I don't think that's true at all. Pharmacology is a very difficult science that we get wrong all the time, yet we still have medicine because we are able to test our medicines by trying them on animals and people. Likewise in economics and sociology and astrophysics we are able to test through natural experiments. A test of a model is its ability to predict. We don't accept untested models just because they're "complicated".
And sure, maybe you believe that economics has more untested models, but that doesn't mean there aren't many tested models in economics.
Edit: reply button is locked out for some reason so replying here.
>And look at how much it costs, how unreliable the results are, and how even after full batch of successful trials, we have no clue why a drug works.
And yet we still do solid pharmacology that results in reliable medicine, just like we can do solid economics that results in models with high predictive power.
>If you take a large enough sample and apply enough statistics to it, you can see something that looks sort of like evidence to your hypothesis. In the end, you're not much closer to knowing why it happens (and why it happens only some percentage of the time). Compare that to hard sciences, where most of the time, you can design experiments based on first principles, and you can connect the results back to fundamental theories through a string of formal math.
The idea of statistical approximation does not distinguish between controlled experiments and observational study at all. We were able to statistically model the relationship between speed and energy before we could explain gravity, i.e. we were able to figure something out before we could explain why. And most experiments in physics resulted in approximation, such as newtonian physics, that works well enough at low speeds but breaks down at high speeds. Our current model of gravity was made in the 1970s, yet before 1970 we could explain that when you jump you fall to the earth. The fact that approximation is used is not remarkable in the slightest. That's what modeling is. A model that is too complicated is useless, a model that is too simple is inaccurate. All models are approximations to some level.
>Again, "tested" in physics vs. "tested" in economics are apples-to-oranges.
Yeah, that's why newton discovered relativity, right? No, we have areas of clear evidence and areas outside of our ability to measure for every field. Just becomes some areas of a field are difficult doesn't mean every area is difficult. Just because we couldn't model what happens to a ball thrown at 0.9c in the 1700s, doesn't mean we couldn't model a ball thrown at 0.9 m/s.
>Ultimately, my main point is that economics is so hard that even our best results are pretty bad, and marginally useful.
Look on the IGM site for policy recommendations that we have clear economic consensus on. ]If a country chooses to ignore economics, e.g. zimbabwe and greece, the results are very predictable.