By Brian Fath, IIASA Advanced Systems Analysis Program and Towson University
Brian Fath. © Matthias Silveri | IIASA
The seminal book The Limits to Growth by Donella Meadows and colleagues was a first attempt to make a world model that integrated environment, economics, population, and industrial pollution. Without drastic changes to curb human population growth, consumption of non-renewable resources and industrial effluence, the model scenario projected a collapse of the world social-industrial system, because physically it is not possible to keep growing on a finite planet. This important message spurred many people in the environmental sciences, but was largely ignored, or worse ridiculed, by the dominant economic and political leaders. Perhaps their work was too pessimistic (although some could say realistic) and called for change for which society was not yet ready.
My co-authors and I feel their message was interpreted incorrectly. The restrictions imposed by The Limits to Growth do not entail stagnation and strife but rather give us an opportunity for new priorities, greater equity, and greater well-being. Living within the limits can offer agreeable, pleasant, even thriving and wonderful living conditions.
Therefore we have written a book, which shows that following nature provides guidance and pathways to Flourishing within Limits to Growth.
People today are confronted with a number of very serious problems: poverty, increased inequalities among countries and people, refugees, regional conflicts and civil wars, global climate change, accelerating exploitation of the global non-renewable and renewable resources, rapid land use change and urbanization, and increased emissions of harmful chemicals into the environment. History has shown us that we cannot solve these problems using traditional methods based on short-sighted economic growth.
Additionally, we know from natural laws that continuous growth in a finite environment is not possible. How can we ensure sustainable development for society on Earth? It would be possible by imitating the system that understands how to sustain long-term development: to learn from nature and follow nature’s way. Nature shifts from quantitative biomass growth when the resources become limiting to qualitative development by increasing resource use efficiency, in terms of both improved network connectivity and information on process regulation and feedbacks. The two main ecosystem functions, flow of energy and transfer of nutrients, are accomplished by renewable energy and complete recycling of the needed elements. Nature also originated and perfected the use the 3Rs: Reduce, Reuse, and Recycle.
“The restrictions imposed by The Limits to Growth do not entail stagnation and strife but rather give us an opportunity for new priorities, greater equity, and greater well-being” Photo: Innsbruck, Austria ©Nikolai Sorokin | Dollar Photo Club
Our book employs a global model to experiment with applying these properties of nature in society. Using global statistics, the model considers how the development will change if:
- A revenue-neutral, resource-based Pigovian tax is increased significantly and along with commensurate tax reduction to enhance recycling and application of renewable energy
- We increase investment in education, innovation, and research significantly to raise the level of understanding by the population and to develop new progressive ideas to address our global problems.
- We increase pollution abatement considerably to reduce its negative impacts on our health, nature, and production.
- We increase aid from the developed to the developing countries to 0.8% of GNP, which would enhance the cooperation among countries, reduce poverty and population growth and thereby also the number of refugees. In this context, it is important that the aid is given as support to education, health care, and family planning and not at all as military aid.
The model calculations show that it is possible to obtain a win-win situation, where both industrialized and developing nations can achieve a better standard of living – the developing countries mostly quantitatively and the developed countries mostly qualitatively. The calculations are compared with scenarios based on “business as usual” practices. The business as usual scenario shows a major collapse around the year 2060, which is in accordance to the Limits to Growth results from 1972 and the follow-up-publications from the Club of Rome.
Furthermore, the book demonstrates calculations of ecological footprints and sustainability by assessing our consumption and loss of work energy due to our use of resources and destruction of nature. These calculations lead to the following conclusions:
- Maintain natural areas and the ecosystem services they provide.
- Improve agricultural production by increasing efficiencies and technologies.
- Shift our thoughts and actions from quantitative growth to qualitative development, for instance by using the three R’s.
- Shift to renewable energy.
- Leave today’s policy focused entirely on short-sighted economic considerations and start to discuss how we can improve environmental management, increase the level of education and research, and achieve greater equality in society.
- Develop and promote alternative measures of welfare and well-being.
