Talking naked 5/5: Should we talk about the next generation of IAMs and what this means for the environmental movement?

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This is the fifth of a 5-piece series we wrote together with Salvi Asefi-Najafabady– Talking Naked: a series of essay-commentaries on climate-economy models, politics in science, environment, ethics, and society. We will be posting them here. This work is a deeper elaboration of a paper we published recently in the journal Globalizations.

Understanding that the challenge is to inspire action, In this piece we will conclude our commentary with some recommendations for devising the next generation of academic models and policy assessments..

Here is the link to the first installment and the intro to this series: Should we talk about the next generation of climate-economy models?

The link to the second installment: should we talk about the pursuit of amoral economic growth and the enormous pressures it imposes on the Earth and Human system?

The link to the third installment: Talking naked 3/5: Should we talk about the fundamentals of Neoclassical Economics (and Equilibrium Models)?

And the link to the fourth part of the series: Talking naked 4/5: Should we talk about the fundamental problem of unidirectional coupling in Integrated Assessment Models and scenario analyses?

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Talking naked 5/5: Should we talk about the next generation of IAMs and what this means for the environmental movement? 

“All over the world people believe they are being lied to, that the figures are false; that they are being manipulated. And there are good reasons for feeling this way. For years people whose lives are becoming more and more difficult were being told that living standards were rising. How could they not feel deceived?”

Nicolas Sarkozy, 2008 (after the crisis)

Economic activity in the world picked up in the 1800’s. Humans learned to harness buried sun power to sustain abnormal rates of growth and in the process, humans built a colossal international economic system. Economic progress allowed humanity to reach levels of wealth that even a few decades ago would have been unthinkable. In the last few decades, humans reached the moon, lifted millions out of poverty, significantly increased life expectancy, invented the internet, among other feats of human ingenuity—including the design of sophisticated IAMs.

However, this accelerated progress has come at the cost of growing inequality and dangerous degradation of the natural resources that support life on Earth. The richest 26 people in the world possess the same wealth as the poorest half of humanity, and they are also disproportionate emitters of greenhouse gases (Vazquez, 2018; Oxfam, 2015). (The top 10% of the world’s top earners produce almost half of the world’s carbon emissions.) Inequality and environmental degradation are starting to affect economic growth and social stability [40]. In 2017, weather and climate-related disasters caused thousands of deaths and hundreds of billions of dollars in losses. Outdoor air pollution is estimated to kill 4.2 million people annually, while water stress linked to climate change is already contributing to migration, which in turn can lead to conflict and political instability (Low, 2018; WHO, 2018). 

The list goes on. And it is poor families and communities that are the most vulnerable and suffer most. These conditions are being perpetuated by technologies, ways of thinking, and ideas that need to be updated. Incremental change is not enough to stop or reverse the damage. Following the 2018 special report of the Intergovernmental Panel on Climate Change (IPCC), the general global community has called governments across the world for drastic and urgent action on mitigation and adaptation to climate change. Reducing carbon emissions is a step that must be taken as soon as possible to mitigate the effects of climate change. However, it is far from sufficient to resolve the catastrophic problems we are facing today. 

“Decoupling,” the idea that we can detach economic growth from material consumption, has so far proved to be an economics unicorn [36, 54]. The implication is that the total use of resources continues to rise—in spite of new technologies and improvements in efficiency. It follows that a perpetual positive economic growth rate can only be sustained by infinite resources. This is physically impossible. Humans already use as much ecological resources as if we lived on 1.75 Earths (Global Footprint Network). 

In spite of the undeniable planetary boundaries, current IAMs (however sophisticated) continue to make projections of positive economic growth. They must have totally missed the point: even at a mere 2.6% global growth per year, which the IMF denounced 2019’s global economic growth rate as “sluggish” [IMF, 2019; World Bank, 2019), the size of the world economy would double every 27 years, meaning that in 2046 we would be using 3.5 Earths. In turn, in 2073 we would be using 7 Earths (double of 3.5), and in 2100, the target date for the Paris Agreement on Climate change, we would be using 14 times the resources the Earth can renew.

With the current models and their underlying assumptions, researchers and experts seem to be overlooking the fact that climate change is not the only problem but a small portion of a larger environmental catastrophe facing our planet, which is a symptom of the underlying global socioeconomic system (Monbiot, 2018). A system-wide change is urgently required, and we believe that making ad-hoc tweaks to standard models and polishing their shortcomings is not enough to drive meaningful change. Following the words of Albert Einstein, we are not just calling for a new framework of thought, but for an openness to consider new ways of thinking and new processes for decision-making.

Time is running out and inclusive and coordinated action between agents in the Human system is an urgent matter. It is imperative that leaders and decision makers reconsider their value system if we are to avoid social collapse—assuming we are not already experiencing it. The silence has been broken and people (even the media) have started to talk about not just climate breakdown, but also the challenges of growth and consumerism. In a recent Pew Research Center survey, over 74% of American adults said “the country should do whatever it takes to protect the environment,” compared with 23% who said “the country has gone too far in its efforts to protect the environment” (Pew Research Center, 2017). A support rate of 74% is far greater than the support received by the Civil Rights movement in America in the 1960s. (A nationwide Gallup poll in February 1965 found 26% of Americans citing civil rights as a problem facing the nation, second only to the expanding war in Vietnam, cited by 29% [Pew Research Center, 2020].) As these numbers suggest, civil society is challenging the status quo, and yet academic and policy circles are failing to move in tandem with global and plural constituencies. This does not need to be the case moving forward. 

Parting remarks

In this series we have touched on the ethical and technical reasons for why a new inclusive working model of the Human-Earth System is needed. Moreover, we have exposed in detail the social and environmental consequences of not having already done so—with climate change being only one of them. 

In part two of this five-piece series we discussed details of the global system of accounts and how we measure prosperity. We also presented the case for bringing ethics and moral values back into a participatory drawing board and into an inclusive decision-making process. In part three we laid out the neoclassical foundations of a consumption-based model of growth, and hinted to the idea that narrowly defining ourselves as objective, rational, atomistic individuals strips us from our humanity and deceives us into thinking we need not care, as a community, for our peers, for nature, or for future generations. In part four we pointed to unidirectionality in the Earth-Human system as the large elephant in the room and gave examples of the implications that distancing ourselves, even in thought, from our natural environment and from other humans can have. We will conclude this last chapter, by emphasizing our responsibility to act and, building on the momentum from others in the scientific community [4, 48], by suggesting some immediate next steps for modelers of Climate-Earth-Economy systems.

“… it is not the spoon that bends, it is only yourself”

Spoon Boy to Neo in the movie Matrix

Searching for solutions is the current academic way of thinking about climate, environmental, and economic challenges. Nonetheless, focusing on finding solutions, however rigorously, is the wrong approach to improving the conditions of the Human and Earth Systems because we do not live in a world of problems but a world of contrasts and contradictions: contradictions that are posed by how the world system is set to function. Contradictions like that economic growth, the force that lifted people out of poverty and cured disease, can be the very thing that pushes us back into those conditions (Monbiot, 2019). Contradictions that scientists and political leaders are failing to confront. 

We understand that the danger of starting a blank slate is that it can discourage any action at all and make the problem worse, and that the challenge is to improve the current state while inspiring action. Fortunately, we are not in unknown ground and some researchers are starting to develop the next generation of climate-economy models, models that are, interestingly, very much related to the 1972 Limits to Growth [4, 48]. 

