Update on the generalized method of moments

After reading all the comments here I remembered that I’ve actually written a paper on the generalized method of moments–including the bit about maximum likelihood being a special case. The basic idea is simple enough that it must have been rediscovered dozens of times by different people (sort of like the trapezoidal rule).

In our case, we were motivated to (independently) develop the (well-known, but not by me) generalized method of moments as a way of specifying an indirectly-parameterized prior distribution, rather than as a way of estimating parameters from direct data. But the math is the same.