Categories
Blogs

There is no elephant in the room

This brief study estimates the relative strengths of population and economic growth as two key drivers of total environmental pressure. In the imagined absence of planetary limits to growth, aggregate consumption in the global South catches up with consumption in the global North by 2073—adding up to almost 29 times today’s environmental pressure. However, this pressure is primarily driven by economic growth per capita, which exceeds by a factor 4.6 the effect of population growth.

Since ‘The Population Bomb’ (Ehrlich, 1968), many continue to blame environmental scarcity on overpopulation. Since ‘The Limits of Growth’ (Meadows et al., 1972), many have added that the culprit is not just overpopulation, but also ‘its terrible twin – overconsumption’ (Kopnina and Washington, 2016: 140; Bradshaw et al., 2021; Czech, 2021). The current environmental crisis supposedly escalates as a result of the impact of a growing number of poor taking on the same habits of resource exploitation as the rich. Growing levels of biophysical throughput, especially in highly populated low and lower-middle income (LLMI) countries are regarded as a writing on the wall. For example, looking at the total Ecological Footprint (EF) per national income band, LLMI countries were responsible for 33% of the total EF in 2017, compared to 29% for high income (HI) countries. LLMI countries have also increased their EF by 345% compared to 116% for HI countries (Table 1).

National income bands (based on World Bank categories)Ecological Footprint of Consumption (global hectares) in 2017Ecological Footprint of Consumption (as % of total) in 2017Change in Ecological Footprint of Consumption (as % increase) from 1961 to 2017Population in 2017Ecological Footprint of Consumption (global hectares per person) in 2017
High income73501862282911612250310386.0
Upper middle income98622301613927228177800463.5
Low & lower-middle income83190321483334534662633952.4
Table 1. Ecological Footprint (EF) per national income band (based on GFN, 2021 and WB, 2021).[i]

The argument suffers from several flaws and limitations. First, with differences in population size, the per capita EF is higher in HI countries with 6.0 global hectares per person compared to 2.4 global hectares per person in LLMI countries. Second, the rising throughput in LLMI results largely from industrial and agricultural production to supply a disproportionate amount of goods to HI countries—and to high-income areas within both HI and LLMI countries. ‘[C]onsumption of affluent households worldwide is by far the strongest determinant and the strongest accelerator of increases of global environmental and social impacts’ (Wiedmann et al., 2020: 1). This leads to an outsourcing of ecological impacts into LLMI countries and their own peripheries (Akizu-Gardoki et al., 2020; Rammelt and Gupta, 2021). EF data such as in Table 1 goes a long way but fails to account for the full range of those externalities (Van den Bergh and Grazi, 2014) which means that the allocation of resources, risks and responsibilities is likely to be even more unequal. Finally, the argument conflates the processes of population and economic growth (Hartmann 1998). The present paper therefore aims to provide a straightforward estimate of the relative strength of these drivers of the environmental crisis.

The drivers of population and consumption

The average population growth rate in the LLMI countries was 1.79% (over the period 2002-2017), which is higher than the average 0.63% rate in the HI countries (Table 2). In 2017, LLMI countries also accounted for 46% of the global population; HI countries for only 16%. Not only is population relatively greater in LLMI, so is the population growth rate.

Consumption will be measured as Gross National Income (GNI) in constant 2010$, which accounts for total income regardless of citizens and businesses are located, and for inflation to express growth in ‘real’ terms. The average economic growth rate (GNI per capita) in LLMI countries was 3.97% (2002-2017), which is also higher than the average 1.22% rate in HI countries. However, the absolute levels of consumption reveal something different. In 2017, LLMI countries accounted for only 8% of total consumption; HI countries for 65%.

We therefore see an inverse relationship between population and consumption levels for these two income bands. In 2017, an average ‘rich’ person claimed 24 times more than an average ‘poor’ person [=(65/16)/(8/46)].