Recent thought experiments suggest that future models will have to be built on more humble premises that acknowledge, upfront, the unequivocal burden of increased human and economic activity on the environment, and that clearly represent the bidirectional coupling of Earth and Human Systems. We believe that the design of the next generation of IAMs and the deliberation of clear guidance for designing policies that are adaptable, flexible, and that persist over time will need more than to rely on a strong collaboration of earth and social scientists. Moreover, we think that the development of the next generation of climate-economy models will also have to pay close attention to public participation as well as inputs from the private sector and government actors. Only through an inclusive, technically sound, and ethically-aware process, will next generation IAMs help devise effective science-based and ethical policies and measures. 

Searching for solutions will continue to lead to conclusions that are irrelevant for our global human experience. To deal with problems, like bending a spoon, we can manipulate reality. But to deal with contradictions, as Spoon Boy told Neo in the movie Matrix, we must first need to change ourselves. The status quo has to be challenged. And IAMs are failing to do so. In fact, they are a show-case of what has gone wrong with the way we measure progress and prosperity and with the social values that rule our global system. Values that are increasingly reflective of commercial interests of large economic powers. We will do better with the next generation of IAMs, but we must first recognize the mistakes we have made with our assumptions and, more importantly, understand that making mistakes is not necessarily a sign of ignorance or stupidity—as the emperor was made to believe by the clever weavers.

REFERENCES

[4] Motesharrei, S., Rivas, J., Kalnay, E., Asrar, G. R., Busalacchi, A. J., Cahalan, R. F., & Hubacek, K. (2016). Modeling sustainability: population, inequality, consumption, and bidirectional coupling of the Earth and Human Systems. National Science Review, 3(4), 470-494.

[36] Parrique, T., Barth, J., Briens, F., Kerschner, C., Kraus-Polk, A., Kuokkanen, A., & Spangenberg, J. H. (2019). Decoupling Debunked: Evidence and Arguments Against Green Growth as a Sole Strategy for Sustainability. European Environmental Bureau: Brussels, Belgium.

[40] Abel, G. J., Brottrager, M., Cuaresma, J. C., & Muttarak, R. (2019). Climate, conflict and forced migration. Global environmental change, 54, 239-249.

[48] Motesharrei, S., Rivas, J., & Kalnay, E. (2014). Human and nature dynamics (HANDY): Modeling inequality and use of resources in the collapse or sustainability of societies. Ecological Economics, 101, 90-102.

[54] Ward, J. D., Sutton, P. C., Werner, A. D., Costanza, R., Mohr, S. H., & Simmons, C. T. (2016). Is decoupling GDP growth from environmental impact possible?. PloS one, 11(10), e0164733. Available here.

Talking naked 4/5: Should we talk about the fundamental problem of unidirectional coupling in Integrated Assessment Models and scenario analyses?

This is the fourth of a 5-piece series we wrote together with Salvi Asefi-Najafabady– Talking Naked: a series of essay-commentaries on climate-economy models, politics in science, environment, ethics, and society. We will be posting them here. This work is a deeper elaboration of a paper we published recently in the journal Globalizations.

In this piece we will examine how current academic approaches to represent Human and Earth Systems are unfit for calculating the real cost of climate change, the social cost of carbon, and for evaluating potential socio-economic policies to address catastrophic and rare climatic conditions. Ultimately, we will examine how integrated models of climate change and economics are a symptom of what has gone wrong with the global political and economic system and why they are also inadequate.

 Here is the link to the first installment and the intro to this series: Should we talk about the next generation of climate-economy models?

A link to the second installment: should we talk about the pursuit of amoral economic growth and the enormous pressures it imposes on the Earth and Human system?

And a link to the third part of the series: Should we talk about the fundamentals of Neoclassical Economics (and Equilibrium Models)?

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 “Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks” Motesharrei et al. (2016)

Current economic modeling methods propose an overly optimistic image of the future, predicting the impact of climate change to be only a few points decrease in the world Gross Domestic Product (GDP) per capita by the end of the century—even for high levels of warming. According to these models, even a global temperature increase above +5 degrees Celsius would allegedly cost less than 7% of the world’s future GDP [16, 17]. And even models that favor a carbon tax to slow climate change, show that reaching the UN target of avoiding temperature rise to 1.5 degree Celsius above pre-industrial levels by 2100 would make humanity poorer than doing nothing at all about climate change (Murphy, 2018). 

Even the 2018 IPCC Special Report on Global Warming of 1.5oC —which announced with no uncertainty that avoiding cataclysm drastic action and technological improvement by 2050—is built on fictitious wishful thinking (at best) as it does not question economic growth as an underlying assumption in any of the scenarios it created to generate the so-called “socioeconomic pathways” (Ehrenreich, 2021).

That the growth imperative is not even questioned by these models make whatever resulting estimates dangerous and they have led some authors to conclude that humanity has far bigger problems than climate change and that “a century of climate change is about as good/bad for welfare as a year of economic growth” [18]. Moreover, not only are they dangerous, they are also unreliable, misleading and founded on oversimplifying assumptions [19].

In the previous chapter of this series, we introduced the first problem with Integrated Assessment Models (IAMs): their unrealistic assumptions about behavior and therefore their incapability of representing the Human System. In the coming paragraphs we will list other weaknesses of IAM-based economic analysis of climate change policy and explore in detail the fundamental problem of unidirectional coupling in IAMs and scenario analysis. 

The second problem of IAMs is more practical. Often, IAMs are formulated in an optimization language such as GAMS (General Algebraic Modeling System) or AMPL (A Mathematical Programing Language). This imposes restrictions in order to find the system’s solution (the idea that an optimal solution, or equilibrium, can be found by solving a system of equations follows from the perfect information assumption discussed above). Technical considerations that limit the type of complexities, nonlinearities, non-convexities, tipping points, and uncertainties a modeler can consider is particularly problematic when studying climate change.

The third drawback of IAMs is that they leave many degrees of freedom for the modeler so that different models can arrive at drastically different conclusions regarding optimal abatement policy and the implied social cost of carbon (SCC) because of the modeler’s choice of functional forms and parameter values. For example, Nordhaus (2008) finds that optimal abatement should initially be very limited, consistent with a SCC of around $20 or less, while Stern (2007) concludes that an immediate and drastic cut in emissions is necessary, consistent with a SCC above $200. 

In a recent report, prominent academics warn that economic assessments of future climate change impacts are misleading because the economic models are expressed solely in terms of effects on output (e.g. gross domestic product), or only extrapolate from past experience, or use inappropriate discounting, and therefore do not provide a clear indication of the potential risks to lives and livelihoods (LSE, 2019). In this piece, we argue that IAMs and the scenario analyses that often accompany them suffer from a weakness that is even more profound than an inappropriate framework for analyzing economic risks. We argue that current climate-economy models are incapable of showing the connections between Human and Earth systems. Therefore, whatever conclusions are derived from analyzing these models will fail to recommend that we change the economic system in order to avoid further consequences of damaging the natural environment. Current models will only provide evidence to kick the can a bit further, but cannot be used to derive scientific support to encourage the establishment of a new world system.

