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The Post-growth Group at UiB

This post looks at the new student led group looking at the socioeconomic concepts of post-growth and degrowth and how they relate to System Dynamics. It provides insight on how students can engage more deeply in the System Dynamics methodology outside of the classroom and relate it to issues of sustainability, a major focus for many students in this program.

Loop Diagram
Causal Loop Diagram from the Post-growth Group at System Dynamics UiB.
Filipe Medeiros


As the semester continues and we all dive more deeply into our studies, I always appreciate the moments where we as students can escape the normal routines of school. While this does include going hiking or taking small trips in the surrounding Bergen area, I also find myself excited by learning about new applications where I can use System Dynamics. I know, call me nerdy, but I find it important to understand how this methodology is used to tackle a wide range of complex problems. While my classes do a great job covering a large extent of that, it still is helpful to use other opportunities to learn about System Dynamics as the field is constantly changing. As such, when the opportunity presented itself to learn how to use System Dynamics within the concepts of post-growth and degrowth, I was curious as to what these ideas meant and how System Dynamics relate to them.

My fellow student and friend Filipe Medeiros introduced me to these concepts. He has done research both in his previous studies and independently in trying to understand how our global economy could work within a more sustainable and equitable framework. He came to System Dynamics in part to further expand upon these new concepts. Post-growth and degrowth are relatively new political movements backed by socio-economic theories and discussions that are gaining traction within academia. From my understanding, post-growth indicates a theory that acknowledges the limitations of our Earth and economic systems. The current economic structures can only provide new benefits up to a certain limit. We must look for other techniques to increase human and environmental well-being. Similarly, degrowth asks us to find ways to shrink the global economy in order to put well-being ahead of profit. This means finding new ways of measuring economic success, such as alternatives to GDP. It also argues for shifting capital from traditionally wealthy countries in the global north to less developed countries in the global south. While I am still learning about these topics, I truly appreciate Filipe’s courage to challenge my own and my classmates’ preconceived ideas of economic structure. I am also grateful for the way my peers and my professors have responded. While we do not always agree and we do challenge each other, this initial idea of learning about new socio-economic theories has become a monthly discussion group where students and professors come together in what we call the Post-Growth Group.

While these ideas are interesting on their own, a core purpose of introducing these theories is to understand how they relate to System Dynamics. From Filipe’s perspective, these socio-economic ideas are similar to System Dynamics in that they put a strong emphasis on holistic thinking. They do not look at problems statically. These theories acknowledge that problems change over time. In response, we must find solutions that can adapt alongside these changing problems. Meanwhile, these theories look to identify causal connections that are previously overlooked. With these similarities, it becomes clear that System Dynamics can be used to measure the causal relationships between variables and then measure how different policies can lead to the goal of a shrinking and more sustainable economy.

To put this in more perspective, the first issue that this group is currently discussing is the impact of emissions from the aviation industry. With it being one of the most unequally polluting industries, a post-growth perspective looks to find ways to mitigate air travel through human behavioral change. Our group uses System Dynamics to model and identify drivers for this behavior. We are currently building a Causal Loop Diagram (CLD) to help us visualize how and why people choose to fly and the consequences of that. This is taking the course over multiple sessions, but it has already become an exciting combination of theory and methodology. It has provided valuable insight into how System Dynamics can be used.

This is really exciting for me as I could apply what I am learning in class in a more casual setting. I was able to lead the first step of building our CLD by being the leader of a Group Model Building session. It was a new skill and technique to gather a group of people and ask them to describe and collaborate what they saw as major drivers of aviation emissions. It was up to us to then find common themes and causal links. We found that many people fly to simply travel. Others identified that decreasing the cost of tickets makes it much more of an incentive to fly. Others recognized how wealth disparities cause certain populations to fly more. Altogether, I was able to help shift the conversation so that we could collectively build a model and find connections between variables.

Right now, our model can be seen under the title above. In this model we identified the absolute emissions as a core variable which has a behavior of exponential growth up until now. It should be noted we focused on commercial flying as this is the biggest driver of aviation emissions. While we have multiple variables, I will specify the three loops identified during our first Group Model Building session. We have a reinforcing loop between the variables of mass tourism and number of flights. Using this example, a reinforcing loop indicates that the combination of effects between variables is strengthened, or reinforced, towards one direction. In this instance, with the rise of mass tourism, there are more flights which further increases mass tourism as more people are able and willing to travel. With more flights, emissions increase.

Another reinforcing loop can be seen between the variables of mass tourism, GDP, and the affordability of flying. With the rise of mass tourism, GDP grows as tourism causes more economic activity, which then causes the affordability of flying to increase. More people have the money to fly. This then causes tourism to increase further, leading to more flights and, thus, more emissions.

We also created a balancing loop which represents a potential policy input to our existing CLD. A balancing loop represents how the effects of a loop over time causes limits or constraints. With the rise of emissions, a policy that introduces a true cost of flying through something such as a carbon tax would decrease the affordability of flying. As flying grows less affordable, or more expensive, the number of flights and emissions would decrease. This policy represents a point of discussion and requires further exploration as in theory this policy would help limit emissions. Yet, the lack of political will to do so forces us to consider if this could be a valid loop to add to our model.

With this being the first iteration of the model. I hope to share more as we continue to flush out new ideas. This is an ever evolving project allowing us to explore our growing knowledge in System Dynamics in fields that are unique and challenge our preconceived ideas on how the world works. Moving forward, we are looking to identify more ways in which policy might be able to mitigate some of the effects of aviation emissions and further post-growth and degrowth concepts within the aviation industry.