- Reduce, rather than reward, financial speculations, exorbitant profits, and stock market gambling.
More information: Listen to an interview with Brian Fath on WCBN Radio.
Jørgensen SE, Fath BD, Nielsen SN, Pulselli F, Fiscus D, Bastianoni S. 2015. Flourishing Within Limits to Growth: Following nature’s way. Earthscan Publisher.
Meadows, DH, Meadows, DL, Randers J., Behrens, W.H. III, (1972) Limits to Growth, New York: New American Library.
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
By Armon Rezai, Vienna University of Economics and Business Administration and IIASA,
and Rick van der Ploeg, University of Oxford, U.K., University Amsterdam and CEPR
The biggest externality on the planet is the failure of markets to price carbon emissions appropriately (Stern, 2007). This leads to excessive fossil fuel use which induces global warming and all the economic costs that go with it. Governments should cease the moment of plummeting oil prices and set a price of carbon equal to the optimal social cost of carbon (SCC), where the SCC is the present discounted value of all future production losses from the global warming induced by emitting one extra ton of carbon (e.g., Foley et al., 2013; Nordhaus, 2014). Our calculations suggest a price of $15 per ton of emitted CO2 or 13 cents per gallon gasoline. This price can be either implemented with a global tax on carbon emissions or with competitive markets for tradable emission rights and, in the absence of second-best issues, must be the same throughout the globe.
The most prominent integrated assessment model of climate and the economy is DICE (Nordhaus, 2008; 2014). Such models can be used to calculate the optimal level and time path for the price of carbon. Alas, most people including policy makers and economists view these integrated assessment models as a “black box” and consequently the resulting prescriptions for the carbon price are hard to understand and communicate to policymakers.
© Cta88 | Dreamstime.com
New rule for the global carbon price
This is why we propose a simple rule for the global carbon price, which can be calculated on the back of the envelope and approximates the correct optimal carbon price very accurately. Furthermore, this rule is robust, transparent, and easy to understand and implement. The rule depends on geophysical factors, such as dissipation rates of atmospheric carbon into oceanic sinks, and economic parameters, such as the long-run growth rate of productivity and the societal rates of time impatience and intergenerational inequality aversion. Our rule is based on the following premises.
- First, the carbon cycle dynamics are much more sluggish than the process of growth convergence. This allows us to base our calculations on trend growth rates.
- Second, a fifth of carbon emission stays permanently in the atmosphere and of the remainder 60 percent is absorbed by the oceans and the earth’s surface within a year and the rest has a half-time of three hundred years. After 3 decades half of carbon has left the atmosphere. Emitting one ton of carbon thus implies that is left in the atmosphere after t years.
- Third, marginal climate damages are roughly 2.38 percent of world GDP per trillion tons of extra carbon in the atmosphere. These figures come from Golosov et al. (2014) and are based on DICE. It assumes that doubling the stock of atmospheric carbon yields a rise in global mean temperature of 3 degrees Celsius. Hence, the within-period damage of one ton of carbon after t years is
- Fourth, the SCC is the discounted sum of all future within-period damages. The interest rate to discount these damages r follows from the Keyes-Ramsey rule as the rate of time impatience r plus the coefficient of relative intergenerational inequality aversion (IIA) times the per-capita growth rate in living standards g. Growth in living standards thus leads to wealthier future generations that require a higher interest rate, especially if IIA is large, because current generations are then less prepared to sacrifice current consumption.
- Fifth, it takes a long time to warm up the earth. We suppose that the average lag between global mean temperature and the stock of atmospheric carbon is 40 years.
We thus get the following back-of-the-envelope rule for the optimal SCC and price of carbon:
where r = ρ+ (IIA-1)x g. Here the term in the first set of round brackets is the present discounted value of all future within-period damages resulting from emitting one ton of carbon and the term in the second set of round brackets is the attenuation in the SCC due to the lag between the change in temperature and the change in the stock of atmospheric carbon.