Integrated Assessment Models combine different strands of knowledge and can vary in the way they work and the questions they can answer. They tend to be technically rigorous and often impressive in the complexity of their architecture, and researchers across disciplines use IAMs to the best of their potential and use them to develop ingenious and robust tools that address key structural considerations for climate change action. Some of these tools and techniques include dealing with the uncertainties of the IAM models as an issue of deep uncertainty and develop dynamic adaptive pathways [13-15]. Moreover, even simple IAMs are insightful enough to earn one of their creators an Economics Nobel Prize in 2018. 

However, it is complicated to accurately represent Earth/Human systems: developers of IAMs require expertise in a wide range of sciences, from Earth sciences to economics to computer science. As a result, IAMs do not model the detailed processes and relationships between Human and Earth systems. Even in complex IAMs, which use additional linked modules representing the global economy, as well as its energy, land, and climate systems to look at the energy technologies, energy use choices, land-use changes, and societal trends behind emissions of greenhouse gases (GHG), fail to represent sound science.

Unfortunately, the lack of consensus or even guidance over what is the “right” approach to representing the future of the Anthropocene, or what are the “best practices” for modeling, make results from IAMs dangerously inaccurate. We say dangerously because oftentimes, the technical rigor and architectural complexity of IAMs give decision makers the impression that they are scientifically sound and trustworthy. As we will show in the paragraphs below, despite the advances and sophistication in modeling, this is not the case—yet.

Integrated but decoupled

The better understood problems with IAMs include how the climate sensitivity parameter (a key parameter in the climate module) is calculated; how the models assume there are infinite potential sinks for carbon; how emission reduction policies have instantaneous effects; and how there is always an optimal rate of fossil fuel extraction. These issues have been discussed extensively elsewhere, so we will just acknowledge them in this commentary (Fiddaman, 2017; Murphy, 2018; [47]). Instead, we will focus on what we have called the fundamental problem of unidirectional coupling in Integrated Assessment Models and scenario analyses.

The most obvious problem of IAMs is their decoupled structure, meaning that the Earth and Human Systems in IAMs do not feedback to each other. In general, that means the tools scientists use to predict the evolution of climate variables in different socio-economic scenarios, do not consider the connection between socio-economic variables and many important climate and environmental variables. Typically, critical Human System variables used in IAMs, such as land use change, demographics, inequality, economic growth, and migration are based on exogenous projections which are demonstrated to be unreliable [4]. This is often referred to as “uni-directional coupling.”

There are many examples of how Earth and Human Systems are coupled, or how output signals in Human (Earth) System are fed back as inputs into the Earth (Human) System. For instance, changes in climate hazards can trigger human migration across different regions of the world, which in turn will have effects on land use, water availability, deforestation, desertification, and so on. Also, it is possible for climate change to eventually make certain areas of the world so dire (and even inhabitable if temperatures rise beyond a certain degree) that economic output will fall, populations will decline, and social inequality and political or even religious tensions will be exacerbated in these regions—as has already happened in places like Syria [21].

The opposite side of the coin would be how declining populations and sluggish economic activity could reduce emissions of GHG, thus mitigating the impact of the Human System on climate change. In this kind of scenario, an economic crisis, which could be aggravated in certain regions by widespread extreme weather events (e.g., along coastlines and in the tropics), could conclude in halting, or at least slowing down, fossil fuel extraction: a scenario that would necessarily be accompanied by a decline of GHG emissions. In fact, recent studies have shown that the 2008 recession caused localized reductions in CO2 emissions from fossil fuel combustion. These declines were experienced mostly in less prosperous regions of the US and the world [22].

A different example of a rather indirect effect of climate change on social tensions are the protests by the Gilets Jaunes in Paris. The protests were triggered by a carbon tax addressing climate change but continue to be fueled by general discontent over increasing inequality and rising living costs in France, which include rising costs of petrol and heating oil. Although the connection between climate change and social tension is much less direct in the case of the Gilets Jaunes than in the case of rural migrants than flee unworkable agricultural areas, the Paris strikes are a legitimate example of political tension that further illustrates the complicated relationship between the two trends that are driving our society towards collapse: environmental degradation and rising inequality.

Current IAMs and complementary scenario analyses (e.g., Representative Concentration Pathways, or RCPs, and Shared Socioeconomic Pathways, or SSPs) do not show these feedbacks, and as a result, current analytical approaches are unable to accurately estimate the economic cost of environmental degradation (including climate change), and scenario analyses are unable to represent realistic human responses to environmental impacts, such as migration, changes in wealth inequality, and changes in regional economic activity (which could include outcomes that are assumed away in the majority of simulated exercises—as negative economic growth rate). Current analytical approaches are unfit for impact evaluation or adaptation and mitigation planning—particularly at the regional or local level (because of scalability issues). This point is made apparent by the finding that population distribution and population density projections from current IAMs are exactly the same for a scenario with sustainable development (SSP1) and a scenario with fossil-fuel intensive development (SSP5) [23]. 

What is to come?

In the next two chapters of this Talking Naked series, we will identify major significant caveats relating to the way IAMs are designed and the considerations they leave unaddressed. Flaws that even the IPCC, which partly derived its recommendations for the special 2018 report from simulated scenarios generated by IAMs, recognizes (CarbonBrief, 2018). 

But we do not want to focus on pointing out the flaws of IAMs or the recommendations that stem from them. Instead, we want to emphasize that the assumptions and the architecture of IAMs are a symptom of an even more profound problem with how social planners, policymakers, and global political and economic powers are dictating the way in which natural and human resources are managed (or mismanaged). Thus, in the final chapter of this series we will argue that current IAMs reflect the values of global social, economic, and political systems that are devised to benefit the few at the expense of the environment, the poor, the vulnerable, and the generations to come. And we will conclude with some thoughts on how the next generation of IAMs can be designed to challenge the very pillars that give rise to an unfair and unsustainable Human system. 

REFERENCES:

[4] Motesharrei, S., Rivas, J., Kalnay, E., Asrar, G. R., Busalacchi, A. J., Cahalan, R. F., & Hubacek, K. (2016). Modeling sustainability: population, inequality, consumption, and bidirectional coupling of the Earth and Human Systems. National Science Review, 3(4), 470-494.

[13] McInerney, D., Lempert, R., & Keller, K. (2012). What are robust strategies in the face of uncertain climate threshold responses? Climatic Change, 112(3-4), 547–568. https://doi.org/10.1007/s10584-011-0377-1

[14] Hall, J. W., Lempert, R. J., Keller, K., Hackbarth, A., Mijere, C., & McInerney, D. J. (2012). Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods. Risk Analysis: An Official Publication of the Society for Risk Analysis, 32(10), 1657–1672. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/j.1539-6924.2012.01802.x/full

[15] Keller, K., Bolker, B. M., & Bradford, D. F. (2004). Uncertain climate thresholds and optimal economic growth. Journal of Environmental Economics and Management, 48(1), 723–741. https://doi.org/10.1016/j.jeem.2003.10.003

[16] Nordhaus, W. (1994). Expert opinion on climatic change. American Scientist, 82(1):4551.

[17] Roson, R. and Van der Mensbrugghe, D. (2012). Climate change and economic growth: impacts and interactions. International Journal of Sustainable Economy, 4(3):270285.

[18] Tol, R. (2018). The Economic Impacts of Climate Change. Review of Environmental Economics and Policy,12(1):425.

