It's obvious why: there are too many confounding variables to run experiments on macroeconomically relevant scales. This is analogous to why econometrics is bu

It's obvious why: there are too many confounding variables to run experiments on macroeconomically relevant scales. This is analogous to why econometrics is bullshit: lack of stationarity in the real world. This is amplified by nonlinearities in the system. So even if things today were broadly comparable to, say, the 1990s (and they're emphatically not), what if there was this little thing somewhere (like an obscure accounting regulation) that led to massive differences in the outcome of the experiment? Tbc, I think there are better and worse ways to deal with the problem, just because we know so little does not mean everything is equally meaningless.