Policy insights from the new rule
This rule gives the following policy insights:
- The global price of carbon is high if welfare of future generations is not discounted much.
- Higher growth in living standards g boosts the interest rate and thus depresses the optimal global carbon price if IIA > 1. As future generations are better off, current generations are less prepared to make sacrifices to combat global warming. However, with IIA < 1, growth in living standards boosts the price of carbon.
- Higher IIA implies that current generations are less prepared to temper future climate damages if there is growth in living standards and thus the optimal global price of carbon is lower.
- The lag between temperature and atmospheric carbon and decay of atmospheric carbon depresses the price of carbon (the term in the second pair of brackets).
- The optimal price of carbon rises in proportion with world GDP which in 2014 totalled 76 trillion USD.
The rule is easy to extend to allow for marginal damages reacting less than proportionally to world GDP (Rezai and van der Ploeg, 2014). For example, additive instead of multiplicative damages resulting from global warming gives a lower initial price of carbon, especially if economic growth is high, and a completely flat time path for the price of carbon. In general, the lower elasticity of climate damages with respect to GDP, the flatter the time path of the carbon price.
Calculating the optimal price of carbon following the new rule
Our benchmark set of parameters for our rule is to suppose trend growth in living standards of 2 percent per annum and a degree of intergenerational aversion of 2, and to not discount the welfare of future generations at all (g = 2%, IIA = 2, r = 0). This gives an optimal price of carbon of $55 per ton of emitted carbon, $15 per ton of emitted CO2, or 13 cents per gallon gasoline, which subsequently rises in line with world GDP at a rate of 2 percent per annum.
Leaving ethical issues aside, our rule shows that discounting the welfare of future generations at 2 percent per annum (keeping g = 2% and IIA = 2) implies that the optimal global carbon price falls to $20 per ton of emitted carbon, $5.5 per ton of emitted CO2, or 5 cents per gallon gasoline.
If society were to be more concerned with intergenerational inequality aversion and uses a higher IIA of 4 (keeping g = 2%, r = 0), current generations should sacrifice less current consumption to improve climate decades and centuries ahead. This is why our rule then indicates that the initial optimal carbon price falls to $10 per ton of carbon. Taking a lower IIA of one and a discount rate of 1.5% per annum as in Golosov et al. (2014) pushes up the initial price of carbon to $81 per ton emitted carbon.
A more pessimistic forecast of growth in living standards of 1 instead of 2 percent per annum (keeping IIA = 2, r = 0) boosts the initial price of carbon to $132 per ton of carbon, which subsequently grows at the rate of 1 percent per annum. To illustrate how accurate our back-of-the-envelope rule is, we road-test it in a sophisticated integrated assessment model of growth, savings, investment and climate change with endogenous transitions between fossil fuel and renewable energy and forward-looking dynamics associated with scarce fossil fuel (for details see Rezai and van der Ploeg, 2014). The figure below shows that our rule approximates optimal policy very well.
The table below also confirms that our rule also predicts the optimal timing of energy transitions and the optimal amount of fossil fuel to be left unexploited in the earth very accurately. Business as usual leads to unacceptable degrees of global warming (4 degrees Celsius), since much more carbon is burnt (1640 Giga tons of carbon) than in the first best (955 GtC) or under our simple rule (960 GtC). Our rule also accurately predicts by how much the transition to the carbon-free era is brought forward (by about 18 years). No wonder our rule yields almost the same welfare gain as the first best while business as usual leads to significant welfare losses (3% of world GDP).
Transition times and carbon budget
||Fossil fuel Only
|Business as usual
Recent findings in the IPCC’s fifth assessment report support our findings. While it is not possible to translate their estimates of the social cost of carbon into our model in a straight-forward manner, scenarios with similar levels of global warming yield similar time profiles for the price of carbon.