[19] Woillez, M.N., Giraud, G., & Godin, A. (2019). Economic impacts of a glacial period: a thought experiment. AFD Research Papers, No. 2019-99, March.

[21] Gleick, P. H. (2014). Water, drought, climate change, and conflict in Syria. Weather, Climate, and Society, 6(3), 331-340.

[22] Asefi‐Najafabady, S., Rayner, P. J., Gurney, K. R., McRobert, A., Song, Y., Coltin, K., & Baugh, K. (2014). A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of results. Journal of Geophysical Research: Atmospheres, 119(17), 10-213.

[23] Asefi-Najafabady, S., Vandecar, K. L., Seimon, A., Lawrence, P., & Lawrence, D. (2018). Climate change, population, and poverty: vulnerability and exposure to heat stress in countries bordering the Great Lakes of Africa. Climatic change, 148(4), 561-573.

[47] Ackerman, D. F. (2010). Can we afford the future?: the economics of a warming world. Zed Books Ltd..

Talking naked 3/5: Should we talk about the fundamentals of Neoclassical Economics (and Equilibrium Models)?

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This is the third of a 5-piece series we wrote together with Salvi Asefi-Najafabady– Talking Naked: a series of essay-commentaries on climate-economy models, politics in science, environment, ethics, and society. We will be posting them here. This work is an a deeper elaboration of a paper we published recently in the journal Globalizations.

In this piece we will examine how the foundations of mainstream economic models at the heart of academic climate-economic analyses renders them incapable of representing or addressing distributional considerations and ecological collapse. Ultimately, we will examine how integrated models of climate change and economics are a symptom of what has gone wrong with the global political and economic system and why they are also inadequate.

Here is the link to the first installment and the intro to this series: Should we talk about the next generation of climate-economy models?

And a link to the second installment: should we talk about the pursuit of amoral economic growth and the enormous pressures it imposes on the Earth and Human system?

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“On the day of the [2018 economics] Nobel announcement, the United Nations’ Intergovernmental Panel on Climate Change (UN IPCC) released a special report advising the governments of the world on various steps necessary to limit cumulative global warming to 1.5 degrees Celsius. The major media coverage treated the two events as complementary. In fact, the are incompatible”

 Robert P. Murphy

Scientists that collaborate with economists in developing Integrated Assessment Models (IAMs) are generally unaware of the details in economics models. In this part of the series, we advise scientists against trusting that traditional economic models feeding into an IAM are sound and robust simply because they have been developed and curated by academics who also publish and get tenure, and who, surely, know what they are doing (and they must know what they are doing because they have been doing it the same way for decades now).

Economic models at the heart of IAMs are elegant and manageable. This is particularly true for simple IAMs but the observation loosely applies to more complex IAMs as well. (After all, most, if not all IAMs that are used to generate estimates of the social cost of carbon can be traced back to one of only four possible authors: William Nordhaus, Chris Hope, David Anthoff, and Richard Tol. Notice that both William Nordhaus and Richard Tol are notorious in the literature for their “astonishingly low” estimates of the social cost of carbon [47, 53].) However, in spite of their mathematical elegance, economic models behind most policy assessments are suboptimal—very suboptimal. 

It may be obvious, but it is expected that economic outcomes reflect the decision-making processes of economic agents. And given that economic agents are human, economic models should focus on representing human behavior—for which there is no agreed upon representation. Here lies the first problem with the Human Systems component in IAMs: they impose unrealistic assumptions about behavior and therefore represent the wrong system. (So wrong, in fact, that even Alan Greenspan, a former head of the US Central Bank said to the US Congress in 2008: “I have found a flaw… a flaw in the model that I perceived was the critical functional structure that defines how the world works—so to speak” [Chakrabortty, 2014].)

In a simple IAM, much like in any other mainstream macroeconomic model, there is one single agent with rational expectations (i.e., an optimizing agent with full information of the system and with a clear decision rule) who makes all possible decisions in the world. This agent is supposed to represent the economic decisions of all actors in the global economy: consumers who have different traditions and habits, religions, income levels, access to resources, and risk preferences; producers who vary in size, technologies, and market reach all the way from the smallholder household practicing sustainable farming in a developing country, to the mom-and-pop’s shop selling an assortment of manufactured goods in a medium-income country, to the large international corporations with complex global production chains. Finally, this economic agent also takes all distributive decisions in the economy, i.e., who gets what (it should be obvious that the representative agent distributes all the wealth equally among all agents in the model, that is, him/her self). In a sense, the representative agent is effectively controlling market and government decisions in the economy (yes, we are saying the State is a player in the economy!). Notice that many of these decisions are by design unnecessary since the agent has only him/herself to trade with and to regulate.

For convenience (and fun), in the remaining sections of this commentary we will refer to this fictitious representative agent as Adam (which perhaps makes you wonder about the importance of being Adam… are our thoughts at all primed by our names?). Formally, a simple IAM introduces Adam’s economic problem as follows:

The objective function: a consumer’s worldview in three equations

Consistent with the assumption of rational expectations discussed above, Adam is a rational economic man with perfect foresight and therefore makes economic decisions that are optimal. Importantly, Adam knows what he wants in life and his preferences do not change.

Adam’s objective is to be as “best off” as possible, given the current technological and climatic conditions. In traditional economics lingo, to be best off is to “maximize welfare,” and welfare is defined as the present value of Adam’s lifetime satisfaction. This present value is equal to the discounted sum of “satisfaction levels” Adam would attain in each time period of his life. The sum of this sequence of satisfaction levels, or levels of “utility,” is discounted to be shown in present values because Adam, being a rational agent, values present consumption more than future consumption. In other words, he prefers one apple today rather than one apple tomorrow—for whatever reason.

In addition to that, Adam derives satisfaction from only two activities: consumption and leisure. That is, Adam does not find his work fulfilling and does not regard as uplifting choices discipline in habits, austerity, or any practice of self-restraint. Given that Adam is alone in the world, he has no reason to help other agents and therefore altruism is not a virtue that can characterize him: it is simply irrelevant in the world set up by the model. In mainstream macroeconomic models, Adam does not have to worry about working conditions of those producing the goods and services he consumes: he simply doesn’t care whether their jobs are safe, whether they get well paid, whether they are old enough to be out of school, whether they have enough free time to spend with their kids, to cook a healthy meal, or to go for a walk. Also, in simple IAMs, Adam does not have to worry about oil spills and environmental pollution associated with the production of the goods he consumes. Finally, Adam doesn’t care if it is people or corporations who produce the goods and services he consumes, or whether corporations have the same democratic rights as citizens. It’s a simple world, that of Adam.

Finally, the utility function of Adam, i.e., the rules that connect Adam’s choices to his level of satisfaction, exhibits “constant relative risk aversion.” In other words, Adam dislikes risks but his aversion to risk does not change with his level of wealth. This means that as Adam gets richer or poorer, his attitude towards a risky decision remains the same. 

Let’s pause for a second and review what we know about Adam as a consumer. Adam does not hold moral views that keep him from consuming too much or devote more time to idleness. Adam does not have to be kind, generous, or compassionate towards others—not only because there are no others but also because even if there were others, he would not derive any satisfaction from any of these activities.

