being of at least one person. See also
Pareto Efficiency (
Wikipedia)
Econometrics (Answers.com) - the application of mathematical and statistical techniques to economics in the study of problems, the analysis of data, and the development and testing of theories and models.
Model - a small copy or imitation of an existing object (
Webster’s New World Dictionary). Cited in
The Promise and Limits of Computer Modeling (Charles Blilie). From the same source:
"a preliminary representation of something, serving as a plan from which the final, usually larger, object is to be constructed" or "
a hypothetical or stylized representation"
Model (economics) (
Wikipedia) - a theoretical construct that represents economic processes by a set of variables and a set of logical and quantitative relationships between them. See also
Bill Parke's caveat , that "
this process inherently ignores important aspects of real-world behavior, making the modeling process an art as well as a mathematical exercise."
1. Involving or containing a random variable or variables.
2. Involving chance or probability.
Mitigation: reducing emissions to reduce future climate change, and
Adaptation: reacting to current changes and preparing society for both predictable and unforeseen changes (
Mitigate and Adapt —but Don’t Forget the Science! (Richard Anthes /
University Corporation for Atmospheric Science Quarterly: Spring 2008)
The Limits To Growth - the Iconic Modeling Exercise.
World3 (
Wikipedia) - the computer simulation used by the Club of Rome study that produced Limits to Growth.
Beyond The Limits to Growth (Donella H. Meadows, Dennis L. Meadows, and Jørgen Randers / Adapted from
IN CONTEXT #32, Summer 1992) - an update. Is sustainability still achievable?
- whether human assumptions or computed calculations are responsible for simulation results
- how much data is necessary to make a computer simulation a meaningful representation of reality.
The Nature, Purposes, Processes and Limitations of Modeling: Basic Readings.
The Promise and Limits of Computer Modeling (Charles Blilie / World Scientific Publishing Company, 2007) - an interesting and far-ranging overview defining "the model", explaining aims and objectives, exploring the nature of modeling, processes, inherent limitations, and the role of models in creating knowledge. From the book:
Comprehensive understanding or prediction of global climate would be utterly impossible without computer models.
The model reduces a system to some idealized or abstract form. Although the model can and will represent details, it usually does not (or cannot) model things in their complete particularity
Models as actually implemented will always have limitations and take time to build
Models ... are always based on imperfect data, and are thus in some way doubtful.
Our necessary ignorance of all conditions affecting an actual system mean that any model... will necessarily fall short of complete accuracy and truth
The chapter Climates of Fact discusses approaches to global climate modeling, as well as the verification and limits of existing climate models.
The Role of Models in Prediction for Decision (Roger A. Pielke Jr /
Cary Conference IX: February 28, 2001) - explores the dangers inherent in confusing prediction in science with prediction for policy, and recommends strategies for overcoming them in environmental decisionmaking processes. Emphasises the importance of understanding uncertainty and predictability. Lists attributes of a good model.
"... alternatives to prediction have become increasingly visible. The prediction process can be judged successful if the goal of climate policy — to reduce the impacts of future climate changes on environment and society — is addressed, independent of whether century-scale climate forecasts prove to be accurate"
"The lesson for decisionmakers is that one is in most cases more likely to reduce uncertainties about the future through decision making rather than through prediction"
- the importance given Economic Modeling in the climate-change policy debate
- the value of Models as tools for exploring policy choices and developing understandings of how economies may respond to different sorts of regulation.
- the limits of Models as tools for precise prediction - results depend on a model's unique set of assumptions, definitions, structure and data.
About using economic models:
- forecasting the future remains inherently uncertain. The longer the time horizon, the larger the uncertainties.
- model results depend on input assumptions and on the structure of the model itself. Critical assumptions and structural biases are not always apparent.
- what is left out of a model can be as important as what goes in.
Categories of assumptions important in driving model results:
(1) specific features of policies being analyzed (including the degree of flexibility allowed in meeting the emissions constraints)
(2) baseline assumptions about how the economy and environment are likely to perform in the absence of the policy
(3) the ease with which consumers/producers can adapt to emissions limits
(4) pace and magnitude of technological change/innovation
(5) what benefits from climate-change mitigation are included, and how.
Examples used are CGE models that simulate the effects of policies on all sectors of economies. Uncertainty is a recurrent theme.
Conclusions:
- results dependent on underlying assumptions and model structure
- results must be seen as approximations only
- mitigation cost estimates are valuable - flexible mitigation options yield lower program costs
- announcing a policy well in advance of implementation reduces overall costs
- allowance allocation reduces costs for stakeholders
- assumptions and limitations must be clearly identified and prominently stated in any report
"As the climate policy debate evolves, it is increasingly important that stakeholders understand the strengths and limitations of economic models and look to them for broad insights, not absolute answers."
Some of the References cited for this White Paper are also online:
Induced Technological Change and Climate Policy (Lawrence H. Goulder / Pew Center on Global Climate Change, 2000) - explores how climate policy may influence the rate and direction of technological change, examines the implications of "
Induced Technological Change" (ITC) for climate policy design. Main findings include:
1) ITC lowers the costs of reducing emissions.
2) ITC justifies more extensive emission reductions than would otherwise be called for.
3) ITC alters the optimal timing of emissions abatement.
4) In the presence of ITC, announcing climate policies in advance can reduce costs.
5) Economic analysis justifies the implementation of public policies to induce technological change.
