"B. Calibration
To quantitatively decompose the contribution of different factors to the growth of shadow banks and fintech firms, we first have to calibrate the model to the conforming loan market data."
I can tell you with a straight face that is not normal science. Economists themselves increasingly recognize so-called "calibration" is a farce.
Also, by the way, you see pretty much the same type of thing in a ton of fMRI neuroscience, medical and psychology studies (even the ones you'll later see on NPR or ted talks). You shouldn't ever believe any one empirical result in basically anything except maybe CERN particle physics type work.
You should start with 'calibration' in economics. No, it is not quite what you (seem to) think it is. No, it is not quite "the same type of thing" as p-hacking and low-powered studies in psychology. (Whose poor reliability, by the way, is almost common knowledge by now.)
Look it up, and see how the sausage is made.
Because it's so easy to check those things (assuming the data is not proprietary or whatnot) I'd argue it's a much lesser problem than the "garden of forking paths" in lab experiments where it's much harder to test robustness of the result.
Moreover, I don't think anyone intelligent is foolish enough to take the coefficients in an econometric study literally; at least I would hope not.