National income bands (based on World Bank categories)Average % growth population 2002-2017Total population in 2017% of total population in 2017Average % growth GNI per capita 2002-2017GNI (constant 2010 US$) in 2017GNI (% of total) in 2017
High income0.63%1.23E+0916%1.22%5.22E+1365%
Upper middle income0.80%2.82E+0938%4.96%2.21E+1327%
Low & lower-middle income1.79%3.47E+0946%3.97%6.16E+128%
TOTAL 7.51E+09100% 8.05E+13100%
Table 2. Changes and levels of population and consumption (based on WB, 2021).

Comparing the drivers’ relative strengths

We see that population and economic growth rates in LLMI exceed those in HI countries. At some point, and in the imagined absence of planetary limits to growth, aggregate LLMI consumption therefore catches up with aggregate HI consumption. A relatively simple back-of-the-envelope calculation gives us the year when this happens. I assume a continuation of past population and economic growth rates from Table 2. I use these rates to extrapolate the growth of total population and average consumption for all three income bands. For each year after 2017, GNI per capita is multiplied by population size to get the projected consumption level. I find that aggregate consumption by LLMI countries catches up with consumption by HI countries by 2073 (Figure 1).

Figure 1. GNI growth for all three income bands, actual (until 2017) and projected (2017 onwards) (based on World Bank 2021).

So, which one is the main driver: population or economic growth? Both are contributing to LLMI catching up with HI by 2073, but not with an equal weight. Since LLMI comprise almost half of the world population and its population growth rate is almost three times that of HI, one might assume that population is the culprit. This would be incorrect.

Let’s take 2017 as a base year with:

            consumption = population × GNI/capita = 100

After 56 years (2017–2073):

            consumption = 100 × (1+0.0179)^56 × (1+0.0397)^56 = 100 × 2.7001 × 8.8481 = 2389.6641

The population factor therefore contributes to aggregate consumption growth by 170.01% (= 270.01%-100%). On the other hand, the average consumption factor contributes by 784.81% (= 884.81%-100%)—4.6 times the contribution from population growth. To this conclusion, I should immediately add that GNI per capita levels hide further inequalities within the income bands, between countries and between individuals (UNU-WIDER, 2021). For example, from the early 1990s to the late 2000s, household income inequality as measured by the population-weighted average level of the Gini index increased by 9% for HI countries and by 11% for LLMI countries (UNDP, 2013). This further undermines attributions of the environmental crisis to the consumption of a large and growing number of ‘poor’ people. Of course, the proposed calculation does not account for the actual biophysical claims and impacts of consumption, which I have measured using the monetary index of GNI. However, throughput and GNI are strongly correlated (Rammelt and Gupta, 2021). Based on Ecological Footprints (EF) rather than GNI, others have also concluded that consumption is the main driver, not population (Galli et al., 2012; Toth and Szigeti, 2016).

Finally, let me propose the following thought-experiment as another way to approach this: say average consumption magically stopped growing from now on (i.e., the GNI per capita growth rate drops to zero after 2017, and stays at that level), aggregate consumption by a relatively faster growing population in LLMI countries would catch up with HI consumption only by 2198. Relative differences in the population growth rates of the two income bands are therefore virtually irrelevant for the ecological crisis in the coming decades. The projected cut-off point would probably occur even later with a more realistic slowing down of population growth rates (Vollset et al., 2020). Similarly, if populations stopped growing from now on (zero growth rate), LLMI consumption would still catch up with HI consumption by 2093 (20 years later than with population growth). Again, per capita consumption growth drives the crisis.