6) To promote ITC and reduce GHG emissions most cost-effectively, policies to reduce emissions and incentives for technological innovation are both required
The Role of Substitution in Understanding the Costs of Climate Change Policy (Dale W. Jorgenson et al / Pew Center on Global Climate Change, 2004) - with a wide range of substitution possibilities and low substitution costs, mitigation costs (damages to welfare, income and production) are likely to be low; narrow substitutability and high substitution costs will lead to higher mitigation costs.
The Costs of Climate Protection: A Guide for the Perplexed (Robert Repetto and Duncan Austin / World Resources Institute, 1997) explains why different economic models reach different conclusions; identifies key assumptions that account for over 80 percent of variations in predicted economic impacts; lists important
questions to ask about assumptions underlying predictions.
Recent Examples of Modeling.
GLOBAL REFERENCES:
Kyoto Protocol (
Wikipedia) - adopted on December 11, 1997, entered into force on February 16, 2005: "
A protocol to the International Framework Convention on Climate Change with the objective of reducing greenhouse gases in an effort to prevent anthropogenic climate change."
What If We Burn Everything? (Fraser Cain /
Universe Today: November 02, 2005) - simulation results from Lawrence Livermore National Laboratory: if we use all available fossil fuels by 2300, the earth will warm by 8 degrees Celsius, with alarming consequences.
The Stern Review on the Economics of Climate Change (HM Treasury, UK) - download chapter-by-chapter or in parts. The Executive Summary (short) is recommended as a preliminary foray. Briefly, it estimates that no action will cost 5% - 20% of global GDP annually. Alternatively, the costs of action to reduce emissions to avoid the worst impacts of climate change can be about 1% of global GDP annually. See also Wikipedia's Stern Review article.
A Question of Balance: Weighing the Options on Global Warming Policies (William Nordhaus / Yale University Press, 2008) - prepublication proof text. Describes the
DICE Model; alternative policies for dealing with global warming; uncertainty analysis. Concludes that damages can be mitigated through good policy - favors gradual restraints on carbon emissions via internationally harmonised carbon taxes.
NORTH AMERICAN REFERENCES:
Climate Economic Modeling (Environmental Protection Agency, USA) - types of models used by EPA: economy-wide models, mitigation models, integrated assessment models, and detailed sector models.
(Margo Thorning / Before the U.S. Senate Committee on Commerce, Science and Transportation Subcommittee on Global Climate Change and Impacts: April 05, 2006) - pros and cons of mandatory approaches to GHG reduction.
AUSTRALIAN REFERENCES:
The MEGABARE model (Australian Bureau of Agricultural and Resource Economics, 1996) – a general equilibrium economic model to assess the economic impact of reductions in Australia’s greenhouse gas emissions,
"developed at ABARE to provide such a global perspective on major Australian policy issues."
The Garnaut Climate Change Review - in April 2007, the Australian Government commissioned an independent study by Professor Ross Garnaut, to examine the impacts of climate change on the Australian economy, and recommend policies to improve prospects for sustainable prosperity. A good place to start is probably the Interim Report Executive Summary (February 2008), or maybe go straight to the Draft Report (July 04, 2008); or the Supplementary Draft Report (September 05, 2008). The Final Report is due by 30 September 2008.
See also:
Middle of the Road ... Towards a Cliff (David Spratt / climate code red: August 30, 2008) - we face a climate emergency which requires actions at emergency speed far beyond "business as usual" and "politics as usual" to bring a rapid transition to a post-carbon, safe-climate future.
Modeling and Policy.
Computer-Based Model Validation Expectations (Roland E. Smith / June 17, 2002) - to reduce the likelihood of erroneous model output or incorrect interpretation of results, implement a sound validation framework that includes a validation policy and independent review.
(Els van Daalen, Leen Dresenb and Marco A. Janssenc / Elsevier Science, 2002) - abstract only. 4 roles played by computer models in environmental policy-making: models as eye-openers, as arguments in dissent, as vehicles in creating consensus and as management tools.
Problems.
ECONOMICS:
Problems With Modern Applied Economics, Applied Economic Analysis (History Of Economic Theory and Thought: July 2008) - is modern applied economics mostly data mining with some semblance of "scientific empirical testing" added to make it seem less ad hoc? "The simplicity of complex systems is to be found in the study of dynamics and iterative processes"
MODELING:
Dr. Doom (Stephen Mihm /
New York Times: August 15, 2008) - Nouriel Roubini doesn't seem to rely on computer modeling for his largely accurate predictions.
Probabilities in Economic Modeling (Itzhak Gilboa, Andrew Postlewaite, and David Schmeidler / 2007) -
"The Bayesian paradigm is an elegant and coherent way to deal with uncertainty. Yet, it is not always clear how should probabilistic beliefs be formed".
Please Models, Just Die (
The Stalwart: August 17, 2008) -
"in finance and economics there has been far too much modeling going on and far too little thinking." Special reference to Nouriel Roubini's subjective, nontechnical approach to economic analysis and prediction.
POLICY / DECISIONMAKING:
ABARE Ignores Inconvenient Truths (Bernard Keane /
Crikey: June 04, 2008) - the Australian Bureau of Agricultural and Resource Economics accused of modeling implausibly optimistic scenarios reflecting a business-as-usual approach.
CHANCES OF SUCCESS:
Light in the Fog (John Garnaut /
Sydney Morning Herald: July 19, 2008) - are mitigation efforts pointless unless the big emitters become part of the solution?
SCIENTIFIC RESEARCH:
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