In this column, NES graduate Konstantin Egorov writes about the work of academic economists. Dispelling the stereotypes, he shows that it is an extremely interesting job that can benefit from a broad knowledge base and a range of skills.
If you ask a random passerby in the street what a typical academic economist's day is like, a frequent response would refer to the fifth column and to ruining the country. If you are lucky, then instead you will hear something about pushing papers at a university department or matching debit with credit. And if you are really lucky, then the answer will be something about empty conversations about money saving instruments and forecasting the end of a crisis. But few people will come up with a description of economists who
And yet, research economists are most likely to be busy with this kind of work, if you unexpectedly stop by their office.
In fact, today, economics has become such a broad and diverse discipline that it is often difficult for economists themselves to describe in detail what their colleagues are working on. But first and foremost, all of them can be united thanks to the fact that they do research, and this is what they have in common with all people of science in general.
In his book The Birth of a Theorem, Cedric Villani perfectly describes the typical day of a researcher. In 2010, Villani was awarded the most prestigious award in mathematics, the Fields Medal, and in this book he tried to lift the veil of secrecy over how academic mathematicians work. His book is almost a diary, where he talks about his everyday life while working on nonlinear Landau damping, which eventually won him the Fields Medal.
It is probably true that Landau damping, be it linear or nonlinear, is of absolutely no interest to anyone in the world except for Villani and a few other people. But in fact, his book reads almost like a detective story, because the scholar managed to convey his emotional experience very vividly and lively. And this experience is more or less familiar to everyone.
For example, imagine that you have a Great Problem in front of you, and it seems completely unsolvable. In the meantime, a small spark of passion appears in you. Of course, it will not work to fully solve the problem, but all of a sudden, you can get somewhat closer to the solution using a certain method. A moderate hope is born in you, and you enthusiastically dive into solving the Great Problem. Obstacles that previously seemed absolutely insurmountable are actually starting to recede. Your hope grows stronger, you get carried away by the work, and now you already think that perhaps the Great Problem is not that unsolvable. Being carried away even more, you find yourself already in the future, winning the most prestigious awards for your ingenious solution…
Then suddenly you find yourself at a dead end: even though you have bypassed the first obstacles, you can't make any further progress. Moreover, the obstacles that you overcame and that seemed to you to be part of the Problem actually turned out to be, of course, very related, but in fact completely different. And therefore, you have not made any progress with the initial Great Problem. You are, of course, terribly upset that you have wasted so much time and effort. You begin to fear that maybe the last years of your life have also passed in vain and nothing will come out of them in the end.
Nevertheless, gradually you calm down a little. You are still facing the same Great Problem, with the difference that now you certainly know from your own experience that it is absolutely insolvable. And yet, for some reason, some passion is born in you again, which over time becomes more and more like an obsession. It seems to you that there is still a small chance that it will be possible to approach the Problem with a new idea... and everything starts over!
So if we look into the office of research economists, then, of course, on top of other things, we will see how they write code, derive formulas, plan experiments and collect data. But if we were also able to follow their feelings, then most likely we would have caught them at one of the stages of this emotional rollercoaster, going from complete despair and sadness, through hope and passion turning into obsession, to complete delight and the feeling that nothing is impossible anymore. And the longer and more difficult the work on the Great Problem is, the more delight and fascination in the end there is, of course.
Such feelings are certainly familiar to many. People who begin to renovate an apartment or build a house, after some time notice that others have begun to consider them simply obsessed. Every athlete or musician has experienced a feeling of great delight when for the first time they manage to make a move or play a tune that they have been working hard on for many months. Academic economists experience all the same emotions when they work on their data and formulas.
Of course, it's not about the data and formulas themselves. After all, people who are obsessed with formulas for the sake of formulas, for the most part, become mathematicians. For economists, as a rule, a Great Problem relates to a better understanding of how people make decisions. And this makes them constantly master new tools and study more and more questions from various spheres of human life.
Just a few generations ago, in the middle of the last century, some economists were already proving theorems and working with data, but a much more typical work was argumentation only with the help of words. Since then, the profession has changed a lot. First, most economists mastered some branches of math, which turned out to be the very new method with which researchers could approach their Great Problem. Then, with the advent of computers, many learned programming and coding, because this was the only way to work with large bodies of data and find numerical solutions to complex mathematical models. Sometime later, economists began to introduce and run experiments, and now they continue to look for new tools for their work.
For example, Melissa Dell and her team recently wrote a Python library that improves text recognition based on images. Thus, they have developed new software that is not directly related to economics in any way. Prior to the release of the library, Dell was not working on document image analysis, as one might think. Her academic interests were related to economic growth and analysis of institutions, often based on historical data. Automatic scanning of text from paper archives instead of manual typing allowed her to increase the amount of information that she and her team could analyze by orders of magnitude. Similarly, other economists continue to master new tools for themselves in pursuit of a solution for their Great Problem, which they otherwise cannot deal with.
Questions that economists ask trying to better understand how people make decisions also change over time. Just like it was in the middle of the past century, they are still answering questions that have since become stereotypical: what is the best instrument to keep money in, why recessions are happening, etc. However, economists are now increasingly working on new topics. Here are just a few examples:
Thus, the typical day of academic economists, on the one hand, constantly changes, and on the other hand, it remains unchanged. Just as it was happening before, economists today are eagerly chasing after a better understanding of how people make decisions. But nowadays, they often have to employ completely different tools than a few generations ago. And of course, it is quite difficult to predict what the work of economists will consist of in several generations.