Introducing the macroeconomics of the climate crisis

Dr Gwiazdowski was runner-up in the Economics Network's Best New Lecturer Award for 2019.

Introduction

This case study is designed to provide a basic introduction to the macroeconomics of the climate crisis on a post-A-level or equivalent macroeconomics module. Generally speaking, climate change is not compulsory learning in most introductory macroeconomic textbooks; however, knowledge of the topic is likely to be crucial for future professional economists, policy economists, and citizens.

The case study requires students to have a basic understanding of a simple, non-technical version of the Solow growth model with technological progress. It is therefore suitable for students on single- or joint-honours economics degrees with only a basic background in mathematics for economics. The goal of this case study is to provide an introduction to the facts of climate change, outline a simple macroeconomic model of climate change, and ask students to critically discuss different solutions to the climate crisis.

The session itself can fit into a 45-minute teaching slot.

Preparation beforehand for staff and students

To understand the Solow growth model, following some preliminary equations and conceptual explanations, students will be left with two equations and three curves. These are the equations for the level of output per effective worker (y):

and an equation describing the dynamics of the capital stock:

The change in the capital stocks depends on the difference between actual investment () and required investment . All equations are expressed in effective-labour terms.

Using this model, students are taught fundamental elements of the growth process. This process includes how and why a model economy converges to its steady-state growth path, the behaviour of the economy in the steady state, and the effect of a change in the savings rate in the short run and the long run.

One exercise that is fundamentally important to the case study is for students to learn the effect of a change in the exogenous growth rate of technology. This is generally taught as part of the preliminary material the week before the case study is taught so that students are familiar with this exercise when it is used.

The explanation goes as follows. Consider an economy operating at its steady-state level of capital per effective worker. In this economy, output per effective worker will be stable, but aggregate output (Y) will grow at the exogenous rate of technological progress, g_A, plus the exogenous rate of population growth, g_N. This is represented by point E₁ on the left hand side of Figure 1 and the black line up to t₁ on the right hand side of the figure. If g_A rises, this will increase the slope of the RI curve. At the previous equilibrium, the AI line is now below the new RI line, therefore the capital stock per effective worker will decline, initially quickly but then at a slower and slower rate until the new equilibrium is reached. The new steady state is at point E₂. In the right panel, the blue dashed line represents the transition to the new steady state between t₁ and t₂, and the red line represents the new faster growth of aggregate output.

Figure 1 – A rise in the rate of exogenous technological progress

Teaching the climate crisis using a non-technical Solow growth model

To begin the session on the climate crisis, we assume that students are already familiar with the “old” stylised facts of economic growth. They understand that there are advanced economies, fast-growing emerging economies, transition economies, and less-developed economies. In terms of extreme poverty and the total population on the planet some progress has been made. However, broadly speaking there has also been a strong correlation between economic growth and CO2 emissions and approximately as much CO2 has been emitted in the past three decades as in the two centuries of economic growth that came before.

When introducing the facts of climate change, it is also helpful for students to understand key economic concepts related to the macroeconomics of the climate crisis. This includes climate change as a market failure and an issue of both intra- and inter-generational inequality (see Tsigaris and Wood 2016). The final part of the empirical introduction outlines other problems of the global environment, specifically that carbon emissions are not the only problem e.g. overuse of fertilisers, loss of forested land, and loss of biodiversity (Raworth 2017).

To teach the case study a few strong but simple assumptions are needed to adapt the standard Solow growth model. First, we assume that exogenous technological growth is either “dirty” or “clean”:

g_A = βg_A,dirty + (1 – β)g_A,clean.

For simplicity, we also assume that all growth up to today has been dirty. We then assume that output using dirty technology is directly proportional to emissions (E_t): Y_t,dirty = E_t. To simplify the analysis we also assume population growth is zero (Rosling 2015), that emissions today are currently above some sustainable level, that there are no emissions from “clean” technology, and that “clean” and “dirty” technology are perfect substitutes (see Acemoglu et al. (2012) for a discussion). Using these assumptions we introduce the “business as usual” scenario of growth and climate change. Without any intervention in the economy, the economy will grow at rate g_A,dirty, emissions will continue to rise as economic growth continues and the likely outcome is environmental disaster with rising sea levels, mass population displacement, more frequent extreme weather events, the spread of new infectious diseases, and “tail risks” that we cannot foresee (consider the red output line in Figure 1 going upwards over time forever).

