In reply to Steve Tadelis.

Thanks for the note Steve. You make an interesting point about applied microeconomists. I wholeheartedly agree with you that the applied micro skill set is tailor-made for causal modeling (I have started calling this 'explanatory modeling' to combat the 'predictive modeling' only message from the pure data mining crowd).

At a recent version of this presentation a student actually posed the question, "what field should I pursue to keep my corporate options open?" I struggled to guide them toward micro or macro. Here is why I struggled. I believe the macroeconomic skill set is immediately associated with a 'forecasting' skill set. This is something that most organizations need and can quickly make the association that the skill sets align. Of course, the odd thing is that most companies don't utilize the type of sophisticated forecasting models that macroeconomists have in their toolkit (exponential smoothing and ARMA models typically suffice).

Then consider the applied microeconomist. The perfect skill set for churn modeling, credit modeling, insurance rate making and a slew of other common tasks. However, I don't think the skill set of an applied microeconomist screams 'predictive modeling' in a way that companies can relate to.

So, long story short, my answer to the student was that micro will probably give you a richer set of useful skills but that macro might be easier to signal your interest in corporate work. Do you agree? Is this something you have passed along to students?