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Abstract
The safe and just space framework devised by Raworth calls for the world’s nations to achieve key minimum thresholds in social welfare while remaining within planetary boundaries. Using data on social and biophysical indicators provided by O’Neill et al., this paper argues that it is theoretically possible to achieve a good life for all within planetary boundaries in poor nations by building on existing exemplary models and by adopting fairer distributive policies. However, the additional biophysical pressure that this entails at a global level requires that rich nations dramatically reduce their biophysical footprints by 40–50%. Extant empirical studies suggest that this degree of reduction is unlikely to be achieved solely through efforts to decouple GDP growth from environmental impact, even under highly optimistic conditions. Therefore, for rich nations to fit within the boundaries of the safe and just space will require that they abandon growth as a policy objective and shift to post-capitalist economic models.
Acknowledgments
I would like to thank Dan O’Neill for his comments on an earlier draft and for insights he shared through conversations and correspondence. Thanks also to the anonymous reviewers, whose comments significantly improved the argument. Any shortcomings are my own.
Notes
1 Rockström et al., “Planetary Boundaries”; Steffen et al., “Planetary Boundaries.”
2 Raworth, “A Safe and Just Space”; Raworth, Doughnut Economics.
3 O’Neill et al., “A Good Life for All.”
4 Per capita equivalents are applied equally across countries. O’Neill et al. do not account for whether some countries require more resource use than others for reasons beyond their control; for instance, Arctic nations may require more energy to heat their homes than tropical nations.
5 O’Neill et al., “A Good Life for All,” 88.
6 Ibid., 90.
7 Ibid., 90.
8 Leeds University, “A Good Life for All.”
9 O’Neill et al., “A Good Life for All,” 92.
10 Leeds University, “A Good Life for All.”
11 In mathematical terms, the normalised data are given by ynorm= (y − ymin) ÷ (y* − ymin), where y is the social indicator, y* is the social threshold and ymin is the lowest value for the social indicator.
12 For instance, changing the lowest actually-existing value for one of the social indicators would change its weighting in the average.
13 Franzoni and Sanchez-Ancochea, Quest for Universal Social Policy.
14 The Moldova result is dubious; there are some concerns about the validity of the biophysical data for Moldova, as it is a very small country and information on trade across its borders is difficult to verify.
15 O’Neill et al., “A Good Life for All,” 91.
16 O’Neill et al., “Supplementary Materials,” Table 3.
17 Hoy and Sumner, “Gasoline, Guns and Giveaways.”
18 Higher levels of inequality tend to increase ecological degradation. For instance, Holland et al., “Cross‐National Analysis”, find that countries with higher levels of inequality have higher levels of biodiversity loss. It is reasonable to expect that removing subsidies for fossil fuels and reallocating surplus military spending would probably reduce CO2 emissions. Redistributing income downward might have a similar effect, given that CO2 emissions are disproportionately high among the richest 10% of each nation; Chancel and Piketty, Carbon and Inequality.
19 Hickel, “True Extent of Global Poverty and Hunger.”
20 NDTV, “Poverty in India”; Prashad, “Making Poverty History.”
21 Cimadamore et al., Poverty and Millennium Development Goals.
22 Wagstaff, “Child Health on a Dollar a Day.”
23 Lahoti and Reddy, “$1.90 per Day.”
24 New Economics Foundation, “How Poor is Poor?”
25 Edward, “The Ethical Poverty Line.”
26 López-Calva and Ortiz-Juarez, “A Vulnerability Approach”; Sumner et al., “Prospects of the Poor.”
27 Kenny, “Why Ending Extreme Poverty”; Pritchett, “Who is Not Poor?”
28 Raworth, Doughnut Economics.
29 Hickel, The Divide, 253–278.
30 Dittrich et al., Green Economies; Schandl et al., “Decoupling Global Environmental Pressure”; UNEP, “Resource Efficiency.”
31 UNEP, “Resource Efficiency,” 106 ff.
32 Alexander et al., “A Critique of Decoupling.”
33 Ward et al., “Is Decoupling Possible?”
34 Anderson and Bows, “Beyond ‘Dangerous’ Climate Change.”
35 Using the equation: Rate of necessary decoupling = GDP growth rate / (1 – Rate of necessary emissions reductions).
36 Decoupling slowed from an average of 2.3% per year in the first half of the period to an average of 1.6% in the second half, according to World Bank, World Development Report 1999/2000, Databank, CO2 emissions (kg per 2010 US$GDP).
37 For concern about the viability of BECCS, see: Anderson and Peters, “The Trouble with Negative Emissions”; Larkin et al., “What if Negative Emissions Technologies Fail?”; Fuss et al., “Betting on Negative Emissions.” For concern about the ecological consequences of implementing BECCS, see: Smith et al., “Biophysical and Economic Limits”; Heck et al., “Biomass-Based Negative Emissions.”
38 Alier, “Socially Sustainable Economic De-growth”; Jackson, Prosperity without Growth; Kallis, “In Defense of Degrowth.”
39 Raworth, Doughnut Economics.
40 Ibid., 245.
41 Ibid., 251.
42 O’Neill et al., “A Good Life for All,” 92.
Additional information
Notes on contributors
Jason Hickel
Jason Hickel is an anthropologist at Goldsmiths, University of London. He is the author of a number of books, including most recently The Divide: A Brief Guide to Global Inequality and its Solutions (Penguin, 2017). He has published widely on international development, political economy and ecological economics, contributes regularly to The Guardian and Al Jazeera, serves on the Task Force on International Development for the Labour Party, and sits on the executive board of Academics Stand Against Poverty. He is a Fellow of the Royal Society of Arts.