Recently I have been thinking a lot about the technological improvements that humankind has seen and about what is yet to come. I am fascinated by that. However that is not the entire picture, not my entire picture. I also started my PhD candidate position in the field of Ecological Economics. And Ecological Economics is one major novel economic branch emphasizing that classical economics and politics have been too reliant on the promise of system-self-optimization (a word I guess). They have been too reliant on the belief that economics and society is going to safe itself and enter an equilibrium with its natural environment, even if nobody does explicitly address that issue. Well, that this belief was some big baloney is nowadays beyond doubt (note that 2018 is doing its best to beat all previous heat and drought records: https://www.democracynow.org/2018/7/5/headlines/heat_records_broken_globally_with_2018_among_the_hottest_years_ever).

Anyway I wanted to see whether I can re-construct a data-driven argument that demonstrates the fallacy of believing in absolute technological salvation. During that reconstruction process, for the first time, I was absolutely able to relate to degrowth economics and its arguments. Here I intend to guide you through that process.

Fortunately, there are metrics and corresponding data available nowadays to deliver such an argument. I took data by the Ecological Footprint Network which translates various impacts mankind causes to an area-wise indicator: The Ecological Footprint. So, for example they would consider how much crop-land humans use up and how much arable land is available, or how much carbon is in the air and how much can be absorbed by forest area. Even though that metric is not without critics, I made use of it for the following exercise.

In figure 1 you see two lines. The horizontal steady line is the estimated carrying capacity of the Earth, meaning it is an estimation of the resources, expressed as an area, that are available per year. The y-axis depicts that area in a unit called global hectares. The blue line however is how much we actually used per year. First one recognizes, during the whole measurement period since 1990 we are already way beyond the carrying capacity. Moreover, one sees that we are using more and more. And as of 2015 we used around 1.7 times more resources than actually available. This is expressed through the overshoot day (https://www.overshootday.org/), which you may have heard about in the news. The amount we use up you could call “impact”. Then the question is what does drive this impact? For answering that question ecological economists came up with a very coarse-grained but convenient model, the IPAT-model. IPAT stands for

Impact = Population * Affluence * Technology

The dimensional analysis of this equation would be:

Impact (gha) = Population (capita) * Affluence ($/capita) * Technology (gha/$)

The impact taken here to be expressed in gha, could be another environmentally related variable. Often the IPAT model is associated only with CO2-Emissions.

With the help of that simple equation you can literally check which factor has the most impact on the left side of the equation. In the following picture the change in each factor plus the change in impact is displayed over time, but always relative to the same base year 1990. For instance, if the growth from 1990 to 2000 was 30%, the value would show 1.3 (for 130%) and if then for the next decade 10% would have been added, the value would show 1.4 (130%+10% = 140%). One clearly can make a distinction between technology and the other two factors, population and affluence. The latter two are both rising while technology is falling. That is due to the fact that the world economy becomes more efficient, in terms of how much resources are used per value added, or gha/$. However, that increase in efficiency is not enough. Two factors are driving the impact upward: Population and Economic Affluence. The present analysis is very simplistic, nevertheless I argue that figure 2 contains a variety of high value information. First, one can spot that population growth and technology improvement basically diverge symmetrically from the 1.0 (no change) line. This symmetry leads to mutual cancellation. Then the third factor comes in, affluence, and drives the impact upward. One even is able to see the close correlation of affluence and impact, a strong indication for the fact that affluence is really the driving force behind impact.

If one then takes these historic growth rates and extrapolates them into the future one arrives at figure 3. In figure 3 I came up with three scenarios: 1) Mean scenario, 2) A high-tech scenario and 3) a degrowth scenario. For the mean scenario I just took the observed historic mean values of each driving factor and kept them constant until the year 2100. For the high-tech scenario I did the same but took the best available and observed improvement rate in technology. For the degrowth scenario I did leave the technological improvement rate at its mean again but assumed the minimum population growth rate and the minimum economic growth rate. The minimum economic growth rate was slightly below zero, so a negative number and therefore it represents an actual economic degrowth scenario.

Clearly only the degrowth scenario brings us rapidly beneath the carrying capacity. The mean scenario fails horribly and I think I do not need to comment further on what will happen if we just do business as usual. Well the high-tech scenario, standing for rapid technological improvement, seems to intersect with the carrying capacity shortly after the turn of the next century. So is technological salvation still an option? I do not think so because A) one needs to acknowledge the interval between lines. Another full century living above Earth’s capacity is probably devastating enough. And B) Just thinking shortly about how probable that technological best-case scenario is quickly yields the insight that it is not very probable.

Looking at the frequency of occurrence in historic improvement rates shows that the rate used in the high-tech scenario only occurred once (the blue bar on the very left in the figure below). Once in 25 years is not that often. Assuming that historic trend for the future, the chance is only 4% for that scenario to become reality in each respective year. Assuming technological growth rates to be independent probabilistic events (which they are not but they are also not entirely dependent) the chance of that scenario to happen is virtually zero. We should rather curb economic activity. I do not want to go back to a society without tech and without innovation at all.

But I do not want to live in a postapocalyptic wasteland either. It is time to decide which economic activities we actually need in order satisfy human needs and which ones not. This way, we may keep up living standards while finally going back to a sustainable way of life in agreement what Earth can carry…