Conclusion

Through a relatively straightforward analysis, this study supports the finding that the main driver for environmental disruption is not population growth, but average consumption growth—especially in HI countries, and to a lesser extent in LLMI countries (and to an even lesser extent by the peripheries in those countries). Commentators often refer to overpopulation as the ‘elephant in the room’ that scholars tend to ignore, or cannot see (Kopnina and Washington, 2016; Czech, 2021). However, as far as global environmental impacts are concerned, it seems we are not dealing with an elephant but with something smaller. Moreover, a focus on overpopulation, or even on the conflated forces of overpopulation plus overconsumption, brings about a not-so-subtle shift of responsibility for environmental problems to the global South (Norton, 2000; Rammelt and Boes, 2013; Fletcher et al., 2014). Resources are not primarily consumed by a fast-growing population in the global South for the satisfaction of basic needs, but by a slow-growing population in the global North for the satisfaction of boundless demands: ‘Instead of a Population Bomb we should speak about an Over-Consumption Detonator of environmental disaster’ (Toth and Szigeti, 2016: 290).

References

Akizu-Gardoki O, Wakiyama T, Wiedmann T, Bueno G, Arto I, Lenzen M et al. (2020) Hidden energy flow indicator to reflect the outsourced energy requirements of countries. Journal of Cleaner Production 278: 123827.

Bradshaw CJA, Ehrlich PR, Beattie A, Ceballos G, Crist E, Diamond J. et al. (2021) Underestimating the challenges of avoiding a ghastly future. Frontiers in Conservation Science 1(615419): 1-9.

Czech B (2021) Population Growth: The Ironic Vexer. Available at: https://steadystate.org/population-growth-the-ironic-vexer/

Ehrlich PR (1968) The population bomb. New York: Ballantine Books.

Fletcher R, Breitling J and Puleo V (2014) Barbarian hordes: the overpopulation scapegoat in international development discourse. Third World Quarterly 35(7): 1195-1215.

Galli A, Kitzes J, Niccolucci V, Wackernagel M, Wada Y and Marchettini N (2012) Assessing the global environmental consequences of economic growth through the ecological footprint: a focus on China and India. Ecological Indicators 17: 99-107.

Global Footprint Network (GFN) (2021). National Footprint and Biocapacity Accounts, 2021 Edition. Available at: http://data.footprintnetwork.org/

Hartmann B (1998) Population, environment and security: a new trinity. Environment and urbanization 10(2): 113-128.

Kopnina H and Washington H (2016) Discussing why population growth is still ignored or denied. Chinese Journal of Population Resources and Environment 14(2): 133-143.

Meadows DH, Meadows DL, Randers J and Behrens WW (1972) The Limits to Growth. London: Earth Island.

Norton BG (2000). Population and consumption: Environmental problems as problems of scale. Ethics & the Environment 5(1): 23-45.

Rammelt CF and Boes J (2013) Galtung meets Daly: A framework for addressing inequity in ecological economics. Ecological economics 93: 269-277.

Rammelt CF and Gupta J (2021) Inclusive is not an adjective, it transforms development: A post-growth interpretation of Inclusive Development. Environmental Science & Policy 124: 144-155.

Toth G and Szigeti C (2016) The historical ecological footprint: From over-population to over-consumption. Ecological Indicators 60: 283-291.

United Nations Development Programme (UNDP) (2013). Humanity Divided: Confronting Inequality in Developing Countries. UNDP: New York

United Nations University World Institute for Development Economics Research (UNU-WIDER) (2021). World Income Inequality Database – WIID. Available at: https://www.wider.unu.edu/database/wiid

Van den Bergh JCJM and Grazi F (2014) Ecological footprint policy? Land use as an environmental indicator. Journal of Industrial Ecology 18(1): 10-19.

Vollset SE, Goren E, Yuan C-W, Cao J, Smith AE, Hsiao T et al. (2020) Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study. The Lancet 396(10258): 1285-1306.

Wiedmann T, Lenzen M, Keyßer LT and Steinberger JK (2020) Scientists’ warning on affluence. Nature communications 11(1): 1-10.

World Bank (WB) (2021). World Development Indicators. Available at:https://databank.worldbank.org/source/world-development-indicators


[i] Table 1 also shows data for upper-middle income countries for the sake of completeness, but I will simplify the argument by leaving this category out.

Leave a Reply

Your email address will not be published. Required fields are marked *