Adam could not be a Buddhist or a monk because he derives more satisfaction from instantaneous consumption and leisure than delayed consumption and leisure (i.e., he does not find it exciting or satisfactory in any way to build anticipation or “dream” about future apples). In addition, Adam will not change his mind about taking a risky decision if he is suddenly struck by bad luck and distress or if he suddenly enjoys abundance in his life. Finally, and importantly, Adam will die alone. Adam has no reason to restrain himself from accumulating as much welfare as possible because his choices have no consequences passed his lifetime.

In case the problems with using Adam as a representative for all of the world’s human population are not already evident, let us elaborate (as others have done elsewhere [24]). According to the Adam model of the world, the Human System does not include any values or relations that are not economic. Also, it is impossible to represent the different sets of values or preferences, different starting levels of wealth, and different chances to prosper that we observe in reality.

There is no uncertainty in this model since Adam has perfect foresight and knows what brings him utility, leading to the conclusion that revealed behavior is optimal behavior. That humans are optimizing agents with fixed and clear preferences is at great odds with what we now know about marketing strategies and how advertisement is used to manipulate preferences (which should not be possible if preferences were static, as Adam’s).

In addition, if there were markets in Adam’s world, the optimal behavior assumption would also mean that markets express preferences perfectly, the economy would therefore always be in equilibrium, or at the very least on its way to equilibrium after an exogenous shock. In economics lingo, to be in “equilibrium” means that no one can be made better off without hurting someone and that therefore, every resource is used wherever it produces the greatest value. If the world were in equilibrium, and the Adams of the world were indeed optimizing agents, there would not be global phenomena like housing bubbles and international financial crises—meaning Adam wouldn’t have to worry about regulating a whole sector of the economy or about bailing out big bankers while people lose their houses, jobs, and pensions. Also, in a world economy that easily returns to equilibrium, there would be no need for policy action in response to climate climate change. There also would be no need for updating economics books. 

Finally, if the Adam model was used to represent an inter-generational situation, as it is done in IAMs, a non-negative discount rate is at odds with moral values and with observed outcomes. In a sense, a positive discount rate is a way to “distribute” the generational wealth gap, and having a positive discount rate means a combination of three things: (1) that Adam values his own well-being over the well-being of his descendants, (2) Adam discounts the wealth of future generations because he expects future generations to be wealthier than him, and (3) it is not optimal in the model for Adam to transfer some of his own well-being onto the well-being of future generations.

The first of the three points can be challenged on moral grounds. But the second and third point are inconsistent with reality: it is not necessarily true that future generations will be wealthier than the current generation (see for example how Millennials are less well off than their parents [Bialik and Fry, 2019]), and it is guaranteed that future generations will face harsher living conditions than any previous generation because of the choice of current and past generations to burn fossil fuels, overuse the Earth’s soil, pollute the oceans, cut the forests, etc.

The higher the discount rate, the less Adam values the future, economically. To be fair, discounting makes sense over relatively short time horizons. However, when considering the long-term future, discounting can yield confusing results. For instance, as Derek Parfit wrote, at a discount rate of 5% annually, one death next year is more important than a billion deaths in 500 years (Walsh, 2019). Or in monetary terms, with a 5% discount rate, it would be worth spending $2,200 today in order to prevent $87 trillion in damages in 500 years ($87 trillion is the current size of the global economy). A typical IAM uses a 3% discount rate. (For reference, the climate-change denying Trump administration used an annual discount rate of 7% for its analysis of the social cost of carbon.)

How environmental degradation affects the Production decision

The second part of Adam’s economic problem is his production decision. In a simple model, Adam produces only one aggregate or composite good that represents all possible goods and services in the global economy. There is only one way to produce this good and it is to use Capital and Labor using some level of technology available to him. 

In reality, the single composite good/sector and functional form of production function (typically some form of the neoclassical “Constant Elasticity of Substitution”, or CES, function) are not the real problems with this approach to modeling production as these restrictions can more or less be easily be relaxed to better reflect observations: more sectors can be added to the model and the model can be calibrated using more disaggregated data. The real problems with how production is represented in the world of Adam have to do with the role of technology in the model and how environmental degradation affects production.

Besides the production function, there are two other factors that enter Adam’s production decision: technology and a penalty term that represents “lost production” due to environmental degradation. In Adam’s world, technological advancement is exogenous and there are no delays in its impact on production (although some IAMs try to model these delays by imposing a logistic function on how new technologies are adopted). In other words, there is no deliberate investment in R&D to invent more fuel-efficient machines, or new methods to drill non-conventional sources of oil and gas, or carbon capturing technologies (even if just as a marketing stunt [Sanderson, 2019]). New technologies in IAMs simply appear and impact the entire composite production instantly, at the same time, and in a unique fashion.

The most problematic fact about the role of technology is that it is the only driver of growth in a simple IAM. In other words, it is only through technological improvement that Adam gets “better” at producing more things with the same amount of capital and labor (i.e., he becomes more productive). Adam does not “learn” how to better use capital and labor, and he cannot “get better” at producing by becoming more educated or having better nutrition: he simply “turns” better by the grace of some external shock.

Finally, let us discuss the penalty term, or how environmental degradation affects production. This term is determined by the so-called “damage function.” The damage function, Omega (is that intentional?), basically reduces output level by some fraction that supposedly reflects how natural conditions reduce productive capacity. For example, depleted soils would reduce Adam’s capacity to grow apple trees and deforestation would reduce the number of fig trees that Adam could use.

Having the penalty term is an attempt to connect man-made (or anthropogenic) impacts on climate and the environment back to productive activities (which are the original cause of the changes in environmental conditions) and express the impacts in economic terms. However, the oversimplification of the process in the model is misleading and even dangerous if policymakers take the output from popular IAMs as “optimal” guidance for policy action. The original purpose of including a damage function is to facilitate decision making by expressing all outcomes in a common unit of measure ($). However, given the serious flaws of the damage functions used in IAMs, it is arguably preferable to shift the analytical approach to one where all impacts on all variables of interest are expressed in different units, as was done in the seminal work for the Club of Rome, The Limits to Growth (1972).

The typical damage function only takes mean global temperature into account and does so in a completely ad-hoc manner. Damage functions have been heavily criticized for their lack of empirical or theoretical foundations. Also, they have shown to be inadequate for evaluating impacts of temperature change outside the calibrating range [28-30, 19].

Firstly, the penalty term effects output levels and not output growth—for no particular reason. Impacts on growth may appear more realistic than level effects as they allow global temperature increases to have permanent impacts and also accounts for resources consumption to counter the effects of warming, reducing investments in R&D and capital and hence economic growth [19]. In addition, and more importantly, the damage function is based on a non-scientific representation of the Earth System.  

Finally, damage functions, in their current form, do not incorporate deep uncertainty: a key feature of the economics of climate change [31]. In the event that climate change is likely to be more catastrophic than we “expect” (i.e., that the probability distribution of climate change impacts has “fat tails”), pollution mitigation would be more beneficial than originally thought. But because  the stylized damage functions running at the heart of IAMs are ad-hoc and formulated to be mathematically convenient, they are incapable of accommodating uncertainty over costs or benefits of pollution abatement and cannot be used to find an “optimal” social cost of carbon. As shown by Martin Weitzman (1974), when there are uncertainties over both the marginal social costs and benefits of emission abatement (this is economics for saying “the cost and benefit to society from reducing emissions by one additional ton of carbon”), a tax on carbon (or equivalently, the price paid to those who avoid emitting one additional ton of carbon) will never be high enough for society to reach the optimal level of emissions reduction because the economic calculations do not account for the “real” benefits of mitigation (here we use “real” to mean an estimate of benefits that accounts for uncertainty).  