Our rule for the global price of carbon is easy to extend for growth damages of global warming (Dell et al., 2012). This pushes up the carbon tax and brings forward the carbon-free era to 2044, curbs the total carbon budget (to 452 GtC) and the maximum temperature (to 2.3 degrees Celsius). Allowing for prudence in face of growth uncertainty also induces a marginally more ambitious climate policy, but rather less so. On the other hand, additive damages leads to a laxer climate policy with a much bigger carbon budget (1600 GtC) and abandoning fossil fuel much later (2077).
In sum, our back-of-the-envelope rule for the optimal global price of carbon and gives an accurate prediction of the optimal carbon tax. It highlights the importance of economic primitives, such as the trend growth rate of GDP, for climate policy. We hope that as the rule is easy to understand and communicate, it might also be easier to implement.
Dell, Melissa, Jones, B. and B. Olken (2012). Temperature shocks and economic growth: Evidence from the last half century, American Economic Journal: Macroeconomics 4, 66-95.
Foley, Duncan, Rezai, A. and L. Taylor (2013). The social cost of carbon emissions. Economics Letters 121, 90-97.
Golosov, M., J. Hassler, P. Krusell and (2014). Optimal taxes on fossil fuel in general equilibrium, Econometrica, 82, 1, 41-88.
Nordhaus, William (2008). A Question of Balance: Economic Models of Climate Change, Yale University Press, New Haven, Connecticut.
Nordhaus, William (2014). Estimates of the social cost of carbon: concepts and results from the DICE-2013R model and alternative approaches, Journal of the Association of Environmental and Resource Economists, 1, 273-312.
Rezai, Armon and Frederick van der Ploeg (2014). Intergenerational Inequality Aversion, Growth and the Role of Damages: Occam’s Rule for the Global Carbon Tax, Discussion Paper 10292, CEPR, London.
Stern, Nicholas (2007). The Economics of Climate Change: The Stern Review, Cambridge University Press, Cambridge.
Note: This article gives the views of the authors, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
“We have to recognize that international approaches to climate change have basically failed. They are not going anywhere, maybe even backwards,” said economist William Nordhaus at a lecture for IIASA staff and young scientists on 23 June. The reason for this failure, he argued, is that international agreements have so far failed to deal with the problem of free riders.
The Kyoto Protocol, for instance, failed as countries dropped out one by one, as soon as mitigation started to become costly. Many countries never even ratified the agreement. Nordhaus explained, “There were no penalties for dropping out.”
Norhaus first introduced the concept of climate clubs at the IIASA 40th Anniversary Conference in 2012.
As the next round of climate talks approach this winter and next in Paris, many researchers say it is time for a new model for international climate change treaties. One new idea, which Nordhaus first proposed at the IIASA 40th Anniversary Conference in 2012, is the concept of “climate clubs.”
Nordhaus said, “Think of the treaty as a club. It’s a voluntary agreement, where members get certain benefits, for a certain cost.” A climate club would work like a free-trade union, such as the EU. It would encourage participation by penalizing non-participants, allowing members of the “climate club” to charge tariffs on all imports of non-participating nations. In his lecture on Monday, Nordhaus expanded on the concept he introduced in 2012, presenting the results of modeling work to determine the tariff rates and carbon prices that would be needed in such an agreement, and how participation would look.
Nordhaus found that more countries were likely to participate when carbon prices were lower. At a carbon price of 25 or 50 dollars, a majority of world regions would participate in the club, while at higher carbon prices of 75 to 100 dollars per ton of carbon dioxide, the highest participation rate would be only about half of that.
At IIASA on Monday. From left: William Nordhaus, IIASA Deputy Director General Nebojsa Nakicenovic, and IIASA Risk Policy and Vulnerability Program Director Joanne Bayer
The high carbon price, Nordhaus explained, would make the cost of participating much higher than the costs of tariffs for non-participants. However, with a lower carbon price, even low penalty tariffs of 3 to 4% could be enough to encourage participation. The idea of tariffs is simpler than previous suggestions of trade penalties based on the carbon emissions impact of specific goods—which in practice are difficult to define, and, as Nordhaus said, “not a big enough stick to induce participation.”