To address this potential nightmare scenario, we consider two response scenarios that do not presume the existence of clean technological solutions to the climate crisis. Scenario 1 is to stop technological progress (g_A = 0), intuition – you cannot ever get a new upgraded mobile phone, laptop, car etc. Alternatively, Scenario 2 is to reverse technological progress until emissions return to sustainable levels (g_A < 0), intuition – we no longer use planes but takes ships across the ocean, we no longer use cars but walk, we replace all smart phones with a Nokia 3210 etc. Once sustainable levels of emissions are reached, we then allow no new technological progress (see Figure 2).

Figure 2 – Climate crisis scenarios without “clean” technology

We now assume the existence of clean technology that has no emissions. We assume that as policymakers we can choose the value of β, and 0 < β < 1. In Scenario 3, as emissions are already above sustainable levels, we set β = 0. In this scenario the growth of output continues as before except that all new growth uses “clean” technology (solid purple line in Figure 3) and the “dirty” economy stagnates (dashed purple line). Alternatively, in Scenario 4 we again set β = 0 but now we also set g_A,dirty < 0. Exogenous technological growth continues at the same rate, but some new, clean discoveries are used to replace old, dirty technology to reduce existing emissions. The rate of new, clean technological growth is lower than before but there is still some rise in output (solid green line). Output using dirty technology declines as this is replaced by new, clean technology (dashed green line). This process continues until output using dirty technology, therefore emissions, declines to the safe emissions level. Then all of our exogenous technological progress is again dedicated to new, clean growth and the economy can grow as fast as before (not drawn).

Figure 3 – Climate crisis scenarios with “clean” technology

Summary

This case study aims to incorporate analysis of the climate crisis within a familiar standard model in a core macroeconomics module and in a non-technical manner. In terms of learning outcomes, students will be expected to understand the stylised facts of economic growth and the climate crisis, they should be able to critically evaluate the additional assumptions appended to the standard Solow growth model, and they should understand the costs and benefits of the four proposed scenarios. For example, only two scenarios return emissions to sustainable levels. Scenario 2 is the “de-growth” scenario. While successful in terms of reducing emissions, students are asked to consider the impact this scenario would have on societal norms and expectations and the change in culture and institutions this solution may require to avoid severe political unrest (we are all a lot poorer and today billions of people have still not reached a standard of living most would deem acceptable).

Scenario four appears optimal because economic growth can continue, albeit at a slower pace initially. However, students are asked to consider the issue of the strong assumption that “clean” and “dirty” technology has perfect substitutability. They are also asked to consider the high levels of taxes and subsidies that would be required for businesses to make such a dramatic shift towards green solutions almost overnight. They are also asked to consider the wisdom of the final steady-state equilibrium in scenario 4 — infinite growth on a finite planet! Students appear to appreciate me suggesting I have no idea what an optimal solution is and that it is up to their generation to help shape their future.

References and further reading

Acemoglu, Daron, Phillippe Aghion, Leonardo Bursztyn, and David Hemous. 2012. “The Environment and Directed Technical Change,” American Economic Review 102(1): 131-166. https://doi.org/10.1257/aer.102.1.131

Blanchard, O., Amighini A. and Giavazzi F. 2017. Macroeconomics: a European perspective 3rd Edition, New York: Pearson (Chapters 10-12)

Raworth, Kate. 2017. Doughnut economics, London: Random House Business Books

Rosling, Hans. 2015. "Why the world population won’t exceed 11 billion" Video lecture on YouTube

Tsigaris, Panagiotis and Joel Wood. 2016. “A simple climate-Solow model for introducing economics of climate change to undergraduate students,” International Review of Economics Education 23: 65-81. https://doi.org/10.1016/j.iree.2016.06.002

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