Modeling human systems as top-down optimization problems defined by experts

Mainstream macroeconomic models that often run at the heart of IAMs are constructed following a “top-down” approach, which is justified by the “rational expectations” assumption. What that implies is that all components in the system behave in accordance to an underlying structure and any solution that may arise from the model will necessarily be confined to that fundamental frame. In other words, the outcome space of the system is restricted to be a subset (or even a non-overlapping set) of the “true” world outcomes. These restrictions have important implications for the economic outcomes of the model. For example, a standard result of mainstream models (that are not even that restrictive) is the full employment of labor in the economy: meaning that anyone who is willing and able to work can find a job and unemployment is zero.

To the casual observer, this perfect synchrony characterizing Neoclassical economics may seem as the work of an all-knowing “invisible hand” (Adam Smith’s all-time favorite). The foundations of a Neoclassical approach are attractive from the modeling standpoint for their elegance, and from the political standpoint for their acceptance of the status quo: if human beings are rational, then the current state of things is optimal, given an underlying socio-economic structure. However, Neoclassical models fail to allow for changes to the very structure of the system and thus are incapable of formulating solutions that would be possible after fundamental social changes. For example, if new institutions were erected to protect worker rights, Adam’s optimal choice of employment may be one between a low-wage job and high-wage job, rather than a choice between a job and no job. 

Since the 20th century, the Neoclassical school has been the dominant school of thought among Western economics and policy-making circles. Like most theories, the neoclassical model is not perfect and it relies on unrealistic assumptions. Yet, it was not until it completely failed to predict the 2007/2008 financial crisis, that this approach started to receive serious criticism. It is now clear among researchers that economics frameworks need updating. 

As we will discuss before the end of this series, we advise scientists to look beyond the traditional economics department and explore different perspectives to modeling the economy before signing to collaborative, interdisciplinary efforts that are policy-oriented and with potential global impacts. In particular, we advocate for the use of “bottom-up” approaches to modeling economic behavior. These are systems in which components emerge and evolve more or less organically. In these systems each component understands only a small part of the whole and follows simple “reactionary” rules, giving rise to outcomes akin to John Maynard Keynes’ “animal spirits.” We argue that models that follow this design are more humble and realistic in their assumptions and limitations. They are more flexible and have the potential to better inform the making of policies that address increased wealth inequality and environmental, particularly in the face of climate change—a phenomena that not even Adam could possibly have full information and certainty over.

REFERENCES:

[19] Woillez, M. N., Giraud, G., & Godin, A. (2019, January). Economic impacts of a glacial period: a thought experiment. In Geophysical Research Abstracts (Vol. 21).

[24] Adler, M., Anthoff, D., Bosetti, V., Garner, G., Keller, K., & Treich, N. (2017). Priority for the worse-off and the social cost of carbon. Nature Climate Change, 7(6), 443-449. https://www.nature.com/articles/nclimate3298

[28] Pindyck, R. (2013). Climate change policy: what do the models tell us? Journal of Economic Literature, 51(3):86072.

[29] Pottier, A. (2016). Comment les économistes réchauffent la planète. Le Seuil.

[30] Pindyck, R. (2017). The use and misuse of models for climate policy. Review of Environmental Economics and Policy, 11(1):100114.

[31] Weitzman, M. L. (2011). Fat-tailed uncertainty in the economics of catastrophic climate change. Review of Environmental Economics and Policy, 5(2), 275-292.

[47] Ackerman, D. F. (2010). Can we afford the future?: the economics of a warming world. Zed Books Ltd..

[53] Anthoff, D. (2019). IAMs in climate economics and the SCC. Lecture at Pennsylvania State University.  https://psu.app.box.com/s/je9wtzhr2nb8l428d0yt834uruj3bbux

Talking naked 2/5: Should we talk about the pursuit of amoral economic growth and the enormous pressures it imposes on the Earth and Human System?

By Laura Villegas Ortiz and Salvi Asefi-Najafabady

“The grim truth is that the rich are able to live as they do only because others are poor: there is neither the physical nor the ecological space for everyone to pursue private luxury” 

George Monbiot

A brief history of growth and dependence on fossil fuels

For the majority of human history, the rate of economic growth per capita was close to zero. Societies were mostly agricultural and the production processes they sustained depended partly on rudimentary technologies, such as plows and domesticated animals, but mostly on access to sunlight, water, and soil nutrients—all factors that are made available through the natural cycles in the Earth’s System. It wasn’t until very recently, when humans found an efficient way to harness fossil fuels, that societies began to grow economically and in population.

Since 1800, the world population has grown from one billion to 7.76 billion in 2018 and we are expected to reach 10 billion by the end of the century. The story of economic growth follows a similar path. It was not until the invention of the steam engine, and its use to efficiently extract coal, that societies began experiencing rates of economic growth substantially larger than zero. (Between 1500 and 1820, the growth rate of per capita income in Western Europe was 0.14%—not too different from the growth rate between 1000 and 1500, which was 0.12% [3].)

Fossil fuels are reservoir of energy: stocks of energy that have been accumulating for hundreds of millions of years. It was precisely the use of fossil fuels that enabled humans to use more energy than what was normally made available to them in the form of wind, sunlight, fire, and running water. Accordingly, using additional energy sources, humans were able to sustain additional growth. Thus, for the last couple hundred years, the unlocking of energy from fossils has allowed humans to grow in population and wealth at a rate beyond the rate that the biogeochemical cycle is capable of maintaining  in the absence of human perturbation [4].

Unprecedented growth has come with an unprecedented impact, and we now face urgent environmental and social issues. Anthropogenic carbon emissions are driving climate change, the human food industry is leading an ecological cleansing of land and oceans, and the modern model of economic growth is leaving the majority of people behind, fueling economic inequality and social tensions and ultimately threatening the social fabric and political stability of countries all over the world. 

Human-born carbon emissions have brought the natural carbon cycle off balance. Since the Industrial Revolution, the level of carbon dioxide in the atmosphere, which humans emit mainly by burning fossil fuels, has increased by about 120 parts per million. Those increases have happened in the past, but the normal time scale for a 100 ppm increase in CO2 would be close to 5,000 years, not one hundred. In the last couple of centuries, humans have caused a big shock to the system (Monroe, 2015; Veritasium, 2014).

Accelerated population and economic growth are no longer possible within the limits of the Earth System, and this is shown by recent phenomena, such as climate change (which results from the process described above). Essentially, we have surpassed the Earth’s capacity to restore and repair the damage imposed by increased human activity. Current trends in extinction rates, coral reef decay, ocean pollution and acidification, overfishing, deforestation, air pollution and climate change point towards critical environmental tension, if not collapse ([5], WRI, 2019; Luo, 2017; WRI, 2019; WHO, 2019; Woodward, 2019).

Ecocide and the pursuit of economic growth

Historical trends of natural resources depletion show that economic growth is no longer sustainable, and yet, the mainstream narrative, even among scientists (economists, climate, and environmental scientists included), is failing to embrace the idea that the core force driving our current environmental conditions is the limitless appetite for growth in consumption (and the limitless appetite for profit from those who produce what is to be consumed—as we are reminded by the mere conception of the “planned obsolescence” commercial strategy). 

