For his IBCP Sustainability group, Mr. Corbin asked students to write an article for 'The Economist' evaluating the role of GDP/ GNI as a measure of a county's success
and recommending alternative indicators which might be more sustainable.
What do you think?
We encourage Econ/ Geo/ Business/ Sustainability classes to discuss these ideas in their classes and respond to them in the comment section below!
By Greta ADRIAN
Model of Economics
We are currently ruled by the neoclassical/classical model of economics,
where the prosperity of an economy is measured as the economic growth of a
country. Meanwhile an environmental/ecological model of economics
focuses on nature and how it cannot grow infinitely. It acknowledges this and
therefore works by keeping the economy working at a stable economic level.
Our current model is flawed as it believes economic growth can continue
forever. Thanks to research we have been able to see that this is not true and
we are starting to deplete the amount of resources we have come to depend
on to live.
The classical model is a “macroeconomics” concept, founded by Adam
Smith, who is known as the father of modern economics. This concept is
where the economy is viewed as a whole, instead of the behavior of
individuals, firms, or markets. Meanwhile the neoclassical model is
“microeconomics”, focused on individual markets within an economy. Both
these models have one thing is common; they believe prosperity is achieved
through economic growth and believe it can continue forever. Supporters of
the neoclassical model think that when resources run out, incentives for
technological change will save the day. This is related to the Boserup theory,
which believes humans will never run out of resources as we will always find
other means of sustaining ourselves. The neoclassical model additionally aligns with technocentricism. This is a value systems which has complete
faith in technology, firmly believing humans have control over nature.
These models cannot be disregarded as completely useless, as they have
been working for the past few hundred years. Economic growth has helped
increase the prosperity of economies when they needed help. The issue is
that because of economic growth, our need for resources has increased
drastically which has created a deficit in resources.
On the other hand, environmental economics is a subset of the
neoclassical model. This model considers services from nature like flood
prevention, water filtration, pollination, etc. and assigns it a monetary value.
These figures are then incorporated into the market. This helps pose the
question “Can we afford not to conserve and protect the natural world?”.
The ecological model sees macroeconomics as a subsystem within the
biosphere which it depends on, therefore does not treat nature as a type of
waste disposal facility. It is now more relevant in a heavily populated world,
7.3 billion in 2018, since there are no longer limitless discoveries and
resources. This model acknowledges that indefinite growth is impossible and
so aims to keep the economy at a ‘steady state equilibrium’.
The current method of measuring a country’s prosperity, GDP, is also
flawed as it does not take into account wellbeing, only calculates a country’s
economic activity. An example of the problem with GDP is Alaska, who
suffered a massive oil spill in 1989. Yet the GDP increased, due to work effort
needed to fix the disaster. Should our environment really have to suffer to
keep our economy’s prosperity?
It could be replaced by Index of Sustainable Economic Welfare (ISEW) or
the Genuine Progress Indicator (GPI).
These methods incorporate well being of people to calculate how well a country is doing.
To conclude, our economic
model is clearly flawed, and will
not be able to continue to provide for future generations. The
environmental/ecological models clearly are a good alternative, which will
allow economies to continue without having to later suffer the consequences.
By Komron ARIPOV
Hackathon: an event, typically lasting several days, in which a large number of people meet to engage in collaborative computer programming.
Since the start of 9th grade, I was interested to learn more about Machine Learning and Artificial Intelligence. The articles written on this website were not only articles, but also an initiative I’ve taken to learn more about this field. As it happened, Python, the programming language of my choice, has an enormous community of users interested in this exact same field.
So in an adventure to learn something I couldn’t find courses for at CDL, nor any institution nearby (or so I thought), my eyes have turned towards Massive Open Online Courses (MOOCs). While they offered very good material, they were best suited for the more older students who had a strong background in statistics, calculus and linear algebra. The thought of having to also learn all of the previously mentioned mathematics sounded interesting, yet would take the effort I never had.
That is until I stumbled upon courses offered by the EPFL Extension School, owned by the Swiss Federal Institute of Technology. The courses were opened for people from any age group to sign up, and the platform allowed the ability to talk to teachers when dealing with a problem and still be have most of the material online. It was also self-paced, and very flexible, so I sent them an email showing my interest in the course.
After about a week, I got a reply from Laura Downhower, the executive director of the EPFL Extension School, inviting me to join them at an SRG hosted hackathon with a topic: “Media and Artificial Intelligence”. I was thrilled! The absences board gave the permission to be absent from school for two days, and the ticket was sitting in my backpack.
So, on a Thursday morning, when a snowstorm hit Geneva, I came 20 minutes late to the event, but still made it on time as others were even more late. There were croissants and drinks, while everyone in the room were introducing themselves. At that point, I was more than sure that I was the youngest participant and gave the room a quick glance to find the Extension School. They were sitting at one table, to which I walked and introduced myself.
At 10:00 the ideas for projects were pitched by a couple of volunteers and half an hour was given so others join the people with the pitches to form teams. Unsurprisingly, I joined the team with two teachers from the Extension School who taught Applied Machine Learning. The rest of the afternoon was spent working on our pitch: “Understanding Switzerland through its news”. We toyed around with the SRG database of news articles and videos, and found some very interesting patterns and structures.
The next morning, on 2nd of March we finished off with a machine learning algorithm and made nice graphs of the data that we explored. We were the first team to present our idea in Geneva, following a transmission of the same exact event from Zurich.
Sadly, our team didn’t win, but the experience, the people I’ve met and the knowledge I’ve gained will forever stay with me.
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