Steve Stigler on robustness

A fine, short meditation on the history of robustness in statistics, motivated by recent work in economics.

Steve Stigler is the son of Nobel economist George Stigler, whose courses I took (and graded for) when I was a gradual student at Chicago. Steve shares his father's writing skills and his interest in intellectual history.

I took (well, audited) Steve's course on (surprise!) robust estimation shortly after I started working with Jim Heckman. It was in that course that I met statistics gradual student Nancy Clements, who ended up, at my instigation, becoming an RA for Heckman and a co-author on the 1997 Review of Economic Studies paper on heterogeneous treatment effects.

A couple of years after auditing his class, I read Steve Stigler's excellent book on The History of Statistics, which I continue to recommend to students at the start of every new econometrics course, whether graduate or undergraduate, that I teach. The book influenced the way I motivate least squares regression, which he frames in the book as a solution to the historical problem of what to do when you want to estimate a line but have more than the two data points required for identification.