Leaders and experts claim the global economy is growing (UN DESAEA, 2019) but what they call growth does not account for the depletion of natural resources or the environmental damage our lifestyles and choices are causing to the entire planet. 

Moreover, in Western countries we claim to have cleaned our industrial pollution, but in reality, what has occurred is that polluting industries have been transferred to Eastern and developing countries such as China and India, in order to not compromise economic profits in the West. Today, there are barely any products found in the U.S. that are not manufactured in China. This transfer of low-tech and polluting industries has now made China the world’s biggest polluter. And, ironically, overwhelmed with pollution, China is fighting pollution and climate change (of course without compromising economic growth) by transferring hundreds of its polluting coal-fired power plants to other countries (NPR, 2019). The level of irony in this story is tragic.

Mainstream economic assessments point to the detachment of economic growth from material consumption as a solution to environmental degradation (they call this detaching “decoupling”). Yet, a recent comprehensive review of evidence shows what economists call decoupling of economic growth and extraction of natural resources is more of a myth than a real option [36]. Moreover, it appears that efficiency gains from technological advances may in some cases result in net increases of resource use (this is known as the rebound effect or the Jevons Paradox).  For example, even if we manage to successfully transition into cleaner sources of energy, that will entail further extraction of rare minerals and ores that are used in the production of batteries (Pitron, 2018). 

Transfering pollution will not solve our global environmental problems, nor will technological change alone. We need to first realize that our planet has limits and allowing a consumption-based economy to grow without breaks inevitably leads to dire consequences, and we are evidencing some of those already, such as the continuous depletion of Earth’s resources and the uncontrolled discharge of waste and pollution into the system. 

Simply focusing on economic growth will inevitably lead to a faster destruction of the planet and will have unforeseen impacts on the distribution of wealth. It should be obvious that there is no substitute for lowering consumption. 

GDP as a measure: the value of nothing 

When all the thinking is done and the analytical architecture is ready for empirical use, a model of economic growth is calibrated using GDP data as a proxy measure of an economy’s means to attain well-being. There are concerns over how GDP is measured and what information goes into it, and researchers should be wary of how they interpret connection between GDP and economic prosperity. 

Gross Domestic Product, or GDP, is the sum of all things produced domestically, without deducting anything (e.g., the value that machinery loses over time from wear and tear). We are not alone in arguing that GDP is a phony construction: an abstract idea that over the last 50 years of international discussion and standard-setting has become extremely complicated and still does not reflect prosperity.

Although the idea of GDP seems simple—the sum of all that is spent in the national economy—in practice, measuring GDP is a complicated matter. For reference, the 2008 UN guide to the System of National Accounts (the guide for measuring GDP) has over 722 pages, and very few people can truly understand how the regularly published GDP figures are constructed [32].

Any book of introductory economics will include the following definition of GDP: GDP=C+I+G+(X-M). As shown in this formula, GDP is the sum of Consumer spending plus Investment spending plus Government spending plus export revenue minus import expenses (the difference X-M is known as the trade balance). 

What does measuring C mean in practice? Does C include spending related to sex trafficking and drug-dealing? What about spending on products that last many years, like houses? Are those purchases included in GDP measures corresponding to each year the product is kept? Why are social services like pensions and other transfer payments not accounted for in government spending? How are financial products of different risks accounted for? Why is risky lending not “less” valuable than “safe” investment? Why is the depletion of natural resources or the cost of environmental degradation not subtracted from the National Income Accounts? 

For some, GDP’s dominance as the primary measure of economic success has been increasingly seen as a symbol of what has gone wrong with market-capitalism: it is counter-intuitive that a measure of well-being improves during times of war or natural calamities simply because these catastrophes trigger spending to finance the war and repair the damages. Why does it take a war to produce jobs? Also, why doesn’t house work, like playing with one’s children, cooking meals for the family to eat at home, and taking care of one’s home and neighborhood not count as measures of well-being? Why is it better for the economy that I pay my neighbor to look after my children and I receive payment to look after my neighbor’s children instead of each looking after our own kids for free? Why is it better for the economy that married couples divorce systematically so each person in the former relationship can now purchase a house and spend money on legal services? Why is it better for the economy that banks systematically lend a lot of money to high-risk borrowers? Why is it not bad for the economy to extract non-renewable natural resources, knowing that they won’t be available in the future? Why do we rely on a measure that can suggest an economy is healthier when one giant corporation grows rapidly while everyone but the corporation (which is technically not a person) is becoming poorer? 

It is because of these ambiguities that we say GDP is, at the very minimum, misleading and incomplete. More importantly, it fails to measure well-being or distribution of wealth in the modern economy: an economy of rapid innovation and intangible, increasingly digital, services. 

A perturbing idea is that getting our economic accounting systems to recognize environmental costs and benefits is not so much an issue of data quality but one of the motives behind current measurement systems [34]. It should be recognized that failing to account for environmental damages only means that increased economic growth is convenient for those designing the accounting system. We believe it is well passed the time to question the principles behind those accounting systems. What values do we want to measure? What do we value?

“Not everything that counts can be measured, not everything that can be measured counts”

William Cameron

The purpose of societies should not be just to grow in the sense of becoming materially richer. Reducing carbon emissions is a step that must be taken as soon as possible to mitigate the effects of climate change. However, it is far from sufficient to resolve the catastrophic problems we are facing today. The silence has been broken and people (even the media) have started to talk about not just climate breakdown, but also growth and consumerism. It is imperative that leaders and decision makers reconsider which value system they seek to represent and perpetuate if we are to avoid social collapse—assuming we are not already experiencing it. 

We are not seeking to advocate for a particular worldview or ontology and we certainly do not presume to have a specific prescription for what the world needs to improve the fabric of society and its connection with planet Earth. However, we believe we can revisit the history of recent societal collapses and derive some general insights. (Collapses in population are common in natural systems and have occurred many times in human societies over the last 10,000 years [4]. Moreover, even advanced societies have collapsed in the last 5,000 years [48].) 

The dramatic collapse of the Roman Empire is an example of a recent and well documented collapse of an advanced society. To reflect upon the challenges of the growth trajectory that characterizes Modern Western societies, we find it useful to examine the thoughts of the Christian philosopher Augustine, who lived at a time when the Roman Empire was rapidly declining. We find Augustine’s criticism useful because Rome shares many features of the Modern West. 

Saint Augustine criticized Rome, its values, and its outlook. In his masterpiece, “The City of God,” Saint Augustine dissected two principles of the Roman society that he contested. The Romans believed in Earthly happiness: they were optimistic engineers, confident of human ingenuity and of their ability to control nature to further their own happiness and satisfaction. In addition, the Romans believed their system was a meritocracy: they thought there was a sort of justice embedded in their social system and that success and wealth was some reflection of “inner virtue”. In a sense, Rome was the Silicon Valley of the fourth and fifth century AD. 

Augustine believed that human nature could not be perfected (which is why he invented the idea of “original sin”). We believe there is wisdom in this Augustine-like acknowledgment of human imperfection. In Saint Augustine’s writings, men could never build “The City of God”. Instead, they were condemned to live in “The City of Men.” This worldview is generous to failure, weakness, and poverty, and in a sense, it is inviting to actions of kindness, compassion, and care. It also invites us to be skeptical about power and the virtue of our rulers. 

