The title suggests a meanwhile well-known discussion of one of the most common economic issues. But please do not expect an article about financial markets, booms, busts, and crashes. Instead the title refers to an economist’s perspective after finishing his or her master’s degree.
At this point in our career I am looking back at about five to six years of study. Large parts of the curriculum were rooted in neoclassical theory or at least dealt with fully rational and well informed representative agents maximizing their utility. Of course, I was sceptical. Until I started studying the term utility did not play such a huge role in my conversations and considerations. Many of my past decisions did not seem very rational. And with regard to information so far I had been taught that the most important thing to know is that I know nothing. So these representative agents I now had to deal with did not seem to represent guys like me or anyone I knew.
However, I was just a student and I was here to learn. So I tried to get used to the approximation called homo oeconomicus and analysed a world that did not seem to be the one I knew, but appeared to be fascinating in its own way. A world that was distinctively describable in clear mathematical terms and thereby allowed me to derive general solutions even to big problems. A world without doubts but with reliable and stable paths towards optimality. Within this world of assumptions and equations I suddenly even seemed to be able to approach the once sceptically seen approximation of my own self – fully rational and well informed.
After some time it therefore certainly felt good to coruscate in solving artificial problems given by exams. Yet, I did not have lost touch with reality and kept asking how to deal with the lack of practical applicability of all our analytically derived solutions. An answer given by a Nobel prize winner was that any lack of applicability arises just because the real world has not sufficiently managed to approach our assumptions yet. This answer was not really satisfying. First, the responsibility of an economist as a social scientist cannot end at conclusions about how the world should have been in order to meet the predictions of a model. Secondly, the world seemed way too far from some of the assumptions used to build this model. Thirdly, I was not in a position to move the world even a tiny bit towards what the assumptions had implied. And last but not least, with regard to some assumptions such movement even did not seem desirable to me.
No wonder therefore that I hopefully longed for the fragments of game theory and institutional economics waiting for us in later semesters. Dealing with bounded rationality, incomplete and asymmetric information, imperfect competition, strategic behaviour and even things like altruism and reciprocity these strands finally seemed to work on dropping some of the assumptions I have seen that critical for so long. What I was not supposed to drop in the course of my study, however, was the analytical framework, the search for general solutions and the therefore necessary simplifications. Five to six years later, I still found myself dealing with representative agents performing mathematical operations, a huge part of the world’s population is not even capable of.
To be clear, I appreciated the theoretical value of analysing a purely materialistic world populated by identical robots following the sacrificed rule of optimization. I still do. Just like I appreciate several other, partly refining, approaches taught in the course of my study. I do so because I appreciate science as a process of trial and error in which both, trials and errors, may be of value. It is the lack of appreciation for its own errors that I complain about when it comes to the economic discipline. It is this hesitant accounting for tiny flaws in an apart from that still idealizing model of an optimizing world, while the real world partly rather occurs to be the other way around: messing up due to people and manmade institutions flawed to the core with a tiny animus for optimality. One has to excuse my exaggeration, but remarkably large and influential parts of the economic discipline seem to consider the errors in hitherto existing approaches only to an extent that does not require a renunciation from the obsession with purely analytical frameworks and general solutions derived therein. Maybe some of us do so because mathematical sophistication makes us feel like natural scientists and technical experts. The bundle of assumptions our mathematical sophistication depends on, though, largely reduces our expertise to knowledge about a bubble we have been creating for decades. When it comes to reality, one of our most remarkable skills just seems to be denial. Equipped with our models we may feel like engineers, but often all we are engineering is a bundle of beliefs – frequently wronged, but bullheadedly preached.
A young economist like me therefore has to make a crucial decision. Either, I am able to accept things just like they are, try to sell what I have learned and ride the bubble for a few more years in order to achieve the ultimate goal: an extraordinary long publication list and a perpetual contract. Or I am simply not able to cotton up to this type of economics and pursue my own trials and errors independent of the expected lack of appreciation.
When I decided to study economics in the first place, I did that because of my interest in the economic system and not because of the returns achievable as an economist. This has not changed at all. So, if reaching out of the bubble means to risk my personal bust, crash and crisis with regard to the common type of a career, I self-confidently will do so. It remains the right and maybe even the utility maximizing path for a type of scientist I want to be. And despite our curriculum often suggests that economics are deadlocked, I meanwhile know that there are still a lot of us trying to change tack. So do not fear a crisis outside the bubble, but look forward to the downturn of beliefs you are not able to share.