You think it's impossible that these two topics are related? Not so. Imagine my delight when I came upon the following quote, embedded in a dry old journal article published in 1983, by The Journal of Economic Review.
"Methodology, like sex, is better demonstrated than discussed, though often better anticipated than experienced" (Leamer, 1983, p. 41).
I think it's poetic.
Although Lerner wrote this paper in 1983 (based on a public lecture presented at the University of Toronto in 1982), it is crammed full of wisdom relative to current events in applied health research. Take, for one example, the presumed belief in the relative power of experimental over nonexperimental data to produce credible inferences. Customary assumptions rely on the belief that the randomized controlled trial (RCT) is the gold standard in medical care research. Maintaining control over randomization automatically equates to "a rigorous study." However, Lerner addresses this question directly when he asks, "Is Randomization Essential" (p. 31)? The answer is: "the randomized experiment and the nonrandomized experiment are exactly the same" (p. 32), at least in terms of drawing credible inferences.
Randomization is customarily the linchpin for determining the value of research today, but really it might better be viewed as one consideration among many others within the context of overall study design. Here is a perspective that levels the playing field between the value of research produced by RCTs and econometric methods as far as their potential to generate valid inferences. Regardless, any applied research is dependent on measurement whether using experimental or nonexperimental data.
My third favorite point: "The job of a researcher is then to report economically and informatively the mapping from assumptions into inferences" (p. 38). Sensitivity analyses ameliorate doubt about the reality of some assumptions, but others are not objective nor are they value free. When this is the case, changes in assumptions can change inferences.
In conclusion, most facts are really opinions, and many opinions are based on conventions rather than truth. So it seems that, just as there are similarities between sex and econometrics, questioning assumptions about econometric modeling conventions might be a process that is similar to how we determine the truths by which we live our lives.