We believe that, without having to make extreme changes, it would be beneficial for our Human and Earth system to move away from putting too much importance on things like pride and ambition, abundance and luxuriousness, speed and efficiency, individualism and competition, meritocracy, charisma and showmanship, fame, and optimism. We think that as a society we can afford to, and in fact we can be better off if we advance other principles that have been less favored by the worldview of recent dominant socio-economic powers. Principles such as sobriety and frugality, patience and forgiveness, friendship and connection, care and compassion, cooperation, discipline and responsibility, contemplation in thought and commitment in practice, realism and honesty.

“It always seems impossible until it is done”

Nelson Mandela

Climate change, ecological collapse, rising social injustice and the weakening of democracy pose a moral imperative for thinkers, political leaders, and global citizens. To shift the paradigm on development and prosperity may not be as impossible as academics tend to think [47]. If we examine the scientific tools that are out there, we can understand that climate scientists have already developed Earth models with the level of sophistication we are calling for (and our calls will become more specific in later chapters of this series). Economists are also ready to propose a new framework for thinking about the economics of climate change and the interaction between humans and nature. 

The ethical discussion of our responsibility with the planet has reached academic circles and economic models are starting to incorporate values in their architecture. We believe that unless the values at the core of any analysis are clear and consciously chosen, there will be no amount of thorough thinking, complex modeling, or honest planning that can address the social and environmental tensions humanity is facing. Before we get to any thinking, any modeling, or any planning, we have to first learn what values we have dismissed or ignored. Then, we start thinking, modeling, and planning again—very soon.

REFERENCES

 [3] Chang, H. J. (2014). Economics: the user’s guide (Vol. 1). Bloomsbury Publishing USA.

[4] Motesharrei, S., Rivas, J., Kalnay, E., Asrar, G. R., Busalacchi, A. J., Cahalan, R. F., & Hubacek, K. (2016). Modeling sustainability: population, inequality, consumption, and bidirectional coupling of the Earth and Human Systems. National Science Review, 3(4), 470-494.

[5] Ceballos, G., Ehrlich, P. R., & Dirzo, R. (2017). Biological annihilation via the ongoing

sixth mass extinction signaled by vertebrate population losses and declines. Proceedings of the National Academy of Sciences, 114(30), E6089-E6096.

[32] Coyle, D. (2014). GDP: A Brief but Affectionate History. Princeton University Press.

[36] Parrique, T., Barth, J., Briens, F., Kerschner, C., Kraus-Polk, A., Kuokkanen, A., & Spangenberg, J. H. (2019). Decoupling Debunked: Evidence and Arguments Against Green Growth as a Sole Strategy for Sustainability. European Environmental Bureau: Brussels, Belgium.

[47] Ackerman, D.F. (2010). Can we afford the future?: the economics of a warming world. Zed Books Ltd..

Talking naked 1/5: a series of essay-commentaries on climate-economy models, politics in science, environment, ethics, and society

By Laura Villegas Ortiz and Salvi Asefi-Najafabay

Should we talk about the next generation of climate-economy models? 

“We cannot solve our problems with the same thinking we used when we created them”

 Albert Einstein

Conventional models of climate and economics ignore or dismiss important aspects of the relationships between Earth and Human Systems and are therefore incapable of representing reality. These models tend to be overly optimistic and illusory but continue being popular because they are accepting of the status quo, they accept and perpetuate the underlying economic structure (i.e., the distribution of money and power in society), making it look as if the only choices that are available are those that are possible without fundamental social changes. In spite of their weaknesses, current climate-economy models continue to be popular because the results that derive from them tend to favour inaction while satisfying the decision-maker appetite for numerically-focused and detailed planning, rather than a general strategy for development that would require an inclusive, pluralistic, and lengthy conversation with their constituencies.

The motivation for writing this series is what we thought was the inadequacy of current climate-economy modeling tools to represent Human-Earth systems. We wanted to challenge the very foundations of mainstream frameworks of thought and of conventional approaches to modeling economic growth pathways. In the process of writing, that idea turned into a much deeper and profound critique of the socioeconomic and even democratic values we hold in Globalized economies. As we wrote and discussed our writings, we found that what we ultimately were calling for was structural reform among global thinkers. And we liked the idea of writing a series of short commentaries because it represented a twist the conventional format, and because it would necessarily give the reader time to reflect. As you will find later in this series, we are also calling for a lot of reflection and introspection. In short, we are not just calling for a change in thinking, but an openness to think differently and an openness to follow different, perhaps more participatory, thinking processes.

In the next few pieces we will examine how current academic approaches to represent Human and Earth Systems are unfit for calculating the real cost of climate change, the social cost of carbon, and for evaluating potential socio-economic policies to address catastrophic and rare climatic conditions; how the foundations of mainstream economic models at the heart of academic climate-economic analyses renders them incapable of representing or addressing distributional considerations and ecological collapse; and how the traditional and ethics-less meaning of prosperity has mislead global economies towards unsustainable paths of growth. Ultimately, we will examine how integrated models of climate change and economics are a symptom of what has gone wrong with the global political and economic system and why they are also inadequate.

Throughout this series, we will argue that traditional academic theoretical structures ignore important implications on two main underlying features with the current Earth-Human system: (1) growing wealth inequality, and (2) the depletion of resources and degradation of the environment that is necessary to sustain the rates of economic growth and consumption our Global societies are demanding. 

We will also argue that current academic thinking has focused on finding solutions to a set of problems so select that whatever conclusions are derived from our analyses are irrelevant for the global situation. Moreover, we will claim that searching for solutions is the wrong approach to improving the conditions of the Human and Earth Systems because we do not live in a world of problems but a world of contrasts and contradictions: contradictions that are posed by how the world system is set to function. Contradictions like that economic growth, the force that lifted people out of poverty and cured disease, can be the very thing that pushes us back into those conditions (Monbiot, 2019). Contradictions that scientists and political leaders are failing to confront. 

With this series, we will join various civic and intellectual groups across the world in calling for a platform to talk about alternative assessment methods to measure the potential future risks and costs of climate change; to question the idea that there can be growth without bounds; and to challenge the very definition of prosperity that implicitly serves as base for the complex architecture of our Human system. We will call for political and academic circles to challenge the prescription of limitless economic growth so that future analytical approaches need not favor policies that further the gap between rich and poor while allowing the heavier polluters to keep polluting at the expense of the environment and the majority of the human population—with the worst misfortunes falling on the most vulnerable groups of society. Finally, we will argue that reviewing the meaning of prosperity and how we conceive and model economic growth, particularly when considering risks and uncertainties posed by climate change, is an essential conversation to inform the updating of integrated assessment models and their accompanying scenario analyses. 

To understand the title of this mini-series, you can recall the child’s tale of “The Emperor’s New Clothes.” And you can think of this series as a cry from the crowd, similar to the naive observation of a child in this fairy tale: “Look at the king! He isn’t wearing anything at all!”

However, we want to take this series one step further than the child in the story. We want to be more than out-sider truth-tellers that point out inconvenient truths or question things others take for granted. We are aware that overly focusing on the flaws of existing systems can cause political paralysis, lead to inaction and make the problem worse. Thus, understanding that the challenge is to inspire action, we will conclude our commentary with some recommendations for devising the next generation of academic models and policy assessments.