BONUS BALTICAPP - Race Against Eutrophication Blog
Theoretical vs. empirical/applied approach
It has become apparent for me recently that there is a great dividing between theoretical and empirical/applied approaches in science. Particularly in economics this dividing seems to be very strict. This was made clear to me when I started an Advanced Econometrics course in PhD program for Economics this fall. We were told that this course is purely theoretical and if there are anyone interested more in applied side of things they may consider hard if the course is too difficult for them. We were told that particularly PhD students in so called applied sciences should probably dismiss. I decided to not to dismiss and it was a good call since so far studies have been going well, although I’m definitely an applied researcher and as such not a “real” researcher, as it was made clear to us.
Ever since I’ve been thinking about this division and classification of the researchers. In my opinion theoretical and applied sides are both rather important. It is clear that there has to be solid theory behind an applied work. But it appears equally clear that good theory is worth of nothing if there is no empirical evidence to support the theory or if there is no application for the theory. In addition, new ideas for theory development may originate form surprising empirical findings. Also, applied work may show that the theory does not hold in practice. Therefore, it seems that there is justification for both sides and those can actually benefit from each other.
Thus, it seems rather counterintuitive that theoretical researchers don’t give much appreciation for applied researchers. In econometrics and statistics this might have something to do with the fact that the methods are often applied in a bad manner and important theoretical aspects are ignored. If theoretical researcher reads such empirical paper that is published in a journal, it is understandable that the theoretical researcher becomes upset and feels that his/hers work is not understood.
In many cases and in many papers statistics are done wrong. The problem might be that statistical and econometrics courses are typically either strictly theoretical or strictly applied. Then we learn advanced theoretical things in one course and some examples and some coding on another course. The problem is that the connection between theory and the empirical application might be left incomplete, to say at least. For example, in our Advanced Econometrics course we struggle mostly with the proofs of the theorems. We have learned how to derive distributions of the test statistics and to show the asymptotic consistency of the parameter. But how to apply these learnings with the real data? In the other hand, I took another course that was purely applied. There we were given some data and some codes and examples, but the theory behind the examples was not discussed at all. A good course would really combine these two worlds, because clearly those are not separate.
I don’t how is the situation in other fields, but at least in Economics I see an opportunity for improvement in how theoretical and applied sides of science should be thought. This would narrow the gap between the field work and work that is done in theory labs. It would probably decrease the hatred between the deputies of the sides. Also the books should entertain the theoretical justifications and empirical applications to really show the students/researchers how the theory is applied correctly to real data.Best regards, Matti Sihvonen