Like any trade agreement, though, Nordhaus’ climate club also means some win and some lose. When he examines the benefits on a regional level, the US, EU, and India appear to gain the most benefits, while Russia and China gain the least. What would it take to get such an agreement off the ground? Nordhaus said that a few key regions would be enough—for example, the EU, the USA, and China.
Watch Nordhaus’ 2012 Lecture at the IIASA Conference
William Nordhaus is Sterling Professor of Economics at Yale University, New Haven, Connecticut, USA. He has a B.A. from Yale University (1963) and a Ph.D. in Economics from MIT (1967). More>>
On October 15, 2012, a young man from Bangladesh named Quazi Mohammad Rezwanul Ahsan Nafis parked next to New York Federal Reserve Bank in a van with what he believed was a 1000-pound bomb, walked a few blocks away, and then attempted to detonate the bomb by mobile phone.
In fact, the bomb was a fake, supplied by undercover agents for the United States FBI. The agents, posing as radical jihadists, had led Nafis along for months, allowing him to believe they were fellow terrorists and gathering information about his plot. The cover was maintained until the moment when his bomb failed to detonate, and Nafis was arrested. Disaster averted.
Researchers at IIASA study many risks to society, from floods, hurricanes, and natural disasters, to the impacts of climate change on future generations. They use models that can help disentangle the costs and benefits of different policies that could help prevent damage or deaths, or mitigate the impacts of global problems like climate change and air pollution. Could the same techniques apply to the dangers of terrorism and jihadists attacks? Could systems analysis help inform intelligence agencies in order to stop more terrorist attacks?
Could systems analysis techniques help guide policies to prevent terrorist attacks? Image Credit: Vjeran Pavic
Yale University Professor Ed Kaplan has done just that in work that he presented at IIASA in late December 2013. His research, which has intersected with IIASA in the past through collaborations with former IIASA Directors Howard Raiffa and Detlof von Winterfeldt, uses operations research to find ways to improve intelligence operations so as to catch more terrorists, before an attack can take place.
Kaplan, an expert on counterterrorism research, refined a simple economic model of customer service, known as a “queuing model” to instead represent the evolution of terror plots by terrorists, and interaction between the terrorists and the undercover agents who are working to uncover those plots.
“The best way to stop an attack is to know it’s about to happen beforehand,” says Kaplan. That means, in large part, having enough agents in the right places to detect attacks. But how many agents is the right number?
At IIASA, Kaplan described his terrorist “queuing model,” which can be applied to show how much a given number of agents would be likely to decrease attacks. Queuing models are an operations research method used to understand waiting times in lines, such as what happens at restaurants, offices, telephone queues or even internet servers.
But in the standard model, customers want to be served, and the servers know who the customers are. In Kaplan’s terrorist model, the terrorists – customers –don’t want to be served, and the servers—the agents—don’t know where their customers are. By modifying the model to account for those differences, Kaplan can answer some tricky questions about the best way for intelligence agencies to fight terrorism.
“Even if you don’t know how many terrorists there are or where they are, you can make it more likely that they will show themselves, you can make it more difficult for them to carry out an attack,” says Kaplan.
Kaplan’s method provides estimates of the numbers of undetected terrorist plots, as well as what it would take to increase detection rates.
Using data from court records of terrorism cases, Kaplan refined his models to include the average time that a terror plot is active – that is, the time from when a terrorist group first starts a plot, to the time that they are either caught, or the attack takes place. Based on the data, he could then calculate how many terror plots were likely to be in progress at any one time. He could also estimate the probability of detecting those plots, and how much that probability could be increased by employing more agents. For example, the model calculates that by increasing FBI agents by a factor of two would increase the detection rate from 80% to 89%.
But the data also point to one disturbing conclusion: A 100% detection rate is impossible. As the number of agents increases, the detection rate increases in ever smaller increments. Kaplan says, “We have to decide how safe is safe enough. When should we stop putting money into Homeland Security, and start putting more back into education and health?”
Download Kaplan’s IIASA presentation (PDF, 2.8 KB)
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.