The appallingly bad neoclassical economics of climate change

ABSTRACT

Forecasts by economists of the economic damage from climate change have been notably sanguine, compared to warnings by scientists about damage to the biosphere. This is because economists made their own predictions of damages, using three spurious methods: assuming that about 90% of GDP will be unaffected by climate change, because it happens indoors; using the relationship between temperature and GDP today as a proxy for the impact of global warming over time; and using surveys that diluted extreme warnings from scientists with optimistic expectations from economists. Nordhaus has misrepresented the scientific literature to justify the using a smooth function to describe the damage to GDP from climate change. Correcting for these errors makes it feasible that the economic damages from climate change are at least an order of magnitude worse than forecast by economists, and may be so great as to threaten the survival of human civilization.

KEYWORDS:

• Climate change
• neoclassical economics
• William Nordhaus

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 It is reproduced below as Table A1 in the Appendix, with the addition of Nordhaus (1991), additional empirical studies located by Nordhaus and Moffat (2017), and one additional methodology.

2 Perhaps this was a concession to the fact that many mines today are open cut. In 1993, Nordhaus specifically noted that ‘underground mining’ was safe from climate change: ‘In reality, most of the U.S. economy has little direct interaction with climate … More generally, underground mining, most services, communications, and manufacturing are sectors likely to be largely unaffected by climate change—sectors that comprise around 85 percent of GDP’ (Nordhaus, 1993, p. 15). That said, none of the ‘enumeration’ studies actually considered the impact of climate change on mining—see Table A1.

3 This is in fact very close to the coefficient Nordhaus used in his damage function in 1999, and higher than he has used since 2008, as discussed on page 14.

4 This data is an amalgam of average temperature by State from 1971 to 2000, real GDP in 2000, and population in 2010. However, similar results would apply with a more coherent set of data, and the regression result derived from it is for illustration purposes only.

5 For this same reason, I do not consider the use of Computable General Equilibrium models to generate numbers for calibrating IAMs, the fourth technique listed by the IPCC in (Arent et al., 2014a, p. SM10-4).

6 The column ‘Critical values’ in Lenton, Held et al.’s Table 1 relates to whether there is a known empirical magnitude that will trigger the tipping point, not whether the tipping point itself is of critical significance. The symbol next to the word ‘Unidentified’, which is used to describe Arctic summer sea ice, states that ‘Meaning theory, model results, or paleo-data suggest the existence of a critical threshold but a numerical value is lacking in the literature’ (Lenton et al., 2008, p. 1788).

7 I use a raw linear regression here just to emphasisz how incorrect it is for Neoclassicals to neglect the impact of energy when discussing climate change. A log-log regression, which is more suitable for forward or backward extrapolation of this relationship, has an even higher correlation coefficient of 0.998. An appropriate nonlinear relation should be used in any realistic model of long term change.

8 The correlation with non-smoothed data is still extremely high at 0.958.

9 This and a later Twitter exchange cited in this paper have been slightly edited for tone and to correct spelling mistakes.

10 Trenberth estimates the mass of the atmosphere at $513.7\times {10}^{18}$ kilograms (Trenberth, 1981, p. 5238). Raising the temperature of one kilogram of air by 1°C requires 1004 joules of energy: the product is $5.158\times {10}^{22}$ joules, or 51,575 million Terajoules. 1 Hiroshima bomb is equivalent to 60 Terajoules (https://www.justintools.com/unit-conversion/energy.php?k1=hiroshima-bomb-explosion&k2=terajoules). The planet’s area is 510 million square kilometres. These calculations do not factor in the energy needed to raise average temperature of the oceans as well, which global warming is also doing, though more slowly. Their mass is about 250 times that of the atmosphere.

11 Nordhaus does use a high discount rate, and criticized Stern for using a much lower one. However, the primary reason Nordhaus uses a high rate is that, in his words, ‘with the low interest rate, the relatively small damages in the next two centuries get overwhelmed by the high damages over the centuries and millennia that follow 2200.’ (Nordhaus, 2007, p. 202. Emphasis added). As I show here, the key weakness of his work is not the discount rate, but the conclusion that there will be ‘relatively small damages in the next two centuries’.

12 DICE stands for ‘Dynamic, Integrated Climate & Economics’. It is dynamic and integrated in name only.

13 DeCanio does a very good job on this topic, though his critique applies equally well to applying Neoclassical ‘representative agent’ models to any macroeconomic issue, let alone to climate change. Other endemic weaknesses of this analysis include the application of cost-benefit analysis rather than the ‘Precautionary Principle’ to such an uncertain topic as climate change, and the poor handling of uncertainty by Neoclassical economics in general.

Additional information

Notes on contributors

Steve Keen

Steve Keen is a Distinguished Research Fellow at the Institute for Strategy, Resilience and Security, University College London (www.isrs.org.uk); specialist on Minsky’s Financial Instability Hypothesis (Keen, 1995; Keen, 2017); author of Debunking Economics (Keen, 2011); blogs at https://www.patreon.com/ProfSteveKeen [email protected]; [email protected].