Three Cheers for the Modest Economist

I agree with every word in Jonathan’s recent blog post.  In 1988, I entered the University of Chicago’s Ph.D. program intending to become a macro economist.  I quickly decided that the subject was too hard and that the macro data were of low quality and since there is (and was) no “control group” there was (and is) no possibility of convincingly testing hypotheses of “what causes what”.    I have lived my life as a happy applied environmental and urban economist and have always been puzzled about how macroeconomists can be so confident about the statements they make.

This is a long winded preface leading up to my discussing Reinhart and Rogoff.    They are brilliant scholars (I have never met either of them) and I doubt they have a political agenda.  Their Harvard stationary guarantees that the public will pay careful attention to what they say and will give them the benefit of the doubt with respect to the methods they use to generate their insights.   When Ivy League academics write an empirical policy piece, they must be aware about how the public will spin their results and will jump from “this is a suggestive finding but more research must be done” to “Harvard Gurus Prove That Austerity Causes Growth”.    The blogosphere has no ability to convey “uncertainty” and the researcher’s doubt about his/her own findings.  The researchers should anticipate this.   I have argued before that in this blog/twitter era that academics are aware of what is sexy and what will set off a domino effect.  Such chain reactions can be a good thing if this leads tenured academics to play less golf and write more academic stuff as they try to become the next “Lady Gaga”.

With regards to Jonathan’s point about urban empirics and weighting, he is correct but the answer depends on what is your question.  In my own empirical work, I have called weighted averages (where you weight the data by the population who lives in the tract), an exposure index because it reflects the average